[{"id":"oa:W4415000238","type":"article-journal","title":"Understanding Driver Expectations and Preferences Around Data Transparency in Vehicular Digital Twins","abstract":"While vehicles become more data-intensive, hardly any studies have systematically examined how drivers of such vehicles perceive the various privacy aspects related to the potential data usage.To address this gap, we present preliminary findings from an online survey of 30 drivers that investigates their expectations and preferences around data transparency in the context of vehicular digital twins (VDTs).We found that privacy aspects related to data access and control are important for potential VDT users, although they expressed uncertainty about their understanding of how the data is collected and used.Nevertheless, participants also showed some tolerance towards data collection and usage if it would potentially have a direct personal benefit.To inform future design of user-centered and privacy-aware VDT interfaces, we conclude that it is relevant to include and further discuss how the expectation of personal benefits might alter or even compromise privacy concerns. CCS Concepts• Human-centered computing → Empirical studies in HCI ; User studies; • Security and privacy → Usability in security and privacy.","author":[{"family":"Demir","given":"Cansu"},{"family":"Leschke","given":"Nicola"},{"family":"Hannibal","given":"Glenda"},{"family":"Akil","given":"Mahdi"},{"family":"Meschtscherjakov","given":"Alexander"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1145/3744335.3758509","URL":"https://doi.org/10.1145/3744335.3758509","source":"openalex"},{"id":"oa:W7128857467","type":"article-journal","title":"Assessment of the State and Development Trends of Centrifugal Compressors for Marine Power Plants","abstract":"Centrifugal compressors (CCs) are key components of marine power plants (MPPs), supporting engine boosting, boil-off gas (BOG) handling on liquefied natural gas (LNG) carriers, and auxiliary services such as heating, ventilation, and air conditioning (HVAC). However, recent publications are often fragmented by domain (aerodynamics, mechanical design, standards, and digitalization), complicating cross-domain engineering decisions for marine duty cycles. This structured review follows an explicit protocol to synthesize peer-reviewed studies (2015–2025) retrieved from Scopus and Web of Science and organizes the evidence by application class: turbocharger-integrated stages for marine diesel and gas-turbine engines, LNG/BOG compression trains, and auxiliary onboard services. The synthesis consolidates (i) aerodynamic KPIs (pressure ratio, efficiency, surge and stall margins, and operating range), (ii) mechanical and lifecycle enablers (seals, bearings, and rotordynamics), and (iii) quantified impacts of digital methods (control, diagnostics, and digital twins). Reported trends include single-stage pressure ratios of ~5.4–5.7, multistage overall pressure ratios exceeding 10, and surge-margin improvements of ~40–44% associated with advanced diffusers as well as casing and endwall treatments. Industrial case studies (non-marine) report downtime reductions of ~25–35% and maintenance-cost reductions of ~25%, while evaluated diagnostic datasets show high accuracy. Key gaps remain in marine-specific validation datasets and harmonized testing and data standards.","author":[{"family":"Afanaseva","given":"Olga"},{"family":"Первухин","given":"ДА"},{"family":"Afanasyev","given":"Mikhail"},{"family":"Khatrusov","given":"Aleksandr"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19040991","URL":"https://doi.org/10.3390/en19040991","source":"openalex"},{"id":"oa:W4404169968","type":"article-journal","title":"Reference architecture for IoT-based predictive maintenance systems using digital twins","abstract":"Context: Predictive maintenance strategies have become essential to industries where asset quality, product quality, or downtime critically impact costs. Internet of Things (IoT) technologies can be leveraged for predictive maintenance strategies when developing new systems or retrofitting existing systems. Additionally, predictive maintenance strategies are accelerated by real-time synchronized, high-resolution representations of physical objects called Digital Twins. Developing IoT-based predictive maintenance systems is complex, and as such, industrially validated guidelines for the development of such systems are preferred. Objective: The main objective of this study is to develop and empirically validate a Reference Architecture for IoT-based Predictive Maintenance Systems using Digital Twins. Method: We proposed a method to create a Reference Architecture for IoT and Cloud-based Predictive Maintenance Systems using Digital Twins. We have applied a systematic casestudy protocol to validate the reference architecture’s usefulness. We derived application architectures for two real industrial case studies and surveyed practitioners. Result: We demonstrated that the methods of creating a Reference Architecture could be used in the Digital Twin-based predictive maintenance domain and showed how an Application Architecture could be designed in this context. The survey results indicate that the respondents were satisfied with the practicality of the Reference Architecture and derived Application Architecture. Conclusion: The proposed Reference Architecture for IoT-based Predictive Maintenance systems using Digital Twins can be practically applied and used in diverse application domains. Furthermore, the Reference Architecture supports the potential of a predictive maintenance system to enhance operational resilience in manufacturing systems and energy infrastructure.","author":[{"family":"Dinter","given":"Raymon"},{"family":"Catal","given":"Cagatay"},{"family":"Arends","given":"Oscar"},{"family":"Deshmukh","given":"Sameer"},{"family":"Elbakly","given":"Fouad"},{"family":"Romdhane","given":"Oumeyma"},{"family":"Grotepass","given":"Kai"},{"family":"Stringer","given":"Marcel"},{"family":"Tekinerdoğan","given":"Bedir"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.rineng.2026.111115","URL":"https://doi.org/10.1016/j.rineng.2026.111115","source":"openalex"},{"id":"oa:W4411094878","type":"article-journal","title":"Digital Twin Monitoring System for Pedestrian Crossings Based on Autonomous Driving Environment","abstract":"In response to the growing demand for pedestrian crosswalk safety and visibility in the era of autonomous driving, this paper proposes and designs a crosswalk environment monitoring system based on virtual-physical twin technology. Leveraging Unreal Engine (UE) and Carla simulation software, the system constructs a high-precision virtual environment, integrating real-time data from on-site sensors and weather APIs to achieve comprehensive and dynamic monitoring of crosswalk conditions. A key innovation of the system is the application of a Vision-Language Model (VLM), which automatically translates monitoring data into understandable natural language text while also enabling threshold-based warnings and safety alerts. This enhances the intelligence and automation of the monitoring system. Compared to traditional monitoring methods that primarily rely on graphical visualization, the proposed approach significantly improves data processing efficiency and safety alert capabilities, offering a more efficient, real-time, and intelligent solution for traffic safety management in the context of autonomous driving.","author":[{"family":"Teng","given":"Xiao"},{"family":"Huang","given":"Lin"},{"family":"Shen","given":"Zhenjiang"},{"family":"Li","given":"Wankai"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3233/atde250241","URL":"https://doi.org/10.3233/atde250241","source":"openalex"},{"id":"oa:W7128918130","type":"article-journal","title":"Gazer 3d: a Robust, Data Driven, Digital Twin and Immersive Visualisation Platform","abstract":"Gazer 3D platform characterizes a leading edge, data-driven, immersive visualization, and digital twin technology revolutionizing the modern industrial sectors. Integrating seamless IoT data, streamlined data management, AR/VR techniques, predictive analytics, and real-time data interaction aids the system for machine monitoring, anomaly detection, and predictive maintenance. The distinct features include 3D visualization, AI/ML-based predictive maintenance, photogrammetry integration, and enterprise-grade security. It addresses the challenges of conventional visualization techniques like data management challenges, data visualization challenges, data overload, data cleaning, lack of real-time data insights, scalability challenges, and lack of interconnectedness with legacy systems. It ensures to be secure with the zero trust security model with multi-layers of authentication and authorizations. This study handles the key differentiating features of Gazer 3D technology in overcoming the challenges of conventional models, mentioning the instances from sectoral applications.","author":[{"family":"Pillai","given":"Renjithkumar"},{"family":"Oconnel","given":"Eoin"},{"family":"Denny","given":"Patrick"},{"family":"Shefeeque","given":"Mohamed"}],"issued":{"date-parts":[[2026]]},"DOI":"10.71097/ijsat.v17.i1.10344","URL":"https://doi.org/10.71097/ijsat.v17.i1.10344","source":"openalex"},{"id":"oa:W4410900110","type":"article-journal","title":"Industrial study on holistic digital factory models","abstract":"Abstract Although studies have demonstrated the potential of holistic digital factory models, their application in industry remains limited. There is a research gap as to why this is the case. In particular, the starting point of the factory operators and their specific requirements for such models are still unclear. This paper presents a mixed-methods study that addresses the existing research gap regarding the implementation of holistic digital factory models. The study investigates the evolving understanding of factory planning, emphasizing the transition from one-time projects to continuous tasks. The key findings reveal a significant need for cross-life-cycle information continuity, highlighting the importance of collaboration and data integration among stakeholders. The research identifies obstacles to achieving holistic digital factory planning, including knowledge management and data availability challenges. Furthermore, the applicability of existing technologies for holistic digital factory models, such as Building Information Modeling and Digital Twins, is examined, demonstrating their relevance in factory planning. Additionally, it is shown that while there is an apparent demand for standardized methods and tools, many existing methodologies are underutilized. The paper concludes with recommendations to further investigate the contrasts between literature and industry practices, as well as the implementation of shared data environments to enhance the efficiency of factory planning processes.","author":[{"family":"Bermpohl","given":"Fabian"},{"family":"Schäfer","given":"Simon"},{"family":"Neumann","given":"Oliver"},{"family":"Reihlen","given":"Eckart"},{"family":"Dickopf","given":"Thomas"},{"family":"Gebel","given":"Thomas"},{"family":"Neuhäuser","given":"Thomas"},{"family":"Daub","given":"Rüdiger"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s11740-025-01344-z","URL":"https://doi.org/10.1007/s11740-025-01344-z","source":"openalex"},{"id":"oa:W4409049613","type":"article-journal","title":"Digital Transformation for Sustainable Transportation: Leveraging Industry 4.0 Technologies to Optimize Efficiency and Reduce Emissions","abstract":"This study investigates how Industry 4.0 technologies can optimize transportation efficiency and contribute to global sustainability goals by reducing CO2 emissions. In response to the pressing climate emergency, the research examines the role of the Internet of Things (IoT), Artificial Intelligence (AI), and predictive analytics in enhancing operational performance and aligning transportation systems with Sustainable Development Goals (SDGs), particularly Goal 13 (climate action) and Goal 9 (industry, innovation, and infrastructure). Using a qualitative research approach, semi-structured interviews and focus groups were conducted with industry experts, and the data were analyzed using thematic analysis and qualitative network mapping in NVivo software. The findings reveal that IoT enhances real-time monitoring, AI enables dynamic route optimization, and predictive analytics supports proactive maintenance, collectively achieving an average emission reductions of 30%. However, adoption is hindered by infrastructure gaps, high implementation costs, skill shortages, and fragmented regulatory frameworks. This study integrates the Technology–Organization–Environment (TOE) framework and Sustainable Corporate Theory to provide a structured analysis of digital transformation in transportation. The findings offer strategic insights for policymakers and industry stakeholders, highlighting the need for stronger regulatory support, targeted incentives, and digital infrastructure investments.","author":[{"family":"Fatorachian","given":"Hajar"},{"family":"Kazemi","given":"Hadi"},{"family":"Pawar","given":"Kulwant"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/futuretransp5020034","URL":"https://doi.org/10.3390/futuretransp5020034","source":"openalex"},{"id":"oa:W4412456672","type":"article-journal","title":"Developing a Competency-Based Transition Education Framework for Marine Superintendents: A DACUM-Integrated Approach in the Context of Eco-Digital Maritime Transformation","abstract":"Amid structural changes driven by the greening and digital transformation of the maritime industry, the demand for career transitions of seafarers with onboard experience to shore-based positions—particularly ship superintendents—is steadily increasing. However, the current lack of a systematic education and career development framework to support such transitions poses a critical challenge for shipping companies seeking to secure sustainable human resources. The aim of this study was to develop a competency-based training program that facilitates the effective transition of seafarers to shore-based ship superintendent roles. We integrated a developing a curriculum (DACUM) analysis with competency-based job analysis to achieve this aim. The core competencies required for ship superintendent duties were identified through three expert consultations. In addition, social network analysis (SNA) was used to quantitatively assess the structure and priority of the training content. The analysis revealed that convergent competencies, such as digital technology literacy, responsiveness to environmental regulations, multicultural organizational management, and interpretation of global maritime regulations, are essential for a successful career shift. Based on these findings, a modular training curriculum comprising both common foundational courses and specialized advanced modules tailored to job categories was designed. The proposed curriculum integrated theoretical instruction, practical training, and reflective learning to enhance both applied understanding and onsite implementation capabilities. Furthermore, the concept of a Seafarer Success Support Platform was proposed to support a lifecycle-based career development pathway that enables rotational mobility between sea and shore positions. This digital learning platform was designed to offer personalized success pathways aligned with the career stages and competency needs of maritime personnel. Its cyclical structure, comprising career transition, competency development, field application, and performance evaluation, enables seamless career integration between shipboard- and shore-based roles. Therefore, the platform has the potential to evolve into a practical educational model that integrates training, career development, and policies. This study contributes to maritime human resource development by integrating the DACUM method with a competency-based framework and applying social network analysis (SNA) to quantitatively prioritize training content. It further proposes the Seafarer Success Support Platform as an innovative model to support structured career transitions from shipboard roles to shore-based supervisory positions.","author":[{"family":"Yu","given":"Yung"},{"family":"Lee","given":"Chang"},{"family":"Ahn","given":"Young"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17146455","URL":"https://doi.org/10.3390/su17146455","source":"openalex"},{"id":"oa:W4412838645","type":"article-journal","title":"Dynamic BIM-based digital twin for lifecycle estimation of infrastructure embodied carbon","abstract":"Embodied carbon plays a pivotal role in whole-life carbon emissions of infrastructure projects. Estimation of embodied carbon by using life cycle assessment (LCA) is complex, as numerous variables can impact its accuracy. This study reviews the literature on existing BIM-LCA workflows, identifying methodology advancements to enhance conventional workflows and exploring the integration with the digital twin. BIM-LCA workflows have been widely applied in the literature for embodied carbon assessment, with improving data interoperability identified as a hotspot to further expand this application. However, existing workflows fail to incorporate time-dependent factors in early-stage estimations, limiting predictive accuracy. Additionally, digital twin technology has not been integrated into current methodologies, limiting real-time data updates and automated monitoring during the operational stage. Therefore, a conceptual framework is proposed to incorporate a digital twin for predicting and real-time monitoring embodied emissions. It offers a pathway toward more accurate and dynamic whole-life carbon emission assessments.","author":[{"family":"Zou","given":"Tingting"},{"family":"Li","given":"Chuan"},{"family":"Lei","given":"Hui"},{"family":"Zhang","given":"Ge"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1201/9781003595120-53","URL":"https://doi.org/10.1201/9781003595120-53","source":"openalex"},{"id":"oa:W7160662231","type":"article-journal","title":"Exploring the feasibility and usefulness of a digital twin in the valorization of organic waste streams in Uganda","abstract":"Valorization of organic waste streams receives growing attention to improve resource efficiency and support a circular economy. One potential valorization option is converting organic waste into biofertilizers, but logistical challenges around waste availability, consistency and transportation hinder its potential. Digital twins—virtual models integrating real-time data—could enhance decision-making for waste valorization, but their application remains limited to data intensive, controlled environments. In this exploratory study we applied the Motivation-Opportunity-Ability framework and an infological approach to assess stakeholder perspectives and feasibility of the digital twin concept in a relatively complex and data-scarce environment: the valorization of organic waste in Uganda. Findings indicate that actors are Motivated to valorize waste for sustainability and economic benefits, but limited waste availability and predictive capacity to optimize the valorization process restrict Opportunities and Ability. Composting of wet coffee pulp with black soldier fly larvae emerged as a promising valorization case, in which a digital model could support decision-making towards improved yields of larvae and frass (output), based on amount, quality and the costs of different waste streams (input). Limited automation, data sharing and value creation make the development of a fully integrated digital twin unlikely in the near future. In the resource-constrained setting of our study, relatively simple digital models that can gradually be advanced based on technical feasibility, perceived importance of parameters and resources available are required instead. To ensure a successful implementation, a user-driven design approach focusing on practical decision-problems rather than on technological potential alone is key. • Digital twins can aid decision-making for waste valorization in a circular economy. • We combined the Motivation-Opportunity-Ability framework and an infological approach. • Despite Motivation, limited organic waste constrains valorization Opportunities. • Wet coffee pulp x BSF larvae composting could benefit from a potential digital twin. • User-driven design and practical decision-problems are key for model implementation.","author":[{"family":"Ronner","given":"E"},{"family":"Butuc","given":"Oana"},{"family":"Ven","given":"Gerrie"},{"family":"Slegers","given":"Petronella"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.crsust.2026.100354","URL":"https://doi.org/10.1016/j.crsust.2026.100354","source":"openalex"},{"id":"oa:W7130383151","type":"article-journal","title":"Tackling the Complexity of Emergency Response Systems: Creating Transport-Focused Digital Twins","abstract":"Providing medical and technical assistance to people in life-threatening situations requires the coordinated cooperation of numerous actors within the emergency response system. The efficiency of the emergency response system is thereby influenced by the transport infrastructure and the traffic conditions. Organizations and authorities with safety responsibilities are increasingly faced with the challenge of assessing the impact of changes to the transport system on the overall system’s effectiveness. The overall objective of this paper is to develop an efficient and cost-effective simulation and analysis platform for generating transport-focused digital twins, enabling organizations and authorities to monitor the current emergency response system and digitally analyze various ‘what-if’ scenarios for future planning. Our model combines various data sources, including real-time traffic data, recorded GPS data from emergency vehicles (EVs), and the road network. The data serves as the foundation for the indicator-based network analysis and the system model. The main actors in the emergency response system are modeled in the agent-based model to analyze the spatiotemporal impact of changes in the transport system on the system’s effectiveness. The developed simulation and analysis platform is applied to a case study of the Munich Fire Department, Germany. First, a network analysis using regression of EV speed on reported real-time traffic speed helps identify problematic areas where EVs are affected by traffic. Secondly, the agent-based model of the Munich fire department demonstrates good validation results against historical incident data, with recorded trajectory data used for model calibration. Our work contributes to efficient, data-driven planning for future emergency response systems.","author":[{"family":"Schuhmann","given":"Fabian"},{"family":"Sturm","given":"Moritz"},{"family":"Zacher","given":"Till"},{"family":"Lienkamp","given":"Markus"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/smartcities9020036","URL":"https://doi.org/10.3390/smartcities9020036","source":"openalex"},{"id":"oa:W4415588295","type":"article-journal","title":"Urban Digital Twin Data Requirements and Reference Architecture for Green Spaces and Ecosystems","abstract":"Abstract As cities face growing pressure from climate change, biodiversity loss, and urbanization, there is an urgent need for data-driven tools to support the planning and resilience of green infrastructure. This paper presents a methodology for developing Urban Digital Twins (UDTs) focused on green space planning, monitoring, and regeneration. The process begins with the identification of Key Performance Indicators (KPIs) across five thematic areas: pollution and climate, natural environment, ecosystems, human perception, and public awareness. Based on these KPIs, a set of enabling digital technologies is evaluated through expert ranking, using Kendall’s W concordance coefficient to assess consensus on their relevance. The results highlight strong agreement among experts, with IoT, GIS, and BIM emerging as the most suitable technologies due to their capacity for real-time sensing, semantic integration, and spatial representation. Drawing from these insights, the paper proposes a five-layer reference architecture for UDTs designed to support adaptive, inclusive, and data-driven urban greening efforts. The findings offer guidance for cities and stakeholders aiming to implement UDTs for urban resilience.","author":[{"family":"Morkūnaitė","given":"Lina"},{"family":"Pupeikis","given":"Darius"},{"family":"Bocullo","given":"Vytautas"},{"family":"Klumbytė","given":"Eglė"},{"family":"Conserva","given":"Andrea"},{"family":"Farinea","given":"Chiara"},{"family":"Bazzica","given":"Alice"},{"family":"Barmann","given":"Peter"},{"family":"Csala","given":"Fruzsina"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/978-3-032-09040-9_5","URL":"https://doi.org/10.1007/978-3-032-09040-9_5","source":"openalex"},{"id":"oa:W7117107096","type":"article-journal","title":"Modeling and Evaluation of Reversible Traction Substations in DC Railway Systems: A Real-Time Simulation Platform Toward a Digital Twin","abstract":"Traditional diode-based rectifiers (TDRs) in railway traction substations (TSSs) are inefficient at handling bidirectional power flow and cannot recover regenerative braking energy (RBE). Replacing these conventional systems with reversible traction substations (RTSSs) requires detailed modeling, extensive simulations, and validation using real data. This paper presents a DT-oriented real-time modeling and Hardware-in-the-Loop (HIL) platform for the analysis and performance assessment of RTSSs in DC railway systems. The integration of interleaved PWM rectifiers enables bidirectional power flow, allowing efficient RBE recovery and its return to the main grid. Modeling railway networks with moving trains is complex due to nonlinear dynamics arising from continuously varying positions, speeds, and accelerations. The proposed approach introduces an innovative multi-train simulation method combined with low-level transient and power-quality analysis. The validated DT model, supported by HIL emulation using OPAL-RT, accurately reproduces real-world system behavior, enabling optimal component sizing and evaluation of key performance indicators such as voltage ripple, total harmonic distortion, passive-component stress, and current imbalance. The results demonstrate improved energy efficiency, enhanced system design, and reduced operational costs. Meanwhile, experimental validation on a small-scale RTSS prototype, based on data from the Italian 3 kV DC railway system, confirms the accuracy and applicability of the proposed DT-oriented framework.","author":[{"family":"Zaninelli","given":"Dario"},{"family":"Kaleybar","given":"Hamed"},{"family":"Brenna","given":"Morris"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app16010080","URL":"https://doi.org/10.3390/app16010080","source":"openalex"},{"id":"oa:W4411605901","type":"article-journal","title":"A Multi-Layer Navigation Approach for Interactive Pedestrian Flow Simulation in Digital Twins","abstract":"Pedestrian flow simulation is crucial for accurately depicting daily activities and dynamics of infrastructures, such as town halls, train stations, or airports. Current pedestrian flow models often lack the capability to interact with environmental changes in real-time or only focus on one-directional interactions via prescribed events. To address this limitation, we propose a hybrid approach that combines graph-based methods for large-scale navigation with the optimal steps model for small-scale navigation and locomotion of agents. This combination enables dynamic updates according to environmental changes provided by other simulations. We demonstrate the effectiveness of our proposed approach in an exemplary airport architecture where pedestrian simulation is coupled with an electrical simulation, resulting in a successful bidirectional coupling. Specifically, we consider a scenario where a saboteur agent meddles with an electrical circuit, causing a ripple effect that impacts ped estrian behavior.","author":[{"family":"Nellinger","given":"Christoph"},{"family":"Stürmer","given":"Jan"},{"family":"Koch","given":"Tobias"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5220/0013555700003970","URL":"https://doi.org/10.5220/0013555700003970","source":"openalex"},{"id":"oa:W7142613171","type":"article-journal","title":"Enhancing Flexible Healthcare Management Through the Adoption of Digital Twin Technology: An Integrated UTAUT2-TOE Framework with SEM-ANN Analysis","abstract":"Abstract This study examines the behavioral and organizational factors that influence the adoption of digital twin (DT) technologies in healthcare, particularly in resource-constrained environments such as Bangladesh. It emphasizes the often-overlooked human and institutional aspects of DT adoption, alongside technical considerations. An integrated model was developed by combining the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) with the Technology-Organization-Environment (TOE) framework, drawing on six key constructs from each. Data collected from 439 healthcare professionals were analyzed using a hybrid approach of structural equation modeling (SEM) and artificial neural networks (ANNs). The results show that all predictors have a significant impact on behavioral intention, with complexity having a negative effect. ANN sensitivity analysis identified regulatory support, effort expectancy, facilitating conditions, and complexity as the most influential factors. These contribute to flexible management dimensions in hospitals. While the model explains 88.4% of the variance in behavioral intention, it accounts for only 8.5% of actual DT adoption, suggesting the influence of other organizational factors. This study is among the first to use an integrated UTAUT2-TOE framework with an SEM-ANN approach for DT adoption in healthcare. The findings provide valuable insights for healthcare policymakers, underscoring the importance of supportive infrastructure, user-friendly technology, and regulatory alignment.","author":[{"family":"Hossain","given":"Ismail"},{"family":"Belal","given":"HM"},{"family":"Ratul","given":"Shahriar"},{"family":"Rahman","given":"Md"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s40171-026-00491-1","URL":"https://doi.org/10.1007/s40171-026-00491-1","source":"openalex"},{"id":"oa:W4413032125","type":"manuscript","title":"An Integrated Digital Twin and BIM Approach to Minimize Environmental Loads for In-situ Production and Yard-Stock Management of Precast Concrete Components","abstract":"Digital Twin (DT) technology has become a cornerstone of data-driven decision-making in the construction industry through its simulation and predictive capabilities. The integration of Building Information Modeling (BIM) and DT forms a closed-loop system that delivers dynamic operational insights, including predictive maintenance, performance tracking, and risk assessment. This study introduces a BIM-enabled DT framework designed to optimize in-situ production and stockyard management of precast concrete (PC) components. Utilizing the Oracle Crystal Ball simulation tool, CO₂ emissions optimization were conducted. Results showed potential reductions up to 8.7% in environmental impact. The framework was validated through application to a large-scale logistics warehouse project, providing practical insights for sustainable construction planning.","author":[{"family":"Park","given":"Junyoung"},{"family":"Kim","given":"Sunkuk"},{"family":"Lim","given":"Jeeyoung"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202508.0226.v1","URL":"https://doi.org/10.20944/preprints202508.0226.v1","source":"preprints"},{"id":"oa:W4411832148","type":"article-journal","title":"Digital Transitions of Critical Energy Infrastructure in Maritime Ports: A Scoping Review","abstract":"This scoping review investigates the digital transition of critical energy infrastructure (CEI) in maritime ports, which are increasingly vital as energy hubs amid global decarbonisation efforts. Recognising the growing role of ports in integrating offshore renewables, hydrogen, and LNG systems, the study examines how digital technologies (such as automation, IoT, and AI) support the resilience, efficiency, and sustainability of port-based CEI. A multifaceted search strategy was implemented to identify relevant academic and grey literature. The search was performed between January 2025 and 30 April 2025. The strategy focused on databases such as Scopus. Due to limitations encountered in retrieving sufficient, directly relevant academic papers from databases alone, the search strategy was systematically expanded to include grey literature such as reports, policy documents, and technical papers from authoritative industry, governmental, and international organisations. Employing Arksey and O’Malley’s framework and PRISMA-ScR (scoping review) guidelines, the review synthesises insights from 62 academic and grey literature sources to address five core research questions relating to the current state, challenges, importance, and future directions of digital CEI in ports. Literature distribution of articles varies across continents, with Europe contributing the highest number of publications (53%), Asia (24%) and North America (11%), while Africa and Oceania account for only 3% of the publications. Findings reveal significant regional disparities in digital maturity, fragmented governance structures, and underutilisation of digital systems. While smart port technologies offer operational gains and support predictive maintenance, their effectiveness is constrained by siloed strategies, resistance to collaboration, and skill gaps. The study highlights a need for holistic digital transformation frameworks, cross-border cooperation, and tailored approaches to address these challenges. The review provides a foundation for future empirical work and policy development aimed at securing and optimising maritime port energy infrastructure in line with global sustainability targets.","author":[{"family":"Daniel","given":"Emmanuel"},{"family":"Makokha","given":"Augustine"},{"family":"Ren","given":"Xin"},{"family":"Olatunji","given":"Ezekiel"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/jmse13071264","URL":"https://doi.org/10.3390/jmse13071264","source":"openalex"},{"id":"oa:W4415912502","type":"article-journal","title":"Comparative analysis on AI-driven human digital twin for personalized and predictive medicine","abstract":"The emergence of digital twin technology in medicine signifies a paradigm shift toward personalized healthcare and precision therapeutics. A human digital twin (HDT) is a dynamic, virtual representation of an individual’s physiological state, constructed and continuously updated via real-time data streams from wearable sensors, advanced imaging, and molecular diagnostics. This paper comparatively analyses the capacity of HDTs to enable high-fidelity simulation of patient-specific disease conditions, thereby optimizing therapeutic intervention, surgical planning, and predictive health management. By integrating advancements in artificial intelligence, machine learning, and the Internet of Things (IoT), HDTs facilitate the modeling of complex, multi-scale biological interactions, from genetic and molecular pathways to systemic organ function. We review current computational frameworks for HDT development, address critical challenges including data integration, model interoperability, and validation, and consider the transformative impact on clinical workflows. Concurrently, we examine the imperative ethical considerations and data security protocols required for responsible clinical deployment. The realization of personal digital twins holds the potential to revolutionize medical practice by facilitating truly individualized therapeutic strategies, improving patient outcomes, and accelerating biomedical discovery.","author":[{"family":"Din","given":"Ghulam"},{"family":"Shams","given":"M"},{"family":"Rahmani","given":"Ahmad"},{"family":"Rehman","given":"Abdul"},{"family":"Ahmed","given":"Mohammed"},{"family":"Shoukat","given":"Muhammad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.59324/jcpmr.2025.1(1).06","URL":"https://doi.org/10.59324/jcpmr.2025.1(1).06","source":"openalex"},{"id":"oa:W4414411536","type":"article-journal","title":"ENACT: Energy-Aware, Actionable Twin Utilizing Prescriptive Techniques in Home Appliances","abstract":"A significant portion of home energy consumption is due to concealed faults and the inefficient usage of home appliances, usually because of user ignorance and a lack of proactive maintenance strategies. In this paper, ENACT, a digital-twin-based system, is proposed as the solution that facilitates better user understanding, encourages sustainable maintenance practices for appliances, and provides prescriptive maintenance recommendations. With the integration of smart plugs, behavioral analysis, and a 3D spatial interface, ENACT offers real-time device monitoring while providing context-aware suggestions. The system was installed in 20 households over a 12-month period, with users engaging with both 2D and 3D models of their surroundings. The quantitative results, including an average System Usability Scale score of 80.5, and qualitative feedback demonstrated intense user engagement, with strong evidence of mindset shifts towards proactive maintenance behavior. The findings confirm that digital twin technologies, when combined with targeted guidance, can significantly improve appliance lifespans, energy efficiency, and user empowerment within homes.","author":[{"family":"Stogia","given":"Myrto"},{"family":"Dimara","given":"Asimina"},{"family":"Papaioannou","given":"Christoforos"},{"family":"Eleftheriou","given":"Orfeas"},{"family":"Papaioannou","given":"Alexios"},{"family":"Krinidis","given":"Stelios"},{"family":"Anagnostopoulos","given":"Christos‐nikolaos"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/smartcities8050155","URL":"https://doi.org/10.3390/smartcities8050155","source":"openalex"},{"id":"oa:W4407357011","type":"article-journal","title":"The digital labour of artificial intelligence in Latin America: a comparison of Argentina, Brazil, and Venezuela","abstract":"The current hype around artificial intelligence (AI) conceals the substantial human intervention underlying its development. This article lifts the veil on the precarious and low-paid ‘data workers’ who prepare data to train, test, check, and otherwise support models in the shadow of globalized AI production. We use original questionnaire and interview data collected from 220 workers in Argentina (2021–2022), 477 in Brazil (2023), and 214 in Venezuela (2021–2022). We compare them to detect common patterns and reveal the specificities of data work in Latin America, while disclosing its role in AI production. We show that data work is intertwined with economic hardship, inequalities, and informality. Despite workers’ high educational attainment, disadvantage is widespread, in ways that change across countries. By acknowledging the interconnections between AI development, data work, and globalized production, we provide insights for the regulation of AI and the future of work, aiming to achieve positive outcomes for all stakeholders.","author":[{"family":"Tubaro","given":"Paola"},{"family":"Casilli","given":"Antonio"},{"family":"Massi","given":"Mariana"},{"family":"Longo","given":"Julieta"},{"family":"Torrescierpe","given":"Juana"},{"family":"Braz","given":"Matheus"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/14747731.2025.2465171","URL":"https://doi.org/10.1080/14747731.2025.2465171","source":"openalex"},{"id":"oa:W4409648104","type":"article-journal","title":"Smart monitoring of the expansion state of boiler water walls in coal-fired power plants using a digital twin model","abstract":"This article presents an approach for monitoring the expansion state of water walls in coal-fired power plants using a digital twin (DT) model. The monitored boiler belongs to a 1000 MW ultrasupercritical power generating unit; it has been in service for more than 14 years and has accumulated more than 100 000 hours of operation. The fracture of the water wall has become a serious problem for safe operation. The size of the water wall is huge, the structure is complex, the stress state is changeable, and the fracture treatment is difficult. Existing online monitoring systems are mainly based on wall temperature, and it is difficult to evaluate the stress state of the water wall. However, there are few technical systems that can monitor the expansion displacement and local strain/stress of water walls online. To address this problem, a DT model is built to monitor the expansion state of boiler water walls. An optical non-contact strain monitoring system (based on digital image correlation (DIC) technologies) coupled with finite element analysis is developed to measure the actual strain/stress data and generate more simulation data for improving the accuracy of the DT model. This monitoring system provides an effective way to prevent the expansion fracture of the water wall.","author":[{"family":"Luo","given":"Lijia"},{"family":"Wang","given":"Weida"},{"family":"Lei","given":"Zhiping"},{"family":"Bao","given":"Shiyi"},{"family":"Bassir","given":"David"},{"family":"Chen","given":"Gongfa"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3176/proc.2025.2.12","URL":"https://doi.org/10.3176/proc.2025.2.12","source":"openalex"},{"id":"oa:W4409628481","type":"article-journal","title":"Achieving carbon-neutral economies through circular economy, digitalization, and energy transition","abstract":"Decarbonization is of utmost importance to effectively address climate change, advance environmental sustainability, and protect biodiversity and ecosystems. Therefore, developed and developing economies are focusing on adopting various approaches to achieve zero carbon emissions. Thus, this study attempted to generate a meaningful relationship between the circular economy, digitalization, energy transition, and eco-friendly trade strategy to capture the role of factors that function to attain carbon neutrality. For the above-given objectives, dynamic econometric methods, such as the cross-sectional autoregressive distributed lag model (CS-ARDL), were adopted to assess the G7 dataset between 1990 and 2022. These findings suggest that the parameters under investigation are important for achieving carbon neutrality in G7 in the long term. Moreover, Panel Corrected Standard Errors (PCSe) confirmed that every aspect affects carbon neutrality. Consequently, the long-term attainment of decarbonization is greatly aided by a circular economy, digitalization, energy transformation, and green trade. Thus, significant and comprehensive policy changes are needed in several sectors, such as the development of digitization, environmental regulations, sustainable and green technology, and renewable energy sources.","author":[{"family":"Zhang","given":"Mingyue"},{"family":"Liu","given":"Ruiqing"},{"family":"Sun","given":"Huijuan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-97810-w","URL":"https://doi.org/10.1038/s41598-025-97810-w","source":"openalex"},{"id":"oa:W4412893652","type":"article-journal","title":"Impact of Digital Transformation on Sustainable Development of Port Performance: Evidence from Tangshan Port","abstract":"Although the importance of digital transformation in contemporary port development has been widely acknowledged, there is little empirical research on the extent to which it promotes sustainable development by reducing costs and increasing efficiency. This study takes the digital transformation of one of the largest ports in northern China—Tangshan Port—as an example, as the application of digital technologies has greatly improved its operational efficiency. By using cargo throughput and container throughput data from Tangshan Port as the experimental group and from Qinhuangdao Port as the control group, difference-in-differences regression models with monthly data and port fixed effects were adopted to clarify the impact of digital transformation on sustainability for different types of cargo throughput, as well as the differential effects of policy impact on port production efficiency and economic performance in the short and long term, in order to examine the impact of digitalization on port operation performance. Our findings demonstrate that digital transformation has a significant positive impact on both port cargo and container throughput, with the long-term effect surpassing the short-term effect. Additionally, regional economic level positively moderates policy impact. These findings provide critical evidence that ports can balance economic growth and environmental sustainability within sustainable development frameworks.","author":[{"family":"Li","given":"YD"},{"family":"Tian","given":"Xin"},{"family":"Lu","given":"Zhiyuan"},{"family":"Wu","given":"Junfeng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17156902","URL":"https://doi.org/10.3390/su17156902","source":"openalex"},{"id":"oa:W4417224688","type":"article-journal","title":"Digital Twins in Biopharmaceutical Manufacturing: Review and Perspective on Human–Machine Collaborative Intelligence","abstract":"The biopharmaceutical industry is increasingly developing digital twins to digitalize and automate the manufacturing process in response to the growing market demands. However, this shift can create challenges for human operators, as the complexity and volume of information can overwhelm their ability to manage the process effectively—particularly during abnormal events. These issues are compounded when digital twins are designed without explicit consideration of operator interaction and collaboration. Our review of current trends in biopharma digital twin development reveals a predominant focus on technology and often overlooks the critical role of human operators. To bridge this gap, this article proposes a collaborative intelligence framework that integrates operators with digital twins. We discuss approaches that can enhance operator trust and human–machine interface usability. Moreover, innovative training programs for preparing operators to understand and utilize digital twins are discussed. The framework aims to strengthen collaboration between operators and digital twins by leveraging their complementary capabilities to improve resilience and productivity in biopharmaceutical manufacturing.","author":[{"family":"Shahab","given":"Mohammed"},{"family":"Destro","given":"Francesco"},{"family":"Braatz","given":"Richard"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.eng.2026.07.039","URL":"https://doi.org/10.1016/j.eng.2026.07.039","source":"openalex"},{"id":"oa:W7127653589","type":"article-journal","title":"From Population-Based PBPK to Individualized Virtual Twins: Clinical Validation and Applications in Medicine","abstract":"Physiologically based pharmacokinetic (PBPK) models are widely used in the context of personalized medicine, as they allow for the evaluation of dosing schedules and routes of administration by predicting absorption, distribution, metabolism and excretion (ADME) of drugs in biological systems. Traditionally, PBPK models have been developed and applied at the population level, enabling the characterization of predefined cohorts, which remains limited in supporting true precision dosing. In this review, we explored the increasingly common shift from population-based to individual PBPK modelling, where individuals are modelled as virtual twins (VTs). Through the inclusion of additional patient-specific data, such as demographic, physiological, phenotypic and genotypic information, models can be personalized, moving beyond traditional one-size-fits-all strategies. Overall, incorporating individual patient data (e.g., septic, psychiatric, cardiac, or neonatal populations) improves model performance. Physiological parameters, particularly renal function, show strong potential given their role in drug elimination, while demographic variables enhance predictive accuracy in certain studies. In contrast, the benefits of including cytochrome P450 (CYP) phenotypic and genotypic data remain inconsistent. We further emphasize methodologies used to evaluate model performance, with a focus on clinical validation through comparisons between predicted and observed concentration-time profiles. Key challenges, including limited sample sizes and data availability, that may compromise predictive precision, are also discussed. Finally, we highlight the potential integration of PBPK-based VTs into broader digital twin frameworks as a promising path toward clinical translation, while acknowledging the critical barriers that must be addressed to enable routine clinical implementation.","author":[{"family":"Gonçalves","given":"Marta"},{"family":"Barata","given":"Pedro"},{"family":"Vale","given":"Nuno"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/jcm15031210","URL":"https://doi.org/10.3390/jcm15031210","source":"openalex"},{"id":"oa:W7128407306","type":"article-journal","title":"Real-time digital twin prototype for cyber-physical analysis of anomalies in PV–PEM–BESS systems for green hydrogen production","abstract":"The deployment of hybrid green hydrogen systems faces challenges due to complex integration and exposure to cyber threats. The lack of secure testbeds to replicate severe anomalies limits the analysis of fault propagation without endangering physical assets. Consequently, it is necessary to develop a testbed to replicate anomalies in the operation of a green hydrogen generation system to facilitate its physical implementation. This article presents the development of a real-time Digital Twin Prototype (DTP) testbed for green hydrogen production systems integrating photovoltaic (PV) generation, a proton exchange membrane water electrolyzer (PEMWE), and a battery energy storage system (BESS), structured with a DC bus and a supercapacitor. The platform is implemented using Hardware In the Loop (HIL) to emulate system dynamics, enabling the safe testing of cyber-physical anomalies such as False Data Injection Attacks (FDIA) and DC bus short circuits. Historical weather data, including irradiance and temperature from a real-site weather station, are streamed to the HIL-based model via User Datagram Protocol (UDP) communication, replicating realistic operating conditions. A cost-effective real-time monitoring architecture is established using a low-cost Single Board Computer (SBC), with data logged in InfluxDB and visualized through Grafana. Results are analysed through flowcharts depicting failure propagation, offering insights into system resilience and control performance. The testbed facilitates the validation of anomaly detection techniques and Energy Management Systems (EMS), while minimizing the need for physical prototyping. This approach enhances operational safety and accelerates development efficiency in renewable hydrogen infrastructures.","author":[{"family":"Hueros-Barrios","given":"Pablo"},{"family":"Espolio-Maestro","given":"Jorge"},{"family":"Rodríguez-Carrasco","given":"Sergio"},{"family":"Santos-Pérez","given":"Carlos"},{"family":"Rodríguez-Sánchez","given":"Francisco"},{"family":"Sánchez","given":"Pedro"},{"family":"Tradacete-Ágreda","given":"Miguel"},{"family":"Blaabjerg","given":"Frede"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.segan.2026.102152","URL":"https://doi.org/10.1016/j.segan.2026.102152","source":"openalex"},{"id":"oa:W4410597221","type":"article-journal","title":"Rewiring Sustainability: How Digital Transformation and Fintech Innovation Reshape Environmental Trajectories in the Industry 4.0 Era","abstract":"This study investigates the long-run impact of digital transformation and fintech innovation on environmental sustainability across OECD countries from 1999 to 2024. Drawing on a novel empirical framework that integrates panel fully modified ordinary least squares, the system-generalized method of moments, and machine learning estimators, the analysis captures both linear and nonlinear dynamics while addressing heterogeneity, endogeneity, and structural complexity. Environmental sustainability is measured by per capita CO2 emissions, while digital transformation and fintech innovation are proxied by secure internet servers and G06Q patent applications, respectively. The findings reveal that both digital infrastructure maturity and fintech-driven innovation significantly reduce carbon emissions, suggesting that technologically advanced digital ecosystems serve as effective instruments for climate mitigation. Robustness checks via the system-generalized method of moments confirm the stability of these relationships, while machine learning models—Random Forest and XGBoost—highlight digital variables as top predictors of emissions reduction. The convergence of results across estimation methods underscores the reliability of the digital–environmental nexus. Policy implications emphasize the need to embed sustainability metrics into digital strategies, promote green fintech regulation, and prepare labor markets for Industry 4.0 transitions. These findings position digital and fintech innovation not merely as enablers of economic growth, but as structural levers for achieving environmentally sustainable development in high-income economies.","author":[{"family":"Teng","given":"Zhuoqi"},{"family":"Xia","given":"Han"},{"family":"He","given":"Yugang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/systems13060400","URL":"https://doi.org/10.3390/systems13060400","source":"openalex"},{"id":"oa:W7138929100","type":"article-journal","title":"Remaining Life Prediction of Power Modules With Digital Twin and Multisource Data Fusion","abstract":"Intelligent power module (IPM) is a critical component of a power conversion system, and accurately predicting the lifetime of the key internal component, the insulated gate bipolar transistor (IGBT), is critical to the safe operation of the system. However, numerous challenges, such as monitoring difference of the internal state, variable degradation processes, and diverse field strengths, make it difficult to predict the IGBT lifetime accurately. Therefore, this paper proposes a remaining useful life (RUL) prediction method based on multi-source data fusion under limited information conditions. A prediction model combining Position Attention Module (PAM) and Long Short-Term Memory Network (LSTM) is designed to accommodate the large variability of the degradation process to enhance the ability to capture the spatio-temporal dependence of degradation features. In addition, to address the difficulty of internal state monitoring and the diversity of operating field strengths, this study constructs a Digital Twin (DT) model of the intelligent power module based on Finite Element Analysis (FEA) to comprehensively analyze the internal state of the device and provide accurate data support for RUL prediction. Meanwhile, to tackle the problems of insufficient health indicators, incomplete failure information, and end-of-life (EOL) fluctuation, a multi-indicator double-layer determination mechanism is proposed to improve the accuracy of the predicted EOL. Eventually, the prediction of the RUL of intelligent power module is achieved under limited observation information. The proposed method is experimentally verified on a 10 A/1200 V IPM from STMicroelectronics with accurate prediction results, and its superiority is further proved by comparing it with other methods.","author":[{"family":"Xia","given":"Qian"},{"family":"Lü","given":"Chang"},{"family":"Hou","given":"Yuluo"},{"family":"Wu","given":"Chenhao"},{"family":"Cui","given":"Zhexin"},{"family":"Abbas","given":"Waseem"},{"family":"Lee","given":"Hiu"},{"family":"Yue","given":"Jiguang"},{"family":"Lyu","given":"Feng"},{"family":"Ahmed","given":"Md"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/tpel.2026.3675186","URL":"https://doi.org/10.1109/tpel.2026.3675186","source":"openalex"},{"id":"oa:W7125392822","type":"article-journal","title":"Empowering the pharmaceutical workforce for the digital future","abstract":"The pharmaceutical industry is undergoing a rapid digital transformation. These changes are reshaping drug substance and drug product development and manufacturing, creating both opportunities and challenges that span pharmaceutical sciences, data science, and automation engineering. However, significant skills gaps persist, limiting the sector's ability to fully leverage digital technologies and sustain innovation. This paper explores the shifting digital and data science skills needs within the pharmaceutical industry, with a focus on industrial pharmacy and pharmaceutical sciences in the UK and Europe. We examine the key technological transformations reshaping the sector, the evolution of job roles, and the attributes required of the future workforce. Building on these insights, we propose an integrated approach to skills development that spans the entire career lifecycle - from embedding digital competencies in higher education to supporting lifelong learning through flexible, industry-aligned continuing professional development. Addressing these skills gaps requires coordinated action from academia, industry, and policymakers. By fostering a collaborative, interdisciplinary, and adaptive learning ecosystem, the pharmaceutical sector can equip its workforce to thrive in a rapidly changing landscape and continue improving global health and wellbeing.","author":[{"family":"Maclean","given":"Natalie"},{"family":"Abrahmsénalami","given":"Susanna"},{"family":"Clark","given":"Catriona"},{"family":"Dörr","given":"Frederik"},{"family":"Florence","given":"Alastair"},{"family":"Ketolainen","given":"Jarkko"},{"family":"Lindow","given":"Morten"},{"family":"Mantanus","given":"Jérôme"},{"family":"Rantanen","given":"Jukka"},{"family":"Reynolds","given":"Gavin"},{"family":"Robertson","given":"Amy"},{"family":"Markl","given":"Daniel"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.ejps.2026.107449","URL":"https://doi.org/10.1016/j.ejps.2026.107449","source":"openalex"},{"id":"oa:W4411611664","type":"article-journal","title":"Literature review of integrating sustainability and digital innovation in waterway transport and maritime logistics","abstract":"Modern waterway transport and maritime logistics industries are being transformed through sustainable practices combined with digital innovation which leads to better operational efficiency along with decreased environmental effects. Green technology adoption requires support from regulatory frameworks and financial incentives to meet emission reduction standards and promote investments in alternative fuels and energy-efficient solutions. IoT-enabled cargo tracking alongside blockchain supply chain transparency and AI predictive maintenance systems improve operational dependability through better resource management. Sustainable practices, including energy-efficient vessel design, route optimization, and shore power integration, contribute to lower fuel consumption and emissions. Smart ports and automated terminals streamline cargo handling, reducing energy use and improving supply chain efficiency. This study examines the relationship between regulatory policies, digital enablers, and sustainability strategies, demonstrating their collective impact on creating a more efficient and environmentally responsible maritime sector. This systematic review examines the intersection of sustainability and digital innovation in waterway transport and maritime logistics. Studies were sourced from Scopus, Web of Science, IEEE Xplore, ScienceDirect, and JSTOR, covering literature on supply chain efficiency, green technology, maritime logistics, inland waterway transport and digital transformation. A total of 52 studies met the inclusion criteria, focusing on regulatory policies, blockchain-enabled transparency, AI-driven predictive maintenance, and sustainable maritime and inland waterway operations. Findings highlight that digitalization enhances environmental sustainability while improving logistical efficiency. Future research should explore policy frameworks that encourage eco-digital maritime ecosystems. This study adheres to PRISMA 2020 guidelines to ensure transparency and rigor.","author":[{"family":"Ugrinov","given":"Stefan"},{"family":"Ćoćkalo","given":"Dragan"},{"family":"Bakator","given":"Mihalj"},{"family":"Stanisavljev","given":"Sanja"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5937/jaes0-57039","URL":"https://doi.org/10.5937/jaes0-57039","source":"openalex"},{"id":"oa:W7114905033","type":"article-journal","title":"Twin Threats in Digital Workplace: Technostress and Work Intensification in a Dual-Path Moderated Mediation Model of Employee Health","abstract":"This study investigates how technostress and work intensification jointly influence employee health harm through two distinct stressor-strain pathways within Pakistan's manufacturing sector. The proposed model specifies two mechanisms, (1) technostress induces IT strain that contributes to health harm, moderated by user satisfaction; and (2) work intensification heightens emotional exhaustion that similarly leads to health harm, moderated by perceived organizational support. Grounded in Conservation of Resources (COR) theory, the framework explains how cumulative digital and organizational demands deplete employee resources, amplifying both psychological and physical harm. A cross-sectional quantitative design was employed, utilizing a structured self-administered questionnaire administered to mid and senior-level employees across manufacturing firms. A total of 252 valid responses were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) using Smart PLS 4. Results revealed that both IT strain and emotional exhaustion significantly mediated the effects of technostress and work intensification, respectively, on health harm. Moreover, user satisfaction significantly moderated the IT strain-health harm relationship, indicating that higher satisfaction with digital tools mitigates the adverse impact of technological stress. Similarly, organizational support weakened the association between emotional exhaustion and health harm, underscoring its protective role in high-pressure work settings. This study offers theoretical advancement by integrating fragmented stressor-strain models and offers practical recommendations to foster digital well-being and supportive organizational work cultures in evolving industrial contexts.","author":[{"family":"Malik","given":"Muhammad"},{"family":"Ali","given":"Mubashar"},{"family":"Malik","given":"Asad"},{"family":"Malik","given":"Shamir"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/ijerph22121856","URL":"https://doi.org/10.3390/ijerph22121856","source":"openalex"},{"id":"oa:W7140405207","type":"article-journal","title":"D2M (design-to-manufacturing) by integrating digital twins and large language models: conceptual framework","abstract":"The rapid growth of digital technologies and artificial intelligence has made digital twins (DTs) and large language models (LLMs) core tools in smart manufacturing. This paper presents a review of DT-LLM integration in manufacturing systems. The review examines key technologies, methods, and application of DT-LLM in the manufacturing industry. The analysis of the reviewed paper identifies promising research area that bridge customised and even personalised demands with flexible production systems. Inspired by this, a novel concept termed Design-to-Manufacturing (D2M) is introduced. Furthermore, a conceptual DT-LLM-enabled D2M framework is proposed to demonstrate how the integration of DT and LLM can revolutionise the traditional design-to-manufacturing process. This framework incorporates digital twin data, generative design, human-AI augmented decision-making, and flexible human-robot collaborative manufacturing system. This paper offers valuable insights into a new manufacturing paradigm designed to meet the rising demand for personalised products.","author":[{"family":"Zhang","given":"Zimo"},{"family":"Li","given":"Juntao"},{"family":"Xiong","given":"Junyan"},{"family":"Tang","given":"DYK"},{"family":"Wang","given":"Qingyang"},{"family":"Guo","given":"Dai"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/27525783.2026.2645373","URL":"https://doi.org/10.1080/27525783.2026.2645373","source":"openalex"},{"id":"oa:W4417198715","type":"article-journal","title":"Digital Twin-Enabled Distributed Robust Scheduling for Park-Level Integrated Energy Systems","abstract":"With the deepening of multi-energy coupling and the integration of high proportions of renewable energy, the Park Integrated Energy System (PIES) 1demonstrates enhanced energy utilization flexibility. However, the random fluctuations in photovoltaic (PV) output also pose new challenges for system dispatch. Existing distributed robust scheduling approaches largely rely on offline predictive models and therefore lack dynamic correction mechanisms that incorporate real-time operational data. Moreover, the initial probability distribution of PV output is often difficult to obtain accurately, which further degrades scheduling performance. To address these limitations, this paper develops a PV digital twin model capable of providing more accurate and continuously updated initial probability distributions of PV output for distributed robust scheduling in PIESs. Building upon this foundation, this paper proposes a distributed robust scheduling method for the PIES based on digital twins. This approach aims to maximize the flexibility of energy utilization in PIESs and overcome the challenges posed by random fluctuations in PV output to PIES operational scheduling. First, a PIES model is established after investigating a park-level practical integrated energy system. To describe the uncertainty of PV output, a PV digital twin model that incorporates historical data and temporal features is developed. The long short-term memory (LSTM) neural network is employed for output prediction, and real-time data are integrated for dynamic correction. On this basis, error perturbations are introduced, and PV scenario generation and reduction are carried out using Latin hypercube sampling and k-means clustering. To achieve multi-energy cascade utilization, the objective of optimization is defined as the minimization of the sum of system operating cost and curtailment cost. To this end, a two-stage distributed robust optimization model is constructed. The optimal scheduling scheme was obtained by solving the problem using the column-and-constraint generation (CCG) algorithm. The proposed method was finally validated through a case study involving an actual industrial park. The findings indicate that the constructed digital twin model achieves a significant improvement in prediction accuracy compared to traditional models, with the root mean square error and mean absolute error reduced by 13.3% and 10.81%, respectively. Furthermore, the proposed distributed robust scheduling strategy significantly enhances the operational economics of PIESs while maintaining system robustness, compared to conventional methods, thereby demonstrating its practical application value in PIES scheduling.","author":[{"family":"Chang","given":"Xiao"},{"family":"Li","given":"Shengwen"},{"family":"Wang","given":"Qiang"},{"family":"Ji","given":"Liang"},{"family":"Huang","given":"Bo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/en18246471","URL":"https://doi.org/10.3390/en18246471","source":"openalex"},{"id":"oa:W4407372557","type":"article-journal","title":"Digital restoration of ancient loom: evaluation of the digital restoration process and display effect of Yunjin Dahualou Loom","abstract":"The Yunjin Dahualou Loom is a precious artifact of China’s cultural heritage, with its production and weaving techniques recognized as invaluable intangible cultural heritage. This paper presents a digital restoration of the Yunjin Dahualou Loom, utilizing digital technology to preserve and inherit textile artifacts while addressing challenges such as the difficulty in the long-term preservation of wooden structures and the lengthy cycles involved in traditional restoration processes. Initially, field research was conducted to gather detailed information regarding the loom’s dimensions, structure, materials, manufacturing principles, and weaving techniques. Using AutoCAD software, the overall structure and weaving principles of the Yunjin Dahualou Loom were systematically organized and visually mapped. Next, Autodesk 3ds Max software was employed to digitally restore and assemble the loom’s various components, while also reconstructing its manufacturing and weaving principles in a digital environment. VRay software was then used to generate materials for the loom and render the scene in high fidelity. Finally, a combined approach using the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation is employed to assess the quality of digital restoration. The AHP is used to calculate weight coefficients, which are then verified through consistency checks. These weights are combined with data collected from fuzzy comprehensive evaluation to assess the digital restoration results. Finally, based on the principle of maximum membership degree, the digital restoration of the Yunjin Dahualou Loom is rated as “very good.” These findings demonstrate that the proposed method effectively reconstructs the loom’s form, structure, and weaving principles, completing its digital restoration. This approach provides a novel and relatively comprehensive method for the dynamic protection of cultural heritage and intangible cultural heritage.","author":[{"family":"Li","given":"Hongyu"},{"family":"Zhang","given":"Jinyu"},{"family":"Peng","given":"Weili"},{"family":"Tian","given":"XC"},{"family":"Shi","given":"Jin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s40494-025-01591-4","URL":"https://doi.org/10.1038/s40494-025-01591-4","source":"openalex"},{"id":"oa:W4410571248","type":"article-journal","title":"Digital Transformation in Agricultural Supply Chains Enhances Green Productivity: Evidence From Provincial Data in China","abstract":"Abstract As global agricultural systems strive to achieve a balance between productivity and sustainability, digital technologies are increasingly recognized for their transformational potential in optimizing supply chain processes. However, the empirical understanding of how digitalization affects green agricultural productivity, especially in developing economies, remains limited. This study explores the influence of digital transformation on green productivity in China's agriculture based on provincial data from 2011 to 2023. The findings reveal that digitalization significantly enhances green productivity, with the consumption stage exerting the greatest effect. Moreover, digital agricultural solutions reduce crop disaster rates, thereby improving resilience and further driving green productivity. These results emphasize the critical role of digitalization in fostering sustainable agricultural practices.","author":[{"family":"Yu","given":"Haiyan"},{"family":"Qubi","given":"Wuniu"},{"family":"Luo","given":"Juan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1029/2025ef006089","URL":"https://doi.org/10.1029/2025ef006089","source":"openalex"},{"id":"oa:W7161641536","type":"article-journal","title":"AI-Enhanced Digital Twin Augmented Reality System for Precision Cranial Trauma Reconstruction.","abstract":"The process of reconstructing cranial trauma requires precise medical work because it needs multiple medical disciplines to work together while using special visual technology. The study introduces an AI-powered Digital Twin Augmented Reality system which enhances surgical planning and intraoperative support and creates personalized reconstruction results. The system creates a dynamic digital twin model of cranial structures by combining patient imaging data which includes CT and MRI scans. The system uses artificial intelligence algorithms to study anatomical differences which help determine the best reconstruction methods and create implant designs. The augmented reality component enables real-time visualization of the digital twin overlaid onto the patient’s anatomy which improves spatial understanding and surgical performance. The system uses artificial intelligence analytics together with augmented reality visualization to achieve accurate alignment while it minimizes uncertainty during surgery and protects against potential complications. Surgeons use the platform's preoperative simulation tools to practice their surgical procedures by testing various reconstruction techniques before actual surgery begins. The experimental results prove that the new method improves accuracy for defect reconstruction while reducing surgical time and enhancing decision-making processes when compared to existing methods. The system uses digital twin technology to provide continuous system updates which operate based on feedback received during surgical procedures thus creating a surgical environment that responds to changes and develops through time. The research demonstrates how artificial intelligence, digital twin modeling and augmented reality technology combine to create advancements in precision medicine for cranial trauma treatment. The system delivers an expandable and cuttingedge solution which will enhance clinical results while streamlining surgical processes and advancing the field of personalized reconstructive surgery","author":[{"family":"Saeed","given":"Soobia"},{"family":"Qadeer","given":"Mohsin"},{"family":"Malik","given":"Noor"},{"family":"Riaz","given":"Izaz"},{"family":"Mcginley","given":"Christopher"},{"family":"Shah","given":"Halah"},{"family":"Riaz","given":"Muhammad"}],"issued":{"date-parts":[[2026]]},"DOI":"10.25258/ijddt.16.28s.96","URL":"https://doi.org/10.25258/ijddt.16.28s.96","source":"openalex"},{"id":"oa:W4413441998","type":"article-journal","title":"Exploring the Role of Digital Twin Technology in Enhancing Supply Chain Resilience: A Conceptual Framework","abstract":"This study explores to development of a comprehensive conceptual framework that integrates technological enablers, operational processes, and resilience outcomes, providing insights into how DTs can address disruptions and improve supply chain performance. The study adopts a conceptual approach, synthesising insights from extensive literature, theoretical underpinnings, and expert input. Key dimensions of the framework—inputs, processes, and outcomes—were identified and structured to illustrate the dynamic relationships between DT technology and resilience. The framework is supported by socio-technical systems theory, the Resource-Based View, and complexity theory to contextualise the interactions between technology and supply chain dynamics. The proposed framework identifies critical enablers, such as IoT, AI, and simulation tools, and links them to key supply chain processes, including real-time monitoring, risk assessment, and scenario planning. These processes enhance resilience dimensions, such as responsiveness, flexibility, and risk mitigation. The study highlights the transformative potential of DTs in improving visibility and decision-making within supply chains. This research fills a significant gap in the existing literature by providing an integrated framework that connects DT technology with supply chain resilience strategies. Supply chain practitioners can leverage this framework to systematically implement DT technology, improving real-time visibility and preparing for potential disruptions through advanced risk assessment and scenario planning.","author":[{"family":"Nagarathnam","given":"Jivaranee"},{"family":"Chinniah","given":"Muruga"},{"family":"Jayamani","given":"Umahdevi"},{"family":"Ibrahim","given":"Irwan"},{"family":"Narayanan","given":"NSP"},{"family":"Sundram","given":"Veera"}],"issued":{"date-parts":[[2025]]},"DOI":"10.22610/imbr.v17i2(i)s.4619","URL":"https://doi.org/10.22610/imbr.v17i2(i)s.4619","source":"openalex"},{"id":"oa:W7108327349","type":"article-journal","title":"Development of a didactic solution for teaching concepts related to Digital Twins using Educational Robot","abstract":"Engineering education faces ongoing challenges in keeping pace with the technological demands driven by the need to apply Industry 4.0 concepts in student training. In response to this, the present study introduces the development of a pedagogical tool built around an educational robot produced through 3D printing. The aim is to integrate active learning methodologies with key Industry 4.0 technologies, such as Digital Twins, asset administration shells, and computational simulation, to create a practical and dynamic learning environment. This hands-on approach was implemented in a graduate-level course on Advanced manufacturing engineering, specifically in the Process simulation module. The activity involved the use of the robot alongside a real-time, bidirectional computational model capable of reading and writing data, applying the Digital Twin concept. The study followed a mixed-method action research design. Results from a student feedback survey revealed that 100% of participants agreed the experience with the computational robot helped solidify theoretical concepts. Furthermore, 77.3% gave the learning experience the highest possible rating, and 95.5% recognized the robot’s potential for use in other modules and courses. These findings suggest that this approach offers an effective strategy for engineering education that is aligned with the principles of Industry 4.0.","author":[{"family":"Freires","given":"Vitoria"},{"family":"Lucas","given":"Atila"},{"family":"Silva","given":"Roberto"},{"family":"Almeida","given":"Ely"}],"issued":{"date-parts":[[2025]]},"DOI":"10.24867/ijiem-398","URL":"https://doi.org/10.24867/ijiem-398","source":"openalex"},{"id":"oa:W4408506420","type":"article-journal","title":"ATTD 2025 Amsterdam & Online—19–22 March and ATTD-ASIA 2024 Singapore—18–20 November","abstract":"Background and Aims: The DiaGame project develops and tests a new concept to empower patients with diabetes in their self-management. We combine real world data with advanced computational algorithms and models and serious gaming. Methods: Data has been collected in daily-life settings in sixty participants (52 type 2 diabetes, 8 type 1 diabetes) using a continuous glucose monitor, smartwatch with in-house software, and public smartphone application acquiring data on blood glucose levels, heart rate, step count, acceleration, participant-reported dietary intake, physical activity, insulin dosing, and mood. We develop and validate a physiology-based mathematical model of the glucose-insulin system to describe and predict glycemic dynamics. This model simulates glucose and insulin concentrations following a mixed meal or OGTT and has previously been validated. Results: The model has been successfully extended to describe the subcutaneous absorption of various insulin analogues, which is important for patients using insulin (type 1 diabetes and type 2 diabetes with intensive insulin therapy). The model accurately captures patient-specific glycemic dynamics of people with T1D. To realize personalized models for T2D patients it is important to consider residual insulin production capacity. By analyzing and comparing personalized models the independent and coherent effects of various lifestyle factors on glycemic dynamics are elucidated. Conclusions: Patient digital twins are developed by updating personalized prediction models with patient-gathered, real world data. Ultimately, these digital twins will be employed to aid self-management education through a personalized interactive serious game. A prototype of this game is currently being evaluated by patients and caregivers.","author":[{"family":"De Vries","given":"Ryan"},{"family":"Reinders","given":"Edouard"},{"family":"Cruts","given":"Elma"},{"family":"Wouters-Van Poppel","given":"Pleun"},{"family":"Hilbers","given":"Peter"},{"family":"Haak","given":"Harm"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1089/dia.2024.78502.abstracts","URL":"https://doi.org/10.1089/dia.2024.78502.abstracts","source":"openalex"},{"id":"oa:W4413928935","type":"article-journal","title":"From Data to Cultural Response: A Machine Learning–Driven Digital Twin Model for Smart Heritage Precincts in Urban Context","abstract":"In the context of Smart Cities, Smart Heritage has emerged as a forward-oriented strategy aimed at enhancing the construction, management, accessibility, and sustainability of culturally significant environments. Yet, within Smart Heritage discourse, the distinction between basic digital representations and truly responsive, sensor-informed systems remains underdeveloped. This study addresses this gap by proposing a machine learning–enhanced digital twin simulation framework that enables both real-time and anticipatory heritage interventions. Using Chinatown Melbourne as an urban heritage case study, five open-access urban datasets, pedestrian counting, on-street parking, microclimate conditions, dwelling functionality, and Microlab sensor data (CO₂, sound level, and accelerometer), were evaluated, with three integrated into a pilot simulation model. A key contribution is the inclusion of a conceptual ‘Heritage Layer’ that overlays cultural significance and symbolic meaning across all stages of system logic and design response. The model also incorporates a dedicated machine learning layer, trained on full-year 2024 sensor data, to forecast environmental and behavioural triggers such as crowd build-up. This predictive capability enables the system to shift from reactive monitoring to proactive design interventions aligned with cultural rhythms. A December 2024 simulation validated the frequency and relevance of trigger-based activations. Rather than relying on platform-specific code, the framework is designed for adaptability across construction informatics environments and heritage precincts globally. Findings demonstrate how Smart Heritage systems can bridge environmental sensing, cultural identity, and post-construction evaluation, offering a scalable methodology for digitally responsive, culturally attuned urban heritage management.","author":[{"family":"Geng","given":"Shiran"},{"family":"Yan","given":"Se"},{"family":"Chau","given":"Hing"},{"family":"Jamei","given":"Elmira"},{"family":"Vrcelj","given":"Zora"}],"issued":{"date-parts":[[2025]]},"DOI":"10.36680/j.itcon.2025.053","URL":"https://doi.org/10.36680/j.itcon.2025.053","source":"openalex"},{"id":"oa:W4409406920","type":"article-journal","title":"AI-POWERED PERSONALIZATION IN DIGITAL BANKING: A REVIEW OF CUSTOMER BEHAVIOR ANALYTICS AND ENGAGEMENT","abstract":"The rapid evolution of digital banking has prompted financial institutions to integrate artificial intelligence (AI) technologies to deliver highly personalized and engaging customer experiences. As customer expectations grow increasingly dynamic, AI-powered personalization has emerged as a strategic imperative, enabling banks to tailor services in real time based on individual behaviors, preferences, and financial patterns. This study systematically reviews the literature on AI-powered personalization in digital banking, with a specific focus on how customer behavior analytics and intelligent algorithms contribute to enhanced engagement, satisfaction, retention, and trust. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 framework, a total of 111 peer-reviewed articles published between 2014 and 2024 were analyzed to identify core themes, methodologies, innovations, and conceptual gaps. The reviewed literature is thematically organized into seven key domains: foundational AI techniques, behavioral data modeling, predictive analytics, customer engagement outcomes, ethical and governance challenges, innovations in emerging markets, and research limitations. The findings reveal that AI-driven personalization not only improves operational efficiency and service quality but also fosters emotional loyalty and increases the lifetime value of banking customers. Advanced AI techniques—such as machine learning, natural language processing, recommender systems, and sentiment analysis—are widely applied to deliver seamless, context-aware experiences across mobile apps, web portals, and virtual assistants. However, the literature also highlights significant challenges, including inconsistent measurement frameworks, regulatory uncertainty, data privacy concerns, and insufficient attention to cultural diversity and longitudinal performance. Emerging markets, while constrained by infrastructural and regulatory limitations, exhibit innovative adaptations through alternative data use and hybrid AI-human service delivery models. This review offers a comprehensive synthesis of the academic discourse on AI personalization in digital banking and underscores critical areas for future research, industry practice, and policy intervention aimed at building inclusive, ethical, and scalable AI solutions.","author":[{"family":"Ashrafuzzaman","given":"Md"},{"family":"Parveen","given":"Rokhshana"},{"family":"Sumiya","given":"Mahiya"},{"family":"Rahman","given":"Anisur"}],"issued":{"date-parts":[[2025]]},"DOI":"10.63125/z9s39s47","URL":"https://doi.org/10.63125/z9s39s47","source":"openalex"},{"id":"oa:W7161031213","type":"article-journal","title":"Toward Real-Time Digital Twins for CO₂ Storage: Graph Neural Network Ensembles for Multi-physics Forecasting and Risk Quantification","abstract":"Accurate forecasting of CO₂ plume migration, geochemical alteration, and geomechanical deformation is essential for secure geological carbon storage, yet high-fidelity thermo-hydro-mechanical-chemical (THMC) simulators remain too expensive for rapid uncertainty screening and digital-twin-style updates. This study develops a graph-based multi-output surrogate trained on THMC simulation outputs to predict three engineering observables relevant to storage performance and risk assessment: gas saturation (Sg), formation-water pH, and vertical surface displacement. The framework is evaluated over a century-long period from 2031 to 2130, spanning both injection and post-injection phases. Three baseline architectures are compared under a strict realization-level split, namely a multilayer perceptron (MLP), a convolutional neural network (CNN), and a graph neural network (GNN). Among the tested baselines, the GNN delivers the strongest overall accuracy and the most faithful spatial reconstruction, particularly for plume front geometry and deformation localization under unseen geological realizations. At the same time, the proposed model should be interpreted as an emulator of simulator-derived observables rather than as a conservation-enforcing THMC solver. We therefore position the framework as a fast forecasting layer complemented by uncertainty quantification and physics-aware plausibility checks, not as a replacement for full-physics simulation in regulatory or site-specific design studies. Millisecond-scale inference and calibrated ensemble prediction intervals make the approach useful for rapid scenario screening, monitoring support, and digital-twin workflows, while future work should incorporate explicit conservation constraints, richer nonlinear geomechanics, and larger training ensembles.","author":[{"family":"Thanh","given":"Hung"},{"family":"Dai","given":"Zhenxue"},{"family":"Zhang","given":"Tao"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s00603-026-05545-5","URL":"https://doi.org/10.1007/s00603-026-05545-5","source":"openalex"},{"id":"oa:W4407031055","type":"article-journal","title":"Exploring the Mechanisms and Pathways Through Which the Digital Transformation of Manufacturing Enterprises Enhances Green and Low-Carbon Performance Under the “Dual Carbon” Goals","abstract":"The coordinated development of digitalization and greening is essential for economic transformation and upgrading, especially given the pressing global carbon emission challenges. China’s commitment to achieving “dual carbon” goals highlights the need for sustainable solutions, particularly in the manufacturing sector, which is a significant source of energy consumption and emissions; carbon emissions account for more than 30%. Integrating advanced digital technologies with manufacturing is critical for reducing carbon and sustainable growth. According to the research results, more than 70% of scholars believe that digital transformation boosts green innovation and low-carbon development, but the mechanisms still need to be clarified, slowing transformation efforts and reducing efficiency. Taking the intellectualization and green low-carbon development of manufacturing enterprises as latent variables, and taking the nine paths obtained by scholars’ research results and investigation interviews to promote green low-carbon performance as observation variables, this paper constructs a structural equation model and deeply explores the mechanism and paths of the intellectualization transformation of manufacturing enterprises affecting carbon reduction, emission reduction and sustainable development of enterprises. The research results show that the digital intelligent transformation of manufacturing enterprises affects the green and low-carbon performance improvement and sustainable development of enterprises through technological innovation, industrial structure transformation and upgrading, and reshaping resource allocation. These strategies lower energy use and emissions, strengthen sustainability, and improve green performance. The findings offer theoretical and practical insights, providing a roadmap for efficient digital transformation in manufacturing to achieve the “dual carbon” goals and support sustainable development.","author":[{"family":"Liu","given":"Jun"},{"family":"Zhang","given":"Peng"},{"family":"Wang","given":"Xiaofei"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17031162","URL":"https://doi.org/10.3390/su17031162","source":"openalex"},{"id":"oa:W4411646643","type":"article-journal","title":"Bibliometric analysis and review of AI-based video generation: research dynamics and application trends (2020–2025)","abstract":"AI-based video generation is rapidly advancing field with significant research focus and broad applications across industries like entertainment, education, and healthcare. To gain a structured understanding of the field, this paper systematically reviews the research dynamics and application trends in video generation from 2020 to April 2025. Utilizing a combined approach of content analysis and bibliometric analysis on 422 research publications selected from the Web of Science Core Collection database, we investigate key developments. The content analysis examines state-of-the-art algorithmic innovations, generation strategies, and prominent application domains. Bibliometric analysis, employing tools like CiteSpace and VOSviewer, maps publication trends, identifies influential authors, institutions, and sources, visualizes collaboration networks, and analyzes the evolution of research hotspots through keywords. Our findings the rise of specific architectures, pinpoint high-activity application areas, reveal evolving thematic clusters, and also remarks persistent challenges, including technical hurdles and critical ethical issues such as deepfake detection, algorithmic transparency, and data privacy. By synthesizing these analyses, this study offers a structured overview of the recent landscape, and highlights areas that may warrant further exploration in AI video generation.","author":[{"family":"Xie","given":"Wei"},{"family":"Hu","given":"Anshu"},{"family":"Xie","given":"Qing"},{"family":"Chen","given":"Junjie"},{"family":"Wan","given":"Ruoyu"},{"family":"Liu","given":"Yuhan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s10791-025-09628-9","URL":"https://doi.org/10.1007/s10791-025-09628-9","source":"openalex"},{"id":"oa:W4411858040","type":"article-journal","title":"Integrating AI in digital project-based blended learning to enhance critical thinking and problem-solving skills","abstract":"This study investigates the impact of a Digital Project-Based Blended Learning (DPBBL) framework, augmented with Artificial Intelligence (AI), on enhancing students' critical thinking and problem-solving abilities. A mixed-methods research design was employed, involving 72 students, who were randomly assigned to either an experimental group (n = 36) utilizing the AI-supported DPBBL framework or a control group (n = 36) engaged in traditional mixed learning methods. Pre-test and post-test assessments were conducted to measure the effectiveness of the intervention. The results indicated a statistically significant improvement in the experimental group, with a mean post-test score of 78.39 compared to the control group’s 73.89. The integration of AI in the DPBBL framework facilitated personalized feedback, adaptive learning pathways, and real-time analytics, which promoted deeper cognitive engagement and higher-order thinking. The findings suggest that the AI-enhanced DPBBL model effectively supports active learning, collaboration, and practical problem-solving skills. However, the study also identified areas for further improvement, such as fostering divergent thinking and reflective evaluation. This research contributes to the educational technology field by demonstrating the potential of AI-enhanced blended learning models to bridge the gap between theoretical knowledge and practical application, offering scalable solutions to contemporary educational challenges. Future research should explore the long-term effects and feasibility of large-scale implementation of this framework.","author":[{"family":"Kurniawan","given":"Dydik"},{"family":"Masitoh","given":"Siti"},{"family":"Bachri","given":"Bachtiar"},{"family":"Warman"},{"family":"Kamila","given":"Vina"},{"family":"Subastian","given":"Eko"},{"family":"Sulfa","given":"Sulfa"},{"family":"Wahyuningsih","given":"Tri"}],"issued":{"date-parts":[[2025]]},"DOI":"10.31893/multiscience.2025552","URL":"https://doi.org/10.31893/multiscience.2025552","source":"openalex"},{"id":"oa:W4409904873","type":"article-journal","title":"Driving SDG15 : The Role of HEIs in Biodiversity Conservation Through Digitalization and Reporting","abstract":"ABSTRACT Education, research, and public engagement are key strategies guiding European higher education institutions (HEIs) in advancing the United Nations Sustainable Development Goals (SDGs). Through stakeholder, legitimacy, and resource‐based view theories, this study examines the contributions of HEIs to saving Life on Land (SDG15), focusing on the role of digital technologies and Partnerships (SDG17) in biodiversity conservation. Despite interest in biodiversity conservation and the adoption of digital technologies in HEIs, knowledge about SDG15 issues is still limited. A double‐level content analysis through Leximancer v.5 and manual analysis was performed on 653 documents (191 sustainability reports and 462 website pages) from 50 European HEIs published between 2018 and 2024. The results highlight the key role of SDG17 and digital technologies in supporting biodiversity conservation efforts but also reveal a lack of standardized reporting frameworks, underscoring the need for a unified European approach to biodiversity disclosure to ensure more consistent and impactful contributions toward the SDGs. To the best of the authors' knowledge, this is the first study to address knowledge gaps on biodiversity practices supported by digitalization and partnerships, as adopted and shared through sustainability reporting by the top 50 universities leading in land conservation in the Times Higher Education (THE) 2024 ranking.","author":[{"family":"Vaio","given":"Assunta"},{"family":"Engelenhoven","given":"Elisa"},{"family":"Zaffar","given":"Anum"},{"family":"Lepore","given":"Luigi"},{"family":"Paolone","given":"Francesco"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/sd.3504","URL":"https://doi.org/10.1002/sd.3504","source":"openalex"},{"id":"oa:W4414382941","type":"article-journal","title":"Talking Tech, Teaching with Tech: How Primary Teachers Implement Digital Technologies in Practice","abstract":"This paper explores how primary school teachers integrate digital technologies into their classroom practice, with a particular focus on the extent to which their stated intentions align with what actually takes place during lessons. Drawing on data from the Bulgarian SUMMIT project on digital transformation in education, the study employed a mixed-methods design combining semi-structured interviews, structured lesson observations, and analysis of teaching materials. The sample included 44 teachers from 26 Bulgarian schools, representing a range of educational contexts. The analysis was guided by the Digital Technology Integration Framework (DTIF), which distinguishes between three modes of technology use—Support, Extend, and Transform—based on the depth of pedagogical change. The findings indicated a strong degree of consistency between teachers’ accounts and observed practices in areas such as the use of digital tools for content visualisation, lesson enrichment, and reinforcement of knowledge. At the same time, the study highlights important gaps between teachers’ aspirations and classroom realities. Although many spoke of wanting to promote independent exploration, creativity, collaboration, and digital citizenship, these ambitions were rarely realised in observed lessons. Pupil autonomy and opportunities for creative digital production were limited, with extended and transformative practices appearing only occasionally. No significant subject-specific differences were identified: teachers across disciplines tended to rely on the same set of familiar tools, while more advanced or innovative uses of technology remained rare. Rather than offering a definitive account of progress, the study raises critical questions about teachers’ digital pedagogical competencies, contextual constraints and the depth of technology integration in everyday classroom practice. While digital tools are increasingly present, their use often remains limited to supporting traditional instruction, with extended and transformative applications still aspirational rather than routine. The findings draw attention to context-specific challenges in the Bulgarian primary education system and the importance of aligning digital innovation with pedagogical intent. This highlights the need for sustained professional development focused on learner-centred digital pedagogies, along with stronger institutional support and equitable access to infrastructure.","author":[{"family":"Aleksieva","given":"Lyubka"},{"family":"Racheva","given":"Veronica"},{"family":"Peytcheva-Forsyth","given":"Roumiana"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/informatics12030099","URL":"https://doi.org/10.3390/informatics12030099","source":"openalex"},{"id":"oa:W4415385645","type":"article-journal","title":"Integrating Digital Twins and Positive Energy Districts: A Framework for Scalable Urban Energy Transformation","abstract":"Positive Energy Districts (PEDs) offer a path to urban climate neutrality but present significant management complexity. Digital Twins (DTs), dynamic virtual replicas, provide powerful tools for monitoring, simulation, and control needed for PEDs. This paper proposes a structured conceptual and architectural framework for DT-PED integration, delineating functional layers (Data Acquisition, Virtual Modeling, Analytics Engine, Control, Stakeholder Interface) and their interdependencies. This framework provides a blueprint to leverage DTs for managing heterogeneous systems and data streams inherent in PEDs. Addressing key challenges in data, modeling, interoperability, and scalability, identified herein, is crucial for realizing robust, integrated DT-PED solutions needed to accelerate sustainable urban energy transformation.","author":[{"family":"Liu","given":"Xiufeng"},{"family":"Zhang","given":"Xiao"},{"family":"Sarı","given":"Ramazan"},{"family":"Nielsen","given":"Per"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1051/e3sconf/202565404007","URL":"https://doi.org/10.1051/e3sconf/202565404007","source":"openalex"},{"id":"oa:W4415059564","type":"article-journal","title":"Pulpit, power, and predation: “Yahoo Men of God,” prosperity theology, and the Twin Fraud Triangles","abstract":"We analyse public discourse on pastors’ unethical financial exploitation within the charismatic Christian community. Using qualitative content analysis of social-media responses, we examine how the public perceives, discusses, and interprets these cases, privileging emic viewpoints. We find that faith leaders are seen to exploit congregants’ social trust and spiritual devotion for personal gain. Grounded in Donald Cressey’s Fraud Triangle theory, we identify key components of fraudulent behavior in religious contexts while extending the framework to introduce the “Twin Fraud Triangles.” This expanded model incorporates both the cultural logic of perpetrators and the subjective experiences of their congregations and observers, providing a more nuanced understanding of fraud in religious settings. Our findings call for greater awareness and community-led safeguards to protect spiritual and financial well-being. This study contributes to ongoing debates on trust, authority, and moral economies within religious institutions, offering insights that could inform future community responses and interventions.","author":[{"family":"Lazarus","given":"Suleman"},{"family":"Tickner","given":"Peter"},{"family":"Button","given":"Mark"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1177/20503032251381309","URL":"https://doi.org/10.1177/20503032251381309","source":"openalex"},{"id":"oa:W4416196109","type":"article-journal","title":"Scan-to-EDTs: Automated Generation of Energy Digital Twins from 3D Point Clouds","abstract":"Digital Twins (DTs) are transforming construction and energy management sectors by integrating 3D surveying, monitoring, Building Performance Simulation (BPS), and Building Energy Simulation (BES) from the earliest design or retrofit stages. Moreover, dynamic thermal simulations further support energy performance assessments by modeling indoor conditions to meet comfort and efficiency targets. However, their reliability depends on accurate, standards-compliant 3D building models, which are costly to create. This research introduces a complete framework for automatically generating energy-focused Digital Twins (EDTs) directly from unstructured point clouds. Combining Deep Learning-based instance detection, Scan-to-BIM techniques, and computational geometry, the method produces simulation-ready models without manual intervention. The resulting EDTs streamline early-stage performance evaluation, enable scenario testing, and enhance decision making for energy-efficient retrofits, advancing smart-building design through predictive simulation.","author":[{"family":"Roman","given":"OV"},{"family":"Bassier","given":"Maarten"},{"family":"Agugiaro","given":"Giorgio"},{"family":"Ohori","given":"Ken"},{"family":"Farella","given":"Elisa"},{"family":"Remondino","given":"Fabio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15224060","URL":"https://doi.org/10.3390/buildings15224060","source":"openalex"},{"id":"oa:W4408577618","type":"article-journal","title":"A Twin Transition or a policy flagship? Emergent constellations and dominant blocks in green and digital technologies","abstract":"The aim of this paper is to understand whether what has been labelled as “twin transition”, at first as a policy flagship, endogenously emerges as a new technological trajectory stemming by the convergence of the green and digital technologies. Embracing an evolutionary approach to technology, we first identify the set of relevant technologies defined as “green”, analyse their evolution in terms of dominant blocks within the green technologies and concurrences with digital technologies, drawing on 560,720 granted patents by the US Patent Office from 1976 to 2024. Three dominant blocks emerge as relevant in defining the direction of innovative efforts, namely energy, transport and production processes. We assess the technological concentration and underlying complexity of the dominant blocks and construct counterfactual scenarios. We hardly find evidence of patterns of actual endogenous convergence of green and digital technologies in the period under analysis. On the whole, for the time being, the “twin transition” appears to be just a policy flagship, rather than an actual endogenous technological trajectory driving structural change.","author":[{"family":"Nelli","given":"Linnea"},{"family":"Virgillito","given":"Maria"},{"family":"Vivarelli","given":"Marco"}],"issued":{"date-parts":[[2025]]},"DOI":"10.53330/bfvc9329","URL":"https://doi.org/10.53330/bfvc9329","source":"openalex"},{"id":"oa:W7134270809","type":"article-journal","title":"AI-driven digital twin-based security orchestration, automation and response for critical infrastructures","abstract":"Abstract The more critical infrastructures (CIs) being digitized, the more vulnerable they are regarding cyber security attacks. Digitisation-leveraging technologies in the Internet of Things (IoT) and Cyber-Physical Systems (CPS) have been largely adopted for CIs, along with the Digital Twin (DT) paradigm. However, the distributed and heterogeneous nature of IoT or CPS poses significant challenges in safeguarding against diverse attack surfaces, including physical devices, network infrastructures, and third-party integration. To tackle these challenges, we propose an AI-driven DT-based security orchestration automation and response framework (SOAR4BC). Gathering system contexts from the DT in combination with security intelligence from the security tools gives us a holistic context for SOAR, which has not been seen in the existing approaches. We leverage this holistic context into the decision-making core, which utilizes advanced algorithms, like deep reinforcement learning, to generate adaptation recommendations based on incident alerts, risk assessments, and system state observations. By rigorously evaluating tampered data and distributed denial of service (DDoS) scenarios, we validate the SOAR4BC framework’s efficacy in handling security incidents leveraging digital twin environments. We further demonstrate real-world applicability through false-data injection and DoS attacks on an operational electric-vehicle charging testbed, confirming the practical effectiveness of SOAR4BC in securing critical infrastructures. Together, these results establish SOAR4BC as a robust and explainable AI-driven SOAR framework that advances the use of digital twins for cybersecurity in IoT and CPS ecosystems, offering actionable contributions for both research and industrial deployment.","author":[{"family":"Nguyen","given":"Phu"},{"family":"Rauniyar","given":"Ashish"},{"family":"Bartel","given":"Jone"},{"family":"Laufer","given":"Jan"},{"family":"Dalamagkas","given":"Christos"},{"family":"Pohl","given":"Klaus"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s10515-026-00612-1","URL":"https://doi.org/10.1007/s10515-026-00612-1","source":"openalex"},{"id":"oa:W7129386187","type":"article-journal","title":"Enhancing IIoT Security Using Digital Twins in Industry 5.0: A Systematic Literature Review","abstract":"The rapid advancement of Industry 5.0 and the concurrent growth of the Industrial Internet of Things (IIoT) present significant cybersecurity challenges necessitating advanced solutions. Digital Twin technology, which enables the creation of near-perfect digital replicas of physical systems, offers a promising approach to enhancing security and safety. This paper presents a literature review of the existing research to identify the challenges and future directions for integrating DT technology into IIoT from a security perspective. We aim to establish a comprehensive understanding of emerging features, including predictive analytics, real-time threat detection, and cybersecurity management. Additionally, this review highlights critical gaps, including complexity, model fidelity, real-time data processing, and scalability, which hinder the successful deployment of DT technology. Our study will assist researchers, cybersecurity practitioners, and policymakers in understanding the potential, limitations, and future advancements of this crucial area.","author":[{"family":"Whaiduzzaman","given":"Md"},{"family":"Monalisa","given":"Natasha"},{"family":"Himi","given":"Shinthi"},{"family":"Sultana","given":"Shirin"},{"family":"Jan","given":"Tony"},{"family":"Barros","given":"Alistair"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/info17020209","URL":"https://doi.org/10.3390/info17020209","source":"openalex"},{"id":"oa:W4415932675","type":"article-journal","title":"Integrating Reverse Engineering for Digital Model Reconstruction and Remanufacturing of Mechanical Components: A Systematic Review","abstract":"Reverse engineering (RE) is increasingly recognized as a vital methodology for reconstructing mechanical components, particularly in high-value sectors such as aerospace, transportation, and energy, where technical documentation is often missing or outdated. This study presents a systematic review that investigates the application, challenges, and future directions of RE in mechanical component reconstruction. Adopting the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, 68 peer-reviewed studies were identified, screened, and synthesized. The review highlights RE applications in restoration, redesign, internal geometry modeling, and simulation-driven performance assessment, leveraging technologies such as 3D scanning, CAD modeling, and finite element analysis. However, persistent challenges remain across five domains: product complexity, tolerance and dimensional variations, scanning limitations, integration barriers, and human-material-process dependencies, which hinder automation, accuracy, and manufacturability. Future research opportunities include the automated conversion of point cloud data into editable boundary representation (B-rep) models and AI-driven approaches for feature recognition, geometry reconstruction, and the generation of simulation-ready models. Additionally, advancements in scanning techniques to capture hidden or internal features more effectively are crucial. Overall, this review provides a comprehensive synthesis of current practices and challenges while proposing pathways to advance RE in industrial applications, fostering greater automation, accuracy, and integration in digital manufacturing workflows.","author":[{"family":"Debnath","given":"Binoy"},{"family":"Pourfarash","given":"Zahra"},{"family":"Ghorpade","given":"Bhairavsingh"},{"family":"Raman","given":"Shivakumar"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/metrology5040066","URL":"https://doi.org/10.3390/metrology5040066","source":"openalex"},{"id":"oa:W4409618405","type":"article-journal","title":"Revolutionizing Oil Production State Diagnosis With Digital Twin and Deep Learning Fusion Technology","abstract":"As global energy demand continues to grow, the efficiency and safety of oil and gas production systems have become increasingly important. However, the current‐state diagnosis technologies in the oil and gas production sector still face multiple challenges. Traditional monitoring methods often rely on experience and rule‐based approaches, making it difficult to reflect the actual operating status of the system in real time. These methods show insufficient accuracy and response speed when dealing with complex operating conditions and sudden events, leading to potential economic losses and safety hazards. Aiming to enhance the real‐time diagnostic capabilities of oil and gas production processes, this study introduces an improved long short‐term memory (LSTM) neural network into digital twin models. Digital twins have emerged as a potent tool for monitoring and diagnosing the state of oil and gas production processes. However, due to the inherent complexity of these processes, traditional digital twin models often underperform. To address this issue, we propose integrating an advanced LSTM neural network to improve the diagnostic accuracy and efficiency of these models in real‐time applications. Initially, a digital twin model is constructed based on the physical model of oil and gas production processes, simulating the behavior of the real system. Surface data are employed to estimate well data, which is subsequently used to train the LSTM neural network. This trained neural network analyzes real‐time data collected from sensors installed in the physical system and updates the digital twin model accordingly. By comparing the behavior of the real system with that of the digital twin model, deviations can be identified, allowing for accurate diagnosis of the production state. Furthermore, the improved neural network optimizes the performance of the digital twin model by mitigating the impact of complex production processes, enhancing diagnostic accuracy and efficiency. The LSTM network is utilized to predict the future state of oil and gas production based on real‐time data from the same block or well during different periods, enabling deep integration of physical and information layer data, as well as self‐perception and self‐prediction capabilities. Results demonstrate that the proposed method effectively monitors and predicts the operational state of oil and gas production, providing critical data to improve production efficiency. The integration of digital twins and deep learning technology can enhance the intelligence of oil and gas production processes and offer theoretical support for the development of intelligent oil and gas fields in the future.","author":[{"family":"Ren","given":"Shuangshuang"},{"family":"Zhang","given":"Xiangyang"},{"family":"Shen","given":"Fei"},{"family":"Zhu","given":"Longpeng"},{"family":"Li","given":"Jun"},{"family":"Liang","given":"Dong"},{"family":"Liu","given":"Yuanhong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1155/ijap/6480113","URL":"https://doi.org/10.1155/ijap/6480113","source":"openalex"},{"id":"oa:W4410214847","type":"article-journal","title":"A Systematic Literature Review on Integrating Machine Learning Algorithms and Metaheuristic Algorithms in Optimizing Sustainable Digital Architectural Design","abstract":"This systematic literature review investigates how machine learning (ML) algorithms and metaheuristic methods have been integrated into sustainable digital architectural design optimization over the past two decades. The study analyzes 42 peer-reviewed publications, highlighting the critical role of these technologies in enhancing energy efficiency, structural optimization, and environmental sustainability. This review showcases the growing use of ML and metaheuristics to reshape traditional architectural practices by addressing multi-objective optimization models such as generative design and performance improvement. Furthermore, the review outlines the approaches taken in the study, focusing on algorithmic decision-making for material and energy consumption optimization. Despite the promising advancements, several limitations are outlined, including non-standardized procedures and limited applications in practice. The research calls for mixed-method procedures and empirical studies for the validation of algorithmic models in real architectural projects. Practical implications of this study include the potential for ML and metaheuristic algorithms to enhance design procedures, reduce environmental impact, and achieve higher energy conservation, which will result in more sustainable building solutions. Social implications are the broader use of such technologies with the aim to achieve sustainability goals within urban environments, make resource allocation more effective, and enhance occupant comfort. This review contributes to the literature by pointing out the need for standard methods and introducing these technologies into practice to have the maximum impact on sustainable design.","author":[{"family":"Ghoneim","given":"Rehab"},{"family":"Arabasy","given":"Mazin"},{"family":"Osbaa","given":"Rana"},{"family":"Hamad","given":"Rasha"}],"issued":{"date-parts":[[2025]]},"DOI":"10.13189/cea.2025.130334","URL":"https://doi.org/10.13189/cea.2025.130334","source":"openalex"},{"id":"oa:W7118135756","type":"article-journal","title":"RESEARCH PROGRESS AND CHALLENGES OF DIGITAL TWIN TECHNOLOGY IN THE FIELD OF AGRICULTURAL MACHINERY TOOL WEAR","abstract":"With the acceleration of high-performance, green, and intelligent agricultural equipment, premature wear and failure of agricultural machinery tools became a key bottleneck that restricted the high-quality development of agricultural machinery and equipment. Digital twin technology provided innovative theoretical and technical support, which enabled the accurate prediction and evaluation of the wear performance of agricultural machinery tools under dynamic and complex working conditions. This paper explained the key elements of digital twin technology and summarized the development history of tool wear research, categorizing it into three stages: physical experiment-driven, numerical simulation, and digital twin integration. Additionally, it highlighted the progress made in agricultural machinery tools based on digital twin technology, particularly in data acquisition, modeling, and data-driven approaches. The paper also introduced a case study of a self-developed agricultural machinery tool wear performance test machine. However, it addressed the key challenges faced in the application of digital twin technology for monitoring agricultural machinery tool wear, including difficulties in data perception and fusion, insufficient accuracy in multi-physical field modeling, and inadequate real-time performance. Future research focused on developing accurate multi-physics field coupling models, optimizing data processing mechanisms, and creating intelligent analysis frameworks. Additionally, it aimed to promote low-cost and efficient digital twin solutions to enhance the intelligence level and feasibility of agricultural machinery tool wear monitoring.","author":[{"family":"Zhang","given":"Yan"},{"family":"Zhan","given":"Hua"},{"family":"Wu","given":"Jia"},{"family":"Wang","given":"Rui"}],"issued":{"date-parts":[[2025]]},"DOI":"10.35633/inmateh-77-88","URL":"https://doi.org/10.35633/inmateh-77-88","source":"openalex"},{"id":"oa:W7127986677","type":"article-journal","title":"The digital twin of the cyber-study enterprise: new methods for simulating the most complex attacks","abstract":"The study investigates novel methods for modeling complex cyberattacks based on enterprise \"digital twin\" technology. The aim is to analyze the concept of a \"digital twin\" as a tool for cyber exercises, compare it with tradition-al cyber ranges, identify current cybersecurity challenges arising from the use of digital twins, and propose methods for addressing them. The research employs comparative analysis, problem systematization, and the design of architecture-oriented solutions based on technologies such as blockchain, swarm intelligence, adversarial attack defense methods, and approaches to verifiable AI explainability. Key advantages of digital twins over traditional cyber ranges have been identified, including dynamic synchronization, modeling accuracy, and predictive capabilities. Fundamental challenges have been systematized, encompassing issues of data reliability, integration, and telemetry processing, as well as new threat classes such as ensuring cyber resilience in \"swarms\" of interconnected digital twins and securing embedded artificial intelligence. To address these challenges, a comprehensive approach has been proposed, involving decentralized trust systems, collective defense mechanisms, multi-layered AI protection, and verifiable explainability systems. The proposed methods and architectural solutions enable a shift from reactive to proactive cybersecurity strategies, facilitate the creation of self-organizing defense systems, enhance trust in autonomous AI decisions, and lay the foundation for legally compliant auditing in critical infra-structures. The novelty of the work lies in the identification and in-depth analysis of new problem classes related to digital twin ecosystems (\"swarms\") and the security of integrated AI, as well as in the proposal of comprehensive, technology-driven solutions, which defines the direction for the development of next-generation cybersecurity systems.","author":[{"family":"Mai","given":"Moscow"},{"family":"Zakharova","given":"Victoria"},{"family":"Kudryashova","given":"Anastasia"},{"family":"Mtuci","given":"Moscow"}],"issued":{"date-parts":[[2025]]},"DOI":"10.36724/2664-066x-2025-11-5-18-27","URL":"https://doi.org/10.36724/2664-066x-2025-11-5-18-27","source":"openalex"},{"id":"oa:W7141554565","type":"article-journal","title":"AI and Dependency Graph–Based Digital Twins for Context-Aware 6G Robotic Networks","abstract":"6G robotic networks demand highly context-aware and intelligent management to meet extreme performance requirements. These requirements become even more challenging with real-time control and autonomous decision-making scenarios of 6G robotic applications. However, traditional methods fail to provide context-awareness and enhanced cognitive capabilities to meet these requirements in a robotic network. Therefore, in this paper, we introduce a novel dependency graph-based Digital Twin (DT) framework to provide context-awareness and cognitive decision-making capabilities in robotic applications. In this framework, we design a Data Distribution Service (DDS)-based DT layer and a context-aware mediator layer, comprising a Global What-If Engine and an AutoML-based Decision Unit. The What-If Engine constructs four types of dependency graphs based on temporal, data, control, and performance-related information to represent relationships between robots, sensor inputs, and control triggers. Moreover, the AutoML-based Decision Unit selects the most successful algorithm based on the prediction error and scenario conditions. Experimental results demonstrate that our proposed framework provides real-time DT synchronisation under even high-density twin scenarios without computationally overloading the system. The proposed framework also achieves effective learning-based decision-making for regression and classification tasks in 6G robotic applications.","author":[{"family":"Duran","given":"Kübra"},{"family":"Özdem","given":"Mehmet"},{"family":"Chowdhury","given":"Kaushik"},{"family":"Canberk","given":"Berk"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/mcomstd.2026.3672744","URL":"https://doi.org/10.1109/mcomstd.2026.3672744","source":"openalex"},{"id":"oa:W4406686323","type":"article-journal","title":"Trends and Opportunities in Sustainable Manufacturing: A Systematic Review of Key Dimensions from 2019 to 2024","abstract":"Purpose: This systematic literature review analyzes trends, key findings, and research opportunities in manufacturing sustainability from 2019 to 2024, with a focus on the integration of emerging technologies and socio-economic dimensions. Methodology: a systematic review of 181 publications was conducted, emphasizing technological advancements, research gaps, and the influence of global events on sustainable manufacturing. Findings: the review highlights: (1) a shift towards advanced technologies like AI-driven circular economy solutions, digital twins, and blockchain, which have demonstrated potential to reduce energy consumption by 30% and decrease material waste by 20%, significantly enhancing sustainability outcomes; (2) persistent gaps in addressing social, policy, and regulatory dimensions; (3) the role of the COVID-19 pandemic in accelerating digital transformation and reshaping sustainability priorities. Key findings also include PT Indocement achieving a cumulative 35% reduction in natural gas consumption through sustained optimization initiatives and a 12% increase in digital manufacturing adoption among SMEs in developing regions. Practical implications: strategic recommendations are provided for industry, policymakers, and academics to address regional disparities, ensuring a 50% increase in adoption rates of inclusive technologies within developing regions over the next five years, and align sustainability efforts with socio-economic contexts. Originality: this review presents a comprehensive analysis of current trends, actionable insights, and critical areas for future research, highlighting that organizations adopting AI and blockchain technologies report up to a 25% improvement in operational sustainability.","author":[{"family":"Setyadi","given":"Antonius"},{"family":"Soekotjo","given":"Sundari"},{"family":"Lestari","given":"Setyani"},{"family":"Pawirosumarto","given":"Suharno"},{"family":"Damaris","given":"Alana"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17020789","URL":"https://doi.org/10.3390/su17020789","source":"openalex"},{"id":"oa:W4414679242","type":"article-journal","title":"Digital Twin-Driven Environmental Compliance Models for Sustainable Procurement in Oil, Gas, and Utilities","abstract":"This review investigates the role of digital twin technology in enhancing environmental compliance within sustainable procurement systems across the oil, gas, and utilities sectors. As industries face increasing regulatory scrutiny and the need to align operations with environmental, social, and governance (ESG) goals, digital twins offer a promising approach to simulate, monitor, and optimize procurement practices in real time. This paper explores how virtual replicas of physical assets and processes can enable real-time tracking of environmental performance, automate compliance with regulatory thresholds, and facilitate lifecycle analysis of supplier operations. By integrating data analytics, IoT sensors, and AI algorithms within a digital twin ecosystem, organizations can proactively identify non-compliance risks, reduce resource wastage, and enhance transparency across the procurement lifecycle. Furthermore, the paper examines implementation frameworks, adoption challenges, and the strategic value of these systems in driving sustainability-led procurement decisions. Through a structured synthesis of current innovations and future research trajectories, this study provides a roadmap for operationalizing digital twins in environmental compliance across resource-intensive industries.","author":[{"family":"Ike","given":"Patience"},{"family":"Okojie","given":"Joshua"},{"family":"Nnabueze","given":"Stephanie"},{"family":"Idu","given":"Jerome"},{"family":"Filani","given":"Opeyemi"},{"family":"Ihwughwavwe","given":"Sadat"}],"issued":{"date-parts":[[2025]]},"DOI":"10.62225/2583049x.2025.5.5.4960","URL":"https://doi.org/10.62225/2583049x.2025.5.5.4960","source":"openalex"},{"id":"oa:W4413099352","type":"article-journal","title":"Rethinking traffic prediction in Mobile Network Digital Twins: A flexible inductive graph-based learning model for data-scarce scenarios","abstract":"Network Digital Twins (NDTs) are increasingly relying on data-driven approaches for modeling complex network dynamics. Traffic forecasting is crucial for NDTs to provide timely insights for automated network reconfiguration. Existing spatiotemporal forecasting methods, while effective, often rely on pre-constructed graphs, limiting their flexibility in dynamic network environments. This paper introduces Flex+ , an inductive graph-based learning model designed for traffic prediction in data-scarce scenarios. Flex+ focuses on individual eNodeB traffic prediction by extracting local spatial correlations from k-hop subgraphs, combined with temporal information. Its inductive design allows it to operate on unseen nodes during training, enabling adaptability to evolving network topologies. Empirical studies on a large-scale cellular traffic dataset demonstrate that Flex+ achieves a 5.9% improvement in accuracy in inductive settings and a 22% reduction in error in data-scarce scenarios when trained with only 3 days of traffic data. Notably, a Knowledge Distillation (KD) framework is introduced to reduce model size and accelerate inference time up to 10 times while maintaining prediction accuracy.","author":[{"family":"Ngo","given":"Duc"},{"family":"Aouedi","given":"Ons"},{"family":"Piamrat","given":"Kandaraj"},{"family":"Hassan","given":"Thomas"},{"family":"Raipin","given":"Philippe"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.comnet.2025.111569","URL":"https://doi.org/10.1016/j.comnet.2025.111569","source":"openalex"},{"id":"oa:W4417438860","type":"article-journal","title":"Earth Action in Transition: Highlights From the 2025 ESA–NASA International Workshop on AI Foundation Models for EO [Space-Agencies]","abstract":"Over 850 people joined the first International Workshop on AI Foundation Model (FM) for Earth Observation (EO) co-organized by ESA and NASA 5-7 May 2025. Hosted at ESRIN (ESA’s Earth Observation Center, Italy), the event welcomed around 300 people on site, and an additional 550 online, with the promise that FMs can revolutionize EO and Earth sciences. The workshop marked a pivotal moment in aligning the EO and FM communities, fostering a shared commitment to developing open and trustworthy tools that support science discovery, operational applications, and prescriptive analytics. EO data is massive, complex and high dimensional requiring specific yet scalable AI architectures. The workshop emphasized the need for training and architecture enabling interpretability, explainability, and physical consistency. Coordination should be strengthened to minimize redundant development and to better leverage collective expertise. The focus has shifted from prototyping to real-world deployment, with FMs needing further design for integration into digital twins, dashboards, and edge platforms. Transparent benchmarking and user-driven evaluation are key to guiding model development and decision-making. In addition, parameter-efficient adaptation, neural compression, and embedding-based workflows offer promising paths for scaling EO analytics. While FMs show promise, their effectiveness remains context-dependent. The community debated whether to pursue universal models, specialized solutions, or mixtures of experts. The workshop envisioned the future of agentic AI in EO, with multi-agent system powered by EO FMs and vision-language models, that can dynamically reason and act on EO data. This shift from static pipelines to adaptive, smarter systems could redefine the future of EO. This paper summarizes key discussions and concludes with thought-provoking remarks.","author":[{"family":"Longépé","given":"Nicolas"},{"family":"Alemohammad","given":"Hamed"},{"family":"Anghelea","given":"Anca"},{"family":"Brunschwiler","given":"Thomas"},{"family":"Campsvalls","given":"Gustau"},{"family":"Cavallaro","given":"Gabriele"},{"family":"Chanussot","given":"Jocelyn"},{"family":"Delgado","given":"Jose"},{"family":"Demir","given":"Begüm"},{"family":"Dionelis","given":"Nikolaos"},{"family":"Fraccaro","given":"Paolo"},{"family":"Jungbluth","given":"Anna"},{"family":"Kennedy","given":"Robert"},{"family":"Marsocci","given":"Valerio"},{"family":"Ramasubramanian","given":"Muthukumaran"},{"family":"Ramos-Pollán","given":"Raúl"},{"family":"Roy","given":"Sujit"},{"family":"Sümbül","given":"Gencer"},{"family":"Tuia","given":"Devis"},{"family":"Zhu","given":"Xiao"},{"family":"Ramachandran","given":"Rahul"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/mgrs.2025.3592035","URL":"https://doi.org/10.1109/mgrs.2025.3592035","source":"openalex"},{"id":"oa:W4409588175","type":"manuscript","title":"A Structured Data Model for Asset Health Index Integration in Digital Twins of Energy Converters","abstract":"The integration of Digital Twins into energy systems is redefining asset management by enabling real-time monitoring, predictive maintenance, and lifecycle optimization. A central challenge in this context is the structured assessment of asset condition, where the Asset Health Index (AHI) plays a critical role by consolidating heterogeneous data into a single, actionable indicator. This paper presents a structured data model specifically designed to integrate AHI methodologies into Digital Twins for energy converters. The model incorporates standardized practices like RAMI 4.0, organizing asset-related information into interoperable domains including physical hierarchy, operational monitoring, reliability assessment, and risk-based decision-making. A Unified Modeling Language (UML) class diagram formalizes the model architecture, which is deployed on Microsoft Azure using native IoT and analytics services to enable automated AHI calculation. The proposed approach is validated through a case study involving three high-capacity converters in distinct operating environments, demonstrating the model’s effectiveness in anticipating failures, optimizing maintenance strategies, and improving asset resilience. These results support the implementation of scalable, cloud-based digital twin solutions for advanced asset health management in the energy sector.","author":[{"family":"Fernández","given":"Juan"},{"family":"Fernández","given":"Eduardo"},{"family":"Márquez","given":"Adolfo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202504.1152.v1","URL":"https://doi.org/10.20944/preprints202504.1152.v1","source":"openalex"},{"id":"oa:W7130514284","type":"article-journal","title":"An Anomaly‐Enhanced Digital Twin (AEDT) Model for Intelligent Inspection and Management of Civil Infrastructure","abstract":"The increasing frequency of extreme climate events poses significant risks to slope infrastructure, while traditional inspection methods are often inefficient and unsafe. Although unmanned aerial vehicles (UAVs) combined with structure‐from‐motion (SfM) provide high‐fidelity 3D models, they lack the semantic understanding necessary for automated damage assessment. This study addresses this gap by developing and validating an anomaly‐enhanced digital twin (AEDT) framework. The proposed system integrates multiview UAV imagery, SfM‐based 3D reconstruction, and a convolutional neural network (CNN) for automated anomaly classification. This information is then fused into an interactive, geographic information system (GIS)‐compatible DT platform for lifecycle management. A case study on a soil and water conservation (SWC) structure in central Taiwan was conducted for verification. The deep learning module achieved a macroaverage F1‐score of 0.81, demonstrating balanced performance across erosion, spalling, siltation, and collapse classes. This was validated on a held‐out test set derived from a total of 2000 annotated images spanning four anomaly types with three severity levels. Furthermore, the AEDT‐based workflow reduced on‐site inspection time by ~63% compared to conventional manual methods. The resulting AEDT model provides a dynamic, semantically enriched 3D representation of the infrastructure, linking geometric data with damage attributes and historical maintenance records. This research demonstrates a feasible and scalable solution for intelligent infrastructure monitoring, offering a robust tool for enhancing climate resilience and enabling proactive asset management.","author":[{"family":"Pan","given":"Nai"},{"family":"Chang","given":"Bo"},{"family":"Chen","given":"Kuei"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1155/adce/2063316","URL":"https://doi.org/10.1155/adce/2063316","source":"openalex"},{"id":"oa:W7116777914","type":"article-journal","title":"MetaD-DT: A Reference Architecture Enabling Digital Twin Development for Complex Engineering Equipment","abstract":"Digital twin technology is emerging as a critical enabler for the lifecycle management of complex engineering equipment, yet its implementation faces significant hurdles. Generic, one-size-fits-all digital twin platforms often fail to address the unique characteristics of this domain—such as tightly coupled multi-physics, high-fidelity modeling requirements, and the need for real-time model execution under harsh operating conditions. This creates a critical need for a structured, reusable blueprint. However, a dedicated reference architecture that systematically guides the development of such specialized digital twins is notably absent. To bridge this gap, this paper proposes MetaD-DT, a reference architecture designed to enable and streamline the development of digital twins specifically for complex engineering equipment. We detail its comprehensive four-layer architecture, core functional modules, and streamlined graphical development workflow. The MetaD-DT’s efficacy and practical value are validated through two distinct industrial case studies: a health management system for diesel engine Diesel Particulate Filter (DPF) and an intelligent control optimization system for Indirect Air-Cooled (IAC) towers. These applications validate the framework’s ability to support the creation of robust digital twins that can effectively handle complex industrial dynamics and improve O&M (Operation And Maintenance) efficiency. This work provides a systematic architectural blueprint for the future development of specialized and efficient digital twins in the engineering equipment domain.","author":[{"family":"Gao","given":"Hanyu"},{"family":"Wang","given":"Feng"},{"family":"Zhao","given":"Taoping"},{"family":"Gu","given":"Yi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/electronics15010038","URL":"https://doi.org/10.3390/electronics15010038","source":"openalex"},{"id":"oa:W4414586233","type":"article-journal","title":"Fusion Intelligence for Digital Twinning AI Data Centers: A Synergistic GenAI-PhyAI Approach","abstract":"The explosion in artificial intelligence (AI) applications is pushing the development of AI-dedicated data centers (AIDCs), creating management challenges that traditional methods and standalone AI solutions struggle to address. While digital twins are beneficial for AI-based design validation and operational optimization, current AI methods for their creation face limitations. Specifically, physical AI (PhyAI) aims to capture the underlying physical laws, which demands extensive, case-specific customization, and generative AI (GenAI) can produce inaccurate or hallucinated results. We propose Fusion Intelligence, a novel framework synergizing GenAI's automation with PhyAI's domain grounding. In this dual-agent collaboration, GenAI interprets natural language prompts to generate tokenized AIDC digital twins. Subsequently, PhyAI optimizes these generated twins by enforcing physical constraints and assimilating real-time data. Case studies demonstrate the advantages of our framework in automating the creation and validation of AIDC digital twins. These twins deliver predictive analytics to support power usage effectiveness (PUE) optimization in the design stage. With operational data collected, the digital twin accuracy is further improved compared with pure physics-based models developed by human experts. Fusion Intelligence offers a promising pathway to accelerate digital transformation. It enables more reliable and efficient AI-driven digital transformation for a broad range of mission-critical infrastructures.","author":[{"family":"Wang","given":"Ruihang"},{"family":"Li","given":"MH"},{"family":"Cao","given":"Zhiwei"},{"family":"Jia","given":"Jimin"},{"family":"Wen","given":"Yonggang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/mci.2026.3712276","URL":"https://doi.org/10.1109/mci.2026.3712276","source":"openalex"},{"id":"oa:W4408658526","type":"article-journal","title":"TOWARDS A DIGITAL TWIN FOR EMERGENCY RESPONSE: A HYBRID SIMULATION FOR MULTI-SECTORAL RESOURCE ALLOCATION","abstract":"Planning for Emergency Response is crucial to a region’s preparedness for climate resilience. It involves multiple government sectors and necessitates effective cooperation between them. Collective management of emergency response resources can improve resource allocation at a regional scale and overcome local constraints. However, prioritising resources is challenging when a collective sharing strategy is applied. When emergency events are still evolving, another challenge is the estimation of future demands and resource shortages, which trigger further requests for external support. In modelling resource flow dynamics, we are implementing an emergency response Digital Twin that combines a Resource Allocation Model with short-term predictions concerning weather-related emergency events and real-time updates. This paper focuses on the resource allocation model for hybrid simulation. It is applied to a flooding case study from the city of Torbay (UK). It enables a holistic assessment of emergency response, considering the cascading effects of the failure of critical infrastructures for better addressing regional resilience.","author":[{"family":"Chen","given":"Otto"},{"family":"Stantec"},{"family":"Mustafee","given":"Navonil"},{"family":"Li","given":"Qian"},{"family":"Evans","given":"Barry"},{"family":"Khoury","given":"Mehdi"},{"family":"Vamvakeridou-Lyroudia","given":"Lydia"},{"family":"Chen","given":"Albert"},{"family":"Djordjević","given":"Slobodan"},{"family":"Savić","given":"Dragan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.36819/sw25.032","URL":"https://doi.org/10.36819/sw25.032","source":"openalex"},{"id":"oa:W4414063378","type":"article-journal","title":"Unlocking Digital Success: A TOE Framework Analysis of Digital Marketing Adoption for Enhanced SMEs Competitiveness","abstract":"This study analyzes the extent to which Technology-Organization-Environment (TOE) factors contribute to the adoption of electronic marketing and resulting business performance among small and medium-sized enterprises (SMEs) in Mimika, Indonesia. A quantitative, cross-sectional survey design collected data from 218 SMEs using validated tools and applying Partial Least Squares Structural Equation Modeling (PLS-SEM) and bootstrapping methods for analytical assessment. The findings suggest that technological forces have the largest positive effect on electronic marketing adoption (β = 0.573, p < 0.001), followed by organizational forces (β = 0.232, p < 0.001), and environmental forces (β = 0.185, p < 0.005). The adoption of electronic marketing is further seen to positively affect business performance (β = 0.841, p < 0.001). The structural model explains 83.6% of the variance for electronic marketing adoption and 70.7% of the variance for business performance. Despite limitations inherent to the cross-sectional design when it comes to causal implications and geographical limitations applied to generalizability, this research provides the first empirical validation of the TOE framework within the specific context of Indonesian SMEs adopting electronic marketing. The findings are reflective of a technology-led adoption model different from an organizational-led fashion common to more developed countries. The findings indicate that SMEs would be best advised to place importance upon determining their technology-readiness and examining platform compatibility, complemented by developing organizational capacity, to ensure enhanced capability to drive digital transformation, and hence make valuable contributory inputs to context-specific literature for emerging economies where technology-focused factors have a preponderant role to play when choosing an adoption model.","author":[{"family":"Mumin","given":"Halek"},{"family":"Bernardus","given":"Denny"},{"family":"Kaihatu","given":"Thomas"}],"issued":{"date-parts":[[2025]]},"DOI":"10.14419/n81qcx19","URL":"https://doi.org/10.14419/n81qcx19","source":"openalex"},{"id":"oa:W4416570545","type":"article-journal","title":"Agile-Driven Digital Transformation Frameworks for Optimizing Cloud-Based Healthcare Supply Chain Management Systems","abstract":"The increasing complexity of healthcare supply chain systems necessitates agile, data-driven, and cloud-based solutions to enhance operational efficiency, resilience, and patient-centered service delivery. This paper proposes an Agile-Driven Digital Transformation Framework designed to optimize cloud-based healthcare supply chain management systems through iterative development, adaptive planning, and continuous integration of digital technologies. The framework leverages cloud computing, artificial intelligence (AI), Internet of Things (IoT), and blockchain to achieve real-time visibility, predictive analytics, and traceability across procurement, inventory, and distribution networks. By embedding agile methodologies such as Scrum and DevOps within the transformation lifecycle, healthcare organizations can rapidly respond to disruptions, regulatory shifts, and fluctuating demand patterns—particularly during crises such as pandemics. The study explores the synergistic role of digital twins and data interoperability standards (e.g., HL7, FHIR) in fostering transparency and decision intelligence across multi-tier healthcare ecosystems. Additionally, it evaluates the challenges of digital adoption, including cybersecurity risks, data governance, and change management. The proposed framework provides a strategic roadmap for healthcare institutions aiming to modernize their supply chain infrastructure, enhance resource utilization, and ensure resilient, patient-safe delivery of medical goods and services in a cloud-empowered environment.","author":[{"family":"Kaffi","given":"Olalekan"},{"family":"Emmanuel","given":"Igba"},{"family":"Azonuche","given":"Tony"},{"family":"Ijiga","given":"Onuh"}],"issued":{"date-parts":[[2025]]},"DOI":"10.38124/ijsrmt.v4i5.1002","URL":"https://doi.org/10.38124/ijsrmt.v4i5.1002","source":"openalex"},{"id":"oa:W4414598356","type":"article-journal","title":"Toward Smart Healthcare in Digital Twin for 6G‐Powered Sustainable Ultra‐Smart Cities","abstract":"This chapter explores current applications of digital twins (DTs) in healthcare, assesses the contributions and challenges of consortium-based research efforts, and identifies emerging opportunities for innovation. The increasing complexities due to the aging population and disease burden on the global healthcare system provide a novel opportunity for sixth-generation (6G)-powered DT technologies about patients, medical science and healthcare management. The chapter examines two technologies emerging in smart city development: the DTs and the 6G cellular networks. Sustainable ultra-smart cities need to lower their medical wastes with the help of predictive analytics and optimized supply chains. DT technologies are advancing healthcare through enhanced patient monitoring, early diagnosis and assistance in therapy plans. 6G will enhance telemedicine, remote surgery and real-time patient monitoring while integrating artificial intelligence for improved diagnosis to transform smart healthcare.","author":[{"family":"Vaidhehi","given":"M"},{"family":"Malathy","given":"C"},{"family":"Sudhakaran","given":"Pradeep"},{"family":"Cherian","given":"Aswathy"},{"family":"Geetha","given":"R"},{"family":"Kumar","given":"Guntupalli"},{"family":"Vaidhehi","given":"M"},{"family":"Malathy","given":"C"},{"family":"Cherian","given":"Aswathy"},{"family":"Geetha","given":"R"},{"family":"Kumar","given":"Guntupalli"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/9781394411320.ch8","URL":"https://doi.org/10.1002/9781394411320.ch8","source":"openalex"},{"id":"oa:W4407378469","type":"article-journal","title":"Unlocking new opportunities for strategic advisory and innovation with digital twin technology in corporate finance","abstract":"Digital Twin Technology (DTT) has emerged as a transformative force in various industries, enabling real-time simulation and decision-making. In corporate finance, its potential is largely untapped, yet it holds promise for revolutionizing strategic advisory and innovation. This review paper explores the applications, benefits, challenges, and future directions of DTT in the corporate finance sector. The study aims to establish a comprehensive understanding of how DTT can unlock new opportunities for strategic decision-making, risk management, and financial innovation. The study also highlights the technological synergies and collaborative frameworks that can support the adoption of DTT in diverse financial contexts.","author":[{"family":"Odewuyi","given":"Oyindamola"},{"family":"Shodimu","given":"Oluwabanke"},{"family":"Philips","given":"Adeniyi"},{"family":"Okpo","given":"Selina"}],"issued":{"date-parts":[[2025]]},"DOI":"10.30574/wjarr.2025.25.2.0416","URL":"https://doi.org/10.30574/wjarr.2025.25.2.0416","source":"openalex"},{"id":"oa:W7130558332","type":"article-journal","title":"Digital Twins in 2025: A Comprehensive Review of Current Trends, Challenges, and Future Directions","abstract":"Digital twin technology has rapidly evolved from a simulation-based concept into a core enabler of intelligent, datadriven ecosystems across industries. By integrating physical assets with their virtual counterparts through the Internet of Things, artificial intelligence and advanced analytics, digital twins enable real-time monitoring, predictive maintenance and enhanced decision-making. This paper reviews recent developments in digital twin research and implementation from 2023 to 2025, highlighting progress in manufacturing, healthcare, smart cities and energy systems. The convergence of digital twins with emerging technologies such as edge computing, blockchain and the industrial metaverse has considerably expanded their scope, supporting secure, scalable and autonomous operations. Despite these advances, challenges remain concerning interoperability standards, data governance, cybersecurity and the computational demands of high-fidelity models. The review concludes by identifying key research directions, including human-centric design, hybrid physics–AI modelling and the development of sustainable digital infrastructures. Overall, digital twins are positioned as a foundational technology for Industry 5.0 and the wider digital transformation agenda beyond 2025.","author":[{"family":"Saleela","given":"Divya"},{"family":"Mathew","given":"Rincy"},{"family":"Supriya","given":"LP"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/icetce66848.2025.11388090","URL":"https://doi.org/10.1109/icetce66848.2025.11388090","source":"openalex"},{"id":"oa:W7133124558","type":"article-journal","title":"Shedding Light on Explainable AI: Insights, Challenges, and the Future of Infrastructure Management","abstract":"This study presents a systematic review of Explainable Artificial Intelligence (XAI) applications in Transportation Infrastructure Management (TIM), focusing on predictive maintenance of safety-critical assets such as railways and bridges. A predefined review protocol was implemented, and peer-reviewed literature was systematically retrieved from Web of Science and Scopus covering the period 2015 to March 2025. Using structured Boolean search logic and clearly defined inclusion and exclusion criteria—requiring explicit integration of explainability within AI-driven infrastructure maintenance—450 records were initially identified, screened in multiple stages, and refined to 163 eligible studies for detailed analysis. Through structured data extraction and thematic synthesis, the review develops a taxonomy of model-specific, model-agnostic, hybrid, and human-centered XAI approaches while identifying recurring challenges including heterogeneous multi-modal data environments, lack of standardized interpretability metrics, computational constraints in real-time deployment, limited robustness validation under field conditions, and unresolved performance–interpretability trade-offs. The findings demonstrate systematic growth in XAI-driven predictive maintenance research and highlight the need for domain-specific benchmarks, hybrid interpretable architectures, digital twin-assisted validation, and edge-enabled explainable systems to enable scalable, transparent, and regulation-ready infrastructure management aligned with Industry 5.0.","author":[{"family":"Hu","given":"Youwen"},{"family":"Atta","given":"Zunaira"},{"family":"Rahman","given":"Tariq"},{"family":"Qiu","given":"Shi"},{"family":"Wang","given":"Jin"},{"family":"Wei","given":"Wei"},{"family":"Liang","given":"Zhiyu"},{"family":"Zaheer","given":"Qasim"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/ijgi15030100","URL":"https://doi.org/10.3390/ijgi15030100","source":"openalex"},{"id":"oa:W4406891549","type":"article-journal","title":"Does the Digital Economy Promote Renewable Energy?—Evidence From a Cross‐National Sample","abstract":"ABSTRACT Renewable energy is one of the key factors in mitigating climate change and achieving sustainable development. With digital technology at its core, the digital economy has gradually become a new driving force for renewable energy development. However, few studies have examined the impact of the digital economy on renewable energy from a global perspective and explored the transmission mechanisms. Based on the cross‐country data of 68 countries (regions) from 2013 to 2021, this paper adopts a panel model to study the impacts of the digital economy on renewable energy. The results show that (1) digital economy has a positive impact on renewable energy; (2) the impact of digital economy on renewable energy is asymmetric and heterogeneous; (3) the impact of digital economy on renewable energy development has obvious threshold characteristics; (4) digital economy indirectly affects renewable energy through technological innovation and financial development. The research in this paper provides a theoretical basis for promoting renewable energy development and a reference and guidance for countries to realize sustainable development in the context of the digital economy.","author":[{"family":"Liu","given":"Lin"},{"family":"Liu","given":"Jing"},{"family":"Zhang","given":"Jianing"},{"family":"Zhao","given":"Yiyang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/app5.70015","URL":"https://doi.org/10.1002/app5.70015","source":"openalex"},{"id":"oa:W4408213253","type":"article-journal","title":"Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma","abstract":"Deepseek and Qwen large language models (LLM) became popular at the beginning of 2025 with their low-cost and open-access LLM solutions. A company based in Hangzhou, Zhejiang, China, announced its new LLM, DeepSeek v3, in December 2024. Then, Alibaba released its AI model, Qwen 2.5 Max, on January 29, 2025. These tools, which are free, open-source, and have no specified or known query limit, have made a significant impact on the world. Deepseek and Qwen also have the potential to be used by many researchers and individuals around the world in academic writing and content creation. Therefore, it is important to determine the capacity of these new LLMs to generate high-quality academic content. This study aims to evaluate the academic writing performance of both Qwen 2.5 Max and DeepSeek v3 by comparing these models with popular systems such as ChatGPT, Gemini, Llama, Mistral, and Gemma. In this research, 40 articles on the topics of Digital Twin and Healthcare were used. The method of this study involves using generative AI tools to generate texts based on posed questions and paraphrased abstracts of these 40 articles. Then, the generated texts were evaluated through the plagiarism tool, AI detection tools, word count comparisons, semantic similarity tools and readability assessments. It was observed that plagiarism test result rates were generally higher for the paraphrased abstract texts and lower for the answers generated to the questions, but both were above acceptable levels. In the evaluations made with the AI detection tool, it was determined with high accuracy that all the generated texts were detected as AI-generated. In terms of the generated word count comparison, it was evaluated that all chatbots generated satisfactory amount of content. Semantic similarity tests show that the generated texts have high semantic overlap with the original texts. The results of the readability tests of the generated texts showed that the texts were insufficient in terms of readability.","author":[{"family":"Aydın","given":"Ömer"},{"family":"Karaarslan","given":"Enis"},{"family":"Erenay","given":"Fatih"},{"family":"Džakula","given":"Nebojša"}],"issued":{"date-parts":[[2025]]},"DOI":"10.36227/techrxiv.174137796.60885820/v1","URL":"https://doi.org/10.36227/techrxiv.174137796.60885820/v1","source":"openalex"},{"id":"oa:W4415283561","type":"article-journal","title":"Review of Advances in the Robotization of Timber Construction","abstract":"The construction industry faces persistent productivity shortfalls and rising carbon dioxide emissions, which drives a shift toward the use of low-carbon materials and higher degrees of automation. Timber, a renewable and carbon-sequestering material, becomes especially compelling when combined with robotic fabrication. Although rapid advances have been implemented in the last decade, research and practice remain fragmented, and systematic evaluations of technological readiness are scarce. This gap is addressed in this review through critical literature synthesis of robotic timber construction, combining bibliometric analysis with a comparative evaluation of twelve representative case studies from 2020 to 2025. Computational and robotic tools are mapped across the design to fabrication pipeline, and emerging advancements are identified such as digital twins, real-time adaptive workflows, and machine learning driven fabrication, alongside discrete and circular strategies. Barriers to scale up are also assessed, including mid-level technology readiness, regulatory and safety obligations for human–robot interaction, evidence on cost and productivity, and workforce training needs. By clarifying the current level of robotization and specifying both research gaps and industrial prerequisites, this study provides a structured foundation for the next phase of development. It helps scholars by consolidating methods and metrics for rigorous evaluation, and it helps practitioners by highlighting pathways to scalable, certifiable, and circular deployment that align cost, safety, and training requirements.","author":[{"family":"Cheng","given":"Fang"},{"family":"Bier","given":"Henriette"},{"family":"Wang","given":"Ningzhu"},{"family":"Andrasek","given":"Alisa"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15203747","URL":"https://doi.org/10.3390/buildings15203747","source":"openalex"},{"id":"oa:W4408995087","type":"article-journal","title":"Metaverse in hospitality and tourism in the International Journal of Contemporary Hospitality Management: Guest Editorial","abstract":"The metaverse represents a transformative evolution of the internet, integrating virtual reality (VR), augmented reality (AR), artificial intelligence (AI) and blockchain technologies to seamlessly merge physical and digital realms. This convergence fosters highly interactive and immersive experiences, particularly within the hospitality and tourism industries (Buhalis et al., 2023; Chen, 2025). Leading hotel brands, such as Accor Hotels, are leveraging the metaverse to redefine the guest journey by enhancing the pre-trip dreaming and discovery phases through captivating digital experiences. Additionally, virtual avatars in the metaverse are being used to enrich in-stay interactions, creating novel touchpoints for customer engagement. The integration of metaverse technologies into sustainable tourism practices is reshaping urban living, tourism and hospitality. A prominent example is Dubai’s ambitious vision for a smart city, which illustrates the potential of the metaverse in crafting seamless and engaging environments that elevate the experiences of both residents and visitors. With the hospitality and tourism sector poised to tap into an estimated US$20bn market opportunity (McKinsey, 2023), the industry is uniquely positioned to harness these innovations, delivering redefined engagement and digitally enriched, unforgettable experiences.Despite significant advancements in defining and conceptualizing the metaverse (Dwivedi et al., 2022; Koohang et al., 2023; Buhalis et al., 2023), its application within the hospitality and tourism domain remains in its infancy. The current research is marked by a limited number of publications and a predominantly conceptual focus, with commercial adoption yet to reach scale in this sector (Buhalis et al., 2023). Although there have been several publications on metaverse literature (e.g. Gursoy et al., 2023; Chen et al., 2024), a significant gap remains in examining and integrating foundational knowledge specific to the metaverse within the hospitality literature. While existing studies highlight general topics and key contributors, they fail to provide actionable managerial frameworks, limiting both theoretical advancements and practical applications. This special issue addresses these gaps, grounded in diverse theoretical foundations, offering a more comprehensive approach to understanding the potential of the metaverse. While the sustainability benefits of metaverse-enabled tourism development – such as VR adoption for training and other initiatives – are evident, both academic and practitioner circles exhibit a limited understanding of these critical aspects (Foroudi et al., 2024). This special issue addresses these gaps by drawing on diverse theoretical foundations, offering a more comprehensive approach to understanding the metaverse’s potential. While the sustainability benefits of metaverse-enabled tourism development – such as VR adoption for training and other initiatives – are evident, there remains a limited understanding of these critical aspects within both academic and practitioner circles. To fill this gap, our special issue aims to inspire researchers to develop insightful models that help practitioners integrate these technologies into their strategies. This special issue advances current knowledge on the metaverse and its applications in the hospitality and tourism industry by focusing on three critical areas: the theoretical structuring of the metaverse literature, the identification of key research streams and their interrelationships and the exploration of future research directions for both scholars and practitioners. Then, it explores key questions related to the metaverse and its applications within the hospitality and tourism sector.This special issue features 14 articles, organized into three main research streams based on their core focus. The aim is to explore the metaverse and its applications in the hospitality and tourism industry. Collectively, the papers pub","author":[{"family":"Foroudi","given":"Pantea"},{"family":"Marvi","given":"Reza"},{"family":"Zha","given":"Dongmie"},{"family":"Kooli","given":"Kaouther"},{"family":"Bagozzi","given":"Richard"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1108/ijchm-04-2025-228","URL":"https://doi.org/10.1108/ijchm-04-2025-228","source":"openalex"},{"id":"oa:W7125531446","type":"article-journal","title":"Exploring Professionals’ Perceptions of the Potential of Digital Twins in Homecare—A Focus Group Study in Sweden","abstract":"Background/Objectives: The growing number of older adults with complex healthcare needs increases demand for homecare services, while a shrinking workforce often lacks skills for advanced tasks. Digital health is seen as a promising tool to address these challenges. This study explored Swedish homecare professionals’ perceptions of the potential use of digital twins in daily work. Methods: Four focus group discussions were conducted with 31 homecare professionals; two groups each in one urban/rural and one rural municipality. Data were analyzed using inductive content analysis. Results: Three main themes emerged: (i) Perceptions of digital twins as support for older adults, including needs-based, individualized care and proactive support enabling preventive measures; (ii) Perceptions of digital twins as support for professionals, including a better work environment through streamlined tasks and flows and enhanced planning and assessment; and (iii) Concerns about digital twins, focusing on ethical and social issues and limited understanding, which were related to monitoring aspects, the importance of physical visits, and how the technology works. Conclusions: Digital twins are perceived by professionals to have the potential to improve homecare services by supporting both older adults and professionals; however, further research is needed to address concerns and practical implications.","author":[{"family":"Saade","given":"Sandra"},{"family":"Nordin","given":"Susanna"},{"family":"Borg","given":"Johan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/healthcare14030289","URL":"https://doi.org/10.3390/healthcare14030289","source":"openalex"},{"id":"oa:W4413215658","type":"article-journal","title":"A Multi-Model BIM-Based Framework for Integrated Digital Transformation of Design to Construction of Large Complex Underground Caverns","abstract":"The construction of large underground caverns fundamentally differs from building and above ground civil infrastructure projects due to their complex geometries and variable geological conditions. These projects are complex and challenging because a large amount of data is generated from dispersed, independent, and heterogeneous sources. The underground construction industry often uses traditional project management techniques to manage complex interactions between these data sources that are hardly linked, and independent decisions are often made without considering all the relevant aspects. In this context, cavern construction exhibits uncertainties and risks due to unforeseen circumstances, an intricate design, and ineffective information management. Existing research has considered general BIM semantic models at the design stage; however, the digital transformation of cavern construction remains underdeveloped and fails to integrate digital construction throughout the project lifecycle. To address that gap, a novel BIM-based multi-model cavern information modeling framework is presented here to improve project management, construction, and delivery by integrating multiple interlinked data models and project performance data for large underground cavern construction. Data models of cavern construction processes are linked to propose an extension of the Industry Foundation Classes (IFC) schema based on the cavern-specific elements, relationships, and property set definitions. To illustrate the potential of the proposed framework, a theoretical application to the powerhouse cavern construction is presented. The results indicate that the framework has significant potential to improve construction efficiency and safety and establish a robust foundation for the digital transformation of underground cavern projects. The theoretical implementation on the Neelum–Jhelum powerhouse cavern showed that the framework enabled a 92 m cavern realignment to avoid fault zones, achieved a 12.4% reduction in rock bolt usage, and a 9.8% reduction in shotcrete volume. These quantitative improvements illustrate its potential to enhance safety, reduce material costs, and optimize construction efficiency compared to conventional workflows.","author":[{"family":"Tanoli","given":"Waqas"},{"family":"Ullah","given":"Abid"},{"family":"Sharafat","given":"Abubakar"},{"family":"Ismaeil","given":"Esam"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15162834","URL":"https://doi.org/10.3390/buildings15162834","source":"openalex"},{"id":"oa:W4411923688","type":"article-journal","title":"The impact of digital technology on total factor productivity in manufacturing enterprises","abstract":"Digital technology drives high-quality development in manufacturing while serving as a critical enabler for advancing the digital economy. Using data from the Chinese list of manufacturing enterprises from 2012 to 2023, this study empirically analyzes the impact of digital technology on total factor productivity (TFP) in manufacturing and its mechanism of action and further explores its heterogeneity. The results show that digital technology has significantly promoted total factor productivity in manufacturing; this effect was still valid after a series of robustness tests and endogeneity tests were conducted. The mechanism analysis indicated that digital technology enhances total factor productivity in the manufacturing enterprises through the enhancement of the innovation ability of enterprises and the reduction in the operation and management costs. The heterogeneity analysis showed that digital technology has a more significant effect on the total factor productivity enhancement of enterprises in the eastern region, state-owned enterprises, and small and medium-sized enterprises. The conclusions provide clear policy implications for the promotion of the digital transformation of enterprises, accelerating the formation of high-quality productivity in enterprises, and promoting the high-quality development of the manufacturing industry.","author":[{"family":"Tu","given":"Jian"},{"family":"Wei","given":"Xin"},{"family":"Razik","given":"Muhammad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-05811-6","URL":"https://doi.org/10.1038/s41598-025-05811-6","source":"openalex"},{"id":"oa:W7116879861","type":"article-journal","title":"From Conflicting Data to Predictive Insights: A Digital Twin Approach for ADRD Risk and Resilience","abstract":"BACKGROUND: A vast amount of data has been collected on the genetic, lifestyle, and environmental risk factors contributing to Alzheimer's Disease and Related Dementias (ADRD); however, no consensus exists on how to integrate these findings for prediction of an individual's ADRD risk. Each study uses different inclusion/exclusion criteria, and variations in baseline age and follow-up can significantly affect the results. For example, exercise is often cited as a key preventative measure for ADRD, yet its impact varies widely-showing strong effects in some studies (Larson, 2006), and no effect in others (Knutosor, 2021). Similar challenges exist for other risk factors, including diabetes, Vitamin D, and even the presence of amyloid plaques in cognitively normal individuals. We have solved this challenge by analyzing ADRD risk and resilience data within the framework of a causal model, enabling us to reconcile seemingly disparate data and make individualized predictions using digital twins. METHOD: We developed a mechanistic model of brain health and neurodegeneration based on engineering principles of mass balance and closed-loop feedback. The model was calibrated using in vitro, in vivo, clinical, and post-mortem data. Biologically relevant variability was identified by examining mechanisms linked to hazard ratios. Using this model, we generated a digital population that replicates hazard ratio and Kaplan-Meier data (Figure 1). RESULT: This digital population reconciles conflicting data and provides a consistent framework to compare the effect size of risk factors. We can stratify the population into subgroups based on which biological processes fail to compensate, leading to disease progression. Additionally, we can create an individual's digital twin by using the digital population as a Bayesian prior then applying individual health data using Bayesian inference. The resulting digital twin can be used to predict the individual's risk of ADRD and guide personalized treatment and prevention strategies. CONCLUSION: Computational tools are needed to synthesize decades of ADRD research into causal hypotheses that accurately model the range of possible disease etiology. Mechanistic models, enhanced by artificial intelligence, offer an ideal framework for integrating diverse datasets and prior knowledge. Our scalable, high-throughput platform enables the creation of digital twins, improving healthcare and optimizing treatment strategies.","author":[{"family":"Rohrs","given":"Jennifer"},{"family":"Paterson","given":"Tom"},{"family":"Breuner","given":"Don"},{"family":"Funk","given":"Cory"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/alz70860_107177","URL":"https://doi.org/10.1002/alz70860_107177","source":"openalex"},{"id":"oa:W4413428025","type":"article-journal","title":"Exploratory Integration of a Digital Twin with a Data Space: Case Study with the Asset Administration Shell","abstract":"In the context of Industry 4.0, technologies such as Digital Twin (DT) and Data Space (DS) have emerged as a revolution in the way physical assets are represented in simulation models and how their information and data are represented in cloud repositories. The aim of this work was to investigate the technologies of DTs and DSs, with a focus on their application in an industrial context, delving into the approaches and difficulties of the integration of both technologies, so that it can be explored and answered the respective challenges. To this end, literature reviews on these topics were explored by reading various sources, as well as analyzing different methodologies for implementing and integrating the two technologies. The result was a description of the main methodologies for integrating DTs with DSs, with the addition of a practical application using AASX Package Explorer, this being a platform enabling the virtual representations of industrial equipment in the molds of DT technologies, containing the association with server tools from other developers and specifications.","author":[{"family":"Zenza","given":"Francisco"},{"family":"Ferreira","given":"Luı́s"},{"family":"Gonçalves","given":"Carlos"},{"family":"Ribeiro","given":"RLA"},{"family":"Ramos","given":"Ana"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/machines13090751","URL":"https://doi.org/10.3390/machines13090751","source":"openalex"},{"id":"oa:W7139038873","type":"article-journal","title":"Shaping the future of multiple myeloma with artificial intelligence and digital twins: from concept to clinic","abstract":"Multiple myeloma (MM) is an incurable hematological malignancy with significant clinical and biological heterogeneity. Despite development and refinement of numerous prognostic models for MM, challenges with accurate and reliable risk stratification remain, highlighted by unexpected, early relapse or progression of disease in patients termed functional high-risk (FHR). To improve decision-making and optimise outcome, there is an unmet need for precise identification of high-risk (HR) patients, to enable tailored therapeutic strategies. With a complex and rapidly evolving treatment landscape, artificial intelligence (AI) and digital twin (DT) technology have emerged as potential tools for personalized medicine in MM. Through the integration and analysis of large data generated in clinical trials, registries and real-world cohorts, AI can inform therapy selection by creating advanced predictive models. DT, virtual patient-specific disease replicas, act as a dynamic, bidirectional bridge between real-world clinical data and computational simulations. Continuous acquisition of patient data, synchronized with DTs through AI-driven architectures, facilitates iterative risk recalibration. This ensures the virtual models accurately reflect evolving disease biology and treatment response. This review provides an overview of current and emerging risk stratification in MM, including genomic-based definitions of HR disease and the concept of FHR MM. We described the role, limitations and controversies of AI and DT in refining risk assessment, their predictive capacity for outcomes and therapy selection. Finally, we provide perspectives on the future of AI application in MM.","author":[{"family":"Lee","given":"Cindy"},{"family":"Zhang","given":"Yang"},{"family":"Mcclure","given":"Barbara"},{"family":"Yong","given":"Angelina"},{"family":"Scott","given":"Hamish"},{"family":"Kok","given":"Chung"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fdgth.2026.1771531","URL":"https://doi.org/10.3389/fdgth.2026.1771531","source":"europepmc"},{"id":"oa:W7161706151","type":"article-journal","title":"Digital twin-driven fault diagnosis of power substations by multi-modal fusion learning","abstract":"Abstract Substations are critical infrastructures for ensuring reliable power system operation. With increasing digitalization and system complexity, the rapid growth of multi-source data poses significant challenges for accurate and timely fault diagnosis. Existing approaches often struggle to effectively integrate heterogeneous data or adapt to varying operating conditions. To address these limitations, this study proposes a digital twin-driven fault diagnosis framework incorporating a multi-modal fusion model that integrates system topology, alarms, fault waveforms, and SCADA data through Graph Attention Networks and self-attention mechanisms. In this work, the method is validated on a 110 kV substation using 11,597 training and 3,890 testing scenarios generated in CloudPSS. Experimental results demonstrate over 95% accuracy in fault location, 97% in fault type identification, and 90% accuracy in protection failure detection under 30% data loss conditions. The deployed digital twin system further verifies the practical feasibility of the proposed approach, highlighting its robustness in complex operating environments.","author":[{"family":"Wu","given":"Yulun"},{"family":"Chen","given":"Ying"},{"family":"Xiao","given":"Tannan"},{"family":"Ding","given":"Lifu"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41467-026-73483-5","URL":"https://doi.org/10.1038/s41467-026-73483-5","source":"europepmc"},{"id":"oa:W4416128435","type":"article-journal","title":"A Systematic Review of Intelligent Agents, Language Models, and Recurrent Neural Networks in Industrial Maintenance: Driving Value Creation for the Mining Sector","abstract":"This PRISMA 2020–compliant systematic review examines how intelligent agents, large language models (LLMs), and recurrent neural networks (RNNs) can be combined for industrial maintenance, with a sector‐specific focus on mining. Scopus and Web of Science (2018–2025) were searched using replicable queries, and a dual text‐representation pipeline (TF–IDF with bi/trigrams and sentence‐transformer embeddings) was applied. Model selection scanned k over a predefined grid with internal indices (Silhouette, Davies–Bouldin, and Calinski–Harabasz), and robustness was assessed through multiseed stability, bootstrap consensus, representation‐sensitivity checks, and a control run with HDBSCAN. Study quality and risk of bias were appraised with an AI‐and‐control–oriented matrix (ACE‐QA). Two macroclusters emerged. The first centers on distributed control, consensus and formation, fault tolerance, observers, and learning‐based designs (fuzzy/neural/RL), including finite/predefined‐time and event/dynamic event–triggered mechanisms. The second addresses secure and resilient cooperation under cyber threats (DoS, deception, and FDIA), integrating observer‐based estimation and communication‐efficient protocols. Cross‐cutting findings indicate that event‐triggered updates reduce bandwidth and compute requirements, while robust estimation and fault‐tolerant control improve availability under harsh conditions and intermittent networks—typical in mining. A maturity map suggests high technical readiness and growing adoption for RNN‐based sensing analytics, advancing readiness but emerging adoption for multiagent coordination, and early adoption of LLMs for text‐grounded maintenance intelligence. Evidence gaps persist in replicability, cross‐site transfer, uncertainty reporting, and mining‐grade validation at the edge. A design agenda is outlined that prioritizes digital‐twin stress testing, edge‐first evaluation of agent coordination, secure‐by‐design pipelines (authenticated/encrypted messaging and adversarial testing), and shift‐aware validation. In sum, a hybrid stack—RNNs for perception, LLMs for knowledge grounding, and agents for coordinated action—offers a practical route to reliable, secure, and communication‐efficient predictive maintenance in Mining 4.0.","author":[{"family":"Rojas","given":"Luis"},{"family":"Hernández","given":"Beatriz"},{"family":"García","given":"José"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1155/int/9953223","URL":"https://doi.org/10.1155/int/9953223","source":"openalex"},{"id":"oa:W4412006391","type":"article-journal","title":"Sensitivity Analysis and Uncertainty Quantification of a Digital Twin-Based Simulator for Small Modular and Microreactors","abstract":"Abstract For a digital twin (DT) to be effective, it must accurately represent the system it models. Sensitivity Analyses (SA) and Uncertainty Quantification (UQ) are crucial for enhancing the adaptability and reliability of DTs under system variations and uncertainties. This paper presents a comprehensive SA and UQ of a DT-based simulator for Advanced Small-scale (Gen IV) Reactors, focusing on a conceptual 4.5 MWth Small Modular Lead-cooled Fast Reactor (LFR). The simulator integrates design aspects from the main LFR families and seamlessly connects with instrumentation and control (I&C) systems via an advanced human-machine interface (HMI), enabling real-time visualization of reactor transients to enhance operational safety and efficiency. The Sobol global sensitivity analysis was employed to rank influential parameters affecting reactor performance, focusing on first-order and total sensitivity indices. Results showed that at full operating power, key contributors to output variance included coolant heat capacity, core inlet/outlet temperatures, initial (nominal) power, and structural parameters like fuel pitch and radius. Neutron decay fractionswere significant at full power but diminished at lower powers. Time-dependent analysis revealed coolant heat capacity as the dominant factor, while derived parameters had minimal impact. UQ findings indicated that coolant bulk temperature exhibited the highest variability, while cladding temperature had the lowest.Based on these results, optimizations were made to enhance the DT framework’s robustness and effectiveness in simulating reactor dynamics while adhering to safety standards. This research underscores the importance of incorporating advanced SA and UQ techniques in digital twin technologies, vital for risk management and model validation. These findings could inform future design and operational decisions in reactor technology, impacting regulatory practices and industry standards to support the safe and efficient deployment of next-generation nuclear technologies","author":[{"family":"Ndum","given":"Zavier"},{"family":"Lim","given":"Doyeong"},{"family":"Hassan","given":"Yassin"},{"family":"Liu","given":"Yang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1115/vvuq2025-152220","URL":"https://doi.org/10.1115/vvuq2025-152220","source":"openalex"},{"id":"oa:W4411379002","type":"article-journal","title":"Digital design and optimization of the integrated synthesis and crystallization process using data‐driven approaches","abstract":"Abstract This study presents a data‐driven modeling and multi‐objective optimization framework for an integrated section of continuous pharmaceutical manufacturing, focusing on flow synthesis and continuous crystallization. To address data scarcity and trade‐offs among product quality, efficiency, and environmental impact, the framework combines generative adversarial networks (GANs), artificial neural networks (ANNs), and genetic algorithms (GAs). An integrated dual‐GAN (ID‐GAN) generates data under physicochemical constraints, which are merged with real data to train an ANN with 15%–20% mean absolute errors for particle size, productivity, and a sustainability throughput index. The ANN is then coupled with a GA to identify Pareto‐optimal solutions based on user‐defined objectives and constraints. Case studies validate the framework's capability to facilitate process design decisions by systematically exploring trade‐offs among competing objectives, underscoring its potential utility in the digitalization of critical units within continuous manufacturing systems.","author":[{"family":"Ma","given":"Yiming"},{"family":"Li","given":"Wei"},{"family":"Liu","given":"Jiaxu"},{"family":"Shang","given":"Gao"},{"family":"Yang","given":"Huaiyu"},{"family":"Gong","given":"Junbo"},{"family":"Nagy","given":"Zoltán"},{"family":"Benyahia","given":"Brahim"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/aic.18931","URL":"https://doi.org/10.1002/aic.18931","source":"openalex"},{"id":"oa:W7118092783","type":"article-journal","title":"Digital twin and BIM adoption in construction project management: a quantitative expert-based study","abstract":"This study investigates the role of Digital Twin (DT) services in facilitating the adoption of Building Information Modeling (BIM) in construction project management. Despite growing interest in digital transformation within the Architecture, Engineering, and Construction (AEC) industry, empirical evidence on how DT influences BIM implementation remains limited. To address this gap, a structured questionnaire was developed through an extensive literature review and distributed to 53 professionals actively engaged in BIM and DT applications, including contractors, consultants, and academics. The collected data were analyzed using SPSS with reliability tests (Cronbach’s Alpha), Pearson correlation, independent-samples t-tests, and one-way ANOVA with post-hoc analysis. The results revealed strong internal consistency of the survey instrument (Cronbach’s Alpha = 0.944), confirming the robustness of the measurement scale. Correlation analysis showed significant positive associations between DT service factors and BIM adoption (p 0.01). Group comparisons demonstrated that perceptions of DT’s contribution to BIM adoption varied across organizational roles, with notable differences between contractors, consultants, and research institutions (p 0.05). These findings highlight the synergistic relationship between DT and BIM, suggesting that integrating DT services can enhance BIM utilization and overall project performance. The study contributes to academic knowledge and professional practice by providing empirical evidence of DT’s enabling role in digital transformation. Practical implications include guiding policymakers, project managers, and technology providers in making informed decisions regarding DT-enabled BIM adoption. Although limited by its sample size and geographic scope, this research lays the groundwork for future studies employing larger international datasets and advanced statistical modeling. The results confirm the critical importance of DT services in accelerating successful BIM implementation across the construction sector.","author":[{"family":"Nguyen","given":"Luan"},{"family":"Nguyen","given":"Luat"},{"family":"Vu","given":"Kien"},{"family":"Pham","given":"Ngoc"}],"issued":{"date-parts":[[2025]]},"DOI":"10.22363/2312-8313-2025-12-4-509-519","URL":"https://doi.org/10.22363/2312-8313-2025-12-4-509-519","source":"openalex"},{"id":"oa:W4414064408","type":"article-journal","title":"GenAI-Based Digital Twins Aided Data Augmentation Increases Accuracy in Real-Time Cokurtosis-Based Anomaly Detection of Wearable Data","abstract":"Early detection of potential infectious disease outbreaks is crucial for developing effective interventions. In this study, we introduce advanced anomaly detection methods tailored for health datasets collected from wearables, offering insights at both individual and population levels. Leveraging real-world physiological data from wearables, including heart rate and activity, we developed a framework for the early detection of infection in individuals. Despite the availability of data from recent pandemics, substantial gaps remain in data collection, hindering method development. To bridge this gap, we utilized Wasserstein Generative Adversarial Networks (WGANs) to generate realistic synthetic wearable data, augmenting our dataset for training. Subsequently, we use these augmented datasets to implement a cokurtosis-based technique for anomaly detection in multivariate time-series data. Our approach includes a comprehensive assessment of uncertainties in synthetic data compared to the actual data upon which it was modeled, as well as the uncertainty associated with fine-tuning anomaly detection thresholds in physiological measurements. Through our work, we present an enhanced method for early anomaly detection in multivariate datasets, with promising applications in healthcare and beyond. This framework could revolutionize early detection strategies and significantly impact public health response efforts in future pandemics.","author":[{"family":"Kamruzzaman","given":"Methun"},{"family":"Salinas","given":"Jorge"},{"family":"Kolla","given":"Hemanth"},{"family":"Sale","given":"Kenneth"},{"family":"Balakrishnan","given":"Uma"},{"family":"Poorey","given":"Kunal"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/s25175586","URL":"https://doi.org/10.3390/s25175586","source":"openalex"},{"id":"oa:W4414950458","type":"article-journal","title":"Digital assets in zero-defect manufacturing: literature review and proposed framework","abstract":"Market demand for customised, quality-focused products is driving the digital transformation of the manufacturing industry, placing digital asset management at the forefront of Industry 4.0. Digital assets, virtual representations of physical assets, are essential for successfully implementing Industry 4.0 strategies. Understanding the lifecycle of these assets, from design to disposal, is crucial for automating manufacturing processes and minimising product defects. Digital assets complemented by innovative technologies have therefore become increasingly important in zero-defect manufacturing (ZDM) practices, due to their ability to leverage data to improve product quality. However, existing literature takes a fragmented approach, hindering the understanding and integration of digital assets into ZDM frameworks. To address this, this study explores three interrelated dimensions: digital assets, ZDM and the asset lifecycle. A systematic review of 68 recent academic articles was conducted to highlight prevailing trends and synthesise findings in these critical areas. The result is a coherent, practical, integrative framework that provides practitioners and academics with guidance and research directions to help them achieve standardised adoption of digital assets within Industry 4.0. The contribution is operationalised through a Digital-Asset-Driven ZDM (DA-ZDM) reference architecture, emphasising a closed-loop quality pipeline enabled by MLOps to sustain prediction-prevention and detection-repair cycles in real time.","author":[{"family":"Mateo-Casalí","given":"Miguel"},{"family":"Boza","given":"Andrés"},{"family":"Fraile","given":"Francisco"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/00207543.2025.2563746","URL":"https://doi.org/10.1080/00207543.2025.2563746","source":"openalex"},{"id":"oa:W7117160817","type":"article-journal","title":"Intelligent Ventilation and Indoor Air Quality: State of the Art Review (2017–2025)","abstract":"Intelligent ventilation is positioned as a key axis for reconciling energy efficiency and indoor air quality (IAQ) in residential and non-residential buildings. This review synthesizes 51 recent publications covering control strategies (DCV, MPC, reinforcement learning), IoT architectures and sensor validation, energy recovery (HRV/ERV, anti-frost strategies, low-loss exchangers, PCM-air), active envelope solutions (thermochromic windows) and passive solutions (EAHE), as well as evaluation methodologies (uncertainty, LCA, LCC, digital twin) and smart readiness indicator (SRI) frameworks. Evidence shows ventilation energy savings of up to 60% without degrading IAQ when control is well-designed, but also possible overconsumption when poorly parameterized or contextualized. Performance uncertainty is strongly influenced by occupant emissions and pollutant sources (bioeffluents, formaldehyde, PM2.5). The integration of predictive control, scalable IoT networks, and robust energy recovery, together with life-cycle evaluation and uncertainty analysis, enables more reliable IAQ-energy balances. Gaps are identified in VOC exposure under DCV, robustness to sensor failures, generalization of ML/RL models, and standardization of ventilation effectiveness metrics in natural/mixed modes.","author":[{"family":"Rizo-Maestre","given":"Carlos"},{"family":"Flores-Moreno","given":"José"},{"family":"Sanz","given":"Amor"},{"family":"Iribarren","given":"Víctor"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings16010065","URL":"https://doi.org/10.3390/buildings16010065","source":"openalex"},{"id":"oa:W7127380685","type":"article-journal","title":"Restoring Pugin: Toward Predictive Conservation of Historical Buildings Using a Digital Twin Approach","abstract":"Conservation of historic buildings has long relied on traditional, reactive methods that address deterioration only after it occurs, often leading to irreversible damage. This study introduces an innovative approach that integrates Digital Twin (DT) technology with advanced machine learning algorithms to enable predictive and data-driven conservation. Focusing on Nottingham Cathedral, a Grade II listed Gothic Revival building, this research developed a 3D Historic Building Information Model (HBIM) enhanced with real-time environmental monitoring of temperature, humidity, and air quality. The collected data were analysed using MATLABR2024a to train and evaluate several predictive algorithms, including Long Short-Term Memory (LSTM), Backpropagation Neural Network (BPNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Nonlinear Autoregressive Exogenous (NARX) models. The NARX model achieved the highest accuracy (Root Mean Square Error (RMSE) = 0.19) in forecasting indoor environmental conditions. Findings indicate that maintaining an indoor temperature increase of 4–6 °C can effectively reduce relative humidity below 60%, minimising deterioration risks. The study demonstrates how integrating DT and machine learning offers a proactive framework for environmental optimisation and long-term preservation of heritage assets, moving conservation practice from reactive restoration toward predictive conservation.","author":[{"family":"Medjdoub","given":"Benachir"},{"family":"Shakmak","given":"Bubaker"},{"family":"Chalal","given":"Moulay"},{"family":"Khosravi","given":"Mohammadreza"},{"family":"Sajad","given":"Rihana"},{"family":"Bezai","given":"Nacer"},{"family":"Illangakoon","given":"Ayesha"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18031516","URL":"https://doi.org/10.3390/su18031516","source":"openalex"},{"id":"oa:W7126120040","type":"article-journal","title":"Data-efficient digital twin for turbine heat rate of industrial thermal power plant","abstract":"Developing a robust and efficient data-driven digital twin system for industrial thermal power systems remains challenging due to data drift, change in operating behaviour of the system and ineffective data-sampling issues for data-driven model development. We present data-efficient model training framework that incorporates effective data sampling from large volumes of asymmetric and controlled data regimes of industrial power systems. Artificial Neural Network (ANN) model is trained on the sampled and representative dataset to predict turbine heat rate (THR) of 660-megawatt (MW) capacity thermal power plant. Later, THR is minimized by a constrained non-linear optimisation technique at 50%, 75%, and 100% capacity discharge of power plant, and the optimisation-based results are validated in the operation of the power plant with the mean absolute percentage errors of 0.79%, 2.98% and 0.33% respectively. The analysis on cost of operation and carbon dioxide (CO 2 ) reduction reveals that optimising THR through the data-efficient model training and optimisation framework can save around 13 million USD with a reduction of 28 kilotonnes (kt) of CO 2 per year. Finally, the data-efficient trained ANN model is deployed as a digital twin system for monitoring the THR and is found to be more than 90% accurate on 19000 minutes of real-time monitoring window. This research paves the way for data-efficient sampling from the controlled datasets of thermal power plants that leads to improved generalisation capacity of the trained machine learning models for their integration in the digital twin systems for monitoring the performance of industrial power systems. • Data-efficient sampling from asymmetric industrial data-distributions is presented. • Model trained on representative data sample accurately predicts turbine heat rate. • ≈USD 13 million cut in operating cost and ≈28 kt CO 2 per year reduction are achieved. • Data-driven digital twin system monitors the turbine heat rate with > 90% accuracy. • Data-efficient model training enhances the adaptability of next-generation digital tools in industrial operations.","author":[{"family":"Ashraf","given":"Waqar"},{"family":"Muzammil","given":"Shuraim"},{"family":"Nasir","given":"M"},{"family":"Muneeb","given":"Muhammad"},{"family":"Arafat","given":"Syed"},{"family":"Alshehri","given":"Abdulelah"},{"family":"Jumah","given":"Abdulrahman"},{"family":"Debnath","given":"Ramit"},{"family":"Dua","given":"Vivek"},{"family":"Uddin","given":"Ghulam"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.energy.2026.140238","URL":"https://doi.org/10.1016/j.energy.2026.140238","source":"openalex"},{"id":"oa:W4411100532","type":"article-journal","title":"Digital twin of a vessel during operation and assessment of its possible use for the purpose of constructing and implementing of maritime autonomous surface ships trajectory","abstract":"The concept of digital twins, which is the basis and one of the conditions of the fourth industrial revolution in both the general industry and the marine industry, is considered and summarized. The terminology of the concept is analyzed, including many definitions of the term “digital twin”, as well as various approaches to the implementation of this concept in practice. Various types of digital twins, which were introduced by the founder of the concept M. Reeves, are considered: the digital twin of the prototype, the digital twin of the sample, the aggregated digital twin and the operational digital twin. The principles of building a ship's digital twin are substantiated, including individuality, identity, and the need to use mathematical models, machine learning, and artificial intelligence in its structure. A scheme of functioning of a ship's digital twin during operation is constructed, which contains a physical space – a ship, sensors, vessels of the same type, target vessels; navigation space; virtual space – digital twins of ship components, processes, navigation space, other vessels, as well as an operational digital twin designed for targeted information processing. The problems of integrating the concept of digital twins into the development of marine autonomous surface vessels (MASV) are identified, related to the need to store and process a large amount of data, the lack of generally accepted standards for such data, as well as the problem of adequate perception of information by an external captain during remote control of the vessel. In the context of the evolution of the MASV, a predictive assessment of the role of digital twins in the functioning of autonomous vessels in various periods of their evolution has been made, with an emphasis on the task of constructing and implementing the trajectory of the MASV.","author":[{"family":"Ermakov","given":"Sergey"},{"family":"Mulina","given":"Elena"},{"family":"Malinin","given":"Nikita"}],"issued":{"date-parts":[[2025]]},"DOI":"10.24143/2073-1574-2025-2-48-58","URL":"https://doi.org/10.24143/2073-1574-2025-2-48-58","source":"openalex"},{"id":"oa:W4407105546","type":"article-journal","title":"Framework for Asset Digitalization: IoT Platforms and Asset Health Index in Maintenance Applications","abstract":"This study proposes a comprehensive framework for digitalizing and managing assets with low initial digital maturity, focusing on their operation and maintenance (O&M) lifecycle. The framework integrates Internet of Things (IoT) networks with Asset Health Index (AHI) models through four interconnected components. The Asset Definition Model ensures standardized data representation based on IEC 81346-1:2022 and ISO 14224:2016, while the Asset Criticality Model prioritizes maintenance actions using risk-informed analysis. The Asset Monitoring Model enables real-time data acquisition through IoT sensors, facilitating condition-based monitoring and dynamic decision-making. Finally, the Intelligent Asset Management Models support long-term planning by simplifying data complexity and aligning with advanced maintenance strategies. A case study on bridge maintenance demonstrates the practical value of the framework, showcasing its ability to integrate real-time monitoring with predictive decision-making tools. By bridging asset monitoring and lifecycle planning, the framework enhances operational efficiency, reduces maintenance costs, and addresses the challenges posed by limited digital maturity in critical infrastructure. This approach represents a significant advancement in the digital transformation of maintenance management.","author":[{"family":"Fernández","given":"Eduardo"},{"family":"Márquez","given":"Adolfo"},{"family":"Guillén","given":"Antonio"},{"family":"Fort","given":"Eduardo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15031524","URL":"https://doi.org/10.3390/app15031524","source":"openalex"},{"id":"oa:W4409365010","type":"article-journal","title":"Digitalization as an Enabler in Railway Maintenance: A Review from “The International Union of Railways Asset Management Framework” Perspective","abstract":"This paper conducts a comprehensive review of the role of digitalization in railway maintenance management, particularly through the lens of the International Union of Railways (UIC) asset management framework. The study aims to assess how digital technologies such as Big Data, the Internet of Things (IoT), and Artificial Intelligence (AI) serve as enablers for more efficient and effective maintenance practices in the railway sector. By employing a bibliometric analysis, we identify the current trends, challenges, and gaps in the literature concerning the integration of digital tools into maintenance management frameworks. The findings reveal that while digitalization offers significant potential for optimizing maintenance operations and enhancing decision-making processes, its successful implementation requires a more integrated approach that aligns with the strategic goals of railway organizations. This paper also discusses future research directions, emphasizing the need for a global framework incorporating technological advancements and organizational change to achieve sustainable and safe railway operations.","author":[{"family":"Rodríguez","given":"Mauricio"},{"family":"Márquez","given":"Adolfo"},{"family":"Sánchez-Herguedas","given":"Antonio"},{"family":"González-Prida","given":"Vicente"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/infrastructures10040096","URL":"https://doi.org/10.3390/infrastructures10040096","source":"openalex"},{"id":"oa:W4413468743","type":"article-journal","title":"Introducing the Manufacturing Digital Passport (MDP): A New Concept for Realising Digital Thread Data Sharing in Aerospace and Complex Manufacturing","abstract":"In the current data-driven era, effective data sharing is set to unlock billions in value for aerospace and complex manufacturing and their supply chains by enhancing product quality, boosting manufacturing and operational efficiency, and generating new value streams. However, current practices are hindered by fragmented data ecosystems, isolated silos, and reliance on paper-based documentation. Although the Digital Thread (DTh) initiative holds promise, its implementation remains impractical due to interoperability challenges, security and intellectual property risks, and the inherent difficulty of capturing and managing the overwhelming volume of data in such complex products as a holistic thread. This paper introduces the Manufacturing Digital Passport (MDP), a novel industry-driven concept that employs a product-centric, system-independent digital carrier to facilitate targeted, structured sharing of technical product data across the supply chain. The conceptual contribution of this work is the analytical formalisation of the MDP as a value-oriented carrier that shifts DTh thinking from costly, system-wide interoperability toward an incremental, ROI-driven record of lifecycle data. Rooted in real-world challenges and built on foundational principles of modularity, value creation, and model-based structures, the MDP, by design, enhances traceability, security, and trust through a bottom-up, incremental, use case-driven approach. The paper outlines its benefits through core design principles, definition, practical features, and integration strategies with legacy systems, laying the groundwork for a structured adoption roadmap in high-value manufacturing ecosystems.","author":[{"family":"Mabkhot","given":"Mohammed"},{"family":"Kalawsky","given":"Roy"},{"family":"Liaqat","given":"Amer"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/systems13080700","URL":"https://doi.org/10.3390/systems13080700","source":"openalex"},{"id":"oa:W4407249544","type":"article-journal","title":"Digital Twin-Based Evaluation of Vehicular Controller Area Network Intrusion Detection Systems","abstract":"The functions and operations of a modern automobile are becoming increasingly computerised, with this transformation made possible by Electronic Control Units (ECUs) that communicate and coordinate with each other on the in-vehicle network. Controller Area Network (CAN) is one of the most popular protocols for the in-vehicle network, supporting low latency and reliable communications. However, the CAN protocol does not have provisions for security, such as encryption, authentication, and authorisation, which makes it vulnerable to cyberattacks, particularly in today’s automotive landscape characterised by extensive connectivity with external devices, vehicles, and infrastructure. While intrusion detection systems (IDS) for CAN have emerged as a key security measure, assessing their performance against realistic attacks remains a challenge since testing with real vehicles poses significant costs and safety risks and testbeds suffer from a lack of fidelity in terms of the CAN frame transmission timings and generated payloads. This work proposes a digital twin (DT)-based framework for CAN IDS evaluation that replicates the functionality of real-world ECUs and CAN bus of a vehicle with real-time flow of data from the physical bus to its virtual representation. The main contribution of this work is a CAN DT that can not only enable the generation of realistic attack traffic for simple and sophisticated attack scenarios but also the generation of diverse combinations of attack and real driving scenarios. This DT can facilitate the evaluation of both the detection capability and performance of CAN IDS. This work presents the methodology for generating the proposed DT and discusses current findings as well as future work","author":[{"family":"Sharmin","given":"Shaila"},{"family":"Mansor","given":"Hafizah"},{"family":"Kadir","given":"Andi"},{"family":"Ismail","given":"Amelia"}],"issued":{"date-parts":[[2025]]},"DOI":"10.31436/ijpcc.v11i1.530","URL":"https://doi.org/10.31436/ijpcc.v11i1.530","source":"openalex"},{"id":"oa:W4411154040","type":"article-journal","title":"Intelligent Digital Twin for Predicting Technology Discourse Patterns: Agent-Based Modeling of User Interactions and Sentiment Dynamics in DeepSeek Discourse Case","abstract":"Understanding user interaction patterns during technology-triggered public discourse provides critical insights into how emerging technologies gain social meaning. This study develops an intelligent digital twin framework for modeling discourse dynamics around DeepSeek, an indigenous large language model that generated approximately 250,000 social media interactions during a 13-day period. By integrating LLM-enhanced semantic analysis with agent-based modeling, we create a comprehensive virtual representation that captures both content characteristics and behavioral dynamics. Our analysis identifies six distinct thematic domains that structure public engagement: Technological Competition, Technological Breakthrough, User Feedback, Financial Market, Social Influence, and Information Security. The agent-based simulation reveals distinctive participation and sentiment patterns across different user segments, with general users expressing stronger positive sentiments than domain experts and institutional accounts. Network analysis demonstrates the evolution from random-like initial connection patterns to scale-free structures with pronounced influence hubs. The simulation results illuminate how individual behaviors aggregate to produce complex discourse patterns, offering insights into the micro-mechanisms underlying technology reception. This research advances digital twin methodologies beyond physical systems into social phenomena, providing a framework for anticipating public responses to technological innovations and informing more effective communication strategies.","author":[{"family":"Zhang","given":"Kaihang"},{"family":"Dong","given":"Changqi"},{"family":"Guo","given":"Yifeng"},{"family":"Yu","given":"Guang"},{"family":"Mi","given":"Jianing"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/systems13060451","URL":"https://doi.org/10.3390/systems13060451","source":"openalex"},{"id":"oa:W7140186081","type":"article-journal","title":"Advancing digital depth: AI-enhanced 3D reconstruction for post-harvest food supply chain quality management","abstract":"Traditional computer vision-based quality perception lacks depth information, limiting its application to reliable food quality management in the post-harvest supply chain. Three-dimensional (3D) reconstruction technology captures detailed surface geometry and internal structural information for reliable non-destructive quality inspection. Combined with emerging artificial intelligence (AI) technologies, 3D data-driven adaptive management brings potential for next-generation post-harvest quality management. This review analyzed 90 major related studies during 2015–2025, covering high-throughput 3D in-line inspection, high-resolution tomography, portable 3D sensing, and AI-driven 3D reconstruction technologies. Post-harvest supply chain application scenarios are mainly distributed in post-harvest processing (33 studies), manufacturing (29 studies), distribution (15 studies), and consumption (13 studies). Among them, fruit and vegetable products are the most intensively researched, highlighting the suitability and potential benefits of 3D reconstruction for these types of products. Besides, multiple 3D reconstruction technologies have been validated for postharvest evaluation, with X-ray CT dominating postharvest processing, manufacturing, and distribution, and portable RGB imaging devices dominating application in consumption. Besides, relevant 3D reconstruction analysis is evolving from geometry-driven to AI-enhanced analysis and management, highlighting the growing role of 3D reconstruction technology in intelligent, traceable, and sustainable post-harvest supply chain quality management. In the future, by integrating digital twins, IoT, and blockchain technologies, it is expected to build a transparent, tamper-proof quality traceability and control system across the global food supply chain. • 3D reconstruction significantly improves non-destructive food quality inspection. • AI integration expands 3D reconstruction applications in food supply chains. • Applications span post-harvest, processing, logistics, and consumer evaluation. • Enables automation in grading, manufacturing, cold chain, and dietary assessment. • Future trends include sensor fusion, XR, and digital twin for food quality control.","author":[{"family":"Ren","given":"Yuqiao"},{"family":"Tong","given":"Lei"},{"family":"Meng","given":"Weihao"},{"family":"Sun","given":"Da‐wen"},{"family":"Argyropoulos","given":"Dimitrios"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.postharvbio.2026.114329","URL":"https://doi.org/10.1016/j.postharvbio.2026.114329","source":"openalex"},{"id":"oa:W4410097983","type":"article-journal","title":"Digital technologies for precise carbon balancing in timber procurement","abstract":"Abstract Detailed tracking of all relevant– natural and man-made– activities in the forest enables real-time monitoring of carbon dynamics, providing immediate feedback on the carbon impact of specific forestry operations. Carbon is sequestered and emitted at many points along the wood supply chain as well as its upstream and downstream processes. The spatial, technical, and organizational aspects of the associated process steps are very heterogeneous, making them complex to capture in the real world and in the information world. This article initially provides an overview of digital technologies for precise carbon balancing in timber procurement. We then show how to use these technologies to capture and consolidate data at the stem section level to enhance the precision of carbon accounting. This granular approach allows for detailed accounting of carbon sequestration and emissions, which is crucial for developing effective carbon management strategies. We propose technical building blocks and an architecture to consider this in an integrated approach. The architecture is based on Digital Twins to individually acquire data with Internet of Things technologies for networking. Data sovereignty among the participating stakeholders is ensured through a dataspace approach yielding a “Dataspace Forestry 4.0”. Integrated human-machine interfaces give stakeholders access to relevant data, and simulation technologies allow them to explore process variants to support decision-making.","author":[{"family":"Hoppen","given":"Martin"},{"family":"Baier","given":"Simon"},{"family":"Schinke","given":"Lennart"},{"family":"Ziesak","given":"Martin"},{"family":"Schreiber","given":"Lukas"},{"family":"Wahl","given":"Arthur"},{"family":"Chen","given":"Jiahang"},{"family":"Bektas","given":"Anil"},{"family":"Heinze","given":"Frank"},{"family":"Schluse","given":"Michael"},{"family":"Roßmann","given":"Jürgen"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s10342-025-01794-1","URL":"https://doi.org/10.1007/s10342-025-01794-1","source":"openalex"},{"id":"doi:10.21203/rs.3.rs-9717799/v1","type":"article-journal","title":"Operationalizing the Twin Transition: A Cross-Sector DigiCircular Digital Twin Framework for Sustainable Production and Consumption","abstract":"Abstract The twin transition, combining digitalization with circular economy strategies, has emerged as a critical pathway for achieving sustainable production and consumption. However, existing approaches largely treat digital tools and circular practices as isolated interventions, limiting their systemic impact across interconnected value chains. This study proposes a DigiCircular Twin-Transition (DT²) framework, a cross-sector digital twin architecture that integrates real-time life cycle assessment with circular economy governance to enable data-driven sustainability control. The framework federates digital twins from the coffee, textile, logistics, and traceability domains into an integrated decision layer, allowing sustainability indicators to function as operational control variables rather than retrospective reporting metrics. A unified Sustainability Efficiency Index and cross-sector resource-synergy modeling enable multi-objective optimization of energy use, water consumption, emissions, and material circularity. Controlled DT² evaluation experiments indicate substantial improvements compared to baseline operations, including a 30% reduction in aggregate environmental impacts, a 25% increase in resource efficiency, a 20% extension in product life cycles, and a 38% improvement in return on investment over a 10-year horizon. Interoperability and decision reliability are ensured through a federated data schema aligned with ISO 23247 and IEC 62890, while Monte Carlo robustness testing (N = 10,000) and Pareto-front analysis indicate stable and simultaneous optimization of environmental and economic objectives. By embedding verifiable performance synchronization through blockchain-backed governance, the DT² framework extends sustainability management toward predictive and auditable operational monitoring, providing a scalable conceptual and technical framework aligned with SDGs 9, 12, 13, and 17 and global net-zero transition pathways.","author":[{"family":"Rehman","given":"Mizna"},{"family":"Petrillo","given":"Antonella"},{"family":"Felice","given":"Fabio"}],"issued":{"date-parts":[[2026]]},"DOI":"10.21203/rs.3.rs-9717799/v1","URL":"https://doi.org/10.21203/rs.3.rs-9717799/v1","source":"europepmc"},{"id":"doi:10.1145/3672608.3707826","type":"article-journal","title":"Fusing Expert Knowledge and Internet of Things Data for Digital Twin Models: Addressing Uncertainty in Expert Statements","abstract":"Extracting Digital Twin models by fusing expert knowledge with Internet of Things data remains a challenging and open research area. Existing literature offers very limited approaches for seamless and systematic extraction of Digital Twin models from these combined sources. In this paper, we address the research gap by proposing a novel approach that considers and integrates the uncertainty inherent in human expert knowledge into the extraction processes of Digital Twin models. Given that experts possess unique experiences, contextual understandings and judgements, their knowledge can be highly divergent, complex, ambiguous, and even incorrect or incomplete. Consequently, not all expert knowledge statements should be equally weighted in the resulting simulation models. Our contributions include a comprehensive literature review on the uncertainty in expert knowledge and the proposal of an approach to integrate this uncertainty in the extraction of Digital Twin models from fused expert knowledge and IoT data. We demonstrate our approach through a case study in reliability assessment.1","author":[{"family":"Jungmann","given":"Michelle"},{"family":"Lazarova-Molnar","given":"Sanja"},{"family":"Lazarovamolnar","given":"Sanja"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1145/3672608.3707826","URL":"https://doi.org/10.1145/3672608.3707826","source":"openalex"},{"id":"doi:10.1109/models-c68889.2025.00096","type":"article-journal","title":"Model Consistency Management of a Brewery Digital Twin","abstract":"Digital Twins (DTs) are often defined as a pairing of a physical entity (PE) and one or more virtual entities (VEs) where the latter mimics certain behaviors of the former to provide specific services. VEs are typically model-based software systems that incorporate a variety of multi-domain, multi-tool models that are essential throughout the DT’s lifecycle. Any inconsistency among these models, which occurs rather frequently, directly affects the performance, reliability, and effectiveness of a DT. In this paper, we present a system for managing the consistency of VE models contained within a DT of a microbrewery, which encapsulates the fermentation process to optimize beer production.","author":[{"family":"Muctadir","given":"Hossain"},{"family":"Liao","given":"Yanyifan"},{"family":"Cleophas","given":"Loek"},{"family":"Liao","given":"YB"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/models-c68889.2025.00096","URL":"https://doi.org/10.1109/models-c68889.2025.00096","source":"openalex"},{"id":"doi:10.1016/j.jogoh.2026.103235","type":"article-journal","title":"Clinical applications of digital twin technology in In Vitro Fertilisation.","abstract":"BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included \"digital twin,\" \"IVF,\" \"in vitro fertilisation,\" \"assisted reproductive technology,\" \"embryo selection,\" and \"predictive modelling.\" Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.","author":[{"family":"Olawade","given":"David"},{"family":"Abe","given":"Oluwadamilola"},{"family":"Nwazuo","given":"Elizabeth"},{"family":"Apena","given":"Tolulope"},{"family":"Olawuyi","given":"Olabanke"},{"family":"Egbon","given":"Eghosasere"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.jogoh.2026.103235","URL":"https://doi.org/10.1016/j.jogoh.2026.103235","source":"europepmc"},{"id":"doi:10.1016/j.scitotenv.2026.181953","type":"article-journal","title":"Intelligent sediment-groundwater digital twin: A systematic review, meta-analysis, and reference architecture for reliable metal pollution risk assessment.","abstract":"Sediment–groundwater interfaces regulate the mobilisation, transport, and attenuation of metal contaminants within highly heterogeneous and multi-scale subsurface systems. However, efforts to operationalise digital twins in this domain remain fragmented across modelling paradigms, disciplines, and scales of observation and prediction. This study provides a performance-centred, quantitatively harmonised meta-analysis of sediment–groundwater digital twin (SG-DT) implementations, explicitly addressing scale dependence, spatial heterogeneity, and process-level controls. A PRISMA 2020–compliant systematic review and meta-analysis of 175 studies (1997–2026; 27 countries) was conducted. SG-DT applications were stratified across a continuum from pore and laboratory scales to site, reach, and basin domains. Scaling effects were analysed via stratified synthesis and meta-regression, while heterogeneity was operationalised through facies-based zonation, parameter variability, and multi-source observational constraints. Predictive performance was quantified using a redesigned, baseline-consistent effect size (E), enabling harmonisation across heterogeneous metrics and validation protocols. Uncertainty was estimated using random-effects models (REML) with Hartung–Knapp adjustments, and heterogeneity was assessed via τ 2 and I 2 with scale-aware interpretation. Results indicate a robust positive pooled performance gain for surrogate-enabled SG-DTs relative to non-updating baselines under scale-consistent validation, while highlighting limitations related to data dependence and extrapolation. In a subset of comparable studies, SG-DTs achieved a pooled out-of-sample R 2 of 0.67 (95% CI: 0.62–0.72). Meta-regression identifies continuous data assimilation and explicit uncertainty quantification as key drivers of performance, whereas residual heterogeneity reflects unresolved scale mismatches and inconsistent representation of subsurface complexity. SG-DTs are defined as systems coupling a process-informed hydro(geo)chemical core capturing reaction kinetics and flow–transport–geochemical coupling, streaming observations, and an updating operator within a closed-loop framework. As secondary outputs, we provide a scale-aware reference architecture embedded in a continuous verification–validation–uncertainty quantification loop and the SED-GW-DT-REPORT v1.0 standard for reproducible, FAIR-aligned reporting. These findings establish an auditable, scale-consistent evidence base for advancing reliable digital twin development in sediment–groundwater systems.","author":[{"family":"Pourmorad","given":"Saeid"},{"family":"Morsilli","given":"Michele"},{"family":"Lombardo","given":"Luigi"},{"family":"Celico","given":"Fulvio"},{"family":"Dimuccio","given":"Luca"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.scitotenv.2026.181953","URL":"https://doi.org/10.1016/j.scitotenv.2026.181953","source":"europepmc"},{"id":"doi:10.1111/1467-9566.70217","type":"article-journal","title":"Future-Making From Afar: Digital Twins in Medicine.","abstract":"Digital twins in medicine are packaged as inevitable, disruptive technologies that will revolutionise healthcare, yet their integration into clinical practice remains slow. In this article, we extend current research on digital twins by shifting attention to the actors behind the technology and their visions. Drawing on multi-sited fieldwork, we identify from where and how the In Silico medicine community envisions the future of medicine and trace embedded ideas and logics. Our analysis reveals a friction between the narrowing of visions of medicine, the human body and clinicians and the technical features of digital twins, which are intended to open futures and possibilities through virtual interventions. We show how digital twins are developed at a distance from the very practices they seek to revolutionise and how the field attempts to navigate this distance through conversion and training. As with other digital health technologies, the burden of adjustment is placed on clinicians. By attending to how distance between modellers and clinical settings plays out in practice, we show how this \"future-making from afar\" constrains but also enables specific modes of engagement. It offers a starting point for demystifying digital twins in medicine and reflects on the kinds of futures the field promotes.","author":[{"family":"Elhadj","given":"Elisa"},{"family":"Tanninen","given":"Maiju"},{"family":"Hoyweghen","given":"Ine"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1111/1467-9566.70217","URL":"https://doi.org/10.1111/1467-9566.70217","source":"europepmc"},{"id":"doi:10.1021/acsomega.5c11417","type":"article-journal","title":"Integrating Molecular Pathogenesis and Host Response into a Digital Twin Framework for Predicting Therapeutic Outcomes in &lt;i&gt;Balamuthia mandrillaris&lt;/i&gt; Encephalitis.","abstract":"High Resolution Image Download MS PowerPoint Slide Balamuthia mandrillaris is a free-living amoeba that causes granulomatous amoebic encephalitis, a rare but devastating central nervous system infection with mortality exceeding 95%. Treatment relies on empirical, multidrug regimens lasting several months, yet prognostic indicators and optimal dosing strategies remain undefined. Advances in computational biology now permit the creation of digital twins, data-driven and patient-specific virtual replicas that integrate clinical, imaging, molecular, and pharmacological data to simulate disease dynamics and therapeutic response. By incorporating molecular mechanisms of Balamuthia pathogenesis and host susceptibility into such a model, it becomes possible to forecast treatment trajectories, personalize drug dosing, and predict toxicity in real time. This paper outlines the molecular and immunological underpinnings of Balamuthia infection and proposes a digital twin framework that bridges mechanistic biology with predictive analytics to improve management and survival in this neglected infection.","author":[{"family":"Siddiqui","given":"Ruqaiyyah"},{"family":"Maciver","given":"Sutherland"},{"family":"Khan","given":"Naveed"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1021/acsomega.5c11417","URL":"https://doi.org/10.1021/acsomega.5c11417","source":"europepmc"},{"id":"doi:10.3389/frobt.2026.1772854","type":"article-journal","title":"Human-centered digital twins in hospitality: how employee perceptions and system design shape adoption.","abstract":"Introduction: The digital transformation of hospitality is increasingly driven by technologies that integrate human and operational elements of service work. Within this evolution, human-centered Digital Twins leverage both human-related and operational data to digitally represent employees within their work contexts, enabling real-time feedback and data-informed decision making for both employees and organizations. Despite their potential, little is known about how hospitality employees perceive these systems or what shapes their willingness to use them. Methods: This study examines the individual perceptual factors that influence employees' intention to use a human-centered Digital Twin, focusing on performance expectancy, effort expectancy, and trust in the system. In addition, the study explores the role of gamification as a system design feature that may shape how these perceptions translate into adoption intentions. Data were collected from 141 customer-facing hotel employees across Europe using a structured survey based on validated scales. An Exploratory Factor Analysis confirmed the reliability and structural validity of the measurement model, and multiple linear regression analysis was used to test both the baseline and the extended models. Results: Results show that all three perceptual factors significantly and positively influence intention to use, with performance expectancy emerging as the strongest predictor. Gamification moderates the relationship between effort expectancy and intention to use in a non-reinforcing manner: when gamification is higher, the positive effect of effort expectancy becomes weaker. Discussion: These findings suggest that interaction design can alter how employees experience the ease of using advanced digital systems. This study provides empirical evidence on the perceptual determinants that influence front-line employees' intention to use a human-centered Digital Twin in hospitality settings, highlighting the role of both core adoption beliefs and system design features in shaping adoption intentions.","author":[{"family":"Manzano-Farray","given":"Desiree"},{"family":"Segura-Cedres","given":"Moises"},{"family":"Aguiar-Castillo","given":"Lidia"},{"family":"Jerez-Jerez","given":"María"},{"family":"Perez-Jimenez","given":"Rafael"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/frobt.2026.1772854","URL":"https://doi.org/10.3389/frobt.2026.1772854","source":"europepmc"},{"id":"doi:10.3389/fphar.2026.1717309","type":"article-journal","title":"A digital twin approach for transforming prescription drug labeling.","abstract":"Drug development entails extensive data collection by sponsors throughout research and development, followed by regulatory review, culminating in essential yet static prescription drug labeling. As study results are typically presented as isolated summaries, the label can underrepresent the drug's integrated effects across biological systems. We propose that sponsors submit a Digital Twin-based companion app alongside traditional documentation to enable a more comprehensive understanding of the investigational drug for review and, after approval, to support personalized prescribing in clinical practice. The development and implementation of the companion app would proceed by aligning with emerging regulatory guidance and by leveraging robust, scalable technical architecture.","author":[{"family":"Kimko","given":"Holly"},{"family":"Kimko","given":"Edwin"},{"family":"Venkatapurapu","given":"Sai"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fphar.2026.1717309","URL":"https://doi.org/10.3389/fphar.2026.1717309","source":"europepmc"},{"id":"doi:10.1038/s41598-025-32691-7","type":"article-journal","title":"Data-driven vehicle stability control via co-simulation of digital twin and constrained MPC.","abstract":"With the rapid advancement of intelligent connected vehicles and autonomous driving technologies, vehicle lateral stability under high-speed or emergency steering conditions has become a critical safety concern. Traditional control strategies often exhibit limited performance in complex driving scenarios. This study proposes a novel co-simulation framework integrating digital twin technology with constrained Model Predictive Control (MPC) to enhance lateral stability and torque distribution. A high-fidelity digital twin model was constructed to improve real-time accuracy, while an MPC-based controller was designed to optimize handling under extreme conditions. Experimental results demonstrated improved performance: lateral stability error was reduced by 62.5%, and yaw rate error by 57.1%, compared to traditional methods. The key novelty lies in the dynamic, data-driven integration of the digital twin for real-time MPC optimization. These findings provide a robust theoretical foundation and technical support for intelligent vehicle development.","author":[{"family":"Lin","given":"Mu"},{"family":"Zhang","given":"Zhengwei"},{"family":"Huang","given":"Min"},{"family":"Ding","given":"Yu"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-32691-7","URL":"https://doi.org/10.1038/s41598-025-32691-7","source":"europepmc"},{"id":"doi:10.1016/j.critrevonc.2026.105171","type":"article-journal","title":"Digital twins in oncology: From predictive modelling to personalised treatment strategies.","abstract":"The digital twin (DT) concept, originating from engineering disciplines, has emerged as a transformative technology in healthcare, particularly in oncology. A digital twin creates a dynamic, virtual replica of a patient's physiological and pathological state, integrating multi-dimensional data to enable personalised cancer care. Despite growing interest, comprehensive reviews examining the breadth of DT applications in oncology remain limited. This narrative review aims to synthesise current evidence on digital twin applications in oncology, evaluate their potential to transform cancer care delivery, and identify challenges hindering clinical translation. A comprehensive literature search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases from inception to September 2025. Studies describing DT development, validation, or application in any cancer type were included. Grey literature, conference proceedings, and expert commentaries were also reviewed to capture emerging trends. Digital twins demonstrate applications across the cancer care continuum, including precision treatment selection, radiotherapy optimisation, drug development, immuno-oncology modelling, surgical planning, and survivorship care. Integration of multi-omics data, imaging biomarkers, and artificial intelligence enables dynamic simulation of tumour behaviour and treatment response. However, challenges persist in data integration, model validation, computational scalability, and ethical governance. Digital twin technology holds substantial promise for advancing precision oncology through predictive, personalised, and adaptive care strategies. Addressing current limitations through interdisciplinary collaboration and regulatory framework development is essential for clinical implementation. • Digital twins create dynamic virtual replicas of patients for personalised care • Applications span treatment selection, radiotherapy, drug development and surgery • Multi-omics data integration enables tumour behaviour and response simulation • Challenges include data integration, model validation, and scalability issues • AI enhances predictive capabilities through imaging and mathematical modelling","author":[{"family":"Olawade","given":"David"},{"family":"Oisakede","given":"Emmanuel"},{"family":"Bello","given":"Oluwakemi"},{"family":"Analikwu","given":"Claret"},{"family":"Egbon","given":"Eghosasere"},{"family":"Ojo","given":"Adeyinka"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.critrevonc.2026.105171","URL":"https://doi.org/10.1016/j.critrevonc.2026.105171","source":"europepmc"},{"id":"doi:10.3390/s25247510","type":"article-journal","title":"Edge Temporal Digital Twin Network for Sensor-Driven Fault Detection in Nuclear Power Systems.","abstract":"The safe and efficient operation of nuclear power systems largely relies on sensor networks that continuously collect and transmit monitoring data. However, due to the high sensitivity of the nuclear power field and strict privacy restrictions, data among different nuclear entities are typically not directly shareable, which poses challenges to constructing a global digital twin with strong generalization capability. Moreover, most existing digital twin approaches tend to treat sensor data as static, overlooking critical temporal patterns that could enhance fault prediction performance. To address these issues, this paper proposes an Edge Temporal Digital Twin Network (ETDTN) for cloud-edge collaborative, sensor-driven fault detection in nuclear power systems. ETDTN introduces a continuous variable temporal representation to fully exploit temporal information from sensors, incorporates a global representation module to alleviate the non-IID characteristics among different subsystems, and integrates a temporal attention mechanism based on graph neural networks in the latent space to strengthen temporal feature learning. Extensive experiments on real nuclear power datasets from 17 independent units demonstrate that ETDTN achieves significantly better fault detection performance than existing methods under non-sharing data scenarios, obtaining the best results in both accuracy and F1 score. The findings indicate that ETDTN not only effectively preserves data privacy through federated parameter aggregation but also captures latent temporal patterns, providing a powerful tool for sensor-driven fault detection and predictive maintenance in nuclear power systems.","author":[{"family":"Liu","given":"Shiqiao"},{"family":"Ye","given":"Gang"},{"family":"Zhao","given":"Xinwen"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/s25247510","URL":"https://doi.org/10.3390/s25247510","source":"europepmc"},{"id":"doi:10.3389/fpubh.2026.1741438","type":"article-journal","title":"Digital twin virtual hospitals and rural health disparities: a six-country comparative study (2018-2024).","abstract":"Background: Rural health disparities are currently affecting 3.3 billion people worldwide. This study assesses the effectiveness of digital twin virtual hospitals in reducing rural health disparities. Methods: We examined health outcomes in six countries (United States, Australia, China, Brazil, India, Rwanda) between 2018 and 2024, employing fixed-effects panel models to evaluate the effect of digital health interventions on the Rural-Urban Mortality Ratio (RMR) and the gap in the management of chronic diseases. Results: < 0.001). Diminishing marginal returns occurred beyond the investment of $50 per capita. Lower-income countries achieved greater cost-efficiency, with Rwanda's ROI of 1:5.2 compared to the United States's 1:2.3. Three distinct implementation models were identified: technology-driven (United States, Australia), system integration (China), and leapfrog development (India, Rwanda). Conclusion: Digital twin virtual hospitals are associated with reductions in rural health disparities, potentially through predictive and personalized health strategies. Findings suggest that successful implementation depends more on contextually appropriate technology selection than on technological sophistication alone.","author":[{"family":"Wang","given":"Hualei"},{"family":"Chai","given":"Xiuhua"},{"family":"Zhao","given":"Nan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fpubh.2026.1741438","URL":"https://doi.org/10.3389/fpubh.2026.1741438","source":"europepmc"},{"id":"doi:10.3390/bioengineering13010001","type":"article-journal","title":"Digital Twin and Artificial Intelligence Technologies to Assess the Type IA Endoleak.","abstract":"Background/Objectives: Endovascular aneurysm repair (EVAR) is the standard treatment for abdominal aortic aneurysms, but the risk of endoleak compromises its effectiveness. Type IA endoleak, stemming from an inadequate proximal seal, is the most critical complication associated with the highest risk of rupture. Current preoperative planning relies on static anatomical measurements from computed tomography angiography that fail to predict seal failure due to dynamic biomechanical forces. This study aimed to retrospectively validate the predictive accuracy of a novel physics-informed digital twin and artificial intelligence (AI) model for predicting type IA endoleak risk compared to conventional static planning methods. Methods: This was a retrospective, single-center proof-of-concept validation study involving 15 patients who underwent elective EVAR (5 with confirmed type IA endoleak and 10 without type IA endoleak). A patient-specific digital twin was created for each case to simulate stent-graft deployment and capture the dynamic biomechanical interaction with the aortic wall. A logistic regression AI model processed over 16,000 biomechanical measurements to generate a single, objective metric of the endoleak risk index (ERI). The predictive performance of the ERI (using a cutoff of 0.80) was assessed and compared against a 1:3 propensity score-matched conventional control group (n = 45) who received traditional anatomical-based planning. Results: The mean ERI was significantly higher in the endoleak-positive group (0.85 ± 0.10) compared to the endoleak-negative group (0.39 ± 0.11) (p = 0.011). The digital twin/AI model demonstrated superior predictive capability, achieving an overall accuracy of 80% (95% CI: 51.9–95.7) and an area under the curve (AUC) of 0.85 (95% CI: 0.58–0.99). Crucially, the model achieved a sensitivity of 100% and a negative predictive value (NPV) of 100%, correctly identifying all high-risk cases and ruling out endoleak in all low-risk cases. In stark contrast, the matched conventional planning group achieved an overall accuracy of only 51.1% and an AUC of 0.54. Conclusion: This physics-informed digital twin and AI framework successfully validated its capability to accurately and objectively predict the risk of type IA endoleak following EVAR. The derived ERI offers a significant quantitative advantage over traditional static anatomical measurements, establishing it as a highly reliable safety tool (100% NPV) for ruling out endoleak risk. This technology represents a critical advancement toward personalized EVAR planning, enabling surgeons to proactively identify high-risk anatomies and adjust treatment strategies to minimize post-procedural complications. Further large-scale, multicenter prospective trials are necessary to confirm these findings and support clinical adoption.","author":[{"family":"Cho","given":"Sungsin"},{"family":"Kim","given":"Hyangkyoung"},{"family":"Joh","given":"Jin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/bioengineering13010001","URL":"https://doi.org/10.3390/bioengineering13010001","source":"europepmc"},{"id":"doi:10.20944/preprints202512.2781.v1","type":"manuscript","title":"Mechanical Coffee Dryers and Digital Twins: A Systematic Review","abstract":"Mechanical coffee dryers have been widely adopted to reduce weather dependence, improve yield, and stabilize product quality. However, their operation is still energy-intensive and often suboptimal in terms of controlling the temperature, airflow and moisture content of the grains. In parallel, digital twin (DT) technology has emerged to virtually replicate complex processes and enable model-based monitoring, optimization, and control. This article presents a systematic review based on PRISMA on mechanical coffee dryers and their modeling and control strategies and the current and emerging use of digital twins in drying processes, including agricultural and food products with technological analogies to coffee. The results show a large amount of research on mathematical modeling, energy evaluation, and quality evaluation of mechanical coffee drying. Rapidly growing but still predominantly conceptual literature on digital twins for food processing and drying. Finally, only a small convergence between the two fields, with no fully realized digital twin for mechanical coffee dryers having yet been reported. This review found key gaps in the detection, data infrastructure, and development of hybrid physical-informed AI models. Finally, lines of research are proposed for mechanical coffee dryers enabled with digital twins, aimed at energy efficiency, product traceability and quality assurance.","author":[{"family":"Valencia-Payan","given":"Cristian"},{"family":"Olaya","given":"Juan"},{"family":"Corrales","given":"Juan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202512.2781.v1","URL":"https://doi.org/10.20944/preprints202512.2781.v1","source":"europepmc"},{"id":"doi:10.1177/20552076261415934","type":"article-journal","title":"Digital twins in healthcare: A systematic review of current applications, frameworks, and future directions.","abstract":"Objective: This systematic review aims to evaluate current digital twin (DT) applications in healthcare, explore their technological foundations, and propose a roadmap for scalable, patient-centered implementation. Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines, a systematic search was conducted across Medline, Scopus, Web of Science, and EBSCO up to May 2025. Eligible studies included peer-reviewed research on DT applications in clinical or healthcare settings involving human or patient-related data. Methodological quality was assessed using appropriate Joanna Briggs Institute critical appraisal tools based on study design. The systematic review protocol was prospectively registered in Prospective Register of Systematic Reviews (registration number: CRD420251120304). Results: 26 studies were included, with most published between 2023 and 2025. DT applications spanned diagnostics, therapy optimization, physiological monitoring, and system-level modeling. Simulation-based designs dominated, often integrating artificial intelligence, internet of things, and machine learning. While several studies reported strong technical performance (e.g. up to 96.3% accuracy), real-world clinical integration was rare. Notable outcomes included better glycemic control, pain management, and disease progression prediction. Barriers included insufficient infrastructure detail, limited validation, and equity concerns. The roadmap highlights three enablers: privacy-preserving, validation pipelines, and interoperability. Conclusion: DTs offer transformative potential for predictive, personalized, and participatory healthcare. Realizing clinical impact requires bridging the translational gap and scaling personalization. This review outlines key strategies for interdisciplinary innovation and deployment of DTs in healthcare.","author":[{"family":"Calcaterra","given":"Valeria"},{"family":"Guardamagna","given":"Luca"},{"family":"Gatti","given":"Alessandro"},{"family":"Rossi","given":"Virginia"},{"family":"Patanè","given":"Pamela"},{"family":"Marin","given":"Luca"},{"family":"Vandoni","given":"Matteo"},{"family":"Zuccotti","given":"Gianvincenzo"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1177/20552076261415934","URL":"https://doi.org/10.1177/20552076261415934","source":"europepmc"},{"id":"doi:10.3390/biomimetics10110725","type":"article-journal","title":"DT-Loong: A Digital Twin Simulation Framework for Scalable Data Collection and Training of Humanoid Robots.","abstract":"Recent advances in bionic intelligence are reshaping humanoid-robot design, demonstrating unprecedented agility, dexterity and task versatility. These breakthroughs drive an increasing need for large scale and high-quality data. Current data generation methods, however, are often expensive and time-consuming. To address this, we introduce Digital Twin Loong (DT-Loong), a digital twin system that combines a high-fidelity simulation environment with a full-scale virtual replica of the humanoid robot Loong, a bionic robot encompassing biomimetic joint design and movement mechanism. By integrating optical motion capture and human-to-humanoid motion re-targeting technologies, DT-Loong generates data for training and refining embodied AI models. We showcase the data collected from the system is of high quality. DT-Loong also proposes a Priority-Guided Quadratic Optimization algorithm for action retargeting, which achieves lower time delay and enhanced mapping accuracy. This approach enables real-time environmental feedback and anomaly detection, making it well-suited for monitoring and patrol applications. Our comprehensive framework establishes a foundation for humanoid robot training and further digital twin applications in humanoid robots to enhance their human-like behaviors through the emulation of biological systems and learning processes.","author":[{"family":"Liu","given":"Yufei"},{"family":"Li","given":"Yang"},{"family":"Du","given":"Jinda"},{"family":"Rui","given":"Yanjie"},{"family":"Li","given":"Yongyao"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/biomimetics10110725","URL":"https://doi.org/10.3390/biomimetics10110725","source":"europepmc"},{"id":"doi:10.21203/rs.3.rs-9435119/v1","type":"article-journal","title":"Integrated Quality Management Model for Teaching Factory in the Era of Industrial Revolution 4.0 : A Systematic Literature Review","abstract":"Abstract Aim This systematic literature review synthesizes research on quality management models for Teaching Factories (TeFa) in the Industrial Revolution 4.0 (IR 4.0) era, aiming to identify core components and technological enablers for an integrated model aligning pedagogical outcomes with industrial standards. Method Following PRISMA guidelines, a systematic review was conducted across Scopus, Web of Science, IEEE Xplore, and Google Scholar for peer-reviewed articles published between 2015 and 2025. After applying inclusion criteria, 15 primary studies were selected for thematic synthesis. Results Existing TeFa quality models are fragmented. Three themes emerged: (1) technological integration (IoT, cyber-physical systems, cloud monitoring), (2) process alignment (ISO 9001:2015 with industry 4.0 standards), and (3) competency-based assessment (digital rubrics, blockchain certification). No single model integrates all three. Key barriers include interoperability gaps and weak feedback loops. Novelty The study proposes the IR4.0 TeFa QM Integration Matrix, a novel framework mapping four quality dimensions (planning, control, assurance, improvement) against four TeFa layers (physical production, virtual simulation, student assessment, industry collaboration). Practical Implication: Educators gain guidelines for AI-based defect tracking and digital twin audits; industry partners benefit from student outputs meeting real-time production tolerances, reducing rework. Contribution: This review consolidates fragmented knowledge, introduces a testable model bridging pedagogical-industrial quality divides, and sets an agenda for validating cyber-physical quality systems in educational production environments.","author":[{"family":"Saraswati","given":"Eka"},{"family":"Kristiawan","given":"Muhammad"},{"family":"Risdianto","given":"Eko"}],"issued":{"date-parts":[[2026]]},"DOI":"10.21203/rs.3.rs-9435119/v1","URL":"https://doi.org/10.21203/rs.3.rs-9435119/v1","source":"europepmc"},{"id":"doi:10.1177/11795972261431928","type":"article-journal","title":"Medical Digital Twin Technology for Interoperability: Challenges and Opportunities.","abstract":"Digital twins (DT) technology has shown considerable growth in recent years. Previous studies have examined technologies in a variety of areas, including health care. However, limited studies have attempted to provide a thorough discussion of strategies for the seamless integration of DT into health care, particularly in the context of interoperability of heterogeneous medical data. This review examines the underlying concept of DT and its possible integration in healthcare, particularly in the context of healthcare interoperability. It also analyzes the main problems such as the lack of standardized protocols, the non-homogeneity of data formats and technical complexity. Finally, potential opportunities are highlighted such as standardized protocol, the creation of an open data platform and the empowerment of semantic interoperability. In conclusion, this review has provided valuable insights for many professionals, including researchers and healthcare providers, which will contribute to empowering patient-centered or personalized medicine and to the development of digital health.","author":[{"family":"Alang","given":"Tengku"},{"family":"Lee","given":"Yeong"},{"family":"Tan","given":"TX"},{"family":"Mokhtar","given":"Ariffin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1177/11795972261431928","URL":"https://doi.org/10.1177/11795972261431928","source":"europepmc"},{"id":"doi:10.3390/s26051734","type":"article-journal","title":"Adaptive Digital Twin Modeling with Control: Integration of Extended Kalman Filter-Based Recursive Sparse Nonlinear Identification with Model Predictive Control.","abstract":"The adoption of digital twins has revolutionized industrial process simulation, monitoring, and control effectiveness. However, practical implementations of digital twins are hindered by substantial challenges, including extended development time, diminishing model accuracy, and restricted interactive capabilities. Addressing these critical issues, this paper proposes a comprehensive digital twin development framework that integrates digital twin identification, real-time model updating, and advanced process control. The proposed approach first identifies the offline digital twin model through the sparse identification of a nonlinear dynamics algorithm, reducing the digital twin development time while maintaining model fidelity. Then, the identified model is updated by the extended Kalman filter to mitigate the problem of diminishing accuracy. Finally, incorporating the latest updated model into the model predictive control facilitates the control inputs optimization and enhances the interactive capacity of digital twins. Through one industrial case study and two simulation examples, the advantages of the proposed algorithm are demonstrated.","author":[{"family":"Wang","given":"Jingyi"},{"family":"Cao","given":"Liang"},{"family":"Cao","given":"Yankai"},{"family":"Gopaluni","given":"Bhushan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/s26051734","URL":"https://doi.org/10.3390/s26051734","source":"europepmc"},{"id":"doi:10.21203/rs.3.rs-7699256/v1","type":"article-journal","title":"Cost–Reliability Trade-offs in Additive Manufacturing Maintenance: A Digital Twin, Kaplan–Meier, and Monte Carlo Approach","abstract":"Abstract Additive Manufacturing (AM) has matured into a production technology in which long, high-value build cycles magnify the operational and economic consequences of even brief disruptions. This paper advances an integrated maintenance framework that unifies stochastic degradation modeling, condition-based maintenance (CBM), and a digital-twin prognostics layer to jointly minimize lifecycle cost and enforce mission-time reliability. Degradation is represented as a drift–diffusion (Wiener) process, enabling closed-form first-passage benchmarks and efficient numerical propagation. CBM decisions are posed as single-threshold stopping rules acting on filtered state estimates; inspection cadence and preventive thresholds are governed by low-dimensional, saturating control laws equipped with explicit guardrails that bound short-horizon failure risk and preserve a fixed safety margin to the functional limit. The digital twin fuses noisy, discrete measurements via Kalman filtering to produce remaining-useful-life (RUL) summaries that drive real-time adaptation of both cadence and trigger. We articulate a policy taxonomy spanning four archetypes (fixed cadence/trigger (ΔT,M), adaptive cadence/fixed trigger (ΔT k ​,M), fixed cadence/adaptive trigger (ΔT,M k ​), and fully adaptive (ΔT k ​,M k ​)) and evaluate their cost–reliability trade-offs within a Monte Carlo simulation–optimization program that accounts for inspection overhead, preventive/corrective asymmetry, downtime accrual, and production alignment to build boundaries. The framework is analytically transparent, operationally implementable, and readily extensible to richer sensing and learning-based prognostics, offering a principled pathway to reliability enhancement, downtime mitigation, and lifecycle cost optimization in industrial AM.","author":[{"family":"Cheikh","given":"Khamiss"},{"family":"Boudi","given":"El"},{"family":"Rabi","given":"Rabi"},{"family":"Mokhliss","given":"Hamza"},{"family":"Cheikh","given":"Khamiss"},{"family":"Boudi","given":"El"}],"issued":{"date-parts":[[2025]]},"DOI":"10.21203/rs.3.rs-7699256/v1","URL":"https://doi.org/10.21203/rs.3.rs-7699256/v1","source":"europepmc"},{"id":"doi:10.21203/rs.3.rs-7978449/v1","type":"article-journal","title":"Theoretical Analyses and Performance Comparison of Physics-Based, Data-Driven, and Hybrid Models for Digital Twin Applications in Manufacturing","abstract":"Abstract Digital twins (DT) are increasingly important in modern manufacturing systems to extend the physical system’s capabilities and improve manufacturing key performance indicators. Nevertheless, selecting the most effective modeling approach for DT services remains challenging. While physics-based models (PBM), data-driven models (DDM), and hybrid models are all utilized within DT implementations, there is a lack of theoretical understanding regarding their comparative performance under equivalent model input conditions. This research addresses this gap by developing a structured theoretical framework that relates model quality to key input resources: domain knowledge, modeling expertise, and data quality. The framework proposes that hybrid models can systematically outperform both PBM and DDM by optimizing the knowledge-data trade-off through the synergistic integration of physical principles with pattern recognition capabilities. To validate this theoretical framework, we implement and compare all three modeling approaches in an industrial stoneware floor tile polishing case study. Results reveal a performance hierarchy: the hybrid model (R² ≈ 0.55) significantly outperforms both the pure DDM approach (R² ≈ 0.40) and the PBM (R² ≈ 0.08) while providing superior transferability to different process conditions. The case study confirms that hybrid models can extract more value from identical input resources than either pure modeling paradigm alone. In addition to such comparisons, this research provides manufacturers with practical guidance for selecting appropriate modeling strategies in DT implementations, particularly valuable in scenarios with limited data or incomplete physical understanding of complex processes.","author":[{"family":"Wagner","given":"Marcel"},{"family":"Sousa","given":"Fábio"},{"family":"Klar","given":"Matthias"},{"family":"Aurich","given":"Jan"},{"family":"Sousa","given":"Fábio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.21203/rs.3.rs-7978449/v1","URL":"https://doi.org/10.21203/rs.3.rs-7978449/v1","source":"europepmc"},{"id":"doi:10.20944/preprints202508.1387.v1","type":"manuscript","title":"A BIM-Driven Digital Twin Framework for Human-Robot Collaborative Construction with On-Site Scanning and Adaptive Path Planning","abstract":"As the Architecture 4.0 paradigm advances, integrating robotic systems into construction workflows has become vital to address labor shortages and enhance execution precision. However, conventional BIM-based automation struggles to cope with dynamic, cluttered on-site environments. This study presents a closed-loop digital twin framework that fuses 3D BIM modeling, real-time sensor- based site scanning, and human–robot interaction to enable adaptive collaboration in architectural construction. The system continuously updates its digital twin using LiDAR and RGB-D DATA to capture spatial deviations, unexpected obstacles, and environmental changes. Based on these inputs, the robot's motion trajectories are recalculated through an online path replanning module. We validate the system using a wall panel dry-hanging case, involving a 6 degrees of freedom (6DoF) ABB robotic arm and a Unity-VR interface for immersive human supervision. Across 24 experimental runs in cluttered environments, the adaptive system achieved a 92.4% average placement accuracy, reducing positioning error by 47% compared to static BIM-based workflows. Obstacle avoidance success rate reached 95.8%, and average task completion time decreased by 18.6% due to reduced manual intervention. These results demonstrate the framework’s potential to transition construction robotics from pre-scripted automation to intelligent, real-time collaboration.","author":[{"family":"Yuan","given":"Mingyang"},{"family":"Mao","given":"Hedi"},{"family":"Qin","given":"Wen"},{"family":"Wang","given":"Bentian"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202508.1387.v1","URL":"https://doi.org/10.20944/preprints202508.1387.v1","source":"preprints"},{"id":"doi:10.1101/2025.08.17.670697","type":"article-journal","title":"Identifiability-Guided Assessment of Digital Twins in Alzheimer’s Disease Clinical Research and Care","abstract":"Digital twins - personalized, data-driven computational models - are emerging as a powerful paradigm for representing and predicting disease trajectories at the individual level. These models have the potential to support diagnosis, monitor disease evolution, and evaluate therapeutic interventions in virtual settings in the context of clinical trials and patient care. Rigorous model assessment is thus critical for its implementation, but medical data are often sparse, noisy, and vary significantly across individuals, making it challenging to determine whether a digital twin optimized on such data is valid. In such settings, identifiability analysis becomes essential for evaluating whether model parameters can be reliably estimated and interpreted. To address this, we investigate how identifiability can support the clinical application of a computational causal digital twin model for Alzheimer's Disease (AD), where data sparsity and variability are particularly pronounced. Our results show that the magnitude and distribution of biomarker data influence the parameter practical identifiability, and that constraints on the model structure and parameters can significantly affect identifiability. We also observe differences in identifiability across diagnostic groups, with several parameters showing significantly different values between individuals with AD, mild cognitive impairment (MCI), and cognitively normal (CN) subjects. Uncertainty quantification for identifiable parameters and their corresponding model trajectories provides visual insight into variability in disease progression and reveals mild trends related to biomarker data spread. This study represents a first step toward incorporating identifiability techniques into clinical digital twin frameworks, using a data-driven, interpretable example based on a previously published AD model.","author":[{"family":"Jiang","given":"JJ"},{"family":"Petrella","given":"Jeffrey"},{"family":"Hao","given":"Wenrui"},{"family":"Initiative","given":"The"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1101/2025.08.17.670697","URL":"https://doi.org/10.1101/2025.08.17.670697","source":"preprints"},{"id":"doi:10.20944/preprints202508.0708.v1","type":"manuscript","title":"AI-Powered Digital Twin Co-Simulation Framework for Climate-Adaptive Renewable Energy Grids","abstract":"Climate change is accelerating the frequency and intensity of extreme weather events, posing a critical threat to the stability, efficiency, and resilience of modern renewable energy grids. In this study, we propose a modular, AI-integrated digital twin co-simulation framework that enables climate adaptive control of distributed energy resources (DERs) and storage assets in distribution networks. The framework leverages deep reinforcement learning (DDPG) agents trained within a high fidelity co-simulation environment that couples physical grid dynamics, weather disturbances, and cyber-physical control loops using HELICS middleware. Through real-time coordination of photovoltaic systems, wind turbines, battery storage, and demand side flexibility, the trained agent autonomously learns to minimize power losses, voltage violations, and load shedding under stochastic climate perturbations. Simulation results on the IEEE 33-bus radial test system augmented with ERA5 climate reanalysis data, demonstrate improvements in voltage regulation, energy efficiency, and resilience metrics. The framework also exhibits strong generalization across unseen weather scenarios and outperforms baseline rule based controls by reducing energy loss by 14.6% and improving recovery time by 19.5%. These findings position AI-integrated digital twins as a promising paradigm for future-proof, climate resilient smart grids.","author":[{"family":"Addo","given":"Kwabena"},{"family":"Kabeya","given":"Musasa"},{"family":"Ojo","given":"Evans"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202508.0708.v1","URL":"https://doi.org/10.20944/preprints202508.0708.v1","source":"preprints"},{"id":"doi:10.12688/f1000research.174205.1","type":"article-journal","title":"Artificial Intelligence-Based Digital Twins Metaverse to Improve STEM Work Skills and Adaptive Expertise in Higher Education: A Conceptual Framework","abstract":"Rapid advances in Artificial Intelligence (AI), Digital Twin (DT) technology, and the Metaverse have created new opportunities for transforming STEM education and workforce preparation. However, existing learning systems remain fragmented and lack an integrated, human-centered framework capable of supporting high-fidelity simulations, adaptive learning, and real-time competence development aligned with Industry 5.0. This study addresses this gap by developing a unified AI-Based Digital Twins Metaverse (AI-DTM) framework aimed at strengthening STEM employability skills and fostering adaptive expertise in higher education. This research employed a conceptual–analytical design comprising three structured phases: (1) a systematic conceptual synthesis guided by PRISMA 2020 to identify technological, pedagogical, and human-centric mechanisms relevant to AI, DTs, and Metaverse-based learning; (2) construction of an integrated AI-DTM framework through theoretical mapping, concept modeling, and iterative refinement; and (3) expert validation involving specialists in AI systems, digital twins, immersive learning, and instructional design. Evidence from interdisciplinary literature across AI-enhanced learning, DT-enabled simulation, and XR-based experiential environments informed the development of the framework. The resulting AI-DTM framework integrates AI-driven learner modeling, real-time DT simulations, and immersive Metaverse environments to create a unified, adaptive ecosystem. Key outcomes include: (a) personalized learning pathways supported by intelligent analytics and automated feedback; (b) high-fidelity, risk-free simulations that replicate authentic STEM work processes; (c) immersive and collaborative virtual experiences that enhance engagement, problem-solving, and teamwork; and (d) continuous competence profiling enabling the development of adaptive expertise. The framework demonstrates strong alignment with Industry 5.0 principles, supporting human–AI collaboration, data-driven decision-making, and future workforce readiness. This study provides a novel, scalable model that advances the design of AI-enabled learning ecosystems by integrating AI, Digital Twins, and Metaverse technologies into a cohesive architecture. The AI-DTM framework offers theoretical and practical contributions for enhancing STEM employability skills, strengthening adaptive expertise, and guiding institutions.","author":[{"family":"Syarifuddin","given":"Syarifuddin"},{"family":"Kurra","given":"Titus"},{"family":"Susanto","given":"Aris"},{"family":"Saputra","given":"Hendra"},{"family":"Lumbantobing","given":"Marko"},{"family":"Pancawati","given":"Ratna"},{"family":"Lieung","given":"Karlina"},{"family":"Mara","given":"Andry"}],"issued":{"date-parts":[[2025]]},"DOI":"10.12688/f1000research.174205.1","URL":"https://doi.org/10.12688/f1000research.174205.1","source":"preprints"},{"id":"doi:10.21203/rs.3.rs-6978024/v1","type":"article-journal","title":"A Hybrid Metaheuristic Approach for Multi-Objective Load Balancing in Digital Twin-Enabled Cloud Environment","abstract":"Abstract The rapid growth of digital twin services is pushing computational resources requirements to unprecedented levels. While cloud computing provides the scalable infrastructure needed to support these computational demands. However, the critical challenge lies in intelligently distributing workloads across distributed cloud environments through advanced load balancing techniques, where traditional deterministic approaches struggle to find optimal solutions within polynomial time. Therefore, addressing such challenges this paper proposes an efficient service placement approach based on Modified Cuckoo Search Optimization called CSOT-PM to optimize dynamic resource allocation in cloud computing which supporting digital twin services. The proposed work is benchmarked against established algorithms like the Genetic Algorithm (GA) and Ant Colony Optimization (ACO), using performance metrics such as makespan time, resource utilization, energy consumption, and Service Level Agreement (SLA) violations. The proposed algorithm achieves a 30% reduction in energy consumption and an 11% improvement in SLA.","author":[{"family":"Mishra","given":"Anand"},{"family":"Yadav","given":"Rahul"},{"family":"Kaur","given":"Prabhjot"},{"family":"Gargrish","given":"Shubham"},{"family":"Singh","given":"Mukund"},{"family":"Thakur","given":"Hardeo"},{"family":"Gupta","given":"Tarun"},{"family":"Prakash","given":"Shiv"},{"family":"Mishra","given":"Anand"}],"issued":{"date-parts":[[2025]]},"DOI":"10.21203/rs.3.rs-6978024/v1","URL":"https://doi.org/10.21203/rs.3.rs-6978024/v1","source":"preprints"},{"id":"doi:10.20944/preprints202510.0510.v1","type":"manuscript","title":"Musculoskeletal Digital Therapeutics and Digital Health Rehabilitation: A Global Paradigm Shift in Orthopaedic Care","abstract":"Musculoskeletal disorders (MSDs) affect over 1.7 billion people globally and rep-resent the leading cause of disability worldwide. Conventional rehabilitation strate-gies face challenges including limited accessibility, suboptimal adherence, and lack of personalization. Digital therapeutics (DTx)—evidence-based, software-driven interventions regulated as medical devices—have emerged as transformative solu-tions in chronic disease management. This comprehensive review synthesizes current knowledge on musculoskeletal DTx and digital health rehabilitation across ortho-paedic subspecialties. We describe core enabling technologies including artificial intelligence-driven motion analysis, wearable sensors, tele-rehabilitation platforms, and cloud-based ecosystems. Clinical applications spanning spine, upper and lower extremities, sports injuries, and trauma are examined alongside global regulatory frameworks, economic considerations, and implementation challenges. Early clinical evidence demonstrates improvements in functional outcomes, adherence, and cost-effectiveness. Future directions include digital twin technologies, predictive analytics, and integration with precision orthopaedics. By establishing a compre-hensive framework for musculoskeletal DTx implementation, this review highlights their potential to improve outcomes, reduce healthcare costs, and address global rehabilitation access gaps.","author":[{"family":"Lee","given":"Youn"},{"family":"Kim","given":"Tae"},{"family":"Kim","given":"Jong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202510.0510.v1","URL":"https://doi.org/10.20944/preprints202510.0510.v1","source":"preprints"},{"id":"doi:10.20944/preprints202508.0328.v1","type":"manuscript","title":"Navigating Sustainability in Pharma 5.0: The Role of Digital Twins in a Responsible Future","abstract":"Sustainability has become an essential priority across industries, as organizations grapple with the need to reduce environmental impact, conserve resources, and adapt to evolving regulations. In the pharmaceutical sector, the urgency of these demands is particularly acute, given the industry’s substantial energy use, resource consumption, and waste production. Meeting sustainability goals requires innovative approaches that can address these specific challenges. Digital Twin Technology (DTT) emerges as a powerful tool in this context, providing pharmaceutical manufacturers with a comprehensive solution to monitor, simulate, and optimize production processes in real-time. This article explores the transformative impact of Digital Twin Technology (DTT) in fostering sustainable manufacturing within the pharmaceutical industry. It provides an in-depth analysis of how DTT facilitates substantial reductions in material waste, improves energy efficiency, and enables predictive maintenance, thereby optimizing both environmental and operational performance. Drawing on real-time data integration, simulation modeling, and intelligent analytics, the study demonstrates how DTT enhances decision-making, ensures process stability, and minimizes production inefficiencies. A key contribution of this paper is the development of a structured framework that links core DTT functionalities to specific sustainability metrics, including carbon footprint reduction, resource optimization, and lifecycle performance improvement. Furthermore, the paper introduces novel use cases and data-driven strategies for applying DTT in pharmaceutical manufacturing environments, supported by case studies and empirical evidence. It also addresses the challenges of implementation, such as data interoperability, infrastructure requirements, and integration with legacy systems, providing actionable recommendations for overcoming these barriers. By aligning DTT applications with global sustainability agendas such as the UN Sustainable Development Goals (SDGs), this research positions DTT not only as a tool for operational excellence but also as a strategic enabler of environmental stewardship and industry resilience. Ultimately, the paper offers a practical and forward-looking perspective for industry stakeholders seeking to transition towards greener, smarter manufacturing paradigms.","author":[{"family":"Ali","given":"Atif"},{"family":"Ali","given":"Syed"},{"family":"Zaheer","given":"Nawal"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202508.0328.v1","URL":"https://doi.org/10.20944/preprints202508.0328.v1","source":"europepmc"},{"id":"doi:10.20944/preprints202508.0883.v1","type":"manuscript","title":"Secure Cloud‑Streaming Digital Twin (SCSDT): A Cloud‑First Metaverse Architecture for Industrial Training","abstract":"Traditional extended reality (XR) training faces a fundamental trade-off: high-fidelity, in-situ VR solutions offer superior pedagogical outcomes but are limited by expensive, resource-intensive hardware, while web-based alternatives sacrifice immersion for scalability. This research addresses this gap by presenting a novel architecture that delivers immersive XR training with operational efficiency. We introduce SCSDT, a threelayer architecture that fuses cloudGPU streamed metaverse delivery, zerotrust provisioning, and adaptive digitaltwin orchestration. Demonstrated on aviationmaintenance and industrialcyberrange pilots, SCSDT cuts VM provisioning time by an order of magnitude and reduces perlearner power draw by ≈60 %. Repeated-measures ANOVA on a cohort of six technicians over five instructional iterations shows a very large competencegap reduction (η²ₚ = 0.91, p < 0.0001). Our empirical evaluation showed a provisioning speed-up of 12.8× and a 62% energy reduction per learner, with statistically robust learning gains evident across iterations. The system operates over a single HTTPS port and streams at just 200–500 kB/s, enabling widespread access even on LTE links. By inheriting the pedagogical richness of in-situ VR while matching the operational efficiency of web-based labs, SCSDT delivers a superior cost–benefit ratio for enterprise training and successfully answers our research question.","author":[{"family":"Ghinea","given":"Mihalache"},{"family":"Deac","given":"Gicu"},{"family":"Ivanescu","given":"Radu"},{"family":"Deac","given":"Crina"},{"family":"Deac","given":"George"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202508.0883.v1","URL":"https://doi.org/10.20944/preprints202508.0883.v1","source":"preprints"},{"id":"oa:W4408798679","type":"article-journal","title":"AI-Driven Digital Twins for Enhancing Indoor Environmental Quality and Energy Efficiency in Smart Building Systems","abstract":"Smart buildings equipped with diverse control systems serve the objectives of gathering data, optimizing energy efficiency (EE), and detecting and diagnosing faults, particularly in the domain of indoor environmental quality (IEQ). Digital twins (DTs) offering an environmentally sustainable solution for managing facilities and incorporated with artificial intelligence (AI) create opportunities for maintaining IEQ and optimizing EE. The purpose of this study is to assess the impact of AI-driven DTs on enhancing IEQ and EE in smart building systems (SBS). A scoping review was performed to establish the theoretical background about DTs, AI, IEQ, and SBS, semi-structured interviews were conducted with the specialists in the industry to obtain qualitative data, and quantitative data were gathered via a computerized self-administered questionnaire (CSAQ) survey, focusing on how DTs can improve IEQ and EE in SBS. The results indicate that the AI-driven DT enhances occupants’ comfort and energy-efficiency performance and enables decision-making on automatic fault detection and maintenance conditioning to improve buildings’ serviceability and IEQ in real time, in response to the key industrial needs in building energy management systems (BEMS) and interrogative and predictive analytics for maintenance. The integration of AI with DT presents a transformative approach to improving IEQ and EE in SBS. The practical implications of this advancement span across design, construction, AI, and policy domains, offering significant opportunities and challenges that need to be carefully considered.","author":[{"family":"Yitmen","given":"İbrahim"},{"family":"Almusaed","given":"Amjad"},{"family":"Hussein","given":"Mohammed"},{"family":"Almssad","given":"Asaad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15071030","URL":"https://doi.org/10.3390/buildings15071030","source":"openalex"},{"id":"oa:W4412730814","type":"article-journal","title":"AI-enhanced digital twins in maintenance: Systematic review, industrial challenges, and bridging research–practice gaps","abstract":"The convergence of artificial intelligence (AI) and digital twin technology is reshaping maintenance strategies in the era of Industry 4.0. However, gaps persist between academic advancements and industrial adoption and expectation. This study systematically investigates the landscape of AI-enhanced digital twins for maintenance by integrating a systematic literature review (SLR) of related studies with in-depth interviews from industry practitioners. Our analysis reveals that while academia demonstrates robust applications of supervised, deep, and reinforcement learning to optimize digital twin models and prescribe data-driven actions, industrial implementation remains limited by challenges such as high scale dimension, data integration complexities, and insufficient workforce readiness. We identified and articulated three critical gap dimensions, scale, data, and model between academic research and industrial implementation and expectation. To bridge these gaps, we proposed a comprehensive five-layer framework for AI-enhanced digital twins, encompassing physical assets, data transmission, digital twins, AI analytics, and maintenance services. Actionable recommendations are provided, including the adoption of modular architectures, standardized data protocols, hybrid edge-cloud solutions, and targeted workforce upskilling. Our findings not only clarify the current state and challenges of AI-driven digital twins in maintenance but also offer a practical roadmap for accelerating their industrial implementation. This work advances the field by integrating insights from both academic research and industrial practice, offering concrete recommendations to support the practical realization of smart and sustainable maintenance practices.","author":[{"family":"Chen","given":"Siyuan"},{"family":"Bekar","given":"Ebru"},{"family":"Bokrantz","given":"Jon"},{"family":"Skoogh","given":"Anders"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jmsy.2025.07.006","URL":"https://doi.org/10.1016/j.jmsy.2025.07.006","source":"openalex"},{"id":"oa:W4407225421","type":"article-journal","title":"Leveraging Digital Twins for Enhancing Building Energy Efficiency: A Literature Review of Applications, Technologies, and Challenges","abstract":"Amid global efforts to mitigate greenhouse gas emissions, improving the energy efficiency of buildings has emerged as a strategic priority. Buildings account for approximately 40% of global energy consumption and a significant share of CO2 emissions, making them key targets for sustainable practices. This study employs a systematic literature review combined with a bibliometric analysis to explore the transformative potential of digital twins in building energy efficiency. The review synthesizes key contributions of digital twins in real-time monitoring, predictive modeling, renewable energy integration, and proactive maintenance while addressing critical challenges such as interoperability, scalability, and privacy. The originality of this work lies in its integrated approach, which identifies emerging trends and research gaps, providing actionable insights to guide the future adoption of digital twins in the building sector. These findings highlight the pivotal role of digital twins in fostering sustainable and intelligent energy practices.","author":[{"family":"Sghiri","given":"Amina"},{"family":"Gallab","given":"Maryam"},{"family":"Merzouk","given":"Safae"},{"family":"Assoul","given":"Saliha"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15030498","URL":"https://doi.org/10.3390/buildings15030498","source":"openalex"},{"id":"oa:W4410290414","type":"article-journal","title":"Digital twins, synthetic patient data, and in-silico trials: can they empower paediatric clinical trials?","abstract":"Randomised controlled trials are the gold standard to assess the effectiveness and safety of clinical interventions; however, many paediatric trials are discontinued early due to challenges in patient enrolment. Hence, most paediatric clinical trials suffer from lack of adequate power. Additionally, trials are expensive and might expose patients to unproven therapies. Alternatives to overcome these issues using virtual patient data-namely, digital twins, synthetic patient data, and in-silico trials-are now possible due to rapid advances in digital health-care tools and interventions. However, such digital innovations have been rarely used in paediatric trials. In this Viewpoint, we propose using virtual patient data to empower paediatric trials. The use of virtual patient data has the advantages of decreased exposure of children to potentially ineffective or risky interventions, shorter trial durations leading to more rapid ascertainment of safety and effectiveness of interventions, and faster drug approvals. Use of virtual patient data could lead to more personalised treatment options with low costs and could result in faster clinical implementation of interventions in children. However, ethical and regulatory concerns, including replacing humans with digital data, data privacy, and security should be addressed and the safety and sustainability of digital data innovation ensured before virtual patient data are adopted widely.","author":[{"family":"Pammi","given":"Mohan"},{"family":"Shah","given":"Prakesh"},{"family":"Liu","given":"Yang"},{"family":"Hagan","given":"Joseph"},{"family":"Aghaeepour","given":"Nima"},{"family":"Neu","given":"Josef"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.landig.2025.01.007","URL":"https://doi.org/10.1016/j.landig.2025.01.007","source":"openalex"},{"id":"oa:W4409180109","type":"article-journal","title":"IIoT-enabled digital twin for legacy and smart factory machines with LLM integration","abstract":"Recent advancements in Large Language Models (LLMs) have significantly transformed the field of natural data interpretation, translation, and user training. However, a notable gap exists when LLMs are tasked to assist with real-time context-sensitive machine data. The paper presents a multi-agent LLM framework capable of accessing and interpreting real-time and historical data through an Industrial Internet of Things (IIoT) platform for evidence-based inferences. Real-time data is acquired from several legacy machine artifacts (such as seven-segment displays, toggle switches, and knobs), smart machines (such as 3D printers), and building data (such as sound sensors and temperature measurement devices) through MTConnect data streaming protocol. Further, a multi-agent LLM framework that consists of four specialized agents – a supervisor agent, a machine-expertise agent, a data visualization agent, and a fault-diagnostic agent is developed for context-specific manufacturing tasks. This LLM framework is then integrated into a digital twin to visualize the unstructured data in real time. The paper also explores how LLM-based digital twins can serve as real time virtual experts through an avatar, minimizing reliance on traditional manuals or supervisor-based expertise. To demonstrate the functionality and effectiveness of this framework, we present a case study consisting of legacy machine artifacts and modern machines. The results highlight the practical application of LLM to assist and infer real-time machine data in a digital twin environment. Peer-review under responsibility of the scientific committee of the NAMRI/SME. • Legacy and smart machines data integration into a context-aware, high-fidelity digital twin. • Real-time, monitoring and process optimization of environmental and machine IIoT data. • Multi-agent LLM enhances machine control and provides expert-level insights with voice assistance and avatar. • Fault Diagnosis Agent optimizes 3D printing in real time, reducing material waste and improving print quality.","author":[{"family":"Gautam","given":"Anuj"},{"family":"Aryal","given":"Manish"},{"family":"Deshpande","given":"Sourabh"},{"family":"Padalkar","given":"Shailesh"},{"family":"Nikolaenko","given":"Mikhail"},{"family":"Tang","given":"Ming"},{"family":"Anand","given":"Sam"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jmsy.2025.03.022","URL":"https://doi.org/10.1016/j.jmsy.2025.03.022","source":"openalex"},{"id":"oa:W4410737780","type":"article-journal","title":"An Overview of Digital Twin Technology for Power Electronics: State-of-the-Art and Future Trends","abstract":"Power electronic systems (PESs) are pivotal in power generation, transmission, and diverse industrial applications. With the increasing shift toward digitalization, digital twin (DT) technology has emerged as a transformative enabler, enhancing the informatization and intelligence of PESs. This paper offers a comprehensive overview of DT applications for PESs, highlighting core features of real-time synchronization, accurate mapping, seamless data interaction, and high-fidelity modeling. Four prevalent DT modeling approaches are reviewed, with a detailed discussion of their respective strengths and challenges in the context of PESs. The paper further examines the role of DT across three critical lifecycle phases—design, control, and maintenance—illustrating how DT optimizes and drives innovation at each phase. By reviewing over 170 publications, this study identifies key trends, implementation challenges, and research gaps, offering valuable insights into the state-of-the-art and future directions for DT in PESs. This work aims to serve as a foundational reference for researchers and practitioners, fostering a deep understanding of the potential of DT and providing a comprehensive grasp of the application in academics and the industry.","author":[{"family":"Wu","given":"Chenhao"},{"family":"Cui","given":"Zhexin"},{"family":"Xia","given":"Qian"},{"family":"Yue","given":"Jiguang"},{"family":"Lyu","given":"Feng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/tpel.2025.3570638","URL":"https://doi.org/10.1109/tpel.2025.3570638","source":"openalex"},{"id":"oa:W4411578217","type":"article-journal","title":"Review of Applications of Digital Twins and Industry 4.0 for Machining","abstract":"Digital twins, as part of Industry 4.0, are critical for advanced smart manufacturing processes, including machining. Sensor systems in smart manufacturing allow for real-time tracking of all changes in the machining process as well as simulation of an object’s behavior in the real world. It can also intervene and correct any defects that may arise during the machining process. The current review covers basic concepts for machining processes for the first time in detail, including Big Data, the Internet of Things, product lifecycle management, continuous acquisition and lifecycle support, machine learning, digital twin prototypes, digital twin instances, digital twin aggregates, and digital twin environments. The review article examines digital twins for the most common machining processes, such as turning, milling, drilling, and grinding. This review also highlights the benefits and drawbacks, as well as the prospects for using digital twins in smart manufacturing.","author":[{"family":"Silva","given":"Leonardo"},{"family":"Pimenov","given":"Danil"},{"family":"Silva","given":"Rosemar"},{"family":"Erçetin","given":"Ali"},{"family":"Giasin","given":"Khaled"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/jmmp9070211","URL":"https://doi.org/10.3390/jmmp9070211","source":"openalex"},{"id":"oa:W4412993188","type":"article-journal","title":"Digital twins in renewable energy systems: A comprehensive review of concepts, applications, and future directions","abstract":"Digital Twin (DT) technologies are rapidly transforming the design, operation, and lifecycle management of renewable energy systems. This systematic review investigates DT applications across four major renewable energy domains—solar, wind, hydro, and hybrid systems—encompassing all lifecycle phases from initial design and simulation to maintenance and end-of-life (EoL) optimization. Using a PRISMA-guided methodology and keyword-driven thematic classification, the study analyzes over 150 peer-reviewed and industry-sourced publications from 2014 to 2024. A novel taxonomy is introduced to categorize DT applications by energy type and lifecycle phase, offering a structured and comprehensive perspective on current practices and research directions. The review synthesizes enabling technologies within a layered DT architecture, highlighting the roles of Artificial Intelligence (AI), Internet of Things (IoT), cloud/edge computing, and big data in realizing scalable, intelligent, and autonomous systems. Real-world deployments—such as GE's Digital Wind Farm and Huawei's DT-enhanced solar inverters—demonstrate tangible benefits, including up to a 25 % reduction in downtime and 10–20 % improvements in energy yield. Key challenges are critically examined, including model fidelity, data heterogeneity, standardization, and cybersecurity. In response, the study outlines a forward-looking agenda aligned with global sustainability frameworks such as the UN Sustainable Development Goals (SDGs) and the EU Green Deal. By integrating fragmented literature into a coherent, application-driven framework, this work advances academic understanding, supports industrial innovation, and informs policy development for the next generation of intelligent renewable energy systems.","author":[{"family":"Mbasso","given":"Wulfran"},{"family":"Harrison","given":"Ambe"},{"family":"Dagal","given":"Idriss"},{"family":"Jangir","given":"Pradeep"},{"family":"Khishe","given":"Mohammad"},{"family":"Kotb","given":"Hossam"},{"family":"Shaikh","given":"Muhammad"},{"family":"Smerat","given":"Aseel"},{"family":"Fendzi-Donfack","given":"Emmanuel"},{"family":"Kumar","given":"Raman"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.esr.2025.101814","URL":"https://doi.org/10.1016/j.esr.2025.101814","source":"openalex"},{"id":"oa:W4408588037","type":"article-journal","title":"Digital twin integration for dynamic quality loss control in fruit supply chains","abstract":"Effective cold chain management is imperative for minimizing food loss and maintaining quality in perishable logistics. This study integrates digital twin (DT) and artificial intelligence (AI) technologies to establish a “five-dimensional model” for cold supply chains, featuring a two-step approach that improve temperature prediction accuracy for shelf-life estimation. In the first step, a long short-term memory (LSTM) based model—trained solely on experimentally verified temperature data—accurately forecasts in-box conditions. Subsequently, a literature-based kinetic model applies well-established parameters to estimate remaining shelf life. By placing a single sensor at the pallet level and applying our box-level digital twin model, we achieved a temperature prediction error below ±0.3 °C (2σ), which translated into a shelf-life estimation error of under ±1.2 days for highly perishable fruits such as strawberries and lychees. Simulations also reveal the integrated DT–AI system reduces food loss by 8.6 %, 12.1 %, 13.6 %, and 15.5 % for strawberries, lychees, oranges, and apples, respectively, surpassing simpler ambient-based methods in both accuracy and food safety—particularly for highly perishable produce. Although hierarchical scaling of DTs (box, pallet, container) indicates increasing deviations at larger units, this trade-off between model precision and resource efficiency renders the solution practical across diverse cold-supply scenarios. Future work may incorporate end-point quality assessments and advanced management modules to further enhance reliability, reduce waste, and foster sustainability in global food logistics. • Integrates digital twin (DT) and artificial intelligence (AI) technologies for fruit supply chains. • An LSTM (Long Short-Term Memory) model exclusively on experimentally verified temperature data. • A single pallet-level sensor yields < ±0.3 °C error, translating to < ±1.2 days shelf-life deviation for highly perishable fruits. • Cuts food loss by 8.6–15.5 % for strawberries, lychees, oranges, and apples. • Box-level twins achieve the highest precision, balancing accuracy and efficiency.","author":[{"family":"Zou","given":"Yifeng"},{"family":"Wu","given":"Junzhang"},{"family":"Meng","given":"Xiangchao"},{"family":"Wang","given":"Xinfang"},{"family":"Manzardo","given":"Alessandro"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jfoodeng.2025.112577","URL":"https://doi.org/10.1016/j.jfoodeng.2025.112577","source":"openalex"},{"id":"doi:10.3390/digital6020051","type":"article-journal","title":"A Digital Twin-Based Framework for Biomechanical Ergonomics Assessment in Human–Robot Collaboration","abstract":"In today’s manufacturing industry, work-related musculoskeletal disorders (WMSDs) remain among the most prevalent occupational health issues. Collaborative robots (cobots) represent a promising technology to address this challenge. Consequently, ergonomics assessment in human–robot collaboration (HRC) has gained increasing attention in recent years. This study investigates the feasibility of using a coupled digital twin system consisting of a digital human model (DHM) and a cobot digital twin to assess detailed ergonomic parameters such as muscle activations and joint reaction forces in an HRC task. Selected parameters are used to develop an ergonomics map that condenses the effects of human–robot interaction into a single scalar value for each working position in the coronal plane in front of the user. The ergonomics mapping approach is presented, key influencing factors are identified, and critical workspace design implications are discussed.","author":[{"family":"Miehling","given":"Jörg"},{"family":"Guertler","given":"Matthias"},{"family":"Carmichael","given":"Marc"},{"family":"Khonasty","given":"Richardo"},{"family":"Fernandez","given":"Louis"},{"family":"Wartzack","given":"Sandro"},{"family":"Löffelmann","given":"Christopher"},{"family":"Carmichael","given":"Marc"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/digital6020051","URL":"https://doi.org/10.3390/digital6020051","source":"openalex"},{"id":"doi:10.2139/ssrn.7316019","type":"manuscript","title":"ExploraTwin, a Non-Profit Research Platform for Digital Twin Simulations","abstract":"Digital twin simulations show promise, but current empirical evidence suggests that the approach should be tested before being deployed in any particular context. To lower the friction for researchers and practitioners to test and deploy digital twin simulations, this brief commentary introduces \\href{https://exploratwin.org}{ExploraTwin}, an open-access, non-profit research platform for digital twin survey simulations. ExploraTwin supports two modes. In survey mode, researchers can upload a Qualtrics survey file or create a survey within the platform; select an available sample of digital twins; configure and run the simulation, and export analysis-ready data. In panel mode, researchers can assemble a small group of twins for open-ended conversations, document annotation, and moderated, focus-group-style voice discussions. We also developed CroissantTwin, a standardized data format for adding samples of digital twins to the platform. We demonstrate the survey mode workflow by using the platform to replicate 19 experiments on digital twins from the Twin-2K-500 dataset. ExploraTwin's survey execution fidelity is high: 99.6\\% of 197,000 answer units returned a structurally valid response on the first run.","author":[{"family":"Venkatanarayanan","given":"Naveen"},{"family":"Qiu","given":"Yuchen"},{"family":"Peng","given":"Tianyi"},{"family":"Gui","given":"George"},{"family":"Toubia","given":"Olivier"}],"issued":{"date-parts":[[2026]]},"DOI":"10.2139/ssrn.7316019","URL":"https://doi.org/10.2139/ssrn.7316019","source":"openalex"},{"id":"doi:10.21203/rs.3.rs-10340860/v1","type":"article-journal","title":"Fault Diagnosis for Satellite of Multi-Subsystems with Digital Twin Residual","abstract":"Abstract Fault diagnosis for multi-subsystem satellites represents a critical technology for constructing resilient space architectures. However, current Digital Twin (DT)-driven fault diagnostic methods face several challenges, including limited modeling of subsystem couplings and difficulties in dealing with the complex characteristics of satellite fault data. To address these issues, this paper proposes a Digital Twin Residual (DTR)-driven fault diagnostic method for satellite of multi-subsystems. Coupling relationships between satellite subsystems are first incorporated into the modeling process. The satellite fault data are then analyzed and visualized, revealing the impact of residuals on diagnostic performance. Consequently, raw fault data are transformed into residual data, where fault-related features become more significant, enabling effective diagnosis. The proposed DTR method is validated on a satellite fault dataset containing 49 scenarios and achieves superior diagnostic performance against existing DT-driven fault diagnostic methods. This study offers a solution for DT-driven satellite fault diagnosis, contributing to increased reliability and resilience of space systems.","author":[{"family":"Shi","given":"Yu"},{"family":"Deng","given":"Xuelei"},{"family":"Dong","given":"Yunfeng"},{"family":"Liu","given":"Fengrui"}],"issued":{"date-parts":[[2026]]},"DOI":"10.21203/rs.3.rs-10340860/v1","URL":"https://doi.org/10.21203/rs.3.rs-10340860/v1","source":"europepmc"},{"id":"doi:10.3390/s26144460","type":"article-journal","title":"Digital Twin-Enabled Dynamic Aggregation for Efficient Federated Learning.","abstract":"Federated learning (FL) enables collaborative model training without sharing raw data, but it faces challenges due to client heterogeneity, leading to inefficiency and reduced accuracy. This paper proposes a digital twin (DT)-based dynamic FL aggregation method to address these issues. The framework integrates a DT layer on the server side to perform preaggregation evaluations, simulating various aggregation strategies to select the optimal approach before actual global aggregation. An adaptive clustering method based on K-means is employed to group clients with similar characteristics, and a hierarchical aggregation evaluation strategy is designed to optimize both intra-cluster and inter-cluster aggregation, with the goal of minimizing latency and energy consumption while maximizing model accuracy. Simulation results on the MNIST and CIFAR-10 datasets demonstrate that the proposed method not only accelerates model convergence and improves accuracy but also significantly reduces training latency and energy consumption costs compared with baseline FL algorithms. This DT-assisted approach delivers a practical and effective optimization solution for federated learning deployment over large-scale heterogeneous IoT sensor networks.","author":[{"family":"Zhuang","given":"Wenqin"},{"family":"Wang","given":"Yuao"},{"family":"Wang","given":"Guocheng"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/s26144460","URL":"https://doi.org/10.3390/s26144460","source":"europepmc"},{"id":"doi:10.64898/2026.06.24.734391","type":"article-journal","title":"Cerebrovascular Imaging-to-Graph Reconstruction for Individualized Digital Twin Brains","abstract":"ABSTRACT The development of digital twins in medicine, i.e., virtual replicas of human organs, offers a promising path toward precision medicine by enabling interpretable, mechanistic, and actionable insights. In the brain, cerebrovascular twins support individualized modeling of hemodynamics and bio-transport, with broad applications. A major bottleneck, however, is the lack of robust methods to transform in vivo cerebrovascular images into simulation-ready cerebrovascular meshes or graphs. Here, we present CerebroVascular Imaging to Graph reconstruction (CVIG), a robust and multiscale framework for reconstructing whole brain cerebrovascular graphs from in vivo cerebrovascular images. CVIG integrates vessel vectorization, with tolerance to discontinuity in vessel structures, using a topology-guided assembly of vessel trees to generate cerebrovascular graphs from medical images. We demonstrate the ability of CVIG to generate vascular graphs with improved vascular coverage and topological correctness, the capability essential for high fidelity brain biophysical simulations. This work establishes a vascular graph framework for individualized modeling and analysis, providing a key foundation for digital twins of the human brain.","author":[{"family":"Xie","given":"Chen"},{"family":"Hu","given":"Beini"},{"family":"Alakeel","given":"Abdulmalik"},{"family":"Fleischer","given":"Candace"},{"family":"Fedorov","given":"Andrei"}],"issued":{"date-parts":[[2026]]},"DOI":"10.64898/2026.06.24.734391","URL":"https://doi.org/10.64898/2026.06.24.734391","source":"europepmc"},{"id":"doi:10.1186/s41747-026-00753-8","type":"article-journal","title":"Digital twin technologies in prostate cancer as a frontier for precision medicine.","abstract":"Prostate cancer (PCa) is the most frequently diagnosed malignancy among men and presents major clinical and socioeconomic challenges worldwide. Despite advances in early detection, imaging, and therapy, managing PCa remains complex due to disease heterogeneity, risks of overdiagnosis, and overtreatment. Digital twin (DT) technologies might represent an emerging conceptual framework aimed at supporting dynamic, patient-specific virtual modeling for personalized clinical decision-making. By integrating multimodal clinical, imaging, molecular, and physiological data, DTs can simulate disease progression, predict treatment responses, and support proactive, adaptive care. This perspective explores the conceptual framework for DT ecosystems in PCa, highlighting potential clinical impacts, infrastructural requirements, and barriers to implementation. Harnessing DTs could impact PCa management into a truly predictive, personalized, and participatory approach, improving outcomes and optimizing healthcare resource utilization globally. RELEVANCE STATEMENT: DT technologies may enable personalized, predictive PCa management by integrating multimodal patient data to guide diagnosis, treatment selection, and monitoring, with the potential to improve outcomes, reduce overtreatment, and optimize healthcare resource utilization KEY POINTS: DTs create virtual patient models to personalize PCa care. They integrate imaging, clinical, and molecular data into one system. This approach may reduce overdiagnosis and unnecessary treatments.","author":[{"family":"Pecoraro","given":"Martina"},{"family":"Messina","given":"Emanuele"},{"family":"Novelli","given":"Simone"},{"family":"Laschena","given":"Ludovica"},{"family":"Blasilli","given":"Graziano"},{"family":"Tronci","given":"Enrico"},{"family":"Panebianco","given":"Valeria"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1186/s41747-026-00753-8","URL":"https://doi.org/10.1186/s41747-026-00753-8","source":"europepmc"},{"id":"doi:10.1038/s41598-026-53111-4","type":"article-journal","title":"A digital twin-driven computation and analysis framework for low-altitude airspace.","abstract":"This study aims to address critical challenges in low-altitude airspace management, including high dynamic complexity, substantial safety hazards, and information fragmentation, and proposes a digital twin-enabled computation and analysis framework. The proposed framework adopts a four-layer digital twin architecture, enabling high-fidelity spatial mapping through multi-source heterogeneous data fusion, unified spatiotemporal representation, dynamic evolution modeling, and bidirectional physical-virtual closed-loop interaction. The proposed framework also incorporates intelligent components: a bidirectional GRU-Seq2Seq trajectory prediction model and a Kalman filter-based error compensation mechanism, supporting quantitative resource assessment, real-time trajectory analysis, and conflict warning. The proposed framework is verified experimentally in three operational scenarios: conventional single-target flight, multi-target cooperative flight, and extreme weather interference. Experimental results demonstrate that the proposed method has an average trajectory prediction error of 1.52 m under standard conditions, achieving a reduction of 47.9% compared to the Transformer baseline (2.36 m), 38.7% compared to ST-GCN (2.48 m), and 42.2% compared to the traditional geometric twin (2.63 m). Furthermore, the proposed method consistently maintains a low error across varying prediction horizons (5-15 s), with a maximum error of only 3.9 m at 15 s, significantly outperforming Transformer (4.3 m), ST-GCN (4.6 m), and the traditional geometric twin (6.3 m) models. In challenging scenarios involving GPS denial and communication interruption, the proposed method maintains superior robustness, with an average error of 2.15 and 2.38 m, respectively, which are markedly lower than those of competing methods. The results confirm that the proposed method outperforms both traditional geometric twin and deep learning-based approaches in key performance metrics, including position accuracy, prediction stability, and robustness, which validates its efficacy and practical suitability for low-altitude airspace management tasks.","author":[{"family":"He","given":"Zhenghan"},{"family":"Zhang","given":"Weibin"},{"family":"Du","given":"Peng"},{"family":"Liu","given":"Zhiyong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41598-026-53111-4","URL":"https://doi.org/10.1038/s41598-026-53111-4","source":"europepmc"},{"id":"doi:10.1038/s41598-026-43923-9","type":"article-journal","title":"A preliminary model to establish a digital twin for coffee roasting.","abstract":"The coffee industry has an economic impact of over 100 billion dollars per year, making it one of the most valuable markets in the world. Coffee roasting is a crucial step that occurs before the extraction process and is essential to the final quality of the coffee. The roasting of green coffee beans is a complex process involving various chemical reactions that play a crucial role in determining the taste, colour and aroma of the coffee. It consists of three steps: drying, roasting and cooling. All of them are characterised by heat and mass transfer. Heat transfer during the roasting process significantly influences the flavour profile of a coffee cup. The main chemical reaction that occurs during roasting is known as the \"Maillard reaction\", which is fundamental for the sensory profile of roasted coffee. In this study, we first introduce a mathematical model for coffee roasting based on the chemical dynamics of key compounds. The kinetic model is used to determine the variation in concentration of the main chemical substances that characterise the taste and aroma of coffee. The calibration of the model is obtained through an optimisation procedure, capable of estimating the kinetic rate constants. Real data from chemical analyses carried out on coffee samples at the end of the roasting process were used to support the calibration phase, while the initial chemical composition of green coffee was obtained from the ranges available in the literature.","author":[{"family":"Bruno","given":"Manuel"},{"family":"Egidi","given":"Nadaniela"},{"family":"Fatone","given":"Lorella"},{"family":"Giacomini","given":"Josephin"},{"family":"Maponi","given":"Pierluigi"},{"family":"Sagratini","given":"Gianni"},{"family":"Santanatoglia","given":"Agnese"},{"family":"Trebovic","given":"Edin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41598-026-43923-9","URL":"https://doi.org/10.1038/s41598-026-43923-9","source":"europepmc"},{"id":"doi:10.1016/j.ejrad.2026.112865","type":"article-journal","title":"Digital twin applications in radiology and radiotherapy: Applications, challenges, and future perspectives.","abstract":"Digital twin technology has emerged as a transformative innovation in healthcare, offering virtual replicas of physical entities at patient-level, equipment-level, and departmental-level that enable real-time monitoring, prediction, and optimisation. This narrative review synthesizes current evidence on digital twin maturity and clinical translation in radiology and radiotherapy. A comprehensive literature search was conducted across PubMed, Scopus, IEEE Xplore, and Web of Science databases for peer-reviewed articles published from 2018 onwards. The review reveals that digital twin applications in radiology remain predominantly experimental, with equipment-focused implementations (predictive maintenance, workflow optimization) showing greater maturity than patient-level applications. In radiology, emerging applications include personalised imaging protocol optimisation, predictive equipment maintenance, dose management, and workflow enhancement. In contrast, radiotherapy demonstrates more advanced patient-level digital twin integration, facilitating individualised treatment planning, real-time dose adaptation, treatment response prediction, and quality assurance. DT-aligned adaptive radiotherapy report improved local/locoregional control in the low-teens to ∼18% relative range, alongside clinically meaningful toxicity-risk reductions in selected endpoints, while maintaining lower radiation dose to organs. Key benefits include improved patient outcomes, reduced radiation exposure, enhanced treatment precision, and optimised resource utilisation. However, critical gaps persist in standardized validation frameworks, interoperability standards, and regulatory guidance. Implementation faces challenges including data integration complexity, computational requirements, regulatory uncertainties, and domain-specific barriers differing between radiology and radiotherapy contexts. Successful clinical translation requires addressing technical infrastructure gaps, establishing evidence-based validation protocols, and developing reimbursement mechanisms that recognize digital twin value. Digital twin technology demonstrates substantial potential for advancing precision medicine in imaging and radiation oncology.","author":[{"family":"Olawade","given":"David"},{"family":"Akinro","given":"Oluwatosin"},{"family":"Oisakede","given":"Emmanuel"},{"family":"Bello","given":"Oluwakemi"},{"family":"Analikwu","given":"Claret"},{"family":"Egbon","given":"Eghosasere"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.ejrad.2026.112865","URL":"https://doi.org/10.1016/j.ejrad.2026.112865","source":"europepmc"},{"id":"doi:10.1038/s41598-026-46719-z","type":"article-journal","title":"An implemented AI-driven digital twin architecture for proactive pavement maintenance in Finland.","abstract":"Traditional Pavement Management Systems (PMS) are increasingly hindered by aging infrastructure and reliance on reactive, manual inspection-based maintenance strategies. While Digital Twin (DT) technology offers a transformative pathway toward predictive management, existing implementations remain fragmented, often lacking holistic integration between Building Information Modeling (BIM), heterogeneous data sources, and advanced Artificial Intelligence (AI) analytics. To bridge this gap, this study develops and validates a comprehensive, web-based Intelligent Decision Support System (IDSS) founded on a novel four-layer Digital Twin architecture (Physical, Communication, Model, and Service layers). The methodology orchestrates a robust automated pipeline that integrates a sophisticated sequential AI processing chain-comprising generative data augmentation (Diffusion Models), real-time distress detection (YOLOv12) and semantic segmentation (DeepLabV3+), long-term performance prediction (LSTM), and meta-heuristic maintenance optimization (Grey Wolf Optimizer)-within a high-fidelity 3D BIM environment powered by Autodesk Platform Services. Results from a pilot implementation on the KT54 motorway in Finland demonstrate the system's capability to automate objective pavement condition assessment with high accuracy, substantiated by rigorous cross-dataset validation against independent field data and public datasets to ensure robust generalizability beyond the specific case study. The finalized interactive platform provides road authorities with unprecedented situational awareness, enabling real-time 3D monitoring, visualization of future deterioration trends, and the generation of cost-effective, proactive maintenance schedules under budget constraints. This research contributes a validated, scalable framework for transitioning infrastructure management from reactive approaches to a data-driven, predictive digital twin paradigm.","author":[{"family":"Talaghat","given":"Mohammad"},{"family":"Golroo","given":"Amir"},{"family":"Shahhosseini","given":"Vahid"},{"family":"Rasti","given":"Mehdi"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41598-026-46719-z","URL":"https://doi.org/10.1038/s41598-026-46719-z","source":"europepmc"},{"id":"doi:10.1038/s41598-026-48915-3","type":"article-journal","title":"Digital twin analysis of graphene-silicon solar Schottky-heterojunction cell efficiency for terrestrial photovoltaics.","abstract":"Graphene–silicon (Gr–Si) Schottky heterojunction solar cells provide a promising solution for radiation-tolerant and efficient photovoltaic devices. The present study provides the combined predictive modelling and physical characterization to evaluate the degradation assessment of Gr–Si solar cells. The results show Gr–Si devices successfully retain over 84% of their original power conversion efficiency (PCE) at a radiation intensity in terms of fluence in the order of 1015 particles cm−2, compared to only 55% for silicon cells alone. X-ray diffraction (XRD), Raman spectroscopy, and Atom Probe Tomography (APT) showed that graphene retains the interface integrity and is efficient in suppressing radiation-induced imperfections. A physics-informed semi-empirical digital twin (DT) assessment carried out using synthetic degradation datasets and Random Forest Regression, performing prediction efficiency above 96% (R2 > 0.96). Degradation mathematical models were also formulated to describe the characteristics of open-circuit voltage (Voc), short-circuit current density ​(Jsc)​, Fill Factor (FF), and Power Conversion Efficiency (PCE) for defined duration. The experimental validation and machine learning combined assessment provides a robust methodology for real-time monitoring and life-cycle prediction of photovoltaic devices in rich-radiation environments.","author":[{"family":"Kanti","given":"Praveen"},{"family":"Kumar","given":"HGP"},{"family":"Elsaeedy","given":"HI"},{"family":"Wanatasanappan","given":"VV"},{"family":"Syum","given":"Gabr"},{"family":"Hamida","given":"Mohamed"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41598-026-48915-3","URL":"https://doi.org/10.1038/s41598-026-48915-3","source":"europepmc"},{"id":"doi:10.5281/zenodo.21371025","type":"article-journal","title":"DIGITAL TWINS IN PHARMACEUTICAL MANUFACTURING AND QUALITY ASSURANCE: APPLICATIONS, BENEFITS, CHALLENGES, AND FUTURE PERSPECTIVES","abstract":"The pharmaceutical industry is undergoing a digital transformation through the adoption of Industry 4.0 technologies. Among these innovations, Digital Twin (DT) technology has emerged as a powerful tool for improving manufacturing efficiency, product quality, and regulatory compliance. A digital twin is a virtual representation of a physical system that continuously receives and analyzes real-time data from manufacturing processes. In pharmaceutical manufacturing, digital twins enable process simulation, predictive maintenance, quality monitoring, risk assessment, and process optimization. This review discusses the concept, architecture, applications, benefits, challenges, and future prospects of digital twins in pharmaceutical manufacturing and quality assurance.","author":[{"family":"Shelake","given":"Gayatri"},{"family":"Chavan","given":"Ashitosha"},{"family":"Pawar","given":"Keshav"},{"family":"Burungale","given":"Dr"},{"family":"Patil","given":"Dr"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.21371025","URL":"https://doi.org/10.5281/zenodo.21371025","source":"datacite"},{"id":"doi:10.5281/zenodo.21371026","type":"article-journal","title":"DIGITAL TWINS IN PHARMACEUTICAL MANUFACTURING AND QUALITY ASSURANCE: APPLICATIONS, BENEFITS, CHALLENGES, AND FUTURE PERSPECTIVES","abstract":"The pharmaceutical industry is undergoing a digital transformation through the adoption of Industry 4.0 technologies. Among these innovations, Digital Twin (DT) technology has emerged as a powerful tool for improving manufacturing efficiency, product quality, and regulatory compliance. A digital twin is a virtual representation of a physical system that continuously receives and analyzes real-time data from manufacturing processes. In pharmaceutical manufacturing, digital twins enable process simulation, predictive maintenance, quality monitoring, risk assessment, and process optimization. This review discusses the concept, architecture, applications, benefits, challenges, and future prospects of digital twins in pharmaceutical manufacturing and quality assurance.","author":[{"family":"Shelake","given":"Gayatri"},{"family":"Chavan","given":"Ashitosha"},{"family":"Pawar","given":"Keshav"},{"family":"Burungale","given":"Dr"},{"family":"Patil","given":"Dr"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.21371026","URL":"https://doi.org/10.5281/zenodo.21371026","source":"datacite"},{"id":"doi:10.5281/zenodo.22111320","type":"article-journal","title":"Ontologically Integrated Digital Twin of the Entire Hospital Ecosystem","abstract":"The rapid evolution of Healthcare 5.0 demands intelligent hospital ecosystems capable of integrating clinical care, operational management, and physical infrastructure into a unified, continuously adaptive environment. However, contemporary healthcare information systems remain fragmented across Electronic Health Records (EHRs), Internet of Medical Things (IoMT) devices, laboratory systems, imaging platforms, and Building Management Systems (BMS), resulting in severe data siloing, limited semantic interoperability, delayed decision- making, and inadequate real-time situational awareness. Although digital twin technology has emerged as a promising paradigm for creating virtual representations of physical entities, existing healthcare implementations are largely confined to isolated organs, medical devices, or specific clinical workflows, thereby failing to support hospital-wide intelligence and cross-domain reasoning. This paper proposes the Ontologically Integrated Digital Twin (OIDT) framework, a comprehensive and semantically enriched architecture for constructing a scalable, hospital-wide digital twin capable of synchronizing physical, cyber, and organizational processes in real time. The framework is founded on a formal Web Ontology Language (OWL) knowledge model, termed HospitalOnt, which unifies heterogeneous healthcare and infrastructure data by aligning internationally recognized standards including SNOMED CT, LOINC, RxNorm, HL7 FHIR, and the W3C SSN/SOSA sensor ontologies. Through this semantic foundation, OIDT enables machine-understandable relationships among patients, clinicians, medical devices, hospital assets, environmental sensors, workflows, and facility resources. A distributed five-layer architecture is presented, comprising Physical Sensing, Edge Intelligence, Streaming Integration, Semantic Knowledge, and Application Intelligence layers. Real- time data acquisition is achieved through IoMT devices, environmental sensors, and operational systems connected via MQTT and FHIR interfaces. The streaming backbone employs Apache Kafka and Apache Flink for high- throughput ingestion, semantic annotation, event processing, and temporal synchronization. Multi-model persistence is implemented using Neo4j for graph-based knowledge representation, InfluxDB for time-series telemetry, and PostgreSQL for transactional healthcare data, thereby supporting both analytical and operational workloads. To demonstrate intelligent decision support, OIDT integrates multiple AI and simulation components. An LSTM Autoencoder performs predictive maintenance of critical medical equipment, detecting latent degradation patterns before failure. A Prophet-based forecasting model predicts emergency department (ED) patient arrivals and bed occupancy trends, while a Discrete-Event Simulation (DES) engine evaluates alternative resource-allocation strategies under varying operational conditions. The semantic knowledge graph further enables graph-based reasoning and contextual inference, allowing cross-domain queries that combine clinical, operational, and environmental information. The framework was validated on a 200-bed simulated smart hospital testbed incorporating 50 Raspberry Pi edge nodes, synthetic HL7 FHIR event streams, and heterogeneous IoMT telemetry. Experimental results demonstrate substantial operational improvements, including a 28% reduction in average ED waiting time, a 93.0% F1-score for ventilator mechanical failure prediction with a mean lead time of 3.6 hours, an emergency alert propagation latency of 4.1 seconds, representing a 14× improvement over conventional phone-tree workflows, and a 12% reduction in facility energy consumption through context-aware optimization. Semantic interoperability evaluation achieved 96.0% cross-domain query resolution, compared with 24.0% in traditional siloed architectures, while scalability experiments confirmed near-linear performance up to 10,000 concurrent IoT device streams with an avera","author":[{"family":"Balakrishnan","given":"Sooraj"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.22111320","URL":"https://doi.org/10.5281/zenodo.22111320","source":"datacite"},{"id":"doi:10.5281/zenodo.22111319","type":"article-journal","title":"Ontologically Integrated Digital Twin of the Entire Hospital Ecosystem","abstract":"The rapid evolution of Healthcare 5.0 demands intelligent hospital ecosystems capable of integrating clinical care, operational management, and physical infrastructure into a unified, continuously adaptive environment. However, contemporary healthcare information systems remain fragmented across Electronic Health Records (EHRs), Internet of Medical Things (IoMT) devices, laboratory systems, imaging platforms, and Building Management Systems (BMS), resulting in severe data siloing, limited semantic interoperability, delayed decision- making, and inadequate real-time situational awareness. Although digital twin technology has emerged as a promising paradigm for creating virtual representations of physical entities, existing healthcare implementations are largely confined to isolated organs, medical devices, or specific clinical workflows, thereby failing to support hospital-wide intelligence and cross-domain reasoning. This paper proposes the Ontologically Integrated Digital Twin (OIDT) framework, a comprehensive and semantically enriched architecture for constructing a scalable, hospital-wide digital twin capable of synchronizing physical, cyber, and organizational processes in real time. The framework is founded on a formal Web Ontology Language (OWL) knowledge model, termed HospitalOnt, which unifies heterogeneous healthcare and infrastructure data by aligning internationally recognized standards including SNOMED CT, LOINC, RxNorm, HL7 FHIR, and the W3C SSN/SOSA sensor ontologies. Through this semantic foundation, OIDT enables machine-understandable relationships among patients, clinicians, medical devices, hospital assets, environmental sensors, workflows, and facility resources. A distributed five-layer architecture is presented, comprising Physical Sensing, Edge Intelligence, Streaming Integration, Semantic Knowledge, and Application Intelligence layers. Real- time data acquisition is achieved through IoMT devices, environmental sensors, and operational systems connected via MQTT and FHIR interfaces. The streaming backbone employs Apache Kafka and Apache Flink for high- throughput ingestion, semantic annotation, event processing, and temporal synchronization. Multi-model persistence is implemented using Neo4j for graph-based knowledge representation, InfluxDB for time-series telemetry, and PostgreSQL for transactional healthcare data, thereby supporting both analytical and operational workloads. To demonstrate intelligent decision support, OIDT integrates multiple AI and simulation components. An LSTM Autoencoder performs predictive maintenance of critical medical equipment, detecting latent degradation patterns before failure. A Prophet-based forecasting model predicts emergency department (ED) patient arrivals and bed occupancy trends, while a Discrete-Event Simulation (DES) engine evaluates alternative resource-allocation strategies under varying operational conditions. The semantic knowledge graph further enables graph-based reasoning and contextual inference, allowing cross-domain queries that combine clinical, operational, and environmental information. The framework was validated on a 200-bed simulated smart hospital testbed incorporating 50 Raspberry Pi edge nodes, synthetic HL7 FHIR event streams, and heterogeneous IoMT telemetry. Experimental results demonstrate substantial operational improvements, including a 28% reduction in average ED waiting time, a 93.0% F1-score for ventilator mechanical failure prediction with a mean lead time of 3.6 hours, an emergency alert propagation latency of 4.1 seconds, representing a 14× improvement over conventional phone-tree workflows, and a 12% reduction in facility energy consumption through context-aware optimization. Semantic interoperability evaluation achieved 96.0% cross-domain query resolution, compared with 24.0% in traditional siloed architectures, while scalability experiments confirmed near-linear performance up to 10,000 concurrent IoT device streams with an avera","author":[{"family":"Balakrishnan","given":"Sooraj"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.22111319","URL":"https://doi.org/10.5281/zenodo.22111319","source":"datacite"},{"id":"doi:10.48550/arxiv.2608.20539","type":"manuscript","title":"ExploraTwin, a Non-Profit Research Platform for Digital Twin Simulations","abstract":"Digital twin simulations show promise, but current empirical evidence suggests that the approach should be tested before being deployed in any particular context. To lower the friction for researchers and practitioners to test and deploy digital twin simulations, this brief commentary introduces ExploraTwin (https://exploratwin.org), an open-access, non-profit research platform for digital twin survey simulations. ExploraTwin supports two modes. In survey mode, researchers can upload a Qualtrics survey file or create a survey within the platform; select an available sample of digital twins; configure and run the simulation, and export analysis-ready data. In panel mode, researchers can assemble a small group of twins for open-ended conversations, document annotation, and moderated, focus-group-style voice discussions. We also developed CroissantTwin, a standardized data format for adding samples of digital twins to the platform. We demonstrate the survey mode workflow by using the platform to replicate 19 experiments on digital twins from the Twin-2K-500 dataset. ExploraTwin's survey execution fidelity is high: 99.6% of 197,000 answer units returned a structurally valid response on the first run.","author":[{"family":"Venkat","given":"Naveen"},{"family":"Qiu","given":"Yuchen"},{"family":"Peng","given":"Tianyi"},{"family":"Gui","given":"George"},{"family":"Toubia","given":"Olivier"}],"issued":{"date-parts":[[2026]]},"DOI":"10.48550/arxiv.2608.20539","URL":"https://doi.org/10.48550/arxiv.2608.20539","source":"datacite"},{"id":"doi:10.21203/rs.3.rs-8500641/v1","type":"article-journal","title":"A Digital Twin-Driven Computation and Analysis Framework for Low-Altitude Airspace","abstract":"Abstract To address key challenges in low-altitude airspace management, such as high dynamic complexity, significant safety risks, and information fragmentation, a digital twin-based methodology for low-altitude airspace computation and analysis is proposed in this paper. First, a four-layer digital twin system architecture is established. High-fidelity digital twin mapping of the low-altitude airspace is achieved through the integration of multi-source heterogeneous data, the application of unified spatio-temporal representation, the implementation of dynamic evolution modeling, and the facilitation of bidirectional physical-virtual closed-loop interaction. Second, innovative intelligent algorithms, including a bidirectional GRU-Seq2Seq trajectory prediction model and a Kalman filter-based error compensation mechanism, are incorporated. These components form a comprehensive technical framework that supports quantitative airspace resource evaluation, real-time trajectory analysis, and conflict prediction and early warning. Finally, experimental validation is conducted across three scenarios: single-target conventional flight, multi-target collaborative flight, and extreme weather interference. The results indicate that, compared with the conventional geometric twin approach, the proposed method achieves a 37.2% reduction in trajectory deviation, a 62.5% improvement in conflict warning accuracy, and a 28.6% enhancement in site selection safety. Furthermore, it is shown to outperform traditional methods across five core performance metrics, including computational efficiency and trajectory accuracy, which further confirms its strong suitability for supporting the high-quality development of the low-altitude economy.","author":[{"family":"He","given":"Zhenghan"},{"family":"Zhang","given":"Weibin"},{"family":"Du","given":"Peng"},{"family":"Liu","given":"Zhiyong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.21203/rs.3.rs-8500641/v1","URL":"https://doi.org/10.21203/rs.3.rs-8500641/v1","source":"preprints"},{"id":"doi:10.64898/2026.03.06.710030","type":"article-journal","title":"Digital Twin Brain simulation and manipulation of a functional brain network underlying mental illness","abstract":"Linking synaptic-level perturbations to distributed brain-network dynamics remains a central challenge for understanding and treating mental illness. Although recent whole-brain models can reproduce individual brain activity patterns, they largely function as descriptive simulators rather than mechanistic, intervention-capable systems. Here we present an intervention-capable digital twin of the human brain, integrating individual neuroanatomy and task-evoked dynamics within a neuronal-scale framework. Individualised digital twin brains recapitulate a participant-specific compact cortico-subcortical network phenotype that captures transdiagnostic psychopathology across population and clinical cohorts. In silico modulation of excitatory and inhibitory synaptic conductance produces bidirectional, heterogeneous network responses across individuals. Population-scale simulations stratify individuals and predict longitudinal symptom trajectories from DTB-derived response profiles. Independent pharmacological functional MRI data further validate the predicted baseline-dependent network responses in vivo. Together, these findings establish digital brain models as experimental platforms for mechanistic perturbation, behavioural prediction and stratification, providing a foundation for precision neuroscience and psychiatry.","author":[{"family":"Xia","given":"Yunman"},{"family":"Peng","given":"Songjun"},{"family":"Dukart","given":"Juergen"},{"family":"Xie","given":"Y"},{"family":"Xiang","given":"Shitong"},{"family":"Petkoski","given":"Spase"},{"family":"Li","given":"Zilin"},{"family":"Hipp","given":"Joerg"},{"family":"Muthukumaraswamy","given":"Suresh"},{"family":"Forsyth","given":"Anna"},{"family":"Jia","given":"Tianye"},{"family":"Vaidya","given":"Nilakshi"}],"issued":{"date-parts":[[2026]]},"DOI":"10.64898/2026.03.06.710030","URL":"https://doi.org/10.64898/2026.03.06.710030","source":"preprints"},{"id":"oa:W4407896696","type":"article-journal","title":"Digital Wellness Programs in the Workplace: Meta-Review","abstract":"BACKGROUND: Corporate wellness programs are increasingly using digital technologies to promote employee health. Digital wellness programs (DWPs) refer to initiatives that deliver health interventions through digital tools. Despite a growing body of evidence on DWPs, the literature remains fragmented across multiple health domains. OBJECTIVE: This study aims to provide a comprehensive synthesis of existing research on the efficacy (eg, impact on employee's physical health, mental well-being, behavioral changes, and absenteeism) and acceptability (eg, engagement, perceived usefulness, and adoption) of employer-provided DWPs. Specifically, we aim to map the extent, range, and nature of research on this topic; summarize key findings; identify gaps; and facilitate knowledge dissemination. METHODS: We conducted a meta-review of studies published between 2000 and 2023. We adopted a database-driven search approach, including the MEDLINE, PsycINFO, ProQuest Central, and Web of Science Core Collection databases. The inclusion criteria consisted of (1) review articles; (2) publications in English, French, or German; (3) studies reporting on digital health interventions implemented in organizations; (4) studies reporting on nonclinical or preclinical employee populations; and (5) studies assessing the efficacy and acceptability of employer-provided DWPs. We performed a descriptive numerical summary and thematic analysis of the included studies. RESULTS: Out of 593 nonduplicate studies screened, 29 met the inclusion criteria. The most investigated health domains included mental health (n=19), physical activity (n=8), weight management (n=6), unhealthy behavior change (n=4), and sleep management (n=2). In total, 24 reviews focused on the efficacy of DWPs, primarily in relation to health-related outcomes (eg, stress and weight), while fewer reviews addressed organization-related outcomes (eg, burnout and absenteeism). Four reviews explored the mechanisms of action, and 3 assessed the acceptability of DWPs using various measures. Overall, the findings support the efficacy and acceptability of DWPs, although significant gaps persist, particularly regarding the durability of outcomes, the role of technology, and the causal mechanisms underlying behavioral change. CONCLUSIONS: While DWPs show promise across a variety of health domains, several aspects of their effectiveness remain underexplored. Practitioners should capitalize on existing evidence of successful DWPs while acknowledging the limitations in the literature.","author":[{"family":"Amirabdolahian","given":"Saeed"},{"family":"Paré","given":"Guy"},{"family":"Tams","given":"Stefan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.2196/70982","URL":"https://doi.org/10.2196/70982","source":"openalex"},{"id":"oa:W4416953562","type":"article-journal","title":"Digital Twin–Based Simulation and Decision-Making Framework for the Renewal Design of Urban Industrial Heritage Buildings and Environments: A Case Study of the Xi’an Old Steel Plant Industrial Park","abstract":"In response to the coexistence of multi-objective conflicts and environmental complexity in the renewal of contemporary urban industrial heritage, this study develops a simulation and decision-making methodology for architectural and environmental renewal based on a digital twin framework. Using the Xi’an Old Steel Plant Industrial Heritage Park as a case study, a community-scale digital twin model integrating multiple dimensions—architecture, environment, population, and energy systems—was constructed to enable dynamic integration of multi-source data and cross-scale response analysis. The proposed methodology comprises four core components: (1) integration of multi-source baseline datasets—including typical meteorological year data, industry standards, and open geospatial information—through BIM, GIS, and parametric modeling, to establish a unified data environment for methodological validation; (2) development of a high-performance dynamic simulation system integrating ENVI-met for microclimate and thermal comfort modeling, EnergyPlus for building energy and carbon emission assessment, and AnyLogic for multi-agent spatial behavior simulation; (3) establishment of a comprehensive performance evaluation model based on Multi-Criteria Decision Analysis (MCDA) and the Analytic Hierarchy Process (AHP); (4) implementation of a visual interactive platform for design feedback and scheme optimization. The results demonstrate that under parameter-calibrated simulation conditions, the digital twin system accurately reflects environmental variations and crowd behavioral dynamics within the industrial heritage site. Under the optimized renewal scheme, the annual carbon emissions of the park decrease relative to the baseline scenario, while the Universal Thermal Climate Index (UTCI) and spatial vitality index both show significant improvement. The findings confirm that digital twin-driven design interventions can substantially enhance environmental performance, energy efficiency, and social vitality in industrial heritage renewal. This approach marks a shift from experience-driven to evidence-based design, providing a replicable technological pathway and decision-support framework for the intelligent, adaptive, and sustainable renewal of post-industrial urban spaces. The digital twin framework proposed in this study establishes a validated paradigm for model coupling and decision-making processes, laying a methodological foundation for future integration of comprehensive real-world data and dynamic precision mapping.","author":[{"family":"Zhao","given":"Yian"},{"family":"Li","given":"Kun"},{"family":"Zhang","given":"Weiping"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15234367","URL":"https://doi.org/10.3390/buildings15234367","source":"openalex"},{"id":"oa:W4412646300","type":"article-journal","title":"From Process Simulation to Digital Twin: Custom Gasifier Modelling, Complex Kinetics and Optimisation in AVEVA Process Simulation","abstract":"ABSTRACT This study demonstrates the potential of AVEVA Process Simulation (APS) as a platform for developing process engineering digital twins, integrating customised process models, simulation, and optimisation into a unified environment. A custom gasifier model was built within APS, incorporating thermodynamic equilibrium and empirical corrections to enhance predictive accuracy, and validated against experimental data. Various gasification scenarios were simulated to evaluate the influence of equivalence ratio, biomass moisture, and temperature on syngas composition and process performance. APS's flexibility in handling complex kinetic systems was showcased through the implementation of a fugacity‐based kinetic model for methanol synthesis, which deviates from traditional Langmuir‐‐Hinshelwood reaction rates. Notably, APS accepts reaction rates in any mathematical form without the need for adaptation to predefined formats, enabling the seamless implementation of unconventional kinetic expressions. Systematic scenario analysis using APS's case study feature explored the effects of temperature, pressure, and feed composition on methanol yield, identifying optimal ratios and the adverse impact of excess . Finally, multi‐variable optimisation was performed to maximise methanol production by simultaneously tuning key operating variables. The results highlight APS's capability not only as an advanced process simulator but as a foundational tool for creating predictive adaptable digital twins that support process design, optimisation, and decision‐making across the process lifecycle.","author":[{"family":"Pereira","given":"Geisiane"},{"family":"Bispo","given":"Heleno"},{"family":"Costa","given":"Thiago"},{"family":"Neiro","given":"Sérgio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/dgt2.70009","URL":"https://doi.org/10.1049/dgt2.70009","source":"openalex"},{"id":"oa:W4415648041","type":"article-journal","title":"Mixed Reality-Based Multi-Scenario Visualization and Control in Automated Terminals: A Middleware and Digital Twin Driven Approach","abstract":"This study presents a Digital Twin–Mixed Reality (DT–MR) framework for the immersive and interactive supervision of automated container terminals (ACTs), addressing the fragmented data and limited situational awareness of conventional 2D monitoring systems. The framework employs a middleware-centric architecture that integrates heterogeneous subsystems—covering terminal operation, equipment control, and information management—through standardized industrial communication protocols. It ensures synchronized timestamps and delivers semantically aligned, low-latency data streams to a multi-scale Digital Twin developed in Unity. The twin applies level-of-detail modeling, spatial anchoring, and coordinate alignment (from Industry Foundation Classes (IFCs) to east–north–up (ENU) coordinates and Unity space) for accurate registration with physical assets, while a Microsoft HoloLens 2 device provides an intuitive Mixed Reality interface that combines gaze, gesture, and voice commands with built-in safety interlocks for secure human–machine interaction. Quantitative performance benchmarks—latency ≤100 ms, status refresh ≤1 s, and throughput ≥10,000 events/s—were met through targeted engineering and validated using representative scenarios of quay crane alignment and automated guided vehicle (AGV) rerouting, demonstrating improved anomaly detection, reduced decision latency, and enhanced operational resilience. The proposed DT–MR pipeline establishes a reproducible and extensible foundation for real-time, human-in-the-loop supervision across ports, airports, and other large-scale smart infrastructures.","author":[{"family":"Wang","given":"Yubo"},{"family":"Zhang","given":"Enyu"},{"family":"Yang","given":"Ang"},{"family":"Du","given":"Kejun"},{"family":"Gao","given":"Jing"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15213879","URL":"https://doi.org/10.3390/buildings15213879","source":"openalex"},{"id":"oa:W4411154655","type":"article-journal","title":"Path Planning for Lunar Rovers in Dynamic Environments: An Autonomous Navigation Framework Enhanced by Digital Twin-Based A*-D3QN","abstract":"In lunar exploration missions, rovers must navigate multiple waypoints within strict time constraints while avoiding dynamic obstacles, demanding real-time, collision-free path planning. This paper proposes a digital twin-enhanced hierarchical planning method, A*-D3QN-Opt (A-Star-Dueling Double Deep Q-Network-Optimized). The framework combines the A* algorithm for global optimal paths in static environments with an improved D3QN (Dueling Double Deep Q-Network) for dynamic obstacle avoidance. A multi-dimensional reward function balances path efficiency, safety, energy, and time, while priority experience replay accelerates training convergence. A high-fidelity digital twin simulation environment integrates a YOLOv5-based multimodal perception system for real-time obstacle detection and distance estimation. Experimental validation across low-, medium-, and high-complexity scenarios demonstrates superior performance: the method achieves shorter paths, zero collisions in dynamic settings, and 30% faster convergence than baseline D3QN. Results confirm its ability to harmonize optimality, safety, and real-time adaptability under dynamic constraints, offering critical support for autonomous navigation in lunar missions like Chang’e and future deep space exploration, thereby reducing operational risks and enhancing mission efficiency.","author":[{"family":"Liu","given":"Wei"},{"family":"Wan","given":"Gang"},{"family":"Liu","given":"Jia"},{"family":"Cong","given":"Dianwei"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/aerospace12060517","URL":"https://doi.org/10.3390/aerospace12060517","source":"openalex"},{"id":"oa:W4411395706","type":"article-journal","title":"Enhancing predictive maintenance in lean manufacturing for continuous process improvement using digital twin technology","abstract":"The latest advancement in digital technologies has greatly revolutionized modern manufacturing processes, particularly through the adoption of Lean Manufacturing initiatives aimed at minimizing wastage and enhancing operational efficiency. Predictive Maintenance (PM) being one of the primary drivers of transformation in lean manufacturing by reducing equipment downtime and optimizing asset performance. The lack of failure data is one of the biggest obstacles to PM deployment because traditional maintenance methods are used to maintain equipment after they break down. In order to address the issue of data scarcity, this study investigates the use of Digital Twin (DT) technology, which creates a virtual duplicate of the physical item and enables real-time monitoring utilizing sensors and Internet of Things devices for predictive analysis. IoT and data analytics are well complemented by digital twin technology, giving the manufacturer access to real-time information about the state of the machines while they are operating. This connectivity allows them to predict future asset failures accurately and strategically schedule maintenance activities in advance. The findings presented in this paper demonstrate that digital twin applications can reduce maintenance costs by 35% and machine uptime by 98%. It also presents case studies of DT application across different industries, and comparative study of positive impacts achieved through DT adoption. Cumulatively, the study highlights DT's transformational capability to facilitate lean initiatives and demands further investigation into integrations of emerging technology for process improvement.","author":[{"family":"Iheanacho","given":"Chinemerem"},{"family":"Ozurumba","given":"Ebubechukwu"},{"family":"Amajoh","given":"Nkemdi"},{"family":"Igwe","given":"Emeka"}],"issued":{"date-parts":[[2025]]},"DOI":"10.30574/wjarr.2025.26.3.2307","URL":"https://doi.org/10.30574/wjarr.2025.26.3.2307","source":"openalex"},{"id":"oa:W4412416287","type":"article-journal","title":"Multilayer networks describing urban interactions for building the digital twins of five cities in Spain","abstract":"Networks specifying who interacts with whom are crucial for mathematical models of epidemic spreading. In the context of emerging diseases, these networks have the potential to encode multiple interaction contexts where non-pharmaceutical interventions can be introduced, allowing for proper comparisons among different intervention strategies in a plethora of contexts. Consequently, a multilayer network describing interactions in a population and detailing their contexts in different layers constitutes an appropriate tool for such descriptions. These approaches however become challenging in large-scale systems such as cities, particularly in a framework where data protection policies are enhanced. In this work, we present a methodology to build such multilayer networks and make those corresponding to five Spanish cities available. Our work uses approaches informed by multiple available datasets to create realistic digital twins of the citizens and their interactions and provides a playground to explore different pandemic scenario in realistic settings for better preparedness.","author":[{"family":"Rodríguez","given":"Jorge"},{"family":"Aleta","given":"Alberto"},{"family":"Moreno","given":"Yamir"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41597-025-05551-2","URL":"https://doi.org/10.1038/s41597-025-05551-2","source":"openalex"},{"id":"oa:W4417434861","type":"article-journal","title":"Digital Twins in Dentistry: A Narrative Review of Current Applications and Future Horizons","abstract":"Abstract Aim: The integration of Industry 4.0 into healthcare has introduced the Digital Twin (DT), a dynamic virtual replica that mirrors physical biological systems. Traditional dental diagnostics often rely on static two-dimensional methods, which lack predictive capabilities and are prone to errors. This review evaluates the adaptability of DT technology in dentistry, analyzing its potential to enhance diagnostic precision and treatment efficiency compared to conventional modalities. Materials and Methods: A narrative review was conducted using the PICOS framework to assess DT efficacy. A comprehensive literature search spanning 2014 to January 2024 was performed across databases including PubMed, Web of Science, and Scopus. The review synthesized data on DT mechanics, specifically the integration of Artificial Intelligence (AI), Internet of Things (IoT), and Cloud computing within clinical workflows. Results: In Endodontics, DT mitigates the risk of Nickel-Titanium (NiTi) file separation by using real-time thermal and torque monitoring to predict instrument fatigue before failure occurs. In Orthodontics and Orthognathic Surgery, DT fuses facial scans (STL) with CBCT data (DICOM) to create high-fidelity models. These models facilitate “what-if” treatment simulations and the fabrication of patient-specific surgical guides, demonstrating high translational accuracy between virtual planning and postoperative outcomes. Conclusion: DT technology represents a transformative shift from reactive to proactive dental care. By enabling real-time monitoring and predictive simulation, DT enhances surgical precision and personalization, establishing a new standard for data-driven diagnosis and treatment planning.","author":[{"family":"Amarnath","given":"GS"},{"family":"Govula","given":"Kiranmayi"},{"family":"Swapna","given":"Sannapureddy"},{"family":"Thati","given":"Sai"},{"family":"Thota","given":"Lenin"},{"family":"Kowmudi","given":"Maddineni"}],"issued":{"date-parts":[[2025]]},"DOI":"10.4103/jioh.jioh_230_25","URL":"https://doi.org/10.4103/jioh.jioh_230_25","source":"openalex"},{"id":"oa:W4416903890","type":"article-journal","title":"Ultra‐Short‐Term Wind Power Prediction Based on Digital Twins","abstract":"ABSTRACT To address the issue of insufficient consideration of wind turbine physical characteristics and wind farm meteorological features in wind power forecasting, this paper proposes an ultra‐short‐term wind power prediction model based on digital twin technology. The model constructs a digital twin forecasting framework that integrates a digital‐physical model of the wind turbine and a parallel CTransformer‐BiGRU model to enhance prediction accuracy. The deep learning module captures spatiotemporal features in the data, while the digital‐physical model couples the forecasting process with the actual physical conditions of the wind farm, thereby improving prediction precision. Finally, the effectiveness of the proposed algorithm is validated through experimental tests on a real‐world dataset from a wind farm in Xinjiang, China.","author":[{"family":"Yuan","given":"Arthur"},{"family":"Ma","given":"Hengrui"},{"family":"Yang","given":"Changhua"},{"family":"Xiao","given":"Hui"},{"family":"Wang","given":"Bo"},{"family":"Gao","given":"Wenzhong"},{"family":"La","given":"Qing"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/rpg2.70155","URL":"https://doi.org/10.1049/rpg2.70155","source":"openalex"},{"id":"oa:W4414593783","type":"article-journal","title":"Deep learning enhances digital twin of machine tools: a case study on improving grinding accuracy for large shaft","abstract":"Improving the machining accuracy of machine tools is a challenge in practice, and digital twins provide a feasible approach. However, a very difficult issue is that some important data cannot be directly measured during the machining process, which significantly affects the implementation of digital twins. In this paper, by taking large shaft grinding as an example, an approach using deep learning to enhance the digital twin of machine tools is proposed. An enhanced digital twin framework of a grinder is built, where the twin model of grinding accuracy was established by considering the system stiffness and grinding force pattern. Then, the CNN-LSTM neural networks with acceleration and power signals as input were used to deal with the time-varying characteristics of the core parameters to dynamically correct the twin model during the machining process. The corrected twin model was further used to generate the compensation instruction to improve the grinding accuracy. The experimental results show that the grinding accuracies of large shafts with three different profiles are improved by more than 80%, which proves the effectiveness of the proposed approach. Moreover, related discussion and outlook have been provided to help understand that deep learning enhances the digital twin of machine tools.","author":[{"family":"Wang","given":"Dong"},{"family":"Wang","given":"Liping"},{"family":"Yang","given":"Hongli"},{"family":"Zhang","given":"Yun"},{"family":"Li","given":"Xuekun"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/27525783.2025.2553129","URL":"https://doi.org/10.1080/27525783.2025.2553129","source":"openalex"},{"id":"oa:W4415224394","type":"article-journal","title":"Systematic selection framework for digital twin development environments in smart manufacturing","abstract":"Digital Twins (DT) are a core Smart Manufacturing technology that is applicable across industries and use cases. However, manufacturers face numerous challenges when it comes to identifying appropriate tools to build custom applications, considering systems’ complexity, cost, compatibility, interoperability, and other factors. This study presents a systematic framework for selecting suitable Development Environment (DE) for DT applications in manufacturing. By analysing different DEs categorised into three groups (Simulation Engines, Game Engines, and Robotics Engines) before evaluating them based on curated, predefined criteria, the framework assists stakeholders in making informed decisions tailored to their specific project’s requirements. The framework considers factors such as cost, compatibility, scalability, ease of use, and technical capabilities, ensuring accessibility for expert users and practitioners with limited experience. It was evaluated in a real use case for its robustness and practicality. The results demonstrated the framework’s utility in identifying fit-for-purpose DE, highlighting the strengths and limitations of different environments. Challenges include balancing visualisation capabilities with industrial functionality and managing the steep learning curves of complex environments. The framework aims to support manufacturers, researchers, and technology enthusiasts in selecting suitable DE that meet technical requirements and align with strategic goals, ultimately driving innovation and efficiency in manufacturing.","author":[{"family":"Dodero","given":"Carlos"},{"family":"Mccormick","given":"Matt"},{"family":"Malik","given":"Ali"},{"family":"Harik","given":"Ramy"},{"family":"Wuest","given":"Thorsten"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/27525783.2025.2565246","URL":"https://doi.org/10.1080/27525783.2025.2565246","source":"openalex"},{"id":"oa:W4411123954","type":"article-journal","title":"Adapting Agile Methodologies to Incorporate Digital Twins in Sprint Planning, Backlog Refinement, and QA Validation","abstract":"Agile approaches, which offer flexibility, iterative development, and constant feedback, have emerged as the mainstay of contemporary software and hardware development. However, managing dependencies, correctly forecasting system behavior, and evaluating features under real-world circumstances are all difficult tasks for traditional agile approaches. Real-time simulations, predictive analytics, and automated testing are made possible by digital twins (DTs), which are virtual representations of digital or physical systems. The three essential agile processes of sprint planning, backlog refinement, and QA validation are examined in this paper along with how DTs might improve them. By adopting Digital Twins, Agile teams may achieve more exact sprint predictions, risk-based backlog prioritization, and automated QA validation. DTs' capacity to model task allocation and foresee system restrictions helps in sprint planning. DT-driven dependency analysis and dynamic risk assessment enhance backlog refinement, guaranteeing that priority is in line with practical viability. Lastly, by offering virtual testing environments that identify flaws before to deployment, digital twins transform QA validation. This study synthesizes insights from existing literature, industry case studies, and empirical evidence to propose an integrated Agile-Digital Twin framework. The findings suggest that organizations implementing DTs within Agile practices experience enhanced efficiency, reduced technical debt, and improved product quality. However, challenges such as high implementation costs, integration complexity, and skill gaps must be addressed. The paper concludes by highlighting future research directions, including AI-powered Digital Twins for Agile optimization and the role of DTs in DevSecOps.","author":[{"family":"Bakhsh","given":"Mohammed"},{"family":"Alam","given":"Gazi"},{"family":"Nadia","given":"Nusrat"}],"issued":{"date-parts":[[2025]]},"DOI":"10.60087/jklst.v4.n2.006","URL":"https://doi.org/10.60087/jklst.v4.n2.006","source":"openalex"},{"id":"oa:W4414470725","type":"article-journal","title":"Integrating Digital Twin and Nature Based Solutions for Climate Resilient Urban Design: A Predictive Framework for Future Ready Residential Neighborhoods in the Anthropocene","abstract":"The accelerating impacts of climate change and rapid urbanization underscore the urgent need for integrative frameworks that enhance the adaptive capacity of cities. This study proposes a predictive urban design framework that synthesizes Digital Twins (DTs) and Nature-Based Solutions (NbS) to support the development of climate-resilient residential neighborhoods in the Anthropocene era. By fusing real-time environmental data, microclimate simulations, and spatial analytics, the framework enables evidence-based planning, scenario testing, and performance optimization of ecological interventions at the neighborhood scale. Drawing on multidisciplinary insights and experimental applications including smart vertical greening systems, floodable park typologies, and IoT-based irrigation modules the research demonstrates the potential of hybrid DT NbS systems to mitigate urban heat, improve water retention, and reduce building energy demand. Results from case-based simulations, supported by tools such as GREENPASS®, show indoor temperature reductions of up to 3-4 °C, enhanced thermal comfort, and improved ecological performance. The framework applies a standardized set of urban resilience metrics, including Thermal Comfort Score (TCS), Physiological Equivalent Temperature (PET), air temperature, and relative humidity, to quantify the impacts of interventions across both spatial and temporal dimensions. Furthermore, the study emphasizes the importance of participatory co-design and inclusive governance models to ensure that NbS are equitably implemented and responsive to socio-environmental disparities. By aligning digital simulation technologies with ecosystem-based design strategies, this research offers a transferable and scalable model for planning future-ready, regenerative urban neighborhoods.","author":[{"family":"Abbas","given":"Asad"},{"family":"Adeel","given":"Muhammad"},{"family":"Akbar","given":"Ghulam"},{"family":"Hayyat","given":"Sadaqat"},{"family":"Din","given":"Ghulam"}],"issued":{"date-parts":[[2025]]},"DOI":"10.59324/ejsmt.2025.1(5).01","URL":"https://doi.org/10.59324/ejsmt.2025.1(5).01","source":"openalex"},{"id":"oa:W4411814583","type":"article-journal","title":"Digital platforms for circular economy: Empirical development of a taxonomy and archetypes","abstract":"Abstract Digital platforms hold promise to leverage the transition from a linear to a circular economy (CE), as they have already disrupted value-creation mechanisms and formed dynamic ecosystems in various domains. However, the solution space for CE platforms is vast and remains under-researched, challenging platform providers to find purposeful platform configurations and industrial companies to choose the right platform on the market. To support informed platform design decisions and uncover the existing CE platform configurations, we develop a taxonomy from a systematic literature review and an empirical dataset of 129 cases of CE platforms. The taxonomy provides a holistic view of the solution space, advancing our understanding of key configuration options. The taxonomy allows us to perform cluster analysis and derive six CE platform archetypes. These findings advance the theoretical knowledge indicating how platforms can support CE and help decision-makers design CE platforms or identify suitable CE platforms for their own circular activities.","author":[{"family":"Petrik","given":"Dimitri"},{"family":"Hiller","given":"Simon"},{"family":"Morar","given":"Dominik"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s12525-025-00792-w","URL":"https://doi.org/10.1007/s12525-025-00792-w","source":"openalex"},{"id":"oa:W4413175246","type":"article-journal","title":"Photovoltaic Digital Twins: Mathematical Modeling vs. Neural Networks for Energy Management in Smart Buildings","abstract":"Efficiently controlling and managing photovoltaic installations for self-consumption is key to making optimal use of these systems. The first step to achieving that control is modeling the generation of electricity by photovoltaic panels with digital twins. This paper presents an experimental evaluation of four photovoltaic power prediction models in a real-world environment using high-resolution, annual data from a university facility. A mathematical model and three neural network models (MLP, LSTM, and GRU) are compared under standardized metrics. The results demonstrate that the Multilayer Perceptron (MLP) achieves the highest overall accuracy and seasonal consistency. It outperforms the other three models, particularly in scenarios where the relationships between meteorological variables and power generation are predominantly static. However, the mathematical model maintains a competitive performance in conditions of low variability, such as in the summer and autumn. The seasonal analysis reveals the importance of selecting and adjusting models according to operational and climatic contexts. This study’s main contribution is identifying the MLP as the most efficient option for implementing digital twins in photovoltaic installation control. This facilitates real-time monitoring, optimization, and predictive maintenance and contributes to smart, sustainable energy management in buildings to align with climate neutrality guidelines.","author":[{"family":"Dimitrova-Angelova","given":"Doroteya"},{"family":"González","given":"Juan"},{"family":"Carmona-Fernández","given":"Diego"},{"family":"Jaramillo-Morán","given":"Miguel"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15168883","URL":"https://doi.org/10.3390/app15168883","source":"openalex"},{"id":"oa:W4409317683","type":"article-journal","title":"Energy management and industry 4.0: Analysis of the enabling effects of digitalization on the implementation of energy management practices","abstract":"Manufacturing industries face significant challenges in reducing final energy use and improving Energy Management Practices (EnMPs). Industry 4.0 (I4.0) technologies provide transformative opportunities to address these challenges, yet their integration with EnMPs remains underexplored. This study aims to fill this gap by reviewing I4.0 solutions applied in manufacturing and assessing their impact on companies' Energy Management strategies. Specifically, the study develops a Smart Factory framework, categorizes I4.0 technologies into four clusters (system, infrastructure, service, and process) and identifies nine key Areas of Impact. The framework systematically maps these technologies to assess their effects on Energy Management. This model is validated and applied in two Swedish firms manufacturing respectively automotive components and heavy machinery, and machine tool accessories. Results indicate that EnMPs affect multiple areas, while their most notable impact is observed in the area of ‘awareness’, ‘connectivity & integration’, and ‘visualization’. Similarly, I4.0 technologies enhance EnMPs by improving energy monitoring, performance evaluation, and energy-efficient process design. Internet of Things emerged as a critical enabler, facilitating real-time energy data collection and analysis, while Artificial Intelligence and Big Data Analytics provided predictive capabilities to optimize energy use and prevent inefficiencies. Simulation tools and Virtual Reality supported process visualization and design optimization, while Advanced Robotics enhanced flexibility and reduced operational energy waste. Energy-aware production scheduling, predictive maintenance, and the design of energy-efficient systems were the most significantly impacted practices. This framework demonstrates how I4.0 technologies can enable the transition towards smarter, energy-efficient manufacturing, contributing to industrial decarbonization and sustainability goals. By providing actionable insights, the framework equips researchers and practitioners with a systematic approach to integrating digital technologies and energy management strategies, bridging a critical gap in the literature. • Novel framework better integrating synergies between EnMPs and I4.0 technologies. • Increased awareness offered on the roles of I4.0 technologies and EnMPs in manufacturing. • Several areas of impact were identified and analyzed for selected I4.0 technologies and EnMPs. • Data collection and analysis are the most implemented I4.0 technologies for EE.","author":[{"family":"Cagno","given":"Enrico"},{"family":"Accordini","given":"Davide"},{"family":"Thollander","given":"Patrik"},{"family":"Andrei","given":"Mariana"},{"family":"Hasan","given":"ASMM"},{"family":"Pessina","given":"Sonia"},{"family":"Trianni","given":"Andrea"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.apenergy.2025.125877","URL":"https://doi.org/10.1016/j.apenergy.2025.125877","source":"openalex"},{"id":"oa:W4409151876","type":"article-journal","title":"Strategic Sustainability Initiatives and the Circular Economy: Insights From Firm‐Level Targets, Board Dynamics, Stakeholder Pressure, and Digital Transformation","abstract":"ABSTRACT This study contributes to the literature on sustainability, innovation, and corporate governance by advancing the understanding of the circular economy (CE) through an analysis of firm‐level sustainability targets, board dynamics, stakeholder pressure, and digital transformation within firms in the MENA region. Drawing on resource‐based, stakeholder, and innovation theories, we developed models linking sustainability targets and board dynamics to CE performance, with stakeholder pressure as a mediator and digital transformation as a moderator. We tested these hypotheses using data from 647 publicly listed manufacturing companies in the MENA region, spanning 2010–2022. By employing robust econometric techniques, we found strong evidence that embedding sustainability incentives in executive compensation and implementing structured sustainability initiatives significantly enhance CE performance. Additionally, effective boardroom characteristics positively influence CE adoption, while stakeholder pressure mediates the relationship between sustainability targets, board dynamics, and CE performance. Similarly, digital transformation reinforces sustainability governance, strengthening the role of board dynamics and sustainability targets in driving CE adoption. Finally, our findings highlight regional and performance‐based differences in how MENA firms implement sustainability targets and board dynamics to influence CE outcomes. The results remain consistent after multiple robustness tests, including rolling window analysis, sensitivity analysis, and endogeneity tests. The findings emphasize the need for incentive‐driven policies that integrate CE principles into corporate governance, promote sustainability‐linked executive compensation, enhance board diversity, and support digital transformation initiatives. Policymakers should also standardize CE reporting frameworks to align with global sustainability commitments, ensuring transparency, accountability, and long‐term sustainability adoption.","author":[{"family":"Osei","given":"Abednego"},{"family":"Agyemang","given":"Andrew"},{"family":"Cobbinah","given":"Joana"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1111/beer.12818","URL":"https://doi.org/10.1111/beer.12818","source":"openalex"},{"id":"oa:W7134065245","type":"article-journal","title":"Digital Twins at the Edge: A High-Availability Framework for Resilient Data Processing in IoT Sensor Networks","abstract":"The expansion of Internet-of-Things deployments at the network edge challenges service continuity, as single points of failure can interrupt critical data-processing pipelines. This paper introduces the Operational Digital Twin (ODT) —a live, state-synchronized standby system designed for node-level failover in resource-constrained edge environments. In contrast to Digital Twins designed for modeling and analysis, an ODT is designed for operational continuity, standing ready to assume control when the primary node fails. We instantiate this concept through a self-configuring, high-availability architecture that implements the ODT for node-level redundancy. To ground this new conceptual category empirically, we define and validate four measurable criteria for ODT fidelity—state fidelity, synchronization timeliness, behavioral mirroring, and failover validation—establishing a framework that extends beyond passive replication. The design adopts a primary–secondary model with automated node discovery, configuration mirroring, and Virtual IP-based failover. Fault-injection experiments demonstrate low failover latency, prompt service restoration, limited message loss during transitions, and minimal resource overhead. These findings demonstrate that the proposed Operational Digital Twin mechanism reduces single points of failure and provides a lightweight, cost-efficient approach to sustaining reliable data processing in distributed edge environments.","author":[{"family":"Neagu","given":"Madalin"},{"family":"Serban","given":"Codruta"},{"family":"Hângan","given":"Anca"},{"family":"Sebestyen","given":"Gheorghe"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/fi18030137","URL":"https://doi.org/10.3390/fi18030137","source":"openalex"},{"id":"oa:W4414460644","type":"article-journal","title":"Application of a Digital Twin Model in an Operational System for Monitoring Railway Bridges","abstract":"This paper addresses the current issues of the design, operation and monitoring of bridge structures in the context of digitalisation within the transport industry. Purpose: To develop digital twins to improve the reliability and safety of operational bridge structures. Method: The case study of an operational railway bridge highlights the limitations of traditional infrastructure management approaches. The authors propose a solution based on digital twins: a comprehensive system comprising interconnected virtual models and physical structures, as well as automated and periodic monitoring systems and supervisory measures. This solution allows the technical condition of facilities to be monitored in real time. Results: This paper describes a digital information model of the bridge that has been adapted for monitoring individual indicators such as deformation and frequency. A notable feature of the model is its ability to dynamically detail elements, thereby reducing the computational load. Additionally, it proposes an automated assessment of not only the monitoring system sensor readings with calculated boundary parameters, but also of the existing regulatory requirements. This approach enables rapid identification of deviations that significantly reduce the safety of rolling stock movement. Practical significance: This study confirms that digital twins enhance the reliability of bridges by predicting defects and enabling a rapid response. The authors emphasize the importance of developing a domestic regulatory framework and implementing machine learning to analyse long-term trends in the technical condition of structures. The study’s findings suggest that digital twins have the potential to ensure the sustainability of transport infrastructure in the face of increasing loads.","author":[{"family":"Chaplin","given":"Ivan"},{"family":"Patornyak","given":"Aleksey"},{"family":"Efimov","given":"Stefan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20295/1815-588x-2025-3-831-838","URL":"https://doi.org/10.20295/1815-588x-2025-3-831-838","source":"openalex"},{"id":"oa:W7117167632","type":"article-journal","title":"From Local to Global Perspective in AI-Based Digital Twins in Healthcare","abstract":"Digital twins (DTs) powered by artificial intelligence (AI) are becoming important transformational tools in healthcare, enabling real-time simulation and personalized decision support at the patient level. The aim of this review is to critically examine the evolution, current applications, and future potential of AI-based DTs in healthcare, with a particular focus on their role in enabling real-time simulation and personalized patient-level decision support. Specifically, the review aims to provide a comprehensive overview of how AI-based DTs are being developed and implemented in various clinical domains, identifying existing scientific and technical gaps and highlighting methodological, regulatory, and ethical issues. Taking a “local to global” perspective, the review aims to explore how individual patient-level models can be scaled and integrated to inform population health strategies, global data networks, and collaborative research ecosystems. This will provide a structured foundation for future research, clinical applications, and policy development in this rapidly evolving field. Locally, DTs allow medical professionals to model individual patient physiology, predict disease progression, and optimize treatment strategies. Hospitals are implementing AI-based DT platforms to simulate workflows, efficiently allocate resources, and improve patient safety. Generative AI further enhances these applications by creating synthetic patient data for training, filling gaps in incomplete records, and enabling privacy-respecting research. On a broader scale, regional health systems can use connected DTs to model population health trends and predict responses to public health interventions. On a national scale, governments and policymakers can use these insights for strategic planning, resource allocation, and increasing resilience to health crises. Internationally and globally, AI-based DTs can integrate diverse datasets across borders to support research collaboration and improve early pandemic detection. Generative AI contributes to global efforts by harmonizing heterogeneous data, creating standardized virtual patient cohorts, and supporting cross-cultural medical education. Combining local precision with global insights highlights DTs’ role as a bridge between personalized and global health. Despite the efforts of medical and technical specialists, ethical, regulatory, and data governance challenges remain crucial to ensuring responsible and equitable implementation worldwide. In conclusion, AI-based DTs represent a transformative paradigm, combining individual patient care with systemic and global health management. These perspectives highlight the potential of AI-based DTs to bridge precision medicine and public health, provided ethical, regulatory, and governance challenges are addressed responsibly.","author":[{"family":"Piechowiak","given":"Maciej"},{"family":"Goch","given":"Aleksander"},{"family":"Panas","given":"Ewelina"},{"family":"Masiak","given":"Jolanta"},{"family":"Mikołajewski","given":"Dariusz"},{"family":"Rojek","given":"Izabela"},{"family":"Mikołajewska","given":"Emilia"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app16010083","URL":"https://doi.org/10.3390/app16010083","source":"openalex"},{"id":"oa:W7114919867","type":"article-journal","title":"Future Care: Artificial Intelligence and the New Age of Digital Health","abstract":"The change in healthcare is deep-seated, yet it has been brought about by the dynamics of artificial intelligence (AI), of which it has never been so powerful. AI is transforming the methods of disease prevention, detection, and management: through smart diagnostics and intelligent monitoring, customized treatments, virtual hospitals, and so on. Known as FutureCare: Artificial Intelligence and the New Age of Digital Health, this book is a guidebook to the novices on the new age of medicine wherein technology and human intelligence meet, providing safer, faster, and more accurate healthcare solutions. This book is created based on the idea of simplification and explanation of complex concepts in medical AI, and doing it in simple, practical, and prospective way. In every chapter, the authors choose one of the main dimensions of the AI-healthcare ecosystem, including diagnostic innovations and robotic surgery, drug discovery, ethics, and global health impact. As a student, researcher, clinician, policymaker, or technologist this book is an attempt to find a new way of looking at how AI will transform the future of health. With a progressive shift to the world of predictive care over reactive, personalized but not generalized, online but not within the clinical walls, the FutureCare model is necessary. This book challenges the reader to envision that future and provides him with the knowledge necessary to make a contribution to this change.","author":[{"family":"Shukla","given":"Geetanjali"},{"family":"Sinha","given":"Aashna"},{"family":"Gehlot","given":"Anita"},{"family":"Singh","given":"Rajesh"}],"issued":{"date-parts":[[2025]]},"DOI":"10.55938/wlp.v2i6.306","URL":"https://doi.org/10.55938/wlp.v2i6.306","source":"openalex"},{"id":"oa:W4416627226","type":"article-journal","title":"Framework for the Application of Digital Twin Technology in Intelligent Production Line Condition Monitoring and Predictive Maintenance","abstract":"This paper addresses the urgent needs of intelligent manufacturing for highly reliable equipment operation and precise maintenance and delves into the innovative application of digital twin technology in production line condition monitoring and predictive maintenance. By systematically reviewing the core theories of digital twins, multi-source heterogeneous data acquisition and processing technologies, and predictive maintenance methodologies, a five-dimensional integrated framework comprising a physical layer, data layer, model layer, functional layer, and application layer is constructed. This framework innovatively achieves real-time dynamic mapping and bidirectional interaction between physical and virtual spaces, establishes a data-model hybrid-driven mechanism for equipment health status assessment and remaining life prediction, and forms a closed-loop optimization system from condition perception and fault early warning to maintenance decision-making. To verify the effectiveness of the framework, this study conducts a case study using a precision CNC gear machining production line. The results show that the framework can control the latency of critical equipment condition monitoring within 200 milliseconds, improve the accuracy of remaining life prediction by approximately 15% compared to purely data-driven methods, successfully achieve early fault warning, reduce unplanned downtime by 65%, and save maintenance costs by 28%. The research findings provide theoretical guidance and practical examples for achieving precise and forward-looking equipment health management in the context of intelligent manufacturing and have important reference value for promoting the digital transformation of the manufacturing industry.","author":[{"family":"Zhang","given":"Yu"},{"family":"Wang","given":"Mengxi"},{"family":"Zhou","given":"Jiayi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.71451/istaer2572","URL":"https://doi.org/10.71451/istaer2572","source":"openalex"},{"id":"oa:W4413203232","type":"article-journal","title":"Enhancing intellectual property identification and valuation in manufacturing through digital twins","abstract":"This study provides a transdisciplinary and empirical examination of the efficacy of digital twin technology in enhancing intellectual property (IP) identification and valuation within the manufacturing sector. Focusing on a sample of 51 automotive manufacturers in the United Kingdom and Brazil, we address a critical gap in the existing literature by offering empirical evidence of standardised digital twins' practical benefits in IP management, a domain that has been predominantly theoretical until now. Using a mixed-methods research design, we employed 1) A standardized digital twin sub-model for representing IP assets using Asset Administration Shell principles; and 2) Questionnaires assessing current IP identification practices and perceived IP asset values before and after digital twin implementation. Utilizing the Income Approach and the Relief from Royalty Method in adherence to International Valuation Standards, our findings reveal a significant increase in both the number of identified IP assets and their overall valuation post-implementation. We empirically assess the impact of digital twins on IP practices in manufacturing by integrating engineering, legal and innovation management perspectives. Reliability and validity of the results are underpinned by a rigorous systematic methodology, including appropriate statistical analyses and thematic examinations of participant feedback. Across the 51 automotive manufacturers participating in this study, the mean number of identified IP assets rose by 35 % (from 72 to 98 assets, Z = −5.63, p < 0.001) and the mean portfolio valuation more than doubled from USD 23.2m–53.8m (Z = −5.22, p < 0.001). These results demonstrate the method's ability to surface hidden intangible value that can subsequently be monetised.","author":[{"family":"Kauffman","given":"Marcos"},{"family":"Soares","given":"Marcelo"},{"family":"Long","given":"Tengfei"},{"family":"Harris","given":"Lara"},{"family":"Cugul","given":"Jarbas"},{"family":"Manzato","given":"Welington"},{"family":"Zhang","given":"Kathy"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.ijpe.2025.109767","URL":"https://doi.org/10.1016/j.ijpe.2025.109767","source":"openalex"},{"id":"oa:W4414347466","type":"article-journal","title":"A Data-Driven Urban Digital Twin Approach for Evaluating Positive Energy District Potential Using OGC Standards in Stuttgart","abstract":"Abstract. This article introduces an urban digital twin workflow based on OGC standards and newly developed Energy ADE 2.0 that integrates building-scale simulations from SimStadt with district-level assessments using MAPED, connected through interactive web-based visualisation. This approach delivers a modular, open-source pipeline that harmonises multi-scale energy data and enables data-driven scenario analysis and stakeholder engagement in support of net-positive energy planning for urban districts. By connecting detailed simulation tools with standardised, spatially linked data models, the study advances the methodological foundation for assessing Positive Energy Districts (PED) using digital technologies and provides a practical decision-support system for planners and policy-makers involved in sustainable urban transformation.","author":[{"family":"Padsala","given":"Rushikesh"},{"family":"Falay","given":"Basak"},{"family":"Hainoun","given":"Ali"},{"family":"Coors","given":"Volker"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/isprs-archives-xlviii-4-w16-2025-67-2025","URL":"https://doi.org/10.5194/isprs-archives-xlviii-4-w16-2025-67-2025","source":"openalex"},{"id":"oa:W4405993426","type":"article-journal","title":"Cybersecurity Solutions for Industrial Internet of Things–Edge Computing Integration: Challenges, Threats, and Future Directions","abstract":"This paper provides the complete details of current challenges and solutions in the cybersecurity of cyber-physical systems (CPS) within the context of the IIoT and its integration with edge computing (IIoT-edge computing). We systematically collected and analyzed the relevant literature from the past five years, applying a rigorous methodology to identify key sources. Our study highlights the prevalent IIoT layer attacks, common intrusion methods, and critical threats facing IIoT-edge computing environments. Additionally, we examine various types of cyberattacks targeting CPS, outlining their significant impact on industrial operations. A detailed taxonomy of primary security mechanisms for CPS within IIoT-edge computing is developed, followed by a comparative analysis of our approach against existing research. The findings underscore the widespread vulnerabilities across the IIoT architecture, particularly in relation to DoS, ransomware, malware, and MITM attacks. The review emphasizes the integration of advanced security technologies, including machine learning (ML), federated learning (FL), blockchain, blockchain-ML, deep learning (DL), encryption, cryptography, IT/OT convergence, and digital twins, as essential for enhancing the security and real-time data protection of CPS in IIoT-edge computing. Finally, the paper outlines potential future research directions aimed at advancing cybersecurity in this rapidly evolving domain.","author":[{"family":"Zhukabayeva","given":"Tamara"},{"family":"Zholshiyeva","given":"Lazzat"},{"family":"Karabayev","given":"Nurdaulet"},{"family":"Khan","given":"Shafiullah"},{"family":"Alnazzawi","given":"Noha"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/s25010213","URL":"https://doi.org/10.3390/s25010213","source":"pubmed"},{"id":"oa:W7155644585","type":"article-journal","title":"AI-Driven Digital Twin for Predictive Maintenance in Urban Infrastructure: Enhancing Structural Resilience and Sustainability","abstract":"The increasing complexity of urban infrastructure necessitates more efficient and proactive maintenance strategies. Traditional maintenance approaches often rely on reactive measures, leading to increased costs, unplanned downtime, and potential structural failures. The emergence of Artificial Intelligence (AI)-driven Digital Twin technology offers a promising solution by enabling predictive maintenance through real-time monitoring and advanced analytics. This study aimed to evaluate the effectiveness of AI-driven Digital Twin systems in enhancing predictive maintenance for urban infrastructure. A qualitative case study methodology was employed, analyzing multiple infrastructure projects that integrated Digital Twin technology. Data were collected from project reports, real-time sensor outputs, and expert interviews. The predictive capabilities of machine learning models, including Decision Trees, Support Vector Machines (SVM), and Deep Learning networks, were assessed based on their precision, recall, and F1-score. The results demonstrated that Deep Learning models achieved the highest fault detection accuracy, with an F1-score of 92.5%, outperforming other models. The adoption of Digital Twin systems resulted in a 30% reduction in maintenance costs and a 40% decrease in infrastructure downtime. Additionally, AI-driven predictive maintenance improved fault detection efficiency, reducing the average detection time from 15 days to 3 days. These findings highlight the potential of AI-enhanced Digital Twins in optimizing urban infrastructure resilience, cost efficiency, and sustainability. This study underscores the importance of integrating AI and Digital Twin technologies in predictive maintenance strategies. Future research should focus on addressing implementation challenges, including data security, interoperability, and computational costs, to facilitate broader adoption in smart city development","author":[{"family":"Diana","given":"Dita"},{"family":"Anindita","given":"Putri"},{"family":"Mukti","given":"Anggi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.51903/3c72e647","URL":"https://doi.org/10.51903/3c72e647","source":"openalex"},{"id":"oa:W4413456445","type":"article-journal","title":"Digital Twins for Bridge Assessment and Maintenance","abstract":"The increasing number of aging bridges underscores the need for efficient maintenance to enhance safety and reduce costs. This paper explores integrating digital twin technologies into bridge management to improve maintenance efficiency and accuracy. A 15-year-long simulation demonstrates improved inspection accuracy and efficiency, while a case study on a steel bridge illustrates a prototype implementation. This study advances infrastructure management and guides future digital transformation efforts, promoting interoperability and integration with artificial intelligence (AI) and extended reality (XR).","author":[{"family":"Khoshraftar","given":"Ali"},{"family":"Zwaag","given":"Berend"},{"family":"Le","given":"Duc"},{"family":"Durmaz-Incel","given":"Özlem"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/smartnets65254.2025.11106891","URL":"https://doi.org/10.1109/smartnets65254.2025.11106891","source":"openalex"},{"id":"oa:W4415623536","type":"article-journal","title":"Developing Computer Vision-Based Digital Twin for Vegetation Management near Power Distribution Networks","abstract":"The maintenance of power distribution lines is critically challenged by vegetation encroachment, posing significant risks to the reliability and safety of power utilities. Traditional manual inspection methods are resource-intensive and lack the precision required for effective and proactive maintenance. This paper presents an automated, accurate, and efficient approach to vegetation management near power lines by leveraging advancements in LiDAR as a remote sensing technology and deep learning algorithms. The RandLA-Net model is employed for semantic segmentation of large-scale point clouds to accurately identify vegetation, poles, and power lines. A comprehensive sensitivity analysis is conducted to optimize the model’s hyperparameters, enhancing segmentation accuracy. Post-processing techniques, including clustering and rule-based thresholding, are applied to refine the semantic segmentation results. Proximity detection is applied using spatial queries based on a KDTree structure to assess potential risks of vegetation near power lines. Furthermore, a digital twin of the power distribution network and surrounding trees is developed by integrating 3D object registration and surface generation, enriching it with semantic attributes and incorporating it into City Information Modeling (CIM) systems. This framework demonstrates the potential of remote sensing data integration for efficient environmental monitoring in urban infrastructure. The results of the case study on the Toronto-3D dataset demonstrate the computational efficiency and accuracy of the proposed method, presenting a promising solution for power utilities in proactive vegetation management and infrastructure planning. The optimized full 9-class model achieved an overall accuracy of 96.90% and IoU scores of 97.05% for vegetation, 88.09% for power lines, and 82.33% for poles, supporting comprehensive digital twin creation. An auxiliary 4-class model further improved targeted performance, with IoUs of 99.55% for vegetation, 88.79% for poles, and 87.18% for power lines.","author":[{"family":"Bahreini","given":"Fardin"},{"family":"Nikbakht","given":"Mazdak"},{"family":"Amin","given":"Hammad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/rs17213565","URL":"https://doi.org/10.3390/rs17213565","source":"openalex"},{"id":"oa:W4416958461","type":"article-journal","title":"The Global Importance of Machine Learning-Based Wearables and Digital Twins for Rehabilitation: A Review of Data Collection, Security, Edge Intelligence, Federated Learning, and Generative AI","abstract":"The convergence of wearable technologies and digital twin (DT) systems is transforming rehabilitation engineering, enabling continuous monitoring, personalized therapeutic interventions, and predictive modeling of patient recovery pathways. This review examines the growing role of machine learning (ML) in the development and integration of DTs frameworks in rehabilitation, with a focus on wearable sensor data, security and privacy, edge computing architectures, federated learning paradigms, and generative artificial intelligence (GenAI) applications. We first analyze data collection processes, emphasizing multimodal sensing, signal processing, and real-time synchronization between physical and virtual patient models. We then discuss key challenges related to data security, encryption, and privacy protection, especially in distributed clinical environments. The review then assesses the role of edge computing in reducing latency, improving energy efficiency, and enabling real-time local intelligence feedback in wearable devices. Federated learning approaches are discussed as promising strategies for jointly training ML models without compromising sensitive medical data. Finally, we present new GenAI techniques for generating synthetic data, personalizing digital twins, and simulating rehabilitation scenarios. By mapping current progress and identifying research gaps, this article provides a unified view that connects electronic and biomedical engineering with intelligent, secure, and adaptive DT ecosystems for next-generation rehabilitation solutions. Wearable devices with ML and DTs for rehabilitation are developing rapidly, but their current effectiveness still depends on consistent, high-quality data streams and robust clinical validation. The most promising convergence involves combining edge intelligence with federated learning to enable real-time personalization while preserving patient privacy. GenAI further enhances these systems by simulating patient-specific scenarios, accelerating model adaptation, and treatment planning. Key challenges remain related to standardizing data formats, ensuring comprehensive security, and seamlessly integrating these technologies into clinical processes.","author":[{"family":"Piechowiak","given":"Maciej"},{"family":"Goch","given":"Aleksander"},{"family":"Panas","given":"Ewelina"},{"family":"Masiak","given":"Jolanta"},{"family":"Mikołajewski","given":"Dariusz"},{"family":"Rojek","given":"Izabela"},{"family":"Mikołajewska","given":"Emilia"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/electronics14234699","URL":"https://doi.org/10.3390/electronics14234699","source":"openalex"},{"id":"oa:W4416908048","type":"article-journal","title":"Digital Twins Paradigm: A Systematic Review from the Reinforcement Learning Perspective","abstract":"The Digital Twins (DT) paradigm has emerged as a powerful tool for simulating and analyzing complex systems in various domains. A DT is a virtual representation of a real-world object(s) whose goal is to accurately emulate real systems, optimize processes, minimize synchronization delays, cut down on overhead, and automate decision-making. DT technology is moving at a faster than expected pace with advances in Artificial Intelligence (AI), Internet of Things (IoT), Distributed Computing, and 5/6G. Being a highly beneficial technology, DT still faces issues of - (1) limited adaptability, (2) incomplete model representation, (3) suboptimal decision making, (4) limited generalization, and (5) scalability and computational efficiency. Reinforcement Learning (RL) offers unsupervised decision-making and intelligence, which can be immensely beneficial in addressing the current challenges faced by DT. This study offers a thorough analysis of the DT paradigm from the standpoint of RL. The survey compares and contrasts existing reinforcement learning-based Digital Twin frameworks, assessing their advantages and disadvantages. Moreover, discussions of approaches highlighting the tradeoffs between simulation fidelity and computing complexity is also studied. Additionally, a thorough understanding of the Digital Twins paradigm from a reinforcement learning perspective, is presented as a helpful resource for academics and industry professionals in the field. Finally, future research directions in this developing field at the nexus of digital modeling, simulation, and artificial intelligence is discussed.","author":[{"family":"Mohammed","given":"Shahmir"},{"family":"Singh","given":"Shakti"},{"family":"Mizouni","given":"Rabeb"},{"family":"Otrok","given":"Hadi"},{"family":"Damiani","given":"Ernesto"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1145/3777367","URL":"https://doi.org/10.1145/3777367","source":"openalex"},{"id":"oa:W4407749165","type":"article-journal","title":"Integrated Digital-Twin-Based Decision Support System for Relocatable Module Allocation Plan: Case Study of Relocatable Modular School System","abstract":"Relocatable modular buildings (RMBs) offer significant advantages, including flexibility, mobility, and scalability, making them ideal for temporary or rapidly changing scenarios. However, as the scale and quantity of RMB modules increase, their allocation across projects poses complex logistical challenges. Inefficiencies in traditional manual allocation methods, such as suboptimal module selection, increased transportation costs, and project delays, underscore the need for innovative solutions. This study develops a Digital Twin (DT)-based decision support system to optimize the allocation and management of RMB modules. The proposed framework integrates Building Information Modeling (BIM), Internet of Things (IoT), and Geographic Information Systems (GISs), enabling the real-time synchronization of physical assets with their digital counterparts. The DT framework incorporates real-time data acquisition, dynamic module condition assessments, and an algorithm-driven allocation process to streamline resource utilization and logistics planning. The system is validated through a case study of South Korea’s first relocatable modular school system project, demonstrating its capability to optimize module allocation, reduce costs, and enhance lifecycle management. This study advances RMB management by offering a practical, data-driven approach, empowering facility managers to leverage real-time data for preventive maintenance, asset optimization, and sustainable resource utilization.","author":[{"family":"Nguyen","given":"Truong"},{"family":"Ahn","given":"Yonghan"},{"family":"Kim","given":"Byeol"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15042211","URL":"https://doi.org/10.3390/app15042211","source":"openalex"},{"id":"oa:W4415208316","type":"article-journal","title":"Twined ensemble framework for network security: integrating Random Forest, AdaBoost, and Gradient Boosting for enhanced intrusion detection","abstract":"An Intrusion Detection System (IDS) is crucial for safeguarding networks against cyber threats. This research presents a novel Twined Ensemble model, specifically designed to enhance intrusion detection performance using the NSL-KDD dataset. The proposed approach leverages a combination of two algorithms from AdaBoost, Gradient Boosting, or Random Forest for each attack category based on their individual performance. These selected classifiers are then combined using a Soft Voting Ensemble technique, which aggregates their probabilistic outputs to yield more accurate and robust predictions. To address the inherent class imbalance in the NSL-KDD dataset, particularly for underrepresented attacks like U2R and R2L, the Synthetic Minority Oversampling Technique (SMOTE) is employed to generate synthetic examples, thereby improving model generalization for rare classes. The Twined Ensemble model is evaluated using metrics such as Accuracy, Precision, Recall, F1-Score, and Cohen’s Kappa. The model achieves 99.68% accuracy for DoS, R2L, and Probe attacks, and 99.83% for U2R attacks, accompanied by a Cohen’s Kappa score of 1.0, indicating near-perfect classification. This architecture effectively integrates adaptive ensemble learning with class balancing strategies, offering a powerful and reliable solution for modern network intrusion detection. Beyond classification accuracy, this study also evaluates the computational performance of each classifier in terms of training time, prediction latency, and memory consumption. Gradient Boosting, while more accurate, exhibits higher training overhead (428.57 s), whereas AdaBoost and Random Forest maintain significantly faster training times (23.05 s and 24.93 s respectively) with minimal memory usage (< 0.04 MB). These findings demonstrate potential scope for the model’s feasibility for real-time IDS deployment in resource-constrained environments.","author":[{"family":"Reddy","given":"CKK"},{"family":"Reddy","given":"Pulakurthi"},{"family":"Reddy","given":"Pulakurthi"},{"family":"Shuaib","given":"Mohammed"},{"family":"Alam","given":"Shadab"},{"family":"Ahmad","given":"Sadaf"},{"family":"Rajaram","given":"A"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s43926-025-00199-1","URL":"https://doi.org/10.1007/s43926-025-00199-1","source":"openalex"},{"id":"oa:W7128439134","type":"article-journal","title":"From images to physics-based computational models to digital twins: a framework for personalized cancer therapies","abstract":"In this work, we highlight recent advances in computational modeling that have significantly enhanced prospects of personalized cancer therapies by enabling insightful integration of patient-specific data, including medical images. Computational models, encompassing multi-physics and multi-scale approaches, can simulate drug transport and interactions within tissues and environments, including the tumor microenvironment, and facilitate the development of targeted diagnostic and therapeutic strategies. The incorporation of machine learning algorithms has further refined modeling, improving predictive accuracy and enabling real-time adaptive treatment planning. Although challenges remain in model validation and clinical translation, ongoing advancements are steadily bridging these gaps, bringing computational models and technologies closer to routine clinical application for the improvement of patient outcomes.","author":[{"family":"Kashkooli","given":"Farshad"},{"family":"Zhan","given":"Wenbo"},{"family":"Bhandari","given":"Ajay"},{"family":"Yusufaly","given":"Tahir"},{"family":"Kolios","given":"Michael"},{"family":"Rahmim","given":"Arman"},{"family":"Soltani","given":"M"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fradi.2026.1737577","URL":"https://doi.org/10.3389/fradi.2026.1737577","source":"openalex"},{"id":"oa:W7125680050","type":"article-journal","title":"TwinCity: An Urban Digital Twin Framework for Data-Scarce Environments—A Case Study of Benguerir, Morocco","abstract":"Urban Digital Twins (UDTs) are emerging as a new paradigm in smart city strategies, enabling real-time interaction with urban environments and supporting data-driven decision-making. By expanding beyond traditional smart functions, UDTs facilitate the analysis and simulation of urban resilience and sustainability indicators within a virtual city ecosystem, addressing both immediate urban challenges and long-term planning goals. This paper introduces TwinCity, a city-scale Urban Digital Twin framework developed and validated through a case study of the Green City of Benguerir, Morocco. The framework incorporates a technical architecture based on semantic 3D city models, data integration, and simulation scenarios to analyse the solar energy potential of the rooftop, the energy consumption of the building and the morphological indicators. A user-friendly web interface was developed to visualise and interact with the UDT, ensuring its accessibility. By bridging the gap between technical challenges (such as data scarcity) and practical applications, this work offers a replicable model for cities in the Global South.","author":[{"family":"Badreddine","given":"Ouzougarh"},{"family":"Radoine","given":"Hassan"},{"family":"Hajji","given":"Rafika"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/smartcities9020023","URL":"https://doi.org/10.3390/smartcities9020023","source":"openalex"},{"id":"oa:W4409619690","type":"article-journal","title":"Modeling radiologists’ cognitive processes using a digital gaze twin to enhance radiology training","abstract":"Predicting human gaze behavior is critical for advancing interactive systems and improving diagnostic accuracy in medical imaging. We present MedGaze, a novel system inspired by the \"Digital Gaze Twin\" concept, which models radiologists' cognitive processes and predicts scanpaths in chest X-ray (CXR) images. Using a two-stage training approach-Vision to Radiology Report Learning (VR2) and Vision-Language Cognition Learning (VLC)-MedGaze combines visual features with radiology reports, leveraging large datasets like MIMIC to replicate radiologists' visual search patterns. MedGaze outperformed state-of-the-art methods on the EGD-CXR and REFLACX datasets, achieving IoU scores of 0.41 [95% CI 0.40, 0.42] vs. 0.27 [95% CI 0.26, 0.28], Correlation Coefficient (CC) of 0.50 [95% CI 0.48, 0.51] vs. 0.37 [95% CI 0.36, 0.41], and Multimatch scores of 0.80 [95% CI 0.79, 0.81] vs. 0.71 [95% CI 0.70, 0.71], with similar improvements on REFLACX. It also demonstrated its ability to assess clinical workload through fixation duration, showing a significant Spearman rank correlation of 0.65 (p < 0.001) with true clinical workload ranks on EGD-CXR. The human evaluation revealed that 13 out of 20 predicted scanpaths closely resembled expert patterns, with 18 out of 20 covering 60-80% of key regions. MedGaze's ability to minimize redundancy and emulate expert gaze behavior enhances training and diagnostics, offering valuable insights into radiologist decision-making and improving clinical outcomes.","author":[{"family":"Awasthi","given":"Akash"},{"family":"Vu","given":"Tuan"},{"family":"Le","given":"Ngan"},{"family":"Deng","given":"Zhigang"},{"family":"Maulik","given":"Supratik"},{"family":"Agrawal","given":"Rishi"},{"family":"Wu","given":"Carol"},{"family":"Nguyen","given":"Hien"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-97935-y","URL":"https://doi.org/10.1038/s41598-025-97935-y","source":"openalex"},{"id":"oa:W4411190155","type":"article-journal","title":"Digital transformations of supply chain management via RFID technology: A systematic literature review","abstract":"This paper conducts a systematic literature review of 109 peer-reviewed articles to examine the socio-technical factors shaping the implementation of Radio Frequency Identification (RFID) in supply chain management. Guided by socio-technical systems theory, the study categorizes the findings into social and technical subsystems and identifies seven key synergy mechanism factor that underpin successful deployment. The results show that challenges related to strategic decision-making, cultural adaptability, privacy, system integration, and cost-effectiveness plays a significant role in determining implementation outcomes. The study offers a novel socio-technical framework for understanding RFID adoption and contributes to theory by highlighting the interplay between human and technological dimensions. Practical implications are discussed for integrated system design and strategic planning, alongside research limitations and suggestions for future studies.","author":[{"family":"Zhang","given":"Yuxing"},{"family":"Lin","given":"Yong"},{"family":"Esfahbodi","given":"Ali"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jdec.2025.06.001","URL":"https://doi.org/10.1016/j.jdec.2025.06.001","source":"openalex"},{"id":"oa:W4412649565","type":"manuscript","title":"Knowledge Graphs and Artificial Intelligence for the Implementation of Cognitive Heritage Digital Twins","abstract":"This paper explores the integration of Artificial Intelligence and semantic technologies to support the creation of intelligent Heritage Digital Twins (HDT), digital constructs capable of representing, interpreting, and reasoning over cultural data. The study focuses on transforming the often fragmented and unstructured documentation produced in cultural heritage into coherent Knowledge Graphs aligned with the CIDOC CRM family of ontologies, particularly CRMhs and RHDTO. Two complementary AI-assisted workflows are proposed: one for extracting and formalising structured knowledge from heritage science reports, and another for enhancing AI models through the integration of curated ontological knowledge. The experiments demonstrate how this synergy facilitates both the retrieval and the reuse of complex information, while ensuring interpretability and semantic consistency. Beyond technical efficacy, the paper also addresses the ethical implications of AI use in cultural heritage, with particular attention to transparency, bias mitigation, and meaningful representation of diverse narratives. The results highlight the importance of a reflexive and ethically grounded deployment of AI, where knowledge extraction and machine learning are guided by structured ontologies and human oversight, to ensure conceptual rigour and respect for cultural complexity.","author":[{"family":"Felicetti","given":"Achille"},{"family":"Himmiche","given":"Aida"},{"family":"Somenzi","given":"Miriana"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202507.1673.v1","URL":"https://doi.org/10.20944/preprints202507.1673.v1","source":"openalex"},{"id":"oa:W7116835834","type":"article-journal","title":"Integrating Smart City Technologies and Urban Resilience: A Systematic Review and Research Agenda for Urban Planning and Design","abstract":"Cities increasingly utilise digital technologies to tackle climate risks and urban shocks, yet their real impact on resilience remains uncertain. This paper systematically reviews 115 peer-reviewed studies (2012–2024) to explore how smart city technologies engage with planning instruments, governance arrangements, and social processes, following PRISMA 2020 and combining bibliometric co-occurrence mapping with a qualitative synthesis of full texts. Three themes organise the findings: (i) urban planning and design, (ii) smart technologies in resilience, and (iii) strategic planning and policy integration. Across these themes, Internet of Things (IoT) and geographic information system (GIS) applications have the strongest empirical support for enhancing absorptive and adaptive capacities through risk mapping, early warning systems, and infrastructure operations, while artificial intelligence, digital twins, and blockchain remain largely at pilot or conceptual stages. The review also highlights significant geographical and hazard biases: most cases come from high-income cities and concentrate on floods and earthquakes, while slow stresses (such as heat, housing insecurity, and inequality) and cities in the Global South are under-represented. Overall, the study promotes a “smart–resilience co-production” perspective, demonstrating that resilience improvements rely less on technology alone and more on how digital systems are integrated into governance and participatory practices.","author":[{"family":"Varzeshi","given":"Shabnam"},{"family":"Fien","given":"John"},{"family":"Irajifar","given":"Leila"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/smartcities9010002","URL":"https://doi.org/10.3390/smartcities9010002","source":"openalex"},{"id":"oa:W4414352939","type":"article-journal","title":"Can Urban Digital Twins Support the Realization of Sustainable Development Goal 11? Identifying Key Social and Technical Challenges","abstract":"Abstract. The rapid urbanization of cities presents significant sustainability challenges, necessitating big data and digital tools as solutions for efficient resource management. A key advancement in this area is the Urban Digital Twin (UDT). UDTs aim to create dynamic virtual replicas of urban environments, enabling informed decision-making for city planners and policymakers. UDTs enable predictive modeling, resource optimization, and impact assessment of urban interventions. On the other hand, one of the globally accepted sustainable development goals (SDGs) to achieve by 2030 is SDG 11, which focuses specifically on “Sustainable Cities and Communities”. SDGs and SDG 11 consider the cities as a system that consists of the physical urban environment and social dynamics coming from governance, citizens and communities. However, current research on UDTs has primarily focused on technical aspects, leaving the potential of UDTs to support SDG 11 and its social dynamics underexplored. This study aims to understand whether UDTs can support the realization of SDG 11. Therefore, we explore how the capabilities of UDTs, such as monitoring, modelling and simulation, visualization, information provision and collection can support the SDG 11 principles of managing interconnected targets, inclusivity, multi-stakeholder collaboration, and monitoring of SDG 11 targets. We propose a socio-technical framework illustrating how UDTs can support SDG 11 and outline the key social and technical challenges to be addressed to fully realize UDTs’ potential. Finally, we discuss the conclusions and outlook for overcoming such challenges.","author":[{"family":"Yang","given":"Senqi"},{"family":"Macatulad","given":"Edgardo"},{"family":"Biljecki","given":"Filip"},{"family":"Dane","given":"Gamze"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/isprs-annals-x-4-w7-2025-129-2025","URL":"https://doi.org/10.5194/isprs-annals-x-4-w7-2025-129-2025","source":"openalex"},{"id":"oa:W7127128233","type":"article-journal","title":"Digital Twin in Territorial Planning: Comparative Analysis for the Development of Adaptive Cities","abstract":"Increasing urbanisation and the intensification of environmental and climate challenges require a review of governance models and tools supporting urban and territorial planning. The Twin Transition concept (green and digital) requires the integration of advanced monitoring and simulation systems. In this context, Digital Twins (DTs) have evolved from static virtual replicas to dynamic urban intelligence systems. Thanks to the integration of IoT sensors and artificial intelligence algorithms, DT enables the transition from a descriptive to a prescriptive approach, supporting climate uncertainty management and real-time territorial governance. The ability to integrate multi-source data and provide high-resolution site-specific representations makes these tools strategic for planning, resource management, and the assessment of urban and peri-urban resilience. The contribution comparatively analyses different digital twin frameworks, with particular attention to their applicability in highly complex environmental contexts, such as the city of Taranto. As a Site of National Interest, Taranto requires models capable of integrating industrial pollutant monitoring with urban regeneration and biodiversity protection strategies. The study assesses the potential of DT as predictive models to support governance for more sustainable, adaptive, and resilient cities.","author":[{"family":"Mammone","given":"Valeria"},{"family":"Binetti","given":"Maria"},{"family":"Massarelli","given":"Carmine"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/urbansci10020080","URL":"https://doi.org/10.3390/urbansci10020080","source":"openalex"},{"id":"oa:W4413977177","type":"article-journal","title":"Sensor-based slope stability prediction using a digital twin and AI-driven stability forecasting","abstract":"Abstract. The need for better geological risk management techniques has increased due to the frequency and severity of natural disasters like floods and landslides, which are being caused by urbanization and climate change. Such management has always depended on limited simulations and static models derived from historical data. But more dynamic methods for modelling physical situations in real time and predicting future events are now available thanks to recent developments in digital technology, especially Digital Twins (DT). The use of DT in landslide prediction is examined in this work, with an emphasis on the use of inexpensive sensors in real-time monitoring of vital environmental factors such ground movement, pore water pressure, and volumetric water content. The research was conducted on a test site located on the Feo di Vito hill within the University of Reggio Calabria, a geologically vulnerable area. The proposed system integrates real-time environmental monitoring with advanced modeling and predictive techniques, ultimately supporting early risk detection and response. Results highlight the potential of this approach to enhance forecasting accuracy and responsiveness, offering an effective, scalable, and low-cost decision-support tool for mitigating landslide risk in vulnerable areas.","author":[{"family":"Maesano","given":"Cara"},{"family":"Genovese","given":"Emanuela"},{"family":"Calluso","given":"Sonia"},{"family":"Manti","given":"Maurizio"},{"family":"Barrile","given":"Vincenzo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/isprs-archives-xlviii-2-w9-2025-183-2025","URL":"https://doi.org/10.5194/isprs-archives-xlviii-2-w9-2025-183-2025","source":"openalex"},{"id":"oa:W7126199606","type":"article-journal","title":"A conceptual architecture for AI-assisted Digital Twins in natural resource management","abstract":"The management of natural resources is increasingly critical and challenging due to complex interactions among environmental, industrial, and societal processes. Traditional approaches often fail to integrate heterogeneous data, limiting predictive and decision-support capabilities. This study presents a conceptual architecture for an Artificial Intelligence (AI)-assisted Digital Twin (DT) of the Centre-Val de Loire region, designed to unify time-dependent multi-source data. Based on the ENVRI Reference Model, it covers Science, Information, Computational, Engineering, and Technology layers, defining standardized data exchange, communication protocols, and prototype functionalities. A proof of concept FIWARE implementation supports ingestion, monitoring and analytical services for piezometric and meteorological data, exemplified through groundwater dynamics in the Beauce aquifer. It integrates daily observations from 53 piezometric stations over more than five years, managing approximately 2.8 million records in a containerized environment. Results show that the proposed DT architecture can enhance sustainability-oriented decision making, integrating heterogeneous data and predictive analyses while enabling collaboration across scientific and technical domains. Its modular design offers a replicable template for future AI-assisted environmental DTs, scalable to larger regions. Hence, this work illustrates how DTs can improve environmental monitoring and understanding, providing a pathway toward resilient, data-driven management of natural resources. • AI-assisted Digital Twin for natural resource management. • Data architecture design based on the ENVRI Reference Model. • Integration of heterogeneous, temporally correlated environmental data. • Use cases, functions, data exchange and communication protocols. • Viewpoints UML-modeling and complete operative PoC.","author":[{"family":"Iglesias","given":"Félix"},{"family":"Ros","given":"Frédéric"},{"family":"Thuy","given":"Lynh"},{"family":"Gourcy","given":"Laurence"},{"family":"Moquet","given":"Jean"},{"family":"Daële","given":"Véronique"},{"family":"Dupraz","given":"Sébastien"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.ecoinf.2026.103635","URL":"https://doi.org/10.1016/j.ecoinf.2026.103635","source":"openalex"},{"id":"oa:W4408219818","type":"article-journal","title":"Revolutionizing Construction Safety: Unveiling the Digital Potential of Building Information Modeling (BIM)","abstract":"The construction industry is facing issues worldwide, particularly worker fatalities and injury rates. Construction safety requires careful attention and preparation across the project’s entire lifecycle, from design to demolition activities. In the digital era, Building Information Modeling (BIM) has emerged as a transformative technology in the construction industry, offering new opportunities to enhance safety standards and reduce accidents. This study examines the influence of BIM on construction safety, particularly its capacity to transform safety protocols, enhance danger identification, and minimize accidents during the construction project’s duration. The review approach used is based on PRISMA. Scopus and Web of Science were the databases used to search for qualifying publications. From an initial cohort of 502 papers, 125 were chosen as relevant to the scope of this research. A thorough analysis of the existing literature was conducted to examine the processes by which BIM helps to improve safety, such as early hazards identification, conflict detection, virtual safety simulations, and improved communication and collaboration among project stakeholders. This study examined the following knowledge gaps: integration with safety regulations and standards, a comprehensive safety dimension in BIM, BIM for real-time safety monitoring, and a BIM-driven safety culture. The following potential future research directions were highlighted: enhanced BIM applications for safety, longitudinal studies on BIM and safety outcomes, BIM for post-construction safety and maintenance, and BIM for safety training and simulation. In conclusion, the integration of BIM into construction safety protocols presents significant potential for mitigating risks and improving safety management over the asset lifecycle. As the industry increasingly adopts digital technology, BIM will be crucial in establishing safer and more efficient construction environments.","author":[{"family":"Manzoor","given":"Bilal"},{"family":"Charef","given":"Rabia"},{"family":"Antwiafari","given":"Maxwell"},{"family":"Alotaibi","given":"Khalid"},{"family":"Harirchian","given":"Ehsan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15050828","URL":"https://doi.org/10.3390/buildings15050828","source":"openalex"},{"id":"oa:W4413788828","type":"article-journal","title":"Threat Modeling and Attacks on Digital Twins of Vehicles: A Systematic Literature Review","abstract":"This systematic literature review pioneers the synthesis of cybersecurity challenges for automotive digital twins (DTs), a critical yet underexplored frontier in connected vehicle security. The notion of digital twins, which act as simulated counterparts to real-world systems, is revolutionizing secure system design within the automotive sector. As contemporary vehicles become more dependent on interconnected electronic systems, the likelihood of cyber threats is escalating. This comprehensive literature review seeks to analyze existing research on threat modeling and security testing in automotive digital twins, aiming to pinpoint emerging patterns, evaluate current approaches, and identify future research avenues. Guided by the PRISMA framework, we rigorously analyze 23 studies from 882 publications to address three research questions: (1) How are threats to automotive DTs identified and assessed? (2) What methodologies drive threat modeling? Lastly, (3) what techniques validate threat models and simulate attacks? The novelty of this study lies in its structured classification of digital twin types (physics based, data driven, hybrid), its inclusion of a groundbreaking threat taxonomy across architectural layers (e.g., ECU tampering, CAN-Bus spoofing), the integration of the 5C taxonomy with layered architectures for DT security testing, and its analysis of domain-specific tools such as VehicleLang and embedded intrusion detection systems. The findings expose significant deficiencies in the strength and validation of threat models, highlighting the necessity for more adaptable and comprehensive testing methods. By exposing gaps in scalability, trust, and safety, and proposing actionable solutions aligned with UNECE R155, this SLR delivers a robust framework to advance secure DT development, empowering researchers and industry to fortify vehicle resilience against evolving cyber threats.","author":[{"family":"Shah","given":"Uzair"},{"family":"Minhas","given":"Daud"},{"family":"Kifayat","given":"Kashif"},{"family":"Shah","given":"Khizar"},{"family":"Frey","given":"Georg"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/smartcities8050142","URL":"https://doi.org/10.3390/smartcities8050142","source":"openalex"},{"id":"oa:W4406878638","type":"article-journal","title":"The Digital REadiness Assessment MaturitY (DREAMY) framework to guide manufacturing companies towards a digitalisation roadmap","abstract":"Digital technologies are considered the main drivers for the transformation of the manufacturing industry. To effectively navigate this wave of transformation, companies need to understand their current maturity state regarding implemented technologies and organisational processes across various functions. However, many organisations struggle to assess their digital status quo. Addressing this gap, this paper proposes a framework to help manufacturing companies become aware of their digital maturity level and guide them toward a digitalisation roadmap. The framework consists of a maturity model, the Digital Readiness Assessment MaturitY (DREAMY), inspired by the Capability Maturity Model Integration (CMMI), and a digitalisation roadmap tool. The research follows the design research methodology, combining a literature review, expert consultations, and validation through multiple industrial cases to develop, test, and refine the framework. The proposed framework enables companies to assess their current digital maturity, identify strengths and weaknesses, and discover opportunities for improvement, supporting a conscious transition toward Industry 4.0 and the forthcoming Industry 5.0 paradigm.","author":[{"family":"Carolis","given":"Anna"},{"family":"Sassanelli","given":"Claudio"},{"family":"Acerbi","given":"Federica"},{"family":"Macchi","given":"Marco"},{"family":"Terzi","given":"Sergio"},{"family":"Taisch","given":"Marco"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/00207543.2025.2455476","URL":"https://doi.org/10.1080/00207543.2025.2455476","source":"openalex"},{"id":"oa:W4417198669","type":"article-journal","title":"Effects of UAV-Based Image Collection Methodologies on the Quality of Reality Capture and Digital Twins of Bridges","abstract":"Unmanned Aerial Vehicle (UAV)-based photogrammetric reconstruction is a key step in geometric digital twinning of bridges, but ensuring the quality of the reconstruction data through the planning of measurement configurations is not straightforward. This research investigates an approach for quantitatively evaluating the impact of different methodologies and configurations of UAV-based image collection on the quality of the collected images and 3D reconstruction data in the bridge inspection context. For an industry-grade UAV and a consumer-grade UAV, paths for image collection from different Ground Sampling Distance (GSD) and image overlap ratios are considered, followed by the 3D reconstruction with different algorithm configurations. Then, an approach for evaluating these data collection methodologies and configurations is discussed, focusing on trajectory accuracy, point-cloud reconstruction quality, and accuracy of geometric measurements relevant to inspection tasks. Through a case study on short-span road bridges, errors in different steps of the photogrammetric 3D reconstruction workflow are characterized. The results indicate that, for the global dimensional measurements, the consumer-grade UAV works comparably to the industry-grade UAV with different GSDs. In contrast, the local measurement accuracy changes significantly depending on the selected hardware and path-planning parameters. This research provides practical insights into controlling 3D reconstruction data quality in the context of bridge inspection and geometric digital twinning.","author":[{"family":"Zhao","given":"Rongxin"},{"family":"Wu","given":"Huayong"},{"family":"Wang","given":"Feng"},{"family":"Xu","given":"Haisong"},{"family":"Wang","given":"Shuo"},{"family":"Li","given":"Yuxuan"},{"family":"Xu","given":"Tianyi"},{"family":"Shi","given":"Mingyu"},{"family":"Narazaki","given":"Yasutaka"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/infrastructures10120341","URL":"https://doi.org/10.3390/infrastructures10120341","source":"openalex"},{"id":"oa:W4409676198","type":"article-journal","title":"Opportunities and challenges of digital twin applications in the Middle East construction industry","abstract":"Purpose Over the years, the Middle East (ME) has experienced significant advancements in technology, particularly in the digital realm, initiated by Dubai’s 2013 Building Information Modeling (BIM) mandate. However, there are ongoing questions regarding how digital twins (DTs) have been adopted and awareness within the region’s construction industry. This paper aims to explore the current state of DT technology within the construction industry in the ME. It seeks to understand the trends, benefits and challenges associated with the adoption of DTs, as well as the level of awareness among industry professionals regarding this innovative technology. Design/methodology/approach Conducting a comprehensive literature review and semi-structured interviews with 10 construction professionals from various firms in the ME, each possessing significant experience (ranging from 7 to 26 years) in digital construction. The interviews were designed to gather in-depth insights into the advantages, challenges and awareness of DTs in the region. The data collected from these interviews were transcribed and analyzed using thematic analysis facilitated by NVivo 14 software, allowing the identification of key themes and patterns related to the implementation of digital twin technology in the region. Findings There is a growth in Middle Eastern digital twin trends, with developers exploring efficient implementation. Despite theoretical advancements, practical implementation lags. Identified benefits include sustainability enhancement, roles in risk assessment, predictive maintenance, documentation, stakeholder communication, customer satisfaction, safety, production increase, efficiency and real-time monitoring. Challenges involve 26 obstacles categorized into six groups, notably a lack of awareness and understanding of digital twin technology and concerns about data uncertainties. Research limitations/implications The research focused only on the applications of DT within the ME region. Practical implications This paper underscores the importance of standardized policy frameworks for DT adoption in the ME construction industry. Standardization enhances project execution, regulatory compliance and innovation while fostering collaboration among stakeholders. Awareness and education programs are crucial for understanding DT benefits, promoting sustainability and improving operational efficiency, offering a clear roadmap for the effective integration of DT solutions. Originality/value The value of this research lies in its in-depth examination of DT technology’s definition, components, benefits and challenges within the Middle Eastern construction industry. It sheds light on the early stages of DT adoption, emphasizing the need for infrastructure, skilled management and standardization to optimize its integration. The study bridges theoretical knowledge with practical insights, addressing barriers like cultural change, data uncertainties and regulatory gaps while highlighting lessons from related technologies like BIM.","author":[{"family":"Barham","given":"Diala"},{"family":"Matarneh","given":"Sandra"},{"family":"Tezel","given":"Algan"},{"family":"Hasan","given":"Saed"},{"family":"Mereb","given":"Wajdi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1108/uss-07-2024-0041","URL":"https://doi.org/10.1108/uss-07-2024-0041","source":"openalex"},{"id":"oa:W4410502737","type":"article-journal","title":"Competitiveness in the Era of Circular Economy and Digital Innovations: An Integrative Literature Review","abstract":"This study explores the intersection of competitiveness in a circular economy and the role of digital innovations through an integrative literature review. Synthesizing quantitative and qualitative research identifies gaps and offers insights on how these trends shape competitive strategies. The review emphasizes three main areas: technological enablers, operational challenges, and the role of policy and collaboration. It highlights the interrelationship among the circular economy, digital innovations, and competitiveness in promoting sustainable practices. The research suggests that policymakers should support small- and medium-sized enterprises (SMEs) with financial assistance for digital tool adoption and establish regional digital innovation hubs for technology access and training. Standardized data-sharing protocols are crucial for effective circular economy practices and cybersecurity. Ultimately, the review identifies key research opportunities at the nexus of digital innovations and the circular economy, aiming to enhance theoretical knowledge and inform sustainable business model development.","author":[{"family":"Awad","given":"Ibrahim"},{"family":"Nuseibeh","given":"Hasan"},{"family":"Amro","given":"Alaa"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17104599","URL":"https://doi.org/10.3390/su17104599","source":"openalex"},{"id":"oa:W7118558524","type":"article-journal","title":"A Framework for a Digital Twin of Inspection Robots","abstract":"The study addresses the design and implementation of a modular, scalable platform for specialized inspection tasks, highlighting its suitability for future research activities. The work presents a fully validated methodology that encompasses both the physical robot and its digital twin. Specifically, the objective of this work is to design and develop a sensor-equipped mobile robot designed for inspection and surveillance tasks. The study places particular emphasis on the robot’s actuation system, the design and implementation of its control architecture, and the creation of a PC-based control interface. Additionally, suitable sensors can be integrated to enable future capabilities in automatic obstacle detection and autonomous navigation. The paper presents a digital shadow/DT-enabling framework to support inspection and surveillance operations, grounded in the digital representation of the robot.","author":[{"family":"Pelagalli","given":"Cristian"},{"family":"Rea","given":"Pierluigi"},{"family":"Bona","given":"Roberto"},{"family":"Ottaviano","given":"Erika"},{"family":"Kciuk","given":"Marek"},{"family":"Kowalik","given":"Zygmunt"},{"family":"Bijak","given":"Joanna"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/app16020650","URL":"https://doi.org/10.3390/app16020650","source":"openalex"},{"id":"oa:W7117162778","type":"article-journal","title":"Digital Twin and Integrated Sensing and Communication Applications in Internet of Things: Enabling Communication Technologies, Taxonomy, Implications, and Open Issues","abstract":"Future internet of things (IoT) services necessitate the integration of sensing and communication functions within the same system, utilizing digital twin (DT) technology. Integrated sensing and communication (ISAC) can address the need for widespread communication and high-precision sensing by leveraging the benefits of spectrum and hardware resource sharing. The DT represents a promising technology for achieving low latency and high energy efficiency, leveraging real-time monitoring, optimization, and predictive maintenance capabilities. Recent advancements in DT and ISAC for IoT systems research necessitate the establishment of effective communication technology methods between the physical entity and its digital representation. Most prior research reviews have not sufficiently explored the critical enabling technologies for DT and ISAC applications in IoT systems that facilitate communication between a physical entity and its digital counterparts. Previous research has primarily focused on the application of DT technology in IoT systems; however, little emphasis has been placed on the integration of ISAC technology with DT in IoT systems, as well as the important integrated sensing and communication technologies between physical entities and their digital counterparts. This paper presents a systematic literature review that focuses on the analysis of key communication technologies that facilitate connections in DT and ISAC for IoT systems. The implications of communication methods derived from the study are presented, focusing on technologies such as unmanned aerial vehicles (UAVs), reconfigurable intelligent surfaces (RISs), millimeter wave (mmWave), and massive MIMO (mMIMO) technologies. The emphasis on these technologies is due to their significance as essential enablers of integrated sensing and communication between physical entities and their digital counterparts. Furthermore, these technologies are critical for integrating DT and ISAC into the IoT systems to efficiently meet the needs of IoT services. Future discussions are finally addressing open research and the challenges that demand attention.","author":[{"family":"Hamadou","given":"Abdel"},{"family":"Du","given":"Shengzhi"},{"family":"Olwal","given":"Thomas"},{"family":"Wyk","given":"Barend"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app16010073","URL":"https://doi.org/10.3390/app16010073","source":"openalex"},{"id":"oa:W4413429058","type":"article-journal","title":"A Review of 3D Shape Descriptors for Evaluating Fidelity Metrics in Digital Twin","abstract":"Digital Twin (DTw) technology is a cornerstone of Industry 4.0, enabling real-time monitoring, predictive maintenance, and performance optimization across diverse industries. A key requirement for effective DTw implementation is high geometric fidelity—ensuring the digital model accurately represents the physical counterpart. Fidelity metrics provide a quantitative means to assess this alignment in terms of geometry, behavior, and performance. Among these, 3D shape descriptors play a central role in evaluating geometric fidelity, offering computational tools to measure shape similarity between physical and digital entities. This paper presents a comprehensive review of 3D shape descriptor methods and their applicability to geometric fidelity assessment in DTw systems. We introduce a structured taxonomy encompassing classical, structural, texture-based, and deep learning-based descriptors, and evaluate each in terms of transformation invariance, robustness to noise, computational efficiency, and suitability for various DTw applications. Building upon this analysis, we propose a conceptual fidelity metric that maps descriptor properties to the specific fidelity requirements of different application domains. This metric serves as a foundational framework for shape-based fidelity evaluation and supports the selection of appropriate descriptors based on system needs. Importantly, this work aligns with and contributes to the emerging ISO 30138 standardization initiative by offering a descriptor-driven approach to fidelity assessment. Through this integration of taxonomy, metric design, and standardization insight, this paper provides a roadmap for more consistent, scalable, and interoperable fidelity measurement in digital twin environments—particularly those demanding high precision and reliability.","author":[{"family":"Khan","given":"Md"},{"family":"Han","given":"Soonhung"},{"family":"Jauhar","given":"Tahir"},{"family":"Noh","given":"Chiho"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/machines13090750","URL":"https://doi.org/10.3390/machines13090750","source":"openalex"},{"id":"oa:W4407365302","type":"article-journal","title":"A Physics‐Informed Neural Network as a Digital Twin of Optically Turbid Media","abstract":"In this article, a novel methodology for characterizing and creating a digital twin of turbid media with intensity measurements only is presented, employing a unique physics‐informed neural network approach. Unlike previous approaches utilizing various deep neural network architectures that often function as black boxes, the method prioritizes interpretability, offering a clearer understanding of the underlying processes of light propagation through turbid media and estimating the transmission matrix. The possibility and use case of gradient calculation through this presented digital twin are showcased by solving the problem to retrieve the initial wavefront shape of the light that passed through the medium (e.g., the image transmission problem). The results surpassed the accuracy of models directly optimized for this task, underscoring the precision of the proposed digital twin. This capability represents a pivotal advancement for future developments in neuromorphic and deep learning computation and training using such a photonic and optical systems.","author":[{"family":"Kazemzadeh","given":"Mohammadrahim"},{"family":"Collard","given":"Liam"},{"family":"Piscopo","given":"Linda"},{"family":"Vittorio","given":"Massimo"},{"family":"Pisanello","given":"Ferruccio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/aisy.202400574","URL":"https://doi.org/10.1002/aisy.202400574","source":"openalex"},{"id":"oa:W4408363754","type":"article-journal","title":"Public Development: Towards Open Standards and Components for Local Digital Twins","abstract":"Abstract An Open Local Digital Twin (LDT) relies on standards-based interfaces and components to ensure replicability, reuse, and future maintainability. This chapter provides an overview of relevant LDT standards in different Pivotal Points of Interoperability (PPI), in the LDT core components and the data, modelling, and visualisation domains. The chapter aims to provide a neutral overview of useful standards and components at different levels of standardisation, such as encoding standards, syntax and semantic-related standards, and, if available, standards about business interactions. Based on the LDT architecture building blocks (BB), the current maturity level and relation with the Minimal Interoperability Mechanisms (MIMs) concept is scrutinised. This analysis shows a variety of maturity and existing standardisation gaps, mainly related to the interactivity of LDT services and the cooperation between domain-specific simulation models. However, the LDT can benefit from existing standards in the data and visualisation domains, as well as the further development of common ontologies for domain-overarching service customisation support. Cross-domain digital twin cases and scenarios will contribute to more cost-efficient construction of policy-supporting, predictive LDTs.","author":[{"family":"Raes","given":"Lieven"},{"family":"Lathouwer","given":"Bart"},{"family":"Hilgers","given":"Gert"},{"family":"Lefever","given":"Stefan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/978-3-031-81451-8_6","URL":"https://doi.org/10.1007/978-3-031-81451-8_6","source":"openalex"},{"id":"oa:W4413159447","type":"article-journal","title":"Towards Digital Twin of Vehicle Tyre: Theoretical Framework for a Multibody Model","abstract":"The rapid advancement in the automotive industry necessitates the creation of digital twins (DTs), fundamentally transforming design and testing processes. Among the various components, vehicle tyres present significant challenges for accurate modelling. This paper reviews current tyre modelling techniques, exploring their applications, associated challenges, and possibilities. An advanced tyre model (TM) is introduced that emphasises interactions between the tyre and rim, as well as between the three-dimensional tyre and road, while accounting for dynamic variations in gas pressure and thermodynamic factors. The modelling approach involves developing nine nodal discrete elements of varying thickness, with each element comprising twelve rheological components designed to function under tension and compression, alongside four additional rheological elements to evaluate the bending stiffness of each discrete element. During the validation procedure, an RMSE of 0.00892 was achieved by comparing the developed TM to the experimentally validated MF SWIFT model; however, the TM presents much more information regarding tyre parameters, which can be used for vehicle dynamics investigations. Future steps for model improvement are presented.","author":[{"family":"Bogdevičius","given":"Marijonas"},{"family":"Kojis","given":"Paulius"},{"family":"Skrickij","given":"Viktor"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15168933","URL":"https://doi.org/10.3390/app15168933","source":"openalex"},{"id":"oa:W4411689201","type":"article-journal","title":"Leveraging Digital Logistics Twins to Harness Sustainability and Resilience in Manufacturing Networks","abstract":"Abstract The current global business environment poses significant challenges for companies to maintain efficient and sustainable operations. This study focuses on the role of self-imposed restrictions in enhancing the sustainability and resilience of logistics networks. Using the automotive industry as an example, this research analyzes the impact of such restrictions on the overall sustainability and resilience of international logistics networks. Building on a case study research approach, qualitative and quantitative analyses are performed to present a comprehensive understanding of the current situation while developing practical solutions. By examining the threshold between different categories of restrictions, the study provides actionable recommendations for companies to enhance their process planning capabilities and leverage Digital Logistics Twins as a supportive environment. Specifically, by shifting the focus towards more proactive management of self-imposed restrictions, companies can improve their efficiency and sustainability. Furthermore, the insights gained from this study provide a valuable framework for organizations seeking to optimize their operations, leverage the potential of DLT, and contribute to the research on supply chain resilience and the role of digital technologies.","author":[{"family":"Straube","given":"Frank"},{"family":"Gorgas","given":"Benjamin"},{"family":"Coll","given":"Angelica"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/978-3-031-93891-7_81","URL":"https://doi.org/10.1007/978-3-031-93891-7_81","source":"openalex"},{"id":"oa:W4404346980","type":"article-journal","title":"Integrating Brain-Computer Interface and Neuromorphic Computing for Human Digital Twins","abstract":"The integration of immersive communication into a human-centric ecosystem has intensified the demand for sophisticated Human Digital Twins (HDTs) driven by multifaceted human data. However, the effective construction of HDTs faces significant challenges due to the heterogeneity of data collection devices, the high energy demands associated with processing intricate data, and concerns over the privacy of sensitive information. This work introduces a novel biologically-inspired (bio-inspired) HDT framework that leverages Brain-Computer Interface (BCI) sensor technology to capture brain signals as the data source for constructing HDT. By collecting and analyzing these signals, the framework not only minimizes device heterogeneity and enhances data collection efficiency, but also provides richer and more nuanced physiological and psychological data for constructing personalized HDTs. To this end, we further propose a bio-inspired neuromorphic computing learning model based on the Spiking Neural Network (SNN). This model utilizes discrete neural spikes to emulate the way of human brain processes information, thereby enhancing the system's ability to process data effectively while reducing energy consumption. Additionally, we integrate a Federated Learning (FL) strategy within the model to strengthen data privacy. We then conduct a case study to demonstrate the performance of our proposed twofold bio-inspired scheme. Finally, we present several challenges and promising directions for future research of HDTs driven by bio-inspired technologies.","author":[{"family":"Shang","given":"Chen"},{"family":"Yu","given":"Jiadong"},{"family":"Hoang","given":"Dinh"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/mcom.001.2500100","URL":"https://doi.org/10.1109/mcom.001.2500100","source":"openalex"},{"id":"oa:W7128806573","type":"article-journal","title":"Research on Remaining Useful Life Prediction of Equipment Based on Digital Twins","abstract":"Remaining Useful Life (RUL) prediction is a key factor in fault diagnosis, prediction, and health management (PHM) during equipment operation and service. Its purpose is to predict the time interval from the current moment to the complete failure of the equipment, serving as the basis for condition-based maintenance strategies. Effective RUL prediction enables the scheduling of maintenance plans in advance, thereby reducing equipment downtime and safety incidents. The RUL prediction of equipment and its critical components is an important means of fault diagnosis and prediction. Real-time and accurate RUL prediction results are prerequisites for implementing preventive maintenance, condition-based maintenance, and failure-based maintenance strategies, allowing the identification of optimal maintenance timing. This constitutes a crucial aspect of precise equipment support. The real-time, high-efficiency communication of digital twin technology can support real-time online RUL prediction for equipment. This paper introduces digital twin technology and constructs a digital twin-based RUL prediction model for equipment. The study proposes an integrated learning-based RUL prediction method for equipment, validated through experiments to demonstrate its accuracy and robustness. Finally, this paper presents an engineering implementation plan for online RUL prediction of equipment based on digital twins.","author":[{"family":"Wu","given":"Jiaju"},{"family":"Zhou","given":"Yuanlin"},{"family":"Wang","given":"Xiaodong"},{"family":"Chen","given":"Chuan"},{"family":"Ma","given":"Yongqi"},{"family":"Zhang","given":"Chunrui"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/s26041240","URL":"https://doi.org/10.3390/s26041240","source":"openalex"},{"id":"oa:W4408832574","type":"article-journal","title":"Formalizing-modelling-utilizing ontology: A semantic framework for adaptive stakeholder-specific urban digital twins in urban planning processes","abstract":"Urban Digital Twins (UDTs) have emerged as integrated collections of urban data and urban models aspiring to enhance urban planning and decision-making processes. However, current UDTs often fail to connect siloed disciplines, represent diverse stakeholder views, or adapt to the dynamic nature of planning processes. Realizing UDTs potentials is hindered by these socio-technical challenges, we developed and validated FMU Ontology to address them. FMU Ontology provides a set of semantic representations that (1) promote interoperability and integration across disciplinary data and models, (2) enable developing and using a network of stakeholder-specific UDTs that facilitate engagement and consensus-building, and (3) embed these within planning processes to allow UDTs to adapt as stakeholders’ questions and priorities evolve. Furthermore, we validate the efficacy of FMU Ontology through consistency and competency tests. Lastly, in a case study on strategic urban densification in Eindhoven, the Netherlands, we demonstrate how FMU Ontology enables the adaptive and collaborative use of UDTs, addressing key challenges in urban planning and decision-making.","author":[{"family":"Azadi","given":"Shervin"},{"family":"Kasraian","given":"Dena"},{"family":"Nourian","given":"Pirouz"},{"family":"Wesemael","given":"Pieter"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1177/23998083251329398","URL":"https://doi.org/10.1177/23998083251329398","source":"openalex"},{"id":"oa:W4411624728","type":"article-journal","title":"Leveraging digital technology to improve environmental, social, and governance performance of infrastructure projects","abstract":"Purpose This research explores how digital technologies can improve the environmental (E), social (S) and governance (G) performance of infrastructure projects. Design/methodology/approach Grounded in the dynamic capability view (DCV), this study adopted an exploratory qualitative approach. Semi-structured interviews were conducted with infrastructure professionals experienced in digital transformation and Environmental, Social, and Governance (ESG). An inductive thematic analysis was applied to derive insights directly from the data. To interpret and refine the emerging themes in relation to DCV, the research employed an abductive logic through a process of systematic combining allowing theory and empirical data to iteratively inform each other. Findings The results revealed that digital transformation improves ESG performance through informed decision making using real-time data, reduces time consumption in manual data processing, enhances system complexities and facilitates local and global standardization of ESG performance. Furthermore, digital technologies have far-reaching impacts on data collection, structuring, reporting and transparency. Environmental (E), social (S) and governance (G) elements of ESG can significantly be promoted using advanced technologies. The drivers and challenges associated with the adoption of digital technologies to improve ESG performance of infrastructure projects are also highlighted. Practical implications The findings of this research offer valuable insights to infrastructure professionals aiming to improve ESG performance to achieve net-zero targets, promote sustainable investment and enhance competitive advantages by adopting digital transformation in the era of digital economy. Originality/value There is dearth of empirical studies focusing on qualitative research methods that explore the use of digital technologies to advance the performance of infrastructure projects within the framework of ESG.","author":[{"family":"Tumpa","given":"Roksana"},{"family":"Naeni","given":"Leila"},{"family":"Afzal","given":"Fatima"},{"family":"Ghanbaripour","given":"Amir"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1108/md-04-2024-0818","URL":"https://doi.org/10.1108/md-04-2024-0818","source":"openalex"},{"id":"oa:W4413371915","type":"article-journal","title":"Integrating Precision Medicine and Digital Health in Personalized Weight Management: The Central Role of Nutrition","abstract":"Obesity is a global health challenge marked by substantial inter-individual differences in responses to dietary and lifestyle interventions. Traditional weight loss strategies often overlook critical biological variations in genetics, metabolic profiles, and gut microbiota composition, contributing to poor adherence and variable outcomes. Our primary aim is to identify key biological and behavioral effectors relevant to precision medicine for weight control, with a particular focus on nutrition, while also discussing their current and potential integration into digital health platforms. Thus, this review aligns more closely with the identification of influential factors within precision medicine (e.g., genetic, metabolic, and microbiome factors) but also explores how these factors are currently integrated into digital health tools. We synthesize recent advances in nutrigenomics, nutritional metabolomics, and microbiome-informed nutrition, highlighting how tailored dietary strategies—such as high-protein, low-glycemic, polyphenol-enriched, and fiber-based diets—can be aligned with specific genetic variants (e.g., FTO and MC4R), metabolic phenotypes (e.g., insulin resistance), and gut microbiota profiles (e.g., Akkermansia muciniphila abundance, SCFA production). In parallel, digital health tools—including mobile health applications, wearable devices, and AI-supported platforms—enhance self-monitoring, adherence, and dynamic feedback in real-world settings. Mechanistic pathways such as gut–brain axis regulation, microbial fermentation, gene–diet interactions, and anti-inflammatory responses are explored to explain inter-individual differences in dietary outcomes. However, challenges such as cost, accessibility, and patient motivation remain and should be addressed to ensure the effective implementation of these integrated strategies in real-world settings. Collectively, these insights underscore the pivotal role of precision nutrition as a cornerstone for personalized, scalable, and sustainable obesity interventions.","author":[{"family":"Liu","given":"Xiaoguang"},{"family":"Xu","given":"Miaomiao"},{"family":"Wang","given":"H"},{"family":"Zhu","given":"Lin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/nu17162695","URL":"https://doi.org/10.3390/nu17162695","source":"openalex"},{"id":"oa:W4413038758","type":"article-journal","title":"Metamodeling Approach to Sociotechnical Systems’ External Context Digital Twins Building: A Higher Education Case Study","abstract":"Sociotechnical systems (STSs) are generally assumed to be systems that incorporate humans and technology, strongly depending on a sustainable equilibrium between the following nondeterministic social context ingredients: social structures, roles, and rights, as well as the designers’ Holy Grail, the deterministic nature of the underlying technical system. The fact that the relevant social concepts are more mature than the supporting technologies qualifies the digital transformation of sociotechnical systems as a reengineering rather than an engineering endeavor. Preserving the social mission throughout the digital transformation process in varying social contexts is mandatory, making the digital twins (DT) methodology application a contemporary research hotspot. In this research, we combined continuous transformation STS theory principles, an observer-based system-of-sociotechnical-systems (SoSTS) architecture model, and digital twinning methods to address common STS context representation challenges. Additionally, based on model-driven systems engineering methodology and meta-object-facility principles, the research specifies the universal meta-concepts and meta-modeling templates, supporting the creation of arbitrary sociotechnical systems’ external context digital twins. Due to the inherent diversity, significantly influenced by geopolitical, economic, and cultural influencers, a higher education external context specialization illustrates the reusability potentials of the proposed universal meta-concepts. Substituting higher-education-related meta-concepts and meta-models with arbitrary domain-dependent specializations further fosters the proposed universal meta-concepts’ reusability.","author":[{"family":"Perišić","given":"Ana"},{"family":"Perisic","given":"Ines"},{"family":"Lazić","given":"Marko"},{"family":"Perišić","given":"Branko"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15158708","URL":"https://doi.org/10.3390/app15158708","source":"openalex"},{"id":"oa:W7124918178","type":"article-journal","title":"Pseudoamniotic Band Sequence Risk Factors following Fetoscopic Laser for Twin-Twin Transfusion Syndrome","abstract":"Introduction: Pseudoamniotic band sequence (PABS) is a rare but serious complication following fetoscopic laser photocoagulation (FLP) for twin-twin transfusion syndrome (TTTS). We aim to explore associations between perioperative factors and PABS in monochorionic, diamniotic twins undergoing FLP for TTTS. METHODS: A secondary analysis was conducted using a prospective cohort of 816 FLP procedures performed between 2011 and 2024 at a single fetal therapy center. All cases had confirmed absence of PABS prior to FLP via ultrasound and fetoscopic evaluation. PABS was diagnosed postnatally or suspected after FLP and confirmed after birth. Clinical and perioperative variables were compared between cases with and without PABS using appropriate two-sample tests, with statistical significance set at p < 0.01 to minimize type I error in a smaller cohort. RESULTS: PABS occurred in 11 (1.3%) cases, with only 3 (27.3%) identified prenatally and treated with in utero band lysis. Digital amputation occurred in 3 undiagnosed cases. There were no differences in maternal characteristics between groups. Estimated fetal weight discordance (p = 0.003), gestational age at FLP (p = 0.0004), and chorionamnion separation (CAS, p < 0.0001) differed significantly between cases with and without PABS. CONCLUSION: Observed associations with perioperative factors, particularly with CAS, may inform detailed post-FLP evaluation for PABS. Early detection of PABS may facilitate prenatal intervention and reduce adverse neonatal outcomes. .","author":[{"family":"Lemoine","given":"Felicia"},{"family":"Backley","given":"Sami"},{"family":"Vilchez-Lagos","given":"Gustavo"},{"family":"Espinoza","given":"Jimmy"},{"family":"Hernandez-Andrade","given":"Edgar"},{"family":"Johnson","given":"Anthony"},{"family":"Papanna","given":"Ramesha"},{"family":"Bergh","given":"E"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1159/000550538","URL":"https://doi.org/10.1159/000550538","source":"europepmc"},{"id":"oa:W7154498928","type":"article-journal","title":"AI digital-twin ecosystem translating gut-microbiome–neuroimmune signals into precision sleep–mood interventions","abstract":"We present a novel AI-powered \"gut-brain-sleep\" digital-twin nursing ecosystem (G-B-S DT-N) that translates microbiome and neuroimmune signals into precision interventions for sleep and mood disorders. The ecosystem integrates four key layers: Microbiome Dynamics, Neuro-immune Interface, Sleep-Cognition-Emotion Circuits, and Person-Nurse-Environment Triad. These layers leverage multi-omics data, EEG sleep microstructure, real-time sensors, and EMR feeds to create a dynamic, patient-specific architecture. Uncertainty-aware explainable AI (XAI) modules ensure privacy and interpretability, enabling causal inference through advanced machine learning techniques. Adaptive care pathways, including precision pre-/post-biotic delivery and circadian light prescriptions, are optimized via nurse-in-the-loop reinforcement learning. The digital twin is operationalized through a five-step closed-loop workflow in hospital and community settings. Quantum-accelerated simulations and a proposed RCT (D-TWIN-RCT) will assess efficacy compared to standard care. Social, legal, and ethical frameworks protect data sovereignty and autonomy. This ecosystem offers a scalable solution for managing complex comorbidities, positioning nursing as a key driver of microbiome-precision medicine.","author":[{"family":"Yu","given":"Xue"},{"family":"Fan","given":"Ling"},{"family":"Fan","given":"Shiqing"},{"family":"Li","given":"Hui"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fpsyt.2026.1703605","URL":"https://doi.org/10.3389/fpsyt.2026.1703605","source":"europepmc"},{"id":"oa:W4412733428","type":"article-journal","title":"“Twin transition” and HRM practices: empirical evidence from Italian firms","abstract":"The increasing policy emphasis on achieving a joint green and digital transformation – referred to as the ‘twin transition’ is driving techno-organisational change in new directions. This paper examines how firms’ internal organisation of labour in the manufacturing sector influences their ability to innovate in the interconnected green and digital domains. Given the systemic nature of sustainability transitions, its ‘twin’ evolution introduces complexities that extend beyond the challenges posed by decarbonisation and circularity. Empirical results show that organisational changes and human resource practices, alongside technological advancements, play a pivotal role in facilitating this transition.","author":[{"family":"Antonioli","given":"Davide"},{"family":"Ghisetti","given":"Claudia"},{"family":"Mazzanti","given":"Massimiliano"},{"family":"Nicolli","given":"Francesco"},{"family":"Quatrosi","given":"Marco"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/13662716.2025.2516036","URL":"https://doi.org/10.1080/13662716.2025.2516036","source":"openalex"},{"id":"oa:W4412830433","type":"article-journal","title":"Integrated Geomatic Solutions for the Digital Twin of Florence: Protecting the Arno River and its Historic Urban Landscape from Climate Risks","abstract":"Abstract. The interplay between urban environments and waterways is a critical aspect of sustainable city planning, particularly in historic settings vulnerable to climate change. This study presents the Digital City & River Twin (DiC&RT) framework, focusing on the historic urban fabric of Florence and its interaction with the Arno River. Unlike conventional Urban Digital Twins (UDTs), which often address isolated domains, DiC&RT intends to analyse the complex relationship between the river and the historic city by means of integrated geomatic techniques. The project addresses flood risks, structural stability, and environmental dynamics by creating a comprehensive multi-layered model. DiC&RT employs diverse data acquisition techniques, including static and kinematic LiDAR scanning, unmanned aerial and surface vehicles for photogrammetry and bathymetry, and ground-penetrating radar for subsurface analysis. A geodetic control network ensures high-precision data integration, supporting long-term monitoring. The study assesses the effectiveness of these methods in capturing the geometric and environmental characteristics of the riverbanks, bridges, and urban infrastructure. The results demonstrate the necessity of combining multiple surveying technologies to obtain a holistic representation of the study area. By integrating spatial and predictive modeling, DiC&RT enables real-time risk assessment and scenario simulations for climate change adaptation. This framework offers a scalable solution for heritage conservation, risk analysis, and adaptive urban management, potentially serving as a model for other historic cities facing similar challenges.","author":[{"family":"Tucci","given":"Grazia"},{"family":"Fiorini","given":"Lidia"},{"family":"Meucci","given":"Adele"},{"family":"Conti","given":"Alessandro"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/isprs-archives-xlviii-g-2025-1463-2025","URL":"https://doi.org/10.5194/isprs-archives-xlviii-g-2025-1463-2025","source":"openalex"},{"id":"oa:W7131218446","type":"article-journal","title":"Role of Unified Namespace (UNS) and Digital Twins in Predictive and Adaptive Industrial Systems","abstract":"The primary focus of enhancing the efficiency of operations in the Industry 4.0 setting is Predictive and Preventive Maintenance (PPM). The paper introduces a predictive-maintenance system based on the Unified Namespace (UNS), which involves real-time sensor measurements, photogrammetry, and modelling of a digital twin to improve fault prediction and responsiveness to maintenance. This experiment was conducted over six months in a medium-sized discrete electromechanical production plant equipped with motors, Variable Speed Drives (VSDs), robot/cobots, precision grip systems, pipework systems, Magnemotion/linear motor drives, and a CNC machine. The continuous data, such as high-frequency vibration, temperature, current, and pressure, were monitored and analysed with machine-learning models, including support-vector machines, Gradient Boosting, long-short-term memory, and Random Forest, through which temporal degradation can be predicted. UNS architecture integrated all sensor and imaging data into a vendor-neutral data model through OPC UA to help ensure that all experiments could be integrated consistently and be updated in real time to real digital twins. The suggested system correctly identified mechanical and electrical failures and predicted failures before they really took place. Consequently, machine downtime was reduced by 42.25%, and Mean Time to Repair (MTTR) by 36%, compared to the prior six-month baseline period. These improvements were associated with earlier anomaly detection and digital-twin-supported pre-inspection. Overall, the findings indicate that the integration of UNS with multi-modal sensing and digital-twin technologies may enhance predictive maintenance performance in comparable industrial settings. The framework provides a data-driven, scalable solution to organisations that aim to modernise their maintenance processes, attain greater reliability and better equipment utilisation, as well as enhanced Industry 4.0 preparedness.","author":[{"family":"Pillai","given":"Renjith"},{"family":"Oconnell","given":"Eoin"},{"family":"Denny","given":"Patrick"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/machines14020252","URL":"https://doi.org/10.3390/machines14020252","source":"openalex"},{"id":"oa:W4406901176","type":"article-journal","title":"Towards the validation of manufacturing simulations by means of digital twins: conception, implementation and data acquisition for a composite aircraft moveable manufacturing process","abstract":"Abstract Simulations are used in the development of structures. These methods and their results are increasingly applied on the way toward a more analysis-based certification process for aircraft structures. The absolute basis for being considered as an acceptable means of compliance (AMC) with regard to a certification paragraph is the validation of these methods and their respective results using physical test data. This contribution describes the approach of generating this validation data and its provision by means of a digital twin (Digital twin in Definition & value. Technical report, AIAA & AIA, 12 (2020). https://www.aiaa.org/docs/default-source/uploadedfiles/issues-and-advocacy/policy-papers/digital-twin-institute-position-paper-(december-2020).pdf , 2020) of a manufacturing process. The work is performed for the virtual production of the initial virtual product house (VPH) use case, a composite multispar moveable of a long-range reference aircraft configuration. It includes the definition of the desired validation data, modeling of the manufacturing process by means of an extended formalized process description (FPD) based on Verein Deutscher Ingenieure e.V. (VDI/VDE-Richtlinie 3682-Part 1: Formalised process descriptions-concept and graphic representation. Standard. https://www.beuth.de/de/technische-regel/vdi-vde-3682-blatt-1/230173798 , 2015), the choice of required sensors as well as their integration into an existing tooling as well as the structure itself. Furthermore, the realization and data acquisition during the manufacturing process as well as the creation of a digital twin using a data model based on the formalised process are described. Finally, first results for the evaluation of the use case structure are presented. It is shown that is possible to provide a digital twin based on measured sensor data and provide pre-processing capabilities for this raw data to facilitate the validation of manufacturing process simulations. The creation of this digital twin and the overall realization of the manufacturing is greatly facilitated by the use of FPD and a derived digital life data sheet (LDS).","author":[{"family":"Rädel","given":"Martin"},{"family":"Denker","given":"Björn"},{"family":"Kamp","given":"Bram"},{"family":"Liebers","given":"Nico"},{"family":"Prussak","given":"Robert"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s13272-024-00800-3","URL":"https://doi.org/10.1007/s13272-024-00800-3","source":"openalex"},{"id":"oa:W4410309131","type":"article-journal","title":"Impact of digital transformation for sustainable circular economic environments","abstract":"Abstract Digital Transformation is a global phenomenon, capturing the attention in every industry and spurring major investment. However, digital transformation is not a single objective, but a multi-faceted approach depending on specific industrial goals and their digital maturity. Digital transformation is the way of change from a monolithic business approach to fully digitalized business strategies, resulting in digital transformation a key economic objective and a major success factor of a comprehensive corporate transformation. In addition to digital technologies, processes, and procedures, and aside from that also skilled employees required keeping pace in reacting quickly to changes in order to adapt to necessary needs and opportunities in the markets, to drive growth and innovation. In the first of the four industrial evolutions, steam power was a disruptive technology that has changed the working capabilities. In the second it was the assembly line and in the third the computer. Today, in the fourth industrial evolution, everything is digital. Intelligent digital technologies such as Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Big Data and Analytics, Automated Robots, and others are accelerating a profound transformation in the way industries work and do business. However, beside digital transformation a second transformation narrative occur, which refers to the circularity of business models, based on the foundation, that sustainability, and specifically circularity is a path to an environmentally friendly production and profitability. This business model is not yet widespread everywhere, but economic, social, and technological changes are enabling circularity be enticing. Given this fact, circular economy makes sense not only from an environmental perspective, it’s also likely the way forward to the central goal of waste reduction in production, and also initiating a prosperous environmentally friendly business strategy. In this context, digital transformation can enhance circular economy and circular business models tantalizingly as enabler. Doing so, the technologies used beside circularity byproduct design, production, maintainability and for product life extension, are enabled by data streams about condition, location, availability of required resources. Furthermore, digital transformation technologies enable repairability, reusability of materials, recovery and recycling of materials used and others in circular economy. In this sense, the paper introduces the fundamental background of both transformation narratives in detail with their special capabilities, and also explains their pros and cons and potential applications.","author":[{"family":"Möller","given":"Dietmar"},{"family":"Wang","given":"Qichen"},{"family":"Huang","given":"Liangchao"},{"family":"Xiong","given":"Bin"},{"family":"Guo","given":"Yilin"},{"family":"Shi","given":"Tianle"},{"family":"Zhang","given":"Ru"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s44438-025-00001-3","URL":"https://doi.org/10.1007/s44438-025-00001-3","source":"openalex"},{"id":"oa:W4410459541","type":"article-journal","title":"Idealized aortic annuloplasty FSI digital twin of 3D-printed phantoms with 4D-flow MRI comparison","abstract":"BACKGROUND: Aortic annuloplasty, involving the implantation of an external ring around the aortic root to reduce annular dimensions, is a promising treatment for aortic valve insufficiency. However, its hemodynamic effects remain underexplored due to the absence of computational models validated by experimental and clinical data. METHODS: This study introduces a computational fluid-structure interaction (FSI) model of supra valvular aortic annuloplasty using 4D-flow magnetic resonance imaging (MRI). Native and post-annuloplasty conditions of idealized aortic root phantoms, including the aortic valve, were CAD-modelled and 3D-printed with elastic resin. These phantoms were tested in a mock circulatory flow-loop providing normal pulsatile physiologic conditions using a glycerol-water mixture to simulate blood viscosity. Flow and pressure data collected from sensors were used as boundary conditions for FSI simulations. Experimental velocity fields from 4D-flow MRI were compared to computational results to assess model accuracy. RESULTS: MRI scans of the annuloplasty model showed an increased peak systolic velocity (up to 145.4 cm/s) and localized flow alterations, corresponding to a higher pressure gradient across the valve. During regurgitation, the annuloplasty model showed broader velocity distributions compared to the native condition. The FSI simulations closely matched 4D-flow MRI data, with strong correlation coefficients (r > 0.93) and minimal Bland-Altman differences, particularly during systolic phases. CONCLUSIONS: This study establishes an integrative methodology combining in-vitro, in-silico, and clinical imaging techniques to evaluate aortic annuloplasty hemodynamics. The in-vitro validated digital twin framework offers a pathway for patient-specific modelling, enabling prediction of surgical outcomes and optimization of aortic valve repair strategies.","author":[{"family":"Bontempi","given":"Luca"},{"family":"Zattoni","given":"Marta"},{"family":"Ramella","given":"Anna"},{"family":"Migliavacca","given":"Francesco"},{"family":"Ringgaard","given":"Steffen"},{"family":"Kim","given":"Won"},{"family":"Johansen","given":"Peter"},{"family":"Colombo","given":"Monika"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.compbiomed.2025.110398","URL":"https://doi.org/10.1016/j.compbiomed.2025.110398","source":"openalex"},{"id":"oa:W4412631376","type":"article-journal","title":"A Deep Reinforcement Learning-Based Concurrency Control of Federated Digital Twin for Software-Defined Manufacturing Systems","abstract":"Modern manufacturing demands real-time, scalable coordination that legacy manufacturing management systems cannot provide. Digital transformation encompasses the entire manufacturing infrastructure, which can be represented by digital twins for facilitating efficient monitoring, prediction, and optimization of factory operations. A Federated Digital Twin (FDT) emerges by combining heterogeneous digital twins, enabling real-time collaboration, data sharing, and collective decision-making. However, deploying FDTs introduces new concurrency control challenges, such as priority inversion and synchronization failures, which can potentially cause process delays, missed deadlines, and reduced customer satisfaction. Traditional concurrency control approaches in the computing domain, due to their reliance on static priority assignments and centralized control, are inadequate for managing dynamic, real-time conflicts effectively in real production lines. To address these challenges, this study proposes a novel concurrency control framework combining Deep Reinforcement Learning with the Priority Ceiling Protocol. Using SimPy-based discrete-event simulations, which accurately model the asynchronous nature of FDT interactions, the proposed approach adaptively optimizes resource allocation and effectively mitigates priority inversion. The results demonstrate that against the rule-based PCP controller, our hybrid DRLCC enhances completion time maximum of 24.27% to a minimum of 1.51%, urgent-job delay maximum of 6.65% and a minimum of 2.18%, while preserving lower-priority inversions.","author":[{"family":"Anwar","given":"Rubab"},{"family":"Kwon","given":"Jin"},{"family":"Kim","given":"Won"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15158245","URL":"https://doi.org/10.3390/app15158245","source":"openalex"},{"id":"oa:W4406858191","type":"article-journal","title":"Mechanical property strengthening by post-heat treatments in NiTiCu shape memory alloys fabricated by twin-wire arc additive manufacturing","abstract":"To address the challenges of wide transformation hysteresis as well as the poor properties of NiTi-based alloys fabricated by twin-wire arc additive manufacturing, post-heat treatments were employed in as-deposited NiTiCu alloys. After aging at 450°C, 550°C, and 650°C, the alloys exhibited significant reduction in the precipitate sizes, narrow transformation hysteresis, uniform distribution of microhardness, and substantial improvement in mechanical properties. With the increase of the aging temperature, the matrix grain size and the precipitate size coarsened, which was detrimental to the resultant mechanical properties. The alloys aged at 450°C exhibited the narrowest transformation hysteresis of 11.7°C and optimal mechanical properties (tensile strength of 539 MPa and fracture strain of 6.9%). The enhancement of mechanical properties can be attributed to the smaller matrix grain size and precipitate size and the higher proportion of high-angle grain boundaries in this material condition. This work provides practical significance for the twin-wire arc additive manufacturing and performance optimisation of NiTi-based ternary alloys.","author":[{"family":"Chen","given":"Long"},{"family":"Zhao","given":"Miao"},{"family":"Wu","given":"Jiehao"},{"family":"Oliveira","given":"JP"},{"family":"Teshome","given":"Fissha"},{"family":"Pang","given":"Bowen"},{"family":"Shen","given":"Jiajia"},{"family":"Wu","given":"Yiming"},{"family":"Zhou","given":"Naixun"},{"family":"Schell","given":"Norbert"},{"family":"Zeng","given":"Zhi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/17452759.2025.2457579","URL":"https://doi.org/10.1080/17452759.2025.2457579","source":"openalex"},{"id":"oa:W4410478082","type":"article-journal","title":"Advancing cultural heritage: a decadal review of digital transformation in Chinese museums","abstract":"Museum digitization provides feasibility for preserving, displaying, and sharing cultural heritage and increases public engagement and education. This study aims to systematically examine the progress of Chinese museums’ digitization and understand its achievements and limitations in the last decade. To this end, a systematic literature review was conducted in three scientific databases: Web of Science, Scopus, ScienceDirect, and Google Scholar as a supporting database. The sample was selected based on the PRISMA guidelines. The results indicate that the digital reform of Chinese museums includes the digital management system, digitization information collection, online exhibitions, virtual tours, and the application of virtual reality, augmented reality, big data, and artificial intelligence. These technologies offer visitors new and exciting experiences, enrich exhibition forms, and promote public learning. Immersive technologies and interactive experiences are the hot topic of research. Therefore, the effectiveness of museum exhibitions can be improved by encouraging visitor engagement and interaction.","author":[{"family":"Yang","given":"Chunlan"},{"family":"Wook","given":"Tengku"},{"family":"Rosdi","given":"Fadhilah"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s40494-025-01714-x","URL":"https://doi.org/10.1038/s40494-025-01714-x","source":"openalex"},{"id":"oa:W4414109725","type":"article-journal","title":"Digital Twins for Precision Oncology: Modelling Foundations, Clinical Applications, and Open Challenges","abstract":"The field of digital twins (DT) is a rapidly expanding area in healthcare. Although DTs have long been established in engineering and military contexts, their adoption in medicine remains in its infancy. However, in cancer care, DTs have extraordinary potential to revolutionise early disease detection, treatment response prediction, prognostication, decision-making and personalised patient management. In this review, we focus on oncology DTs with emphasis on [a] current applications, [b] identifying key deployment challenges and bottlenecks to clinical adoption, [c] describing available development tools, and [d] discussing ethical considerations. We also chart the growing influence of DTs as a transformative force in personalised cancer care.","author":[{"family":"Alam","given":"Mahmood"},{"family":"Bilal","given":"Muhammad"},{"family":"Ashraf","given":"Shazad"},{"family":"Omar","given":"Nabil"},{"family":"Qadir","given":"Junaid"}],"issued":{"date-parts":[[2025]]},"DOI":"10.22541/au.175753019.93675772/v1","URL":"https://doi.org/10.22541/au.175753019.93675772/v1","source":"openalex"},{"id":"oa:W4409919710","type":"article-journal","title":"Predicting Filter Medium Performances in Chamber Filter Presses with Digital Twins Using Neural Network Technologies","abstract":"Efficient solid–liquid separation is crucial in industries like mining, but traditional chamber filter presses depend heavily on manual monitoring, leading to inefficiencies, downtime, and resource wastage. This paper introduces a machine learning-powered digital twin framework to improve the operational flexibility and predictive control of a traditional chamber filter press. A key challenge addressed is the degradation of the filter medium due to repeated cycles and clogging, which reduces filtration efficiency. To solve this, a neural network-based predictive model was developed to forecast operational parameters, such as pressure and flow rates, under various conditions. This predictive capability allows for optimized filtration cycles, reduced downtime, and improved process efficiency. Additionally, the model predicts the filter medium’s lifespan, aiding in maintenance planning and resource sustainability. The digital twin framework enables seamless data exchange between filter press sensors and the predictive model, ensuring continuous updates to the training data and enhancing accuracy over time. Two neural network architectures, feedforward and recurrent, were evaluated. The recurrent neural network outperformed the feedforward model, demonstrating superior generalization. It achieved a relative L2-norm error of 5% for pressure and 9.3% for flow rate prediction on partially known data. For completely unknown data, the relative errors were 18.4% and 15.4%, respectively. Qualitative analysis showed strong alignment between predicted and measured data, with deviations within a confidence band of 8.2% for pressure and 4.8% for flow rate predictions. This work contributes an accurate predictive model, a new approach to predicting filter medium cycle impacts, and a real-time interface for model updates, ensuring adaptability to changing operational conditions.","author":[{"family":"Teutscher","given":"Dennis"},{"family":"Weber-Carstanjen","given":"Tyll"},{"family":"Simonis","given":"Stephan"},{"family":"Krause","given":"Mathias"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15094933","URL":"https://doi.org/10.3390/app15094933","source":"openalex"},{"id":"doi:10.1038/s41746-026-02402-1","type":"article-journal","title":"Too many bits: tackling the waste epidemic in digital medicine.","abstract":"As digital medicine expands, the growing volume of unused (or underutilized) data are creating a hidden epidemic of technological waste. For example, the concept of a digital twin has gained rapid traction. A virtual replica to mirror an organ, physiological system or a patient to explore predictive simulation, real-time monitoring and/or “what-if” scenarios. Yet, a digital twin generates big data e.g., sensor streams, metadata, audit logs, simulations, and backups. Over time, much of that data may become dormant, but require storage. That is the burden of going digital, invisible waste with the accumulation of unused files, logs, archives, and dormant applications/apps especially in Cloud and institutional infrastructures. The environmental, financial, and operational costs of digital waste are rarely discussed in medicine (or health), yet it matters as data ecosystems scale. In contrast (physical) electronic/e-waste is broadly discussed. Here, we discuss why digital medicine researchers and institutions must take digital waste seriously. We highlight Digital Cleanup Day (21 March 2026) and raise awareness to embed data sustainability metrics into digital medicine.","author":[{"family":"Wall","given":"Conor"},{"family":"Stange","given":"Luke"},{"family":"Solba","given":"Heidi"},{"family":"Gillespie","given":"Brian"},{"family":"Parks","given":"David"},{"family":"Godfrey","given":"Alan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41746-026-02402-1","URL":"https://doi.org/10.1038/s41746-026-02402-1","source":"europepmc"},{"id":"doi:10.1038/s41746-026-02464-1","type":"article-journal","title":"A novel digital twin strategy to examine the implications of randomized clinical trials for real-world populations.","abstract":"Randomized clinical trials (RCTs) guide medical practice; however, their generalizability across populations varies. We developed a statistically informed Generative Adversarial Network model, RCT-Twin-GAN, that leverages relationships between covariates and outcomes to generate a digital twin of an RCT conditioned on covariate distributions from a second patient population. We reproduced the disparate treatment effects of RCTs with similar interventions: the Systolic Blood Pressure Intervention Trial (SPRINT) and the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Blood Pressure Trial. To demonstrate treatment effects of each RCT conditioned on the other RCT population, we evaluated the cardiovascular event-free survival of SPRINT-Twins conditioned on the ACCORD cohort and vice versa. The digital twins demonstrated balanced treatment arms (mean absolute standardized mean difference (MASMD)) of covariates 0.019 (SD 0.018), and the ACCORD-conditioned covariates of the SPRINT-Twins distributed more similarly to ACCORD than SPRINT (MASMD 0.0082 SD 0.016 vs. 0.46 SD 0.20). Notably, SPRINT-conditioned ACCORD-Twins reproduced the non-significant outcome seen in ACCORD (0.88 (0.73-1.06) vs. 0.87 (0.68-1.13)), while ACCORD-conditioned SPRINT-Twins reproduced the significant outcome seen in SPRINT (0.75 (0.64-0.89) vs. 0.79 (0.72-0.86)). Finally, we applied this approach to a real-world population in the electronic health record. RCT-Twin-GAN simulates the translation of RCT-derived treatment effects across patient populations.","author":[{"family":"Thangaraj","given":"Phyllis"},{"family":"Shankar","given":"Sumukh"},{"family":"Huang","given":"Sicong"},{"family":"Nadkarni","given":"Girish"},{"family":"Mortazavi","given":"Bobak"},{"family":"Oikonomou","given":"Evangelos"},{"family":"Khera","given":"Rohan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41746-026-02464-1","URL":"https://doi.org/10.1038/s41746-026-02464-1","source":"europepmc"},{"id":"doi:10.1038/s41746-025-01910-w","type":"article-journal","title":"A scoping review of human digital twins in healthcare applications and usage patterns.","abstract":"Digital twins have become increasingly popular across various industries as dynamic virtual models of physical systems. In healthcare, Human Digital Twins (HDTs) serve as virtual counterparts to patients. According to the National Academies of Sciences, Engineering, and Medicine (NASEM), a digital twin must be personalized, dynamically updated, and have predictive capabilities to-in the context of health care-inform clinical decision-making. This scoping review aims to assess the current state of HDTs in healthcare, examining whether the literature aligns with the NASEM definition and identifying trends. A systematic literature search was conducted, covering articles published from January 2017 to July 2024. Only 18 of the 149 included studies (12.08%) fully met the NASEM digital twin criteria. Digital shadows made up 9.4% of studies, general digital models comprised 10.07%, and virtual patient cohorts were another 10.07%. Only two studies mentioned verification, validation, and uncertainty quantification (VVUQ), a critical NASEM standard for model reliability.","author":[{"family":"Tudor","given":"Brant"},{"family":"Shargo","given":"Ryan"},{"family":"Gray","given":"Geoffrey"},{"family":"Fierstein","given":"Jamie"},{"family":"Kuo","given":"Frederick"},{"family":"Burton","given":"Robert"},{"family":"Johnson","given":"Joyce"},{"family":"Scully","given":"Brandi"},{"family":"Asantekorang","given":"Alfred"},{"family":"Rehman","given":"Mohamed"},{"family":"Ahumada","given":"Luis"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41746-025-01910-w","URL":"https://doi.org/10.1038/s41746-025-01910-w","source":"europepmc"},{"id":"doi:10.5005/jp-journals-10005-3234","type":"article-journal","title":"The New Era of Holistic and Precision Dentistry with Integration of Digital Twin Technology: A Scoping Review.","abstract":"Technology has embraced all sectors of mankind with its trailblazers extending to exponential growth and development at an infinite arena of futuristic advancements. The education system has also undergone a progressive reformation and hyper-realistic transformations by incorporating these technological innovations, thereby creating the concept of education at your pace, possible in the most acceptable manner. However, in developing countries like India, where health care continues to be a booming sector with augmented growth and developments, the inclusion of these technological advancements still remains as an interest of concern and viability. The lack of financial investments, inability to obtain individual patient data and screening records from both urban and rural medical care settings, lack of connectivity with cities and villages within the country, and providential glitches of communication all continue to barrel as a hindrance in incorporating technological progression within one of the highly anticipated sectors of the nation. Digital twin technology is also expected to cater both the health care professionals as well as the patients with an extremely well-defined treatment plan, schedules, and a multitude of options incorporating highly efficient consultants from across the country in a speck of second. Hence, this article will discuss in detail the strategic and sequential advancements that will forefront on the application of the concept of digital twin technology into the Indian health care system, thereby creating a more simplified treatment environment with highly effective disease diagnosis and treatment strategies. How to cite this article: . The New Era of Holistic and Precision Dentistry with Integration of Digital Twin Technology: A Scoping Review. Int J Clin Pediatr Dent 2025;18(8):1046-1050.","author":[{"family":"Thribhuvanan","given":"Lakshmi"},{"family":"Saravanakumar","given":"Ms"},{"family":"Panikkar","given":"Priyanka"},{"family":"Durairaj","given":"Preethi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5005/jp-journals-10005-3234","URL":"https://doi.org/10.5005/jp-journals-10005-3234","source":"europepmc"},{"id":"doi:10.1177/20552076261438961","type":"article-journal","title":"Digital twin applications in adult critical care: A scoping review of current development and implementation trends.","abstract":"Objective: Digital twins (DTs) show promise in critical care by enabling personalised treatment and optimising clinical decision-making. Despite the complexity and data-intensive nature of critical care, the implementation of DTs in this setting remains under-investigated. This scoping review aimed to summarise DT research in critical care and identify current evidence gaps. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines, seven electronic databases were searched. Studies reporting the development or evaluation of DT models in adult critical care were included. Data were extracted on study characteristics and DT development features, including modelling approaches, levels of data integration, and key findings. Results: Twenty-three studies were included, with most originating from North America and Europe. Retrospective designs using hospital datasets derived from intensive care unit and emergency department settings were common. Data integration predominantly corresponded to the digital model level of the DT maturity, whereas fully automated DT implementations were rare. Regarding modelling approaches, mathematical models were most frequently developed, followed by machine learning-based predictive models. DT application primarily focused on predictive modelling and virtual patient simulations to enhance personalised treatment, support clinical decision-making, and optimise organisational resource allocation. Conclusion: DT technologies in critical care remain in the exploratory and early stages of development and implementation. Further research incorporating higher levels of data integration, real-time deployment, and longitudinal external validation is warranted, alongside broader consensus on ethical governance and data privacy.","author":[{"family":"Kim","given":"Yeonwoo"},{"family":"Kim","given":"Jiin"},{"family":"Kim","given":"Yeonju"},{"family":"Choi","given":"Mona"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1177/20552076261438961","URL":"https://doi.org/10.1177/20552076261438961","source":"europepmc"},{"id":"doi:10.1038/s41746-025-02283-w","type":"article-journal","title":"Enhancing telesurgical safety with predictive digital twin synchronization: a framework for latency compensation in robotic surgery.","abstract":"This study addresses the critical challenge of master-slave latency in robot-assisted telesurgery by introducing a Digital Twin Visual Assistance (DTVA) system. DTVA integrates parametric 3D modeling and virtual endoscopic visualization within a tri-layered architecture to enable real-time bidirectional synchronization. The system was evaluated on a geographically distributed robotic platform using programmable latency emulation. Results demonstrated that DTVA maintained spatial precision within 2 mm error under typical conditions and reduced peg-transfer completion time by 13.6% under 900 ms communication latency while lowering operator workload by 27.2%. Clinical validation through teleoperated radical nephrectomy under 300 ms communication latency confirmed feasibility, with all procedures completed successfully without complications and favorable perioperative outcomes. The study establishes DTVA's capacity to mitigate latency effects and demonstrates preliminary clinical feasibility for telesurgical procedures.","author":[{"family":"Yuan","given":"Hang"},{"family":"Li","given":"Junjie"},{"family":"Guan","given":"Bo"},{"family":"Chu","given":"Guangdi"},{"family":"Jiao","given":"Wei"},{"family":"Zheng","given":"Hongzhi"},{"family":"Liu","given":"Xingchi"},{"family":"Zhao","given":"Jianchang"},{"family":"Li","given":"Jianmin"},{"family":"Li","given":"Jinhua"},{"family":"Yang","given":"Xuecheng"},{"family":"Niu","given":"Haitao"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41746-025-02283-w","URL":"https://doi.org/10.1038/s41746-025-02283-w","source":"europepmc"},{"id":"oa:W4412602550","type":"article-journal","title":"Integrating Digital Twin and BIM for Special-Length-Based Rebar Layout Optimization in Reinforced Concrete Construction","abstract":"The integration of Building Information Modeling (BIM) and Digital Twin (DT) technologies offers new opportunities for enhancing reinforcement design and on-site constructability. This study addresses a current gap in DT applications by introducing an intelligent framework that simultaneously automates rebar layout generation and reduces rebar cutting waste (RCW), two challenges often overlooked during the construction execution phase. The system employs heuristic algorithms to generate constructability-aware rebar configurations and leverages Industry Foundation Classes (IFC) schema-based data models for interoperability. The framework is implemented using Autodesk Revit and Dynamo for rebar modeling and layout generation, Microsoft Project for schedule integration, and Autodesk Navisworks for clash detection. Real-time scheduling synchronization is achieved through IFC schema-based BIM models linked to construction timelines, while embedded clash detection and constructability feedback loops allow for iterative refinement and improved installation feasibility. A case study on a high-rise commercial building demonstrates substantial material savings, improved constructability, and reduced layout time, validating the practical advantages of BIM–DT integration for RC construction.","author":[{"family":"Widjaja","given":"Daniel"},{"family":"Lim","given":"Jeeyoung"},{"family":"Kim","given":"Sunkuk"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15152617","URL":"https://doi.org/10.3390/buildings15152617","source":"openalex"},{"id":"oa:W4409446562","type":"article-journal","title":"Smart Government Initiatives: Transforming Global Supply Chains through Digital Change","abstract":"This empirical research aims to explore the effects of smart government initiatives on the global supply chain to evaluate the pharmaceutical manufacturing industry in the UAE. Through the synthesis of information collected from this sector’s stakeholders, the research reveals how digital innovation, spurred by smart initiatives initiated by the government, acts as a mediator between supply chain efficiency and effectiveness. The research also shows strategies which encompasses data analytics, IoT and blockchain revolutionise and transform the supply chain by increasing its transparency, responsiveness and flexibility. These digital changes, which have been supported by government policies, not only enhance efficiency, but also help improve coordination between supply chain members and optimize performance indicators internationally. The research findings presented here are relevant to policymakers and leaders of industries to design great technologies for supply chain improvements. Therefore, the study has implications that make it necessary for government agencies to develop effective strategies and policies that support smart causes meant for enhancing digital integration in the sectors. Overall, the study for the pharmaceutical manufacturers indicates that the willingness to adopt digital change supported by governmental frameworks leads to significant improvements of the supply chain performance regarding lead time as well as reliability. In addition, these advancements can contribute toward global competitiveness through the superior management of supply networks especially for global supply chains and reducing risks of supply chain disruptions.","author":[{"family":"Alzoubi","given":"Haitham"},{"family":"Tan","given":"Cheng"},{"family":"Khatib","given":"Mounir"},{"family":"Alshurideh","given":"Muhammad"},{"family":"Shwedeh","given":"Fanar"},{"family":"Ramakrishna","given":"Y"},{"family":"Lee","given":"Khai"}],"issued":{"date-parts":[[2025]]},"DOI":"10.32479/irmm.18962","URL":"https://doi.org/10.32479/irmm.18962","source":"openalex"},{"id":"oa:W7155408699","type":"article-journal","title":"Greenhouse gas accounting in urban digital twins","abstract":"Abstract As current efforts remain insufficient to limit global warming to 1.5 °C, increasing expectations are placed on emerging technologies such as urban and national digital twins (DTs). Their number and spatial coverage are rapidly expanding, alongside a growing diversity of exploratory use cases. While the literature highlights their potential across multiple domains, a knowledge gap persists regarding their methodological application to subnational spatial greenhouse gas accounting, a key evidence base for local climate action. This study applies a multi-method approach to examine how frontrunner cities utilise DTs in greenhouse gas inventories and to assess their potential for spatial subnational greenhouse gas accounting. Interview findings indicate that greenhouse gas inventories and urban DT initiatives are largely pursued as disconnected efforts within cities. Five case studies demonstrate significant untapped potential beyond current inventory practices. DTs can help address limitations and biases in existing approaches by providing complementary insights into local emission patterns across regions, cities, and rural municipalities. Realising this potential requires systematic metadata attribution to distinguish between various emissions allocation principles, enabling georeferenced, disaggregated calculations and spatiotemporal representation of results. These methodological advances substantially enhance the interpretability, transparency, and policy relevance of subnational greenhouse gas inventories.","author":[{"family":"Lylykangas","given":"Kimmo"},{"family":"Dembski","given":"Fabian"},{"family":"Joutsiniemi","given":"Anssi"},{"family":"Heinonen","given":"Jukka"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1088/2634-4505/ae5a57","URL":"https://doi.org/10.1088/2634-4505/ae5a57","source":"openalex"},{"id":"oa:W4407404847","type":"article-journal","title":"Security and Privacy in Physical–Digital Environments: Trends and Opportunities","abstract":"Over recent decades, internet-based communication has grown exponentially, accompanied by a surge in cyber threats from malicious actors targeting users and organizations, heightening the demand for robust security and privacy measures. With the emergence of physical–digital environments based on Mixed Reality (MR) and the Metaverse, new cybersecurity, privacy, and confidentiality challenges have surfaced, requiring innovative approaches. This work examines the current landscape of cybersecurity concerns in MR and Metaverse environments, focusing on their unique vulnerabilities and the risks posed to users and their data. Key challenges include authentication issues, data breaches, and risks to user anonymity. The work also explores advancements in secure design frameworks, encryption techniques, and regulatory approaches to safeguard these technologies. Additionally, it identifies opportunities for further research and innovation to strengthen data protection and ensure a safe, trustworthy experience in these environments.","author":[{"family":"Pereira","given":"Carolina"},{"family":"Marto","given":"Anabela"},{"family":"Ribeiro","given":"Roberto"},{"family":"Gonçalves","given":"Alexandrino"},{"family":"Rodrigues","given":"Nuno"},{"family":"Rabadão","given":"Carlos"},{"family":"Costa","given":"Rogério"},{"family":"Santos","given":"Leonel"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/fi17020083","URL":"https://doi.org/10.3390/fi17020083","source":"openalex"},{"id":"oa:W7134232795","type":"article-journal","title":"Logistics equipment condition monitoring and prediction based on digital twin and machine learning","abstract":"The use of digital twins is becoming a foundation for automation that will improve how industries handle and organize data about both virtual and physical things. It enables analyzing industrial data more seamlessly by merging the Internet of Things (IoT) with Artificial Intelligence (AI) to make sense of it. The growth of online retailers has made it harder for logistics professionals to keep people safe, make sure products are of superior quality, and run smoothly. The most recent advancements of digital twin (DT) have made it easier to create predictive maintenance. Using DT makes it easier to accurately assess equipment status and detect problems before they occur, thereby making the system more reliable. This shift from reactive to preventive operations makes maintenance plans more efficient, reduces disruptions, and boosts the company's profits and competitive advantage. Nevertheless, the research and implementation of Digital Twin (DT) for Predictive Maintenance remains developing, likely due to the incomplete exploration of the function and significance of machine learning (ML) within this context by academics and industry alike. In this paper, a digital twin solution in which the logistics equipment is monitored and continuously maintained through the application of ML algorithms in an IOT environment is proposed. The logistics 2.0-enabled system generates virtual replicas of physical logistics assets, such as forklifts, conveyor belts, automated guided vehicles, cranes, and warehousing robotic, and the digital twins are synchronized in real-time via IoT sensor networks. For anomaly detection, Remaining Unit Life (RUL) prediction, and failure classification, this study utilized Isolation Forest (iForest), Autoencoders, Long Short-Term Memory (LSTM) networks, and Random Forest (RF) machine learning models. The architecture consists of three layers, each of which is connected to the other named the physical layer, including heterogeneous IoT sensors (vibration, temperature, acoustic, and current/voltage, GPS, and load sensors); the digital twin layer, enabling real-time synchronization and simulation; and the ML layer running predictive maintenance and optimization models. Results from the application of the proposed system show a 30-50% reduction in the equipment downtime, 20-40% diminishment in the maintenance cost, longer lifespan for the equipment, and better operational safety.","author":[{"family":"Han","given":"Fang"},{"family":"Liu","given":"Lijun"},{"family":"Sun","given":"Junyan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41598-026-43380-4","URL":"https://doi.org/10.1038/s41598-026-43380-4","source":"europepmc"},{"id":"oa:W4409378177","type":"article-journal","title":"Land surface temperature, tropospheric and ionospheric anomalies analysis and implementation of a co-seismic PWV digital twin for the February 6, 2023 Turkey earthquake","abstract":"A dual powerful earthquake hit Turkey on 6 February 2023 with a magnitude of 7.8. A preliminary geophysical analysis of land surface temperature (LST), tropospheric and ionospheric parameters was carried out. Precipitable water vapor (PWV), derived from Global Navigation Satellite System (GNSS) data, increased significantly and peaked over the stations when the earthquake burst. Moreover, total electron content (TEC) surge occurred, with a travelling ionospheric disturbance (TID) spreading from the northeast to the southwest in the south. LST observations from two-temporal scales indicates that a precursory thermal anomaly occurred 3 weeks in advance, and a low-temperature condition during the earthquake. For the period 18–24 January, LST was more than 10 °C higher than that of the past 10 years in the same period. However, a significant low-LST was observed on the days of mainshock from 4–6 February, with the anomaly index at the epicenter being −1.66, −1.82, and −1.80 with descending range of −8.66 °C, −10.05 °C and −9.27 °C, respectively. In terms of algorithms, we introduced different features to construct a digital twin to predict the PWV for 2023 Turkey earthquake, yielding a root mean square error (RMSE) averaging 4.60 mm when compared to GNSS-PWV.","author":[{"family":"Guo","given":"Ao"},{"family":"Jiang","given":"Nan"},{"family":"Xu","given":"Yan"},{"family":"Liu","given":"Tong"},{"family":"Xu","given":"Tianhe"},{"family":"Bastos","given":"Luísa"},{"family":"Li","given":"Zeqi"},{"family":"Jia","given":"Ranran"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/19475705.2025.2491470","URL":"https://doi.org/10.1080/19475705.2025.2491470","source":"openalex"},{"id":"oa:W4407410928","type":"article-journal","title":"Digital Synergy and Strategic Vision: Unlocking Sustainability-Oriented Innovation in Saudi SMEs","abstract":"This research examines the proposition that enhancing sustainable innovation can be particularly effective when the focus is on strategy, machine learning, and digitalization. The study specifically targets the complex interactions among strategic alignment (SA), sustainability-oriented innovation (SOI), and digital transformation (DT) within small and medium-sized enterprises (SMEs) in Saudi Arabia, particularly within the service sector. A moderated mediation framework was constructed to analyze the influence of SA on SOI, the mediating role of DT, and the moderating effect of strategic orientation (SO). Data were collected through structured surveys from 339 SMEs using a quantitative research design and a cross-sectional methodology. The partial least squares structural equation modeling (PLS-SEM) technique was employed to validate the proposed framework and hypotheses. The results indicate that SA significantly boosts SOI, with DT acting as a strong mediator in this connection. Furthermore, SO moderates the relationships between SA and SOI, SA and DT, and DT and SOI, highlighting its essential role in shaping the dynamics of sustainable innovation. These findings emphasize the necessity of aligning strategic initiatives with digital advancements to foster innovation that achieves a balance among economic, social, and environmental objectives. This study contributes to existing literature by filling the research gap regarding SOI and DT in Saudi SMEs and offers practical insights for SMEs facing sustainability challenges. Future research should delve deeper into digital technology configurations, industry-specific contexts, and cross-national applications to improve the applicability of these findings.","author":[{"family":"Zaki","given":"Karam"},{"family":"Alhomaid","given":"Abrar"},{"family":"Ghareb","given":"Ashraf"},{"family":"Shared","given":"Hany"},{"family":"Rasian","given":"Alaa"},{"family":"Khalifa","given":"Gamal"},{"family":"Elnagar","given":"Ahmed"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/admsci15020059","URL":"https://doi.org/10.3390/admsci15020059","source":"openalex"},{"id":"oa:W4416143793","type":"article-journal","title":"Machine learning and digital twins in smart irrigation: optimising water use through agricultural data analytics","abstract":"Efficient water use in agriculture is increasingly critical amid intensifying water scarcity and climate variability. This review synthesises current research on the integration of machine learning (ML) and digital twin (DT) technologies in smart irrigation systems to enhance water-use efficiency and agricultural sustainability. It categorises key data inputs for ML-driven irrigation such as soil properties, weather and climate variables, crop characteristics, remote sensing and GIS data, and IoT-based sensor systems, and discusses their roles in training predictive models. The review compares supervised, deep learning, reinforcement learning, and unsupervised ML models in terms of their applicability, data requirements, and decision-making capabilities in irrigation scheduling and control. It highlights the importance of data preprocessing, feature selection, and data fusion techniques in improving model performance and adaptability. Moreover, the paper explores how digital twins extend the utility of ML through real-time monitoring, scenario simulation, and feedback-based automation. Practical case studies illustrate the potential of ML-DT integration, while challenges such as data accessibility, infrastructure gaps, and ethical concerns are critically assessed. The review concludes by outlining design strategies for modular, scalable smart irrigation architectures suited to smallholder and resource-constrained farming contexts, particularly in Southeast Asia.","author":[{"family":"Bautista","given":"Christian"},{"family":"Gallegos","given":"Ralph"},{"family":"Lampayan","given":"Rubenito"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/27525783.2025.2562418","URL":"https://doi.org/10.1080/27525783.2025.2562418","source":"openalex"},{"id":"oa:W4411062797","type":"article-journal","title":"Advancing digital innovation in the AEC industry: A bibliometric analysis on the BIM, AI and IoT integration","abstract":"Abstract Recently digitalization is reshaping the Architecture, Engineering, and Construction (AEC) industry, especially through the integration of Building Information Modeling (BIM) with emerging technologies, notably the Internet of Things (IoT), and Artificial Intelligence (AI). Previous research highlights the transformative benefits of these advancements, by enabling efficient data sharing, fostering effective collaboration, enhancing visualization, and improving productivity and safety. However, the fusion of BIM with IoT, and AI remains in its infancy. This research endeavors to take into account this gap by conducting a bibliometric analysis to map key themes, identify emerging trends, and pinpoint gaps among current scholarly findings, using VOSviewer and a dataset of 122 academic articles, spanning the years 2019 to 2024, sourced from the Scopus database. Findings reveal the increasing adoption of BIM as a backbone for data exchange, IoT to capture real-time data and AI for predictive analysis and automation. Technologies such as digital twins, blockchain, and machine learning are identified as significant yet underexplored areas, offering new opportunities for innovation. Challenges such as interoperability and the integration of sustainability principles persist, indicating directions for future research. This study lays a solid groundwork for both researchers and practitioners aiming to navigate and leverage the dynamic advancements in BIM, AI, and IoT within the AEC industry.","author":[{"family":"Ouchtout","given":"Widad"},{"family":"Zaki","given":"Smail"},{"family":"Gartoumi","given":"Khalil"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1088/1755-1315/1499/1/012010","URL":"https://doi.org/10.1088/1755-1315/1499/1/012010","source":"openalex"},{"id":"oa:W4410508627","type":"article-journal","title":"Transforming engineering education in the digital era: findings from a systematic review","abstract":"Introduction According to the Digital Curricula Report on the status of online learning in higher education in the United States, about one-third of higher education is online, a number that has substantially increased after the pandemic (Analytics, 2022). As of October 1, 2024, the Accreditation Board for Engineering and Technology (ABET) has accredited 3,611 programs across 702 institutions in the United States, but only 46 institutions offered 100% online programs, which is significantly lower than other fields. This study aims to explore the factors that influence the acceptance of online learning and teaching in engineering education from the perspectives of students and teachers after the COVID-19 pandemic. Methods This study followed the PRISMA guidelines and included only peer-reviewed articles published between 2020 and 2024, focusing on online engineering education. This systematic review explored the variables affecting student and teacher acceptance of online learning in order to more clearly define challenges in delivering online engineering education and to identify avenues to improve and strengthen it. The inclusion criteria focused on articles addressing instructional design and learning experiences in online education, while the exclusion criteria eliminated studies without key data and those outside the specified timeframe. Discussion The findings of this systematic review highlighted several factors influencing the acceptance of online engineering education, such as technology design, individual characteristics, and social factors. These factors are important for creating effective, engaging, and accessible learning environments that enhance student performance and satisfaction. Further research is needed to develop an approach to examine factor interactions in different contexts, and create a framework aligned with ABET accreditation standards for assessing long-term learning outcomes.","author":[{"family":"Hsu","given":"Yu"},{"family":"Chiang","given":"Danielle"},{"family":"Kehinde","given":"Ifedayo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/feduc.2025.1568917","URL":"https://doi.org/10.3389/feduc.2025.1568917","source":"openalex"},{"id":"oa:W4415817927","type":"article-journal","title":"Toward demographic robustness in digital patient twins: Addressing the gender data gap","abstract":"In this opinion piece, we argue that sex- and gender-based equity must become a foundational criterion in the design and implementation of digital patient twins. Digital patient twins offer a promising avenue for precision medicine by simulating individual health states and treatment responses. However, their clinical utility and fairness depend on whether diverse patient populations are adequately represented and accounted for in the data and devices on which these models are built. Drawing on evidence from cardiology, endocrinology, mental health, and medical device research, this article shows how current digital patient twin initiatives often overrepresent male, white, and socioeconomically privileged populations, while women, gender-diverse individuals, and people of color remain underrepresented. These imbalances can lead to systematic misdiagnoses, misinterpretation of physiological variation, and measurement inaccuracies. Documented examples include under-recognition of heart failure with preserved ejection fraction in women, omission of menstrual cycle-related changes in glycemic control, underdiagnosis of depression in women by speech-based AI models, and oxygen saturation overestimation in patients with darker skin tones. We argue that these disparities are rooted in structural biases in clinical research and are perpetuated when sex- and gender-specific variables, intersectional factors, and subgroup validation are absent from model design. Addressing these limitations requires balanced data representation, integration of sex- and gender-informed knowledge, participatory design with diverse patient groups, subgroup performance testing, transparent reporting, and mitigation of device-related bias. We contend that these are not optional refinements but prerequisites for realizing the promise of personalized care without reproducing or deepening existing health inequities.","author":[{"family":"Mahr","given":"Dana"},{"family":"Hebich","given":"Meike"},{"family":"Weinberger","given":"Nora"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1177/20552076251386660","URL":"https://doi.org/10.1177/20552076251386660","source":"openalex"},{"id":"oa:W7130945332","type":"article-journal","title":"Digitalisation of Shipyard Production Planning: A Review of Simulation, Optimisation, AI, and Digital Twin Methods (2010–2025)","abstract":"Digitalisation is reshaping shipyard production, yet its methodological foundations remain fragmented across simulation, optimisation, Artificial Intelligence (AI), and Digital Twin (DT) research streams. This paper presents a domain-specific methodological review of shipyard production modelling from 2010 to 2025, synthesising advances in Discrete-Event Simulation (DES), multi-objective optimisation, hybrid simulation–optimisation architectures, Machine Learning (ML), reinforcement learning (RL), and DT-enabled cyber-physical systems. Using an explicit evaluative framework based on integration depth, validation basis, and decision scope, the review differentiates between analytically mature but execution-decoupled DES/optimisation approaches and integration-rich yet variably validated DT and AI-driven systems. The analysis shows that hybrid DES-optimisation frameworks currently represent the most operationally credible class of methods, delivering measurable production improvements under structured conditions, whereas many DT and AI contributions prioritise architectural integration and data synchronisation over longitudinal yard-wide KPI validation. A comparative assessment of simulation platforms, optimisation engines, and manufacturing execution system/enterprise resource planning/product lifecycle management infrastructures highlights the central role of structured product–process–resource data and execution-layer connectivity, while severe confidentiality constraints and the scarcity of openly available industrial datasets continue to limit reproducibility and benchmarking. Overall, shipyard production research is progressing toward increasingly integrated and cyber-physical systems, but sustained yard-scale validation and shared benchmark development remain critical prerequisites for translating architectural sophistication into demonstrable operational impact.","author":[{"family":"Bordbar","given":"Amir"},{"family":"Tadros","given":"Mina"},{"family":"Nazemian","given":"Amin"},{"family":"Aung","given":"Myo"},{"family":"Γεωργούλας","given":"Κωνσταντίνος"},{"family":"Louvros","given":"Panagiotis"},{"family":"Boulougouris","given":"Evangelos"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/jmse14040396","URL":"https://doi.org/10.3390/jmse14040396","source":"openalex"},{"id":"oa:W4412796633","type":"article-journal","title":"Methodology and pilot implementation of modular educational-development platform for Interoperable Digital Twin","abstract":"The development of Industry 4.0, especially in the areas of interoperability and the design, implementation and use of digital twins (DT), has been enormous in recent years. This article discusses three key aspects that Industry 4.0 brings with it - virtualization through digital twins, interoperability based on the OPC UA standard, and the use of Industry 4.0's Components - combining assets of physical production line and their Asset Administration Shells (AAS). For development and education, a methodology for an Education and Development Platform (EDP) of Interoperable Digital Twins (I-DT) has been prepared, which conveniently combines these key attributes of Industry 4.0 into a single entity. According to the proposed methodology, the pilot implementation of platform was prepared and tested on industrial technologies. The I-DT platform uses open and affordable technologies, fulfils Industry 4.0 attributes such as interoperability, virtualization, reconfigurability and modularity.","author":[{"family":"Pajpach","given":"Martin"},{"family":"Pribiš","given":"Rudolf"},{"family":"Drahoš","given":"Peter"},{"family":"Kučera","given":"Erik"},{"family":"Haffner","given":"Oto"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-13579-y","URL":"https://doi.org/10.1038/s41598-025-13579-y","source":"europepmc"},{"id":"oa:W4406804796","type":"article-journal","title":"Innovations in Digital Health From a Global Perspective: Proceedings of PRC‐HI 2024","abstract":"The rapid evolution of digital health technologies has sparked transformative changes across the healthcare landscape. These advancements were at the heart of discussions during the recent academic conference co-organized by The First Affiliated Hospital, Sun Yat-sen University (FAH-SYSU) and University of California at Berkeley, the Pacific-Rim Conference on Healthcare Innovation (PRC-HI 2024), convening under the theme “The Future of Medicine: Integrating Robotics, AI and Healthcare.” This article distills the key developments and their implications for the future of healthcare, focusing on innovations in robotic surgery, health data science, and AI for medicine. Robotic surgery has become a cornerstone of modern surgical practices, offering enhanced precision, reduced recovery times, and lower complication rates. Dr. Xiaoyu Yin detailed advancements in robot-assisted pancreatic surgeries at FAH-SYSU, emphasizing the hospital's extensive experience with the Da Vinci surgical system. Since 2015, Dr. Yin has performed over 1000 robotic surgeries, including nearly 700 pancreatic resections. These procedures included advanced techniques such as robot-assisted Whipple procedures, organ-preserving pancreatectomies, and total pancreatectomies. His presentation highlighted the learning curves associated with these complex procedures, showcasing research on iterative improvements in surgical outcomes through case refinement and skill enhancement [1, 2]. Similarly, Dr. Junhang Luo presented a novel “gradual renal segmental artery off-clamping” technique for treating large renal tumors. By utilizing preoperative computed tomography (CT) reconstructions, the technique identifies renal arterial branches, allowing surgeons to precisely minimize ischemia to healthy tissue while ensuring effective tumor removal. Clinical data revealed significantly shorter ischemia times, reduced blood loss, and improved long-term renal function compared to traditional methods. Dr. Qingbo Huang shared groundbreaking work on robotic telesurgery, particularly focusing on its applications in regions with limited medical resources. Through successful demonstrations of remote surgeries between Beijing and distant locations such as Sanya, Dr. Huang's research highlighted how low-latency communication networks and advanced robotic systems can overcome geographical barriers [3]. Dr. Chao Cheng discussed the application of robotic surgery in thoracic procedures, particularly for lung cancer and large thymoma. His presentation highlighted how robotic systems enhance surgical precision and reduce recovery times, with notable success in segmentectomies and thymectomies [4]. The integration of 3D visualization and enhanced dexterity offered by robotic systems has transformed the management of challenging thoracic cases [5, 6]. Dr. Peter Nyirady presented on the potential of robotic surgery in addressing global surgical disparities. Highlighting the contributions of Semmelweis University, his team demonstrated how robotic systems have enhanced outcomes in urological surgeries. He also discussed future directions, such as semi-autonomous surgical systems, and the importance of training programs to keep pace with these advancements. Dr. Chris Fitzpatrick elaborated on the use of AI and data analytics in optimizing robotic surgical practices. Through platforms such as Case Insights, his research highlighted how analyzing surgical video data and performance metrics can identify skill gaps and provide actionable feedback for surgeons [7-10]. This approach has the potential to standardize training and improve surgical outcomes globally. Dr. Veronica Ahumada-Newhart introduced the potential of telepresence robots in improving social inclusion for children with mobility impairments. Her studies revealed that these robots enable remote participation in classroom activities, such as attending lessons and engaging in physical education, reducing feelings of isolation and fostering ","author":[{"family":"Feng","given":"Xiaoru"},{"family":"Sun","given":"Yu"},{"family":"Wu","given":"You"},{"family":"Wu","given":"You"},{"family":"Wang","given":"Haibo"},{"family":"Wu","given":"Yang"},{"family":"Wu","given":"Yang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/hcs2.128","URL":"https://doi.org/10.1002/hcs2.128","source":"openalex"},{"id":"oa:W4411472827","type":"article-journal","title":"Building Sustainable Cities and Communities: Contribution of Digital Twins to a Sustainable Built Environment","abstract":"The widespread adoption of Digital Twins in the Architecture, Engineering, Construction, and Operation (AECO) industry is transforming project dynamics across multiple phases. Digital Twins promises to optimize workflows, enhance process control, and elevate overall project quality throughout the project lifecycle. Despite the immediate benefits observed, the enduring correlation between Digital Twins and fostering a sustainable built environment requires more in-depth exploration. This paper investigates the pivotal role of Digital Twins in advancing the United Nations Sustainable Development Goal (SDG) number 11, which centers on sustainable cities and communities. Drawing on insights extracted from the existing research, a systematic literature review of published scientific research forms the foundation of this study. A bibliometric analysis is conducted, mapping the current landscape of Digital Twins implementations. Four key themes of the contribution of Digital Twins to sustainable cities and communities emerged from this analysis: energy efficiency, urban mobility, resilience, and urban planning. The main findings shed light on the prevailing research trends, identify key themes, and pinpoint existing gaps in the domain. By unraveling the relationship between Digital Twins and sustainable urban development, this research seeks to inform future strategies and innovations in the AECO industry, fostering environmentally conscious practices. Ultimately, this study contributes valuable insights to the ongoing discourse on integrating Digital Twins to pursue sustainable cities and communities.","author":[{"family":"Ayoubi","given":"Ahmad"},{"family":"Ammar","given":"Ashtarout"},{"family":"Abou-Ibrahim","given":"Hisham"}],"issued":{"date-parts":[[2025]]},"DOI":"10.7771/3067-4883.2006","URL":"https://doi.org/10.7771/3067-4883.2006","source":"openalex"},{"id":"oa:W4415719731","type":"article-journal","title":"A Semantic Digital Twin-Driven Framework for Multi-Source Data Integration in Forest Fire Prediction and Response","abstract":"Forest fires have become increasingly frequent and severe due to climate change and intensified human activities, posing critical challenges to ecological security and emergency management. Despite the availability of abundant environmental, spatial, and operational data, these resources remain fragmented and heterogeneous, limiting the efficiency and accuracy of fire prediction and response. To address this challenge, this study proposes a Semantic Digital Twin-Driven Framework for integrating multi-source data and supporting forest fire prediction and response. The framework constructs a multi-ontology network that combines the Semantic Sensor Network (SSN) and Sensor, Observation, Sample, and Actuator (SOSA) ontologies for sensor and observation data, the GeoSPARQL ontology for geospatial representation, and two domain-specific ontologies for fire prevention and emergency response. Through systematic data mapping, instantiation, and rule-based reasoning, heterogeneous information is transformed into an interconnected knowledge graph. The framework supports both semantic querying (SPARQL) and rule-based reasoning (SWRL) to enable early risk alerts, resource allocation suggestions, and knowledge-based decision support. A case study in Sichuan Province demonstrates the framework’s effectiveness in integrating historical and live data streams, achieving consistent reasoning outcomes aligned with expert assessments, and improving decision timeliness by enhancing data interoperability and inference efficiency. This research contributes a foundational step toward building intelligent, interoperable, and reasoning-enabled digital forest systems for sustainable fire management and ecological resilience.","author":[{"family":"Dao","given":"Jicao"},{"family":"Huang","given":"Yijing"},{"family":"Ju","given":"Xiaoyu"},{"family":"Yang","given":"Lizhong"},{"family":"Yang","given":"Xinlin"},{"family":"Liao","given":"Xiang"},{"family":"Wang","given":"Zhenjia"},{"family":"Ding","given":"Dapeng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/f16111661","URL":"https://doi.org/10.3390/f16111661","source":"openalex"},{"id":"oa:W4409247407","type":"article-journal","title":"Digital twins for asset management: case study of snow galleries in Northern Sweden","abstract":"The use of digital twin (DT) technology within the engineering and construction (E&C) industry is valuable for practical applications in asset management of structures. Functional DT in E&C, however, are still in initial stages of development. Efforts toward standardisation of concepts and procedures are necessary to build on existing knowledge and drive progress further on functional DT. This paper proposes a DT of a snow gallery, part of the Iron Ore railway in northern Sweden. The gallery was instrumented with a structural health monitoring (SHM) system that feeds data in real time to the DT, which also includes a 3D model of the gallery. The proposed methodology can be replicated to different structures and scaled for larger amounts of data. The SHM data and the 3D digital model of the snow gallery are connected in a single, integrated platform that enables improved decision-making for maintenance of the gallery. To promote clarity and progress within the field, the proposed DT’s maturity level is classified in terms of autonomy, intelligence, learning and fidelity. The snow galleries, the SHM system, and the proposed DT are all presented and discussed, following a brief review on DT, the importance of level classification and predictive maintenance.","author":[{"family":"Bello","given":"Vanessa"},{"family":"Eliasson","given":"Jens"},{"family":"Dăescu","given":"Cosmin"},{"family":"Gonzalezlibreros","given":"Jaime"},{"family":"Popescu","given":"Cosmin"},{"family":"Blanksvärd","given":"Thomas"},{"family":"Täljsten","given":"Björn"},{"family":"Sas","given":"Gabriel"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/15732479.2025.2483913","URL":"https://doi.org/10.1080/15732479.2025.2483913","source":"openalex"},{"id":"oa:W4410948478","type":"article-journal","title":"The Impact of Supply Chain Digitalization on Firms' Performance: An Empirical Test of How Resource Specificity Explains the Digitalization Paradox","abstract":"ABSTRACT Digitalization is a key driver of supply chain innovation. Existing literature has predominantly focused on the potential positive impacts of supply chain digitalization (SCD) on supply chain performance. However, the paradoxical effects of SCD on overall corporate performance have received limited attention. This study addresses this gap by employing paradox theory to analyze the paradoxical relationship between old specific resources and new specific resources brought by SCD. Econometric methods, panel data from 1440 Chinese listed companies, as well as a text mining approach are used to evaluate the impacts of SCD. This study finds that SCD generates dual effects on enterprises due to resource specificity. Aligning with the majority of existing research, this study confirms the positive impacts of SCD on supply chain capabilities. However, SCD also leads to resource redundancy within firms. The dynamic analysis further reveals that the overall impact of SCD on firm performance is initially nonsignificant but becomes positive over time. The distinctiveness of this study lies in its all‐encompassing approach to the effects of SCD by offering a paradoxical perspective. This study adds insights to supply chain literature and provides new explanations to the “digitalization paradox”. This study also has important practical implications for enterprises.","author":[{"family":"Wu","given":"Yongqiu"},{"family":"Wang","given":"Jie"},{"family":"Xia","given":"Senmao"},{"family":"He","given":"Qile"},{"family":"Zhang","given":"Qingcui"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1111/jbl.70023","URL":"https://doi.org/10.1111/jbl.70023","source":"openalex"},{"id":"oa:W7134052902","type":"article-journal","title":"Digital twin-based multi-view energy efficiency prediction for machining systems","abstract":"Energy efficiency prediction (EEP) of machining systems is essential for energy management and planning. However, the structural complexity and coupled energy consumption across hierarchical levels of machining systems present major challenges for EEP. Current prediction methods, largely reliant on historical data and empirical models, struggle to maintain accuracy when machining condition changes. To address this challenge, this study constructs a multi-view EEP model for machining systems based on the digital twin technology. First, a four views (equipment, workpiece, process, and system) EEP framework is constructed containing a physical machining system, virtual machining system, and twin system. Second, three key technologies for realising multi-view EEP, data acquisition and information interactive perception, energy efficiency state identification and dynamic feature extraction, and low-latency real-time predictive model integration are proposed. Finally, a digital twin platform for multi-view EEP of machining systems was developed and validated. The results demonstrate that the proposed multi-view model and platform enable real-time, accurate EEP across machining systems, offering methodological support for energy savings and emissions reduction with broad application potential.","author":[{"family":"Li","given":"Jie"},{"family":"Yan","given":"Wei"},{"family":"Zhang","given":"Meihang"},{"family":"Zhu","given":"Shuo"},{"family":"Jiang","given":"Zhigang"},{"family":"Fan","given":"Zenglong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/27525783.2026.2634493","URL":"https://doi.org/10.1080/27525783.2026.2634493","source":"openalex"},{"id":"oa:W4414634084","type":"manuscript","title":"A UAV-Aided Digital Twin Framework for IoT Networks with High Accuracy and Synchronization","abstract":"With the continued growth of its core technologies, including the Internet of Things (IoT), artificial intelligence (AI), Big Data and data analytics, and edge computing, digital twin (DT) technology has witnessed a significant increase in industrial applications, helping the industry become more sustainable, smart, and adaptable. Hence, DT technology has emerged as a promising link between the physical and virtual worlds, enabling simulation, prediction, and real-time performance optimization. This work aims to explore the development of a high-fidelity digital twin framework, focusing on synchronization and accuracy between physical and digital systems to enhance data-driven decision making. To achieve this, we deploy several stationary UAVs in optimized locations to collect data from industrial IoT devices, which were used to monitor multiple physical entities and perform computations to evaluate their status. We consider a practical setup in which multiple IoT devices may monitor a single physical entity, and as a result, the measurements are combined and processed together to determine the status of the physical entity. The resulting status updates are subsequently uploaded from the UAVs to the base station, where the DT resides. In this work, we consider a novel metric based on the Age of Information (AoI), coined as the Age of Digital Twin (AoDT), to reflect the status freshness of the digital twin. Factoring AoDT in the problem formulation ensures that the DT reliably mirrors the physical system with high accuracy and synchronization. We formulate a mixed-integer non-convex program to maximize the total amount of data collected from all IoT devices while ensuring a constrained AoDT. Using successive convex approximations, we solve the problem, conduct extensive simulations and compare the results with baseline approaches to demonstrate the effectiveness of the proposed solution.","author":[{"family":"Khalaf","given":"Ghofran"},{"family":"Itani","given":"May"},{"family":"Sharafeddine","given":"Sanaa"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2504.15967","URL":"https://doi.org/10.48550/arxiv.2504.15967","source":"openalex"},{"id":"oa:W4412556458","type":"article-journal","title":"A parameter centric service discovery framework for social digital twins in smart City","abstract":"In the contemporary digital era, the Internet of Things (IoT) and its applications have proliferated extensively, particularly within smart city environments, resulting in increased network traffic and raising the significance of efficient service discovery (SD) mechanisms. The social Internet of Things (SIoT) is an emerging paradigm that enables IoT devices to autonomously establish social relationships based on rules defined by their owners, thereby enhancing services through social relations. Things can interact with others; thus, the huge volume of traffic is increased. Each node or device could select an appropriate peer for the discovery of services, which is thus helpful for human beings. Although numerous service discovery and query processing models have been proposed in the recent literature. However, the existing state-of-the-art approaches often lack a comprehensive analysis of the parameters. Most traditional state-of-the-art models primarily focus on relationships or device similarity. Also neglecting the vital factors, for instance, query processing, efficiency, spatial-temporal dynamics, and service provisioning, etc. Thus, to solve this issue, this research proposes an exhaustive analysis of the main parameters needed to implement service discovery mechanisms for Social IoT and studies their relative importance based on a dataset of real objects. Based on the advanced parameters' selection, an efficient service discovery algorithm is proposed. The proposed model emphasizes efficiency by optimizing the service discovery through reduced social graph traversal (i.e., fewer hops), consideration of the service types, and integration of caching mechanisms. We have conducted a comprehensive analysis of key parameters essential for implementing an effective service discovery mechanism in SIoT, prioritizing based on their importance. Experimental validation demonstrates the superiority of the proposed over state-of-the-art models, confirming its efficacy, scalability.","author":[{"family":"Amin","given":"Farhan"},{"family":"Khan","given":"Salabat"},{"family":"Choi","given":"Gyu"},{"family":"Abid","given":"Muhammad"},{"family":"Díez","given":"Isabel"},{"family":"Montero","given":"Elisabeth"},{"family":"Noya","given":"Irene"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-10423-1","URL":"https://doi.org/10.1038/s41598-025-10423-1","source":"openalex"},{"id":"oa:W4416425336","type":"article-journal","title":"A grey-box temperature model for digital twins of building-integrated rooftop greenhouses","abstract":"Urban agriculture is increasingly recognized as a strategy for enhancing food security, sustainability, and climate resilience in cities. Building-Integrated Rooftop Greenhouses (BIRTGs) offer a compelling solution by combining food production with building energy synergies. However, accurately predicting indoor temperature in such systems remains challenging due to their low thermal inertia, highly variable heat transfer dynamics, and the complex, time-dependent thermal interactions introduced by crops. This study presents a grey-box temperature model tailored for BIRTGs and designed for integration into Digital Twin (DT) frameworks. The model captures heat exchanges with the outdoor environment, host building, solar radiation, ventilation and plant evapotranspiration. Unlike traditional models, the evapotranspiration component is calibrated using sensor data, bypassing the need for complex crop-specific inputs. The model was calibrated and validated using experimental data from a BIRTG at Universitat Politècnica de Catalunya, both with and without crops. Validation results showed high predictive accuracy, with RMSE values of 2.2 °C without plants and 2.0 °C with plants. Furthermore, a systematic evaluation of 70 dataset combinations revealed that a single day of calibration data is sufficient to accurately forecast temperature over a 24-hour period. These results highlight the suitability of the model for real-time climate control and automation in urban agriculture using DTs.","author":[{"family":"López-Carreño","given":"Rubén"},{"family":"Macarulla","given":"Marcel"},{"family":"Gassó","given":"Santiago"},{"family":"Tejedor","given":"Blanca"},{"family":"Pardo-Bosch","given":"Francesc"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.buildenv.2025.114036","URL":"https://doi.org/10.1016/j.buildenv.2025.114036","source":"openalex"},{"id":"oa:W4413968487","type":"article-journal","title":"Smart Decision-Making: The Role of Digital Twins, Retrieval-Augmented Generation-Enhanced AI, and Learning Analytics","abstract":"Decision-making in higher education institutions faces complex challenges due to increasing data, regulatory demands, resource management, and changing educational needs. Effective decisions require accurate, timely insights into institutional processes. This study introduces an integrated decision-support approach consisting of Learning Analytics, Digital Twins, and Generative Artificial Intelligence (AI) with Retrieval-Augmented Generation (RAG). The objective is to enhance decision accuracy and operational efficiency in higher education. Learning Analytics provide insights into student performance, teaching effectiveness, and curriculum efficiency. Generative AI with RAG facilitates rapid retrieval and synthesis of institutional documentation and regulatory framework, enhancing decision accuracy. Digital Twins simulate institutional operations, enabling predictive resource planning and infrastructure modeling. Preliminary results indicate significant improvements in strategic planning and resource management by using an integrated decision support approach. Collectively, these technologies transform strategic decision-making and efficiency in higher education, enabling an agile and smart approach, offering a robust solution to contemporary challenges.","author":[{"family":"Vrček","given":"Neven"},{"family":"Ređep","given":"Nina"},{"family":"Šlibar","given":"Barbara"},{"family":"Grabar","given":"Darko"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5334/uproc.170","URL":"https://doi.org/10.5334/uproc.170","source":"openalex"},{"id":"oa:W4409345902","type":"article-journal","title":"MonoAlg3D: Enabling Cardiac Electrophysiology Digital Twins with an Efficient Open Source Scalable Solver on GPU Clusters","abstract":"ABSTRACT Modelling and simulation are essential in biomedicine, and specifically in computational cardiology. Reliable, efficient and accurate solvers are critical. This study presents an open source, GPU-based cardiac electrophysiology solver for scalable digital twin multiscale simulations (M ono A lg 3D), incorporating conduction system calibration and performance optimization. The solver employs the monodomain equation coupled with the Purkinje network, solved via the finite volume method, featuring a GPU-based linear solver and concurrent simulation dispatch with MPI. We demonstrate a 10.94× speedup over a CPU-based solution and scalability by running 512 simulations on 128 compute nodes, completing all coarse-mesh simulations in less than 24 minutes and fine-mesh simulations in 303 minutes. We also demonstrate integration into a cardiac digital twin pipeline for personalisation based on clinical data. The proposed open source solver enhances computational efficiency and physiological fidelity, enabling large-scale, high-speed cardiac simulations. This work marks a significant step toward fast and scalable cardiac simulations on GPU architectures, with integration in a Digital Twin personalisation pipeline including the conduction system.","author":[{"family":"Berg","given":"Lucas"},{"family":"Oliveira","given":"Rafael"},{"family":"Camps","given":"Julià"},{"family":"Wang","given":"Zhinuo"},{"family":"Doste","given":"Rubén"},{"family":"Buenoorovio","given":"Alfonso"},{"family":"Santos","given":"Rodrigo"},{"family":"Rodríguez","given":"Blanca"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1101/2025.04.09.647733","URL":"https://doi.org/10.1101/2025.04.09.647733","source":"preprints"},{"id":"oa:W7134970444","type":"article-journal","title":"Future-Proofing Heritage Future-Proofing Heritage with ARGUS: A Multimodal Digital Twin Approach for Sustainable Preservation","abstract":"The preservation of cultural heritage faces increasing challenges from environmental, climatic, and anthropogenic pressures. The ARGUS Horizon Europe project addresses these challenges by proposing an innovative predictive preservation approach that leverages AI-driven digital twins and multimodal data fusion to assess and mitigate risks to heritage sites. Our research focuses on developing a sustainable, dynamic decision support system (DSS) that integrates multi-scale on-site and remote sensing data, enabling holistic heritage management, while focusing on the preventive rather than the reactive aspects. The primary research question treated in this paper relates to how digital twins incorporating multi-dimensional data and an ontology background enhance the preservation and adaptive management of cultural heritage in a changing environment.","author":[{"family":"Pavlidis","given":"George"},{"family":"Koutsoudis","given":"Anestis"},{"family":"Tsiafaki","given":"Despoina"},{"family":"Karta","given":"Melpomeni"},{"family":"Sevetlidis","given":"Vasileios"},{"family":"Arampatzakis","given":"Vasileios"},{"family":"Sarris","given":"Apostolos"},{"family":"Polidorou","given":"Miltiadis"},{"family":"Klinkenberg","given":"Victor"},{"family":"Boukhers","given":"Zeyd"},{"family":"Kong","given":"Lingxiao"},{"family":"Farinetti","given":"Emeri"},{"family":"Navarro","given":"Fernando"},{"family":"Kakogiannos","given":"Ioannis"},{"family":"Aparicio","given":"Sofia"},{"family":"Heras","given":"Javier"},{"family":"Ramonet","given":"Fernando"},{"family":"Agapiou","given":"Athos"},{"family":"Hadjipetrou","given":"Stylianos"},{"family":"Michaelides","given":"Kyriakos"},{"family":"Patsalidis","given":"Stavros"},{"family":"Kyriakidis","given":"Phaedon"},{"family":"Papakonstantinou","given":"Apostolos"},{"family":"Athanasoulis","given":"Demetrios"},{"family":"Maris","given":"Christos"},{"family":"Vakoulis","given":"Themistoklis"},{"family":"Nagata","given":"Tomoki"},{"family":"Beyer","given":"Katrin"},{"family":"Saloustros","given":"Savvas"}],"issued":{"date-parts":[[2026]]},"DOI":"10.64888/caaproceedings.v52i1.942","URL":"https://doi.org/10.64888/caaproceedings.v52i1.942","source":"openalex"},{"id":"oa:W4406359717","type":"article-journal","title":"Constructing Digital-Twin Roadways for Testing and Evaluation of Autonomous Roadside Mowing Vehicles","abstract":"In Indiana, roadside mowing operations span over 11,000 miles and are performed by contracted crews using tractors and hand-held trimmers, exposing workers to significant safety risks, including reported casualties. Autonomous mowers offer a promising solution to enhance safety, but large-scale deployment requires rigorous testing to ensure reliability. This study addresses this need by developing digital-twin roadside environments to evaluate autonomous mowing systems. The method generates realistic roadways that accurately replicate real-world conditions, achieving single-float rounding planar accuracy over tens of meters, enabling risk-free and comprehensive testing. Leveraging remote sensing data, model libraries, and a georeferenced data mapping tool, the approach overcomes challenges in scalability and fidelity, even in locations with low-density source data. Digital roadway construction accelerates testing, enhances the realism of virtual deployments, and supports the development of autonomous mowing technologies. Furthermore, this approach has broader applications for generating test environments for various roadway-related systems.","author":[{"family":"Mardikes","given":"Michael"},{"family":"Evans","given":"John"},{"family":"Brown","given":"Ethan"},{"family":"Sprague","given":"Nathan"},{"family":"Wiegman","given":"Timothy"},{"family":"Shaver","given":"Gregory"}],"issued":{"date-parts":[[2025]]},"DOI":"10.36227/techrxiv.173687650.09495419/v1","URL":"https://doi.org/10.36227/techrxiv.173687650.09495419/v1","source":"openalex"},{"id":"oa:W7124418503","type":"article-journal","title":"Accelerating fused filament fabrication FFF optimization with AI-Powered digital twins and High-Fidelity simulations","abstract":"Abstract This study introduces a novel AI-based prediction framework for Fused Filament Fabrication (FFF) process optimization, integrating high-fidelity simulation with machine learning and design of experiments (DOE) analysis. In the proposed approach, a full-factorial DOE matrix is employed to drive Digimat-AM, a physics-based thermo-mechanical simulation tool, generating an exhaustive dataset to train six machine learning models (Random Forest, XGBoost, ANN, SVR, AdaBoost, and KNN). These models predict four critical responses: deflection, residual stress, print time, and shape tolerance (dimensional accuracy), and their performance is benchmarked against classical DOE response-surface models. The AI models exhibit outstanding predictive accuracy: ensemble methods (Random Forest, XGBoost) achieved near-perfect agreement with simulation outputs, significantly outperforming DOE models. Interpretability is ensured via 3D response-surface plots, which illustrate the influence of parameter interactions and align with known thermo-mechanical trends. This combination of predictive fidelity and transparent analysis delivers valuable design insights and practical utility. The trained ML models serve as fast surrogates (digital twins), enabling rapid “what-if” scenario exploration and reducing reliance on trial-and-error in print optimization. This AI-driven framework streamlines additive manufacturing workflows by accelerating process tuning and laying the foundation for intelligent, data-driven FFF optimization.","author":[{"family":"Brayek","given":"Baha"},{"family":"Qarssis","given":"Y"},{"family":"Ghennioui","given":"Abdellatif"},{"family":"Hami","given":"Abdelkhalak"},{"family":"Tarfaoui","given":"Mostapha"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s00170-025-17219-7","URL":"https://doi.org/10.1007/s00170-025-17219-7","source":"openalex"},{"id":"oa:W4407806341","type":"manuscript","title":"Personalized Education with Generative AI and Digital Twins: VR, RAG, and Zero-Shot Sentiment Analysis for Industry 4.0 Workforce Development","abstract":"The Fourth Industrial Revolution (4IR) technologies, such as cloud computing, machine learning, and AI, have improved productivity but introduced challenges in workforce training and reskilling. This is critical given existing workforce shortages, especially in marginalized communities like Underrepresented Minorities (URM), who often lack access to quality education. Addressing these challenges, this research presents gAI-PT4I4, a Generative AI-based Personalized Tutor for Industrial 4.0, designed to personalize 4IR experiential learning. gAI-PT4I4 employs sentiment analysis to assess student comprehension, leveraging generative AI and finite automaton to tailor learning experiences. The framework integrates low-fidelity Digital Twins for VR-based training, featuring an Interactive Tutor - a generative AI assistant providing real-time guidance via audio and text. It uses zero-shot sentiment analysis with LLMs and prompt engineering, achieving 86\\% accuracy in classifying student-teacher interactions as positive or negative. Additionally, retrieval-augmented generation (RAG) enables personalized learning content grounded in domain-specific knowledge. To adapt training dynamically, finite automaton structures exercises into states of increasing difficulty, requiring 80\\% task-performance accuracy for progression. Experimental evaluation with 22 volunteers showed improved accuracy exceeding 80\\%, reducing training time. Finally, this paper introduces a Multi-Fidelity Digital Twin model, aligning Digital Twin complexity with Bloom's Taxonomy and Kirkpatrick's model, providing a scalable educational framework.","author":[{"family":"Lin","given":"Yu"},{"family":"Petal","given":"Karan"},{"family":"Alhamadah","given":"Ahmed"},{"family":"Ghimire","given":"Sujan"},{"family":"Redondo","given":"Matthew"},{"family":"Corona","given":"David"},{"family":"Pacheco","given":"Jesús"},{"family":"Salehi","given":"Soheil"},{"family":"Satam","given":"Pratik"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2502.14080","URL":"https://doi.org/10.48550/arxiv.2502.14080","source":"openalex"},{"id":"oa:W4406824314","type":"article-journal","title":"Monitoring and Modeling the Soil‐Plant System Toward Understanding Soil Health","abstract":"Abstract The soil health assessment has evolved from focusing primarily on agricultural productivity to an integrated evaluation of soil biota and biotic processes that impact soil properties. Consequently, soil health assessment has shifted from a predominantly physicochemical approach to incorporating ecological, biological and molecular microbiology indicators. This shift enables a comprehensive exploration of soil microbial community properties and their responses to environmental changes arising from climate change and anthropogenic disturbances. Despite the increasing availability of soil health indicators (physical, chemical, and biological) and data, a holistic mechanistic linkage has not yet been fully established between indicators and soil functions across multiple spatiotemporal scales. This article reviews the state‐of‐the‐art of soil health monitoring, focusing on understanding how soil‐microbiome‐plant processes contribute to feedback mechanisms and causes of changes in soil properties, as well as the impact these changes have on soil functions. Furthermore, we survey the opportunities afforded by the soil‐plant digital twin approach, an integrative framework that amalgamates process‐based models, Earth Observation data, data assimilation, and physics‐informed machine learning, to achieve a nuanced comprehension of soil health. This review delineates the prospective trajectory for monitoring soil health by embracing a digital twin approach to systematically observe and model the soil‐plant system. We further identify gaps and opportunities, and provide perspectives for future research for an enhanced understanding of the intricate interplay between soil properties, soil hydrological processes, soil‐plant hydraulics, soil microbiome, and landscape genomics.","author":[{"family":"Zeng","given":"Yijian"},{"family":"Verhoef","given":"Anne"},{"family":"Vereecken","given":"Harry"},{"family":"Bendor","given":"Eyal"},{"family":"Veldkamp","given":"A"},{"family":"Shaw","given":"Liz"},{"family":"Ploeg","given":"Martine"},{"family":"Wang","given":"Yunfei"},{"family":"Su","given":"Zhongbo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1029/2024rg000836","URL":"https://doi.org/10.1029/2024rg000836","source":"openalex"},{"id":"oa:W7203645321","type":"article-journal","title":"A consensus framework for digital twin development in lyophilization","abstract":"Abstract Digital twins (DTs) are emerging as the central enabler for an Industry 4.0 approach to pharmaceutical freeze-drying, promising real-time insight, closed-loop control and virtual validation of processes that are traditionally conservative, lengthy and material-intensive. This paper consolidates expertise from academia, equipment suppliers and biopharma manufacturers to define a five-level DT maturity model for lyophilization and to map the technologies, methodologies and regulatory concepts needed to progress through those levels. We first analyze the physical, mathematical and computational challenges unique to freezing, primary and secondary drying, and show how first-principles, CFD, coupled and probabilistic models can be combined with advanced PAT (wireless temperature probes, TDLAS, dP-dT mass-flow calculation, RGA, NIR) to create a continuously updated design space that is both equipment- and scale-aware. The ISO 23247 reference architecture is then translated into a lyophilization context to standardize data models and information exchange. Commercial platforms (Siemens xDT, Ansys Twin Builder, IMA Sentinel) are reviewed to illustrate implementation pathways, while emerging technologies-spray freeze-drying, RF/microwave heating and AI-enabled visual inspection-highlight the need for adaptable, hybrid mechanistic-ML twins. Regulatory guidance from FDA, ICH and ASME V&V 40 is synthesized into a risk-based verification and validation strategy that aligns DT credibility with product-quality impact. Finally, a road-map of actionable steps-spanning sensor selection, model calibration, uncertainty quantification, operator training, and data governance-is outlined for organizations to adopt during development, tech transfer, and commercial manufacture. Collectively, these recommendations provide a coherent framework for deploying fit-for-purpose, GMP-compliant DTs that shorten cycle times, enhance robustness and accelerate delivery of high-quality lyophilized products.","author":[{"family":"Kazarin","given":"Petr"},{"family":"Metsiguckel","given":"Efimia"},{"family":"Alexeenko","given":"Alina"},{"family":"Tchessalov","given":"Serguei"},{"family":"Aglave","given":"Ravindra"},{"family":"Bakri","given":"Wisam"},{"family":"Authelin","given":"Jean‐rené"},{"family":"Dowling","given":"Denis"},{"family":"Ganguly","given":"Arnab"},{"family":"Gong","given":"Emily"},{"family":"Horner","given":"Marc"},{"family":"Fontana","given":"Lauren"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1186/s41120-026-00150-w","URL":"https://doi.org/10.1186/s41120-026-00150-w","source":"openalex"},{"id":"oa:W4416826450","type":"article-journal","title":"The Twin Transition in Practice. Digital Technologies, Sustainability, and the Role of Family Ownership in Europe","abstract":"ABSTRACT This paper examines whether and to what extent digital technologies (DTs) foster the adoption of environmental sustainability (ES), and how this relationship is moderated by family ownership. Using data from approximately 14,000 European firms surveyed in the Flash Eurobarometer 486, we estimate a recursive simultaneous equation model via a conditional mixed‐process (CMP) to address potential endogeneity concerns. Results indicate that digitalization has a positive influence on ES adoption, although the marginal effect declines as firms implement more DTs. Family firms exhibit a stronger overall commitment to sustainability than their non‐family counterparts. However, because of their distinctive organizational traits, they tend to adopt ES practices less responsively as digitalization increases. Further analyses reveal heterogeneity across the sustainability practices. These findings underscore the relevance of ownership in shaping digitalization outcomes and contribute to the growing literature on the twin transition by informing more tailored policy strategies for an inclusive and effective green pathway.","author":[{"family":"Aiello","given":"Francesco"},{"family":"Mannarino","given":"Lidia"},{"family":"Pupo","given":"Valeria"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/bse.70434","URL":"https://doi.org/10.1002/bse.70434","source":"openalex"},{"id":"oa:W4407394123","type":"article-journal","title":"Research on digital empowerment, innovation vitality and manufacturing supply chain resilience mechanism","abstract":"As global manufacturing competition increasingly emphasizes supply chain resilience, enhancing the risk resistance of manufacturing supply chains through digital empowerment has become a critical priority. This study leverages the opportunities of the digital economy to deeply investigate the mechanisms that enhance supply chain resilience. Using data from China' s A-share listed manufacturing companies from 2012 to 2020, a research framework is constructed based on information asymmetry and transaction cost theories. Employing text analysis and factor analysis, the study develops indicators for digital empowerment and supply chain resilience and examines their relationship through both theoretical analysis and empirical testing. The findings reveal that: (a) Digital empowerment significantly enhances supply chain resilience in the manufacturing sector, and this conclusion is robust across various robustness checks. (b) Mechanism analysis demonstrates that digital empowerment drives supply chain resilience primarily by enhancing innovation vitality within enterprises. (c) The moderating analysis shows that environmental uncertainty positively influences the resilience of digitally empowered manufacturing supply chains. (d) Further analysis indicates that the effects of digital empowerment on supply chain resilience vary depending on factor intensity, supply chain position, and industry competition levels. These results validate the positive role of digital empowerment in promoting supply chain resilience and explore the 'black box' mechanism from the perspective of innovation vitality. The study also highlights the moderating influence of environmental uncertainty. By advancing the understanding of how the digital economy fosters high-quality development in manufacturing, this research provides actionable insights for strengthening supply chain resilience, achieving greater control over supply chain dynamics, and promoting deeper integration between digital technologies and the real economy.","author":[{"family":"Wang","given":"Huiyan"},{"family":"Chen","given":"You"},{"family":"Xie","given":"Jiaping"},{"family":"Liu","given":"Caixuan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1371/journal.pone.0316183","URL":"https://doi.org/10.1371/journal.pone.0316183","source":"openalex"},{"id":"oa:W4413244148","type":"article-journal","title":"Telemedicine, eHealth, and Digital Transformation in Poland (2014–2024): Trends, Specializations, and Systemic Implications","abstract":"Background: Between 2014 and 2024, Poland underwent a significant digital transformation in its healthcare sector, evolving from isolated initiatives to a cohesive national eHealth ecosystem. This review examines the development, clinical significance, and research trends in telemedicine in Poland, providing comparative insights from 1995 to 2015 and assessing the impact of the COVID-19 pandemic. Methods: A narrative review was conducted using the PubMed, Scopus, EMBASE, and Web of Science databases to identify peer-reviewed articles published between January 2014 and December 2024. A total of 1012 records were identified, and 212 articles were included after applying predefined inclusion criteria. These articles were categorized by medical specialty, study type, COVID-19 relevance, and clinical versus nonclinical focus. Gray literature and policy reports were examined only to provide a context for the findings. Results: Ninety-six publications were included in the clinical studies. The most common specialties are cardiology, psychiatry, geriatrics, general practice, and rehabilitation. In earlier years, survey-based and observational designs were predominant, whereas later years saw an increase in interventional trials and studies enabled by Artificial Intelligence (AI). The COVID-19 pandemic has had a significant impact on research activity, accelerating the adoption of digital technologies in previously underrepresented fields, such as pulmonology and palliative care, as well as in the routine use of modern Internet communication technologies for daily patient–doctor interactions. Discussion: Advancements in digital health (including eHealth and telemedicine) in Poland have been driven by policy reforms, technological advancements, and epidemiological events, such as COVID-19. Various fields have evolved from feasibility studies to clinical trials, and emerging specialties have focused on user experience and implementation. However, the adoption of AI and its interoperability remains underdeveloped, primarily because of regulatory and reimbursement challenges. Conclusions: Poland has made significant strides in institutionalizing digital health; however, ongoing innovation necessitates regulatory alignment, strategic funding, and enhanced collaboration between academia and industry. As the country aligns with the European Union (EU) initiatives, such as the European Health Data Space, it has the potential to lead to regional integration in digital health.","author":[{"family":"Glinkowski","given":"Wojciech"},{"family":"Cedro","given":"Tomasz"},{"family":"Wołk","given":"Agnieszka"},{"family":"Doniec","given":"Rafał"},{"family":"Wołk","given":"Krzysztof"},{"family":"Wilk","given":"Szymon"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15168793","URL":"https://doi.org/10.3390/app15168793","source":"openalex"},{"id":"oa:W4407012905","type":"manuscript","title":"Digital Twin Synchronization: Bridging the Sim-RL Agent to a Real-Time Robotic Additive Manufacturing Control","abstract":"With the rapid development of deep reinforcement learning technology, it gradually demonstrates excellent potential and is becoming the most promising solution in the robotics. However, in the smart manufacturing domain, there is still not too much research involved in dynamic adaptive control mechanisms optimizing complex processes. This research advances the integration of Soft Actor-Critic (SAC) with digital twins for industrial robotics applications, providing a framework for enhanced adaptive real-time control for smart additive manufacturing processing. The system architecture combines Unity's simulation environment with ROS2 for seamless digital twin synchronization, while leveraging transfer learning to efficiently adapt trained models across tasks. We demonstrate our methodology using a Viper X300s robot arm with the proposed hierarchical reward structure to address the common reinforcement learning challenges in two distinct control scenarios. The results show rapid policy convergence and robust task execution in both simulated and physical environments demonstrating the effectiveness of our approach.","author":[{"family":"Ali","given":"Matsive"},{"family":"Giri","given":"Sandesh"},{"family":"Liu","given":"Sen"},{"family":"Yang","given":"Qin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2501.18016","URL":"https://doi.org/10.48550/arxiv.2501.18016","source":"openalex"},{"id":"oa:W4412159090","type":"article-journal","title":"Digital technologies to accelerate the impact of climate smart agriculture by next-generation farmers in Africa","abstract":"The adoption of digital technologies for scaling Climate-Smart Agriculture (CSA) practices can enhance agricultural productivity, food security, and livelihood sustainability of smallholder farmer communities in Africa. While digital agronomy supports for smallholder farmers present significant opportunities for strengthening agricultural extension systems, there are also significant barriers faced by smallholders in accessing and using digital agronomy services. Despite the rapid growth in phone and internet access in Africa, many smallholder farming communities and households lack effective access to the phone and internet services necessary for effective digital agronomy delivery. The digital divide that constrains smallholder farmers acts as a brake on the ambitions and targets for CSA scaling and for agricultural sector development across Africa, including in the Comprehensive Africa Agriculture Development Programme (CAADP) held in Strategy and Action Plan, and the Kampala CAADP Declaration on Building Resilient and Sustainable Agrifood Systems in Africa. Currently, there are a broad range of digital technologies (e.g., radio, mobile phone apps, video, mobile phone apps, animations, and social media platforms) that can be harnessed for scaling CSA amongst smallholder farmers, with a rapidly growing number of digital agronomy developers and providers. However, the affordability of phone and internet services for poorer smallholders, in addition to lack of technology infrastructure and digital literacy skills, remains a barrier to “last mile” delivery of effective digital agronomy services. As digital access becomes more affordable and digital agronomy systems become more powerful, pervasive (e.g., via social media and peer-to-peer training approaches) and localized (e.g., using artificial intelligence and machine translation), there is significant potential for digital agronomy systems to augment and strengthen national agricultural extension systems supporting smallholder farmers. In particular, digital agronomy services can help accelerate scaling of Climate-Smart Agriculture (CSA) practices for the millions of smallholder farmers who are most vulnerable to the unfolding climate crisis affecting their farming systems and livelihoods.","author":[{"family":"Mollel","given":"Margareth"},{"family":"Quiroz","given":"Luis"},{"family":"Varley","given":"Ciara"},{"family":"Firestine","given":"Alex"},{"family":"Mcloughlin","given":"Mary"},{"family":"Kafunah","given":"Jefkine"},{"family":"Kharkar","given":"Shrutik"},{"family":"O'farrell","given":"Jemima"},{"family":"Ndlovu","given":"Noel"},{"family":"Johnston","given":"Angharad"},{"family":"Mckeown","given":"Peter"},{"family":"Brychkova","given":"Galina"},{"family":"Murray","given":"Úna"},{"family":"Moreno-Leiva","given":"Simón"},{"family":"Spillane","given":"Charles"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fsufs.2025.1462328","URL":"https://doi.org/10.3389/fsufs.2025.1462328","source":"openalex"},{"id":"oa:W4411673050","type":"article-journal","title":"Digital twins suggest a mechanistic basis for differing responses to increased flow rates during high-flow nasal cannula therapy","abstract":"Abstract Background Inconsistent responses to increased flow rates have been observed in patients with acute hypoxemic respiratory failure (AHRF) treated with high-flow nasal cannula (HFNC) therapy, with a significant minority in two recent studies exhibiting increased respiratory effort at higher flow rates. Digital twins of patients receiving HFNC could help understand the physiological basis for differing responses. Methods Patient data were collated from previous studies in AHRF patients who were continuously monitored with electrical impedance tomography and oesophageal manometry and received HFNC at flow rates of 30, 40 or 45 L/min. Patients, based on their responses to an increase in flow rate to 60 L/min, were categorised into two groups: five responders with reduced oesophageal pressure swings ΔP es (− 3.1 cmH 2 O on average), and five non-responders with increased ΔP es (+ 2.0 cmH 2 O on average). Two cohorts of digital twins were created based on these data using a multi-compartmental mechanistic cardiopulmonary simulator. Digital twins’ responses to increased HFNC flow rates (60 L/min) were simulated with constant respiratory effort to assess changes in gas exchange and lung mechanics, and with varying respiratory effort to quantify their combined effects on lung mechanics and P-SILI indicators. Results The digital twins accurately replicated patient-specific responses at all flow rates. Responder digital twins showed a mean 20 mL/cmH 2 O increase in lung compliance at higher flow rates, versus a 6 mL/cmH 2 O decrease in compliance with non-responders. In digital twins of responders versus non-responders, increased flow rates produced a mean change in lung stress of − 1.5 versus + 1.2 cmH 2 O, in dynamic lung strain of − 8.8 versus + 16.4%, in driving pressure of − 1.3 versus + 1.1 cmH 2 O, and in mechanical power of − 0.8 versus + 1.2 J/min. Higher flow rate dependent positive end-expiratory pressure in digital twins of non-responders did not cause recruitment, and reduced tidal volumes due to higher functional residual capacities—to compensate for the resulting worsened gas-exchange, non-responders increased their respiratory effort, in turn increasing patient self-inflicted lung injury ( P -SILI) indicators. In digital twins of responders, reductions in tidal volumes due to higher FRCs resulting from increased PEEP were outweighed by alveolar recruitment. This increased compliance and improved gas exchange, permitting reduced respiratory effort and decreases in P -SILI indicators. Conclusions Failure to reduce spontaneous respiratory efforts in response to increased HFNC flow rates could be due to a deterioration in lung mechanics, with an attendant risk of P -SILI.","author":[{"family":"Shamohammadi","given":"Hossein"},{"family":"Saffaran","given":"Sina"},{"family":"Tonelli","given":"Roberto"},{"family":"Chiavieri","given":"Valentina"},{"family":"Grasselli","given":"Giacomo"},{"family":"Clini","given":"Enrico"},{"family":"Mauri","given":"Tommaso"},{"family":"Bates","given":"Declan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1186/s40635-025-00773-5","URL":"https://doi.org/10.1186/s40635-025-00773-5","source":"openalex"},{"id":"oa:W4410707196","type":"article-journal","title":"Single-shot reconstruction of three-dimensional morphology of biological cells in digital holographic microscopy using a physics-driven neural network","abstract":"Recent advances in deep learning-based image reconstruction techniques have led to significant progress in phase retrieval using digital in-line holographic microscopy (DIHM). However, existing phase retrieval methods have technical limitations in 3D morphology reconstruction from single-shot holograms of biological cells. In this study, we propose a deep learning model, named MorpHoloNet, for single-shot reconstruction of 3D morphology by integrating physics-driven and coordinate-based neural networks. By simulating optical diffraction of coherent light through a 3D phase shift distribution, MorpHoloNet is optimized by minimizing the loss between simulated and input holograms on the detector plane. MorpHoloNet enables direct reconstruction of 3D complex light field and 3D morphology of a test sample from its single-shot hologram without requiring multiple phase-shifted holograms or angular scanning. It would be utilized to reconstruct spatiotemporal variations in 3D translational and rotational behaviors, as well as morphological deformations of biological cells from consecutive single-shot holograms captured using DIHM. Here, the authors demonstrate MorpHoloNet: a physics-driven, coordinate-based deep learning model enabling single-shot reconstruction of 3D morphology and refractive index distribution of biological cells in digital holographic microscopy without angular scanning.","author":[{"family":"Kim","given":"Jihwan"},{"family":"Kim","given":"Youngdo"},{"family":"Lee","given":"Hyo"},{"family":"Seo","given":"Eunseok"},{"family":"Lee","given":"Sang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41467-025-60200-x","URL":"https://doi.org/10.1038/s41467-025-60200-x","source":"openalex"},{"id":"oa:W4411887319","type":"article-journal","title":"Research Status and Progress of Digital Twin Models for Electric Power System Equipment","abstract":"With the development of smart grids, traditional methods for managing and maintaining grid equipment are becoming inadequate to meet the increasingly complex needs of power systems. Digital twin technology, as an advanced digital means, achieves real-time monitoring, prediction, and optimization of the entire lifecycle of grid equipment by creating virtual replicas of physical entities. This paper focuses on research into digital twin models for grid equipment, exploring their applications and challenges in improving operational and maintenance efficiency and ensuring the safe and reliable operation of the electric power system. The paper first introduces the technical characteristics of digital twins, then presents three digital twin models for grid equipment: a substation power equipment inspection system model, an ultra-high voltage direct current (UHVDC) system model, and a reality-based modeling model. Finally, it looks ahead to the future trends in the development of digital twin models for the electric power system and draws conclusions.","author":[{"family":"Xu","given":"Ning"},{"family":"Hu","given":"Lina"},{"family":"Di","given":"Xiaomeng"},{"family":"Tang","given":"Yi"},{"family":"Dong","given":"Liang"},{"family":"Sun","given":"Ximin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1145/3729706.3729778","URL":"https://doi.org/10.1145/3729706.3729778","source":"openalex"},{"id":"oa:W4417182014","type":"article-journal","title":"Blockchain-based access management framework for interoperable digital twins in industrial IoT","abstract":"Introduction Digital Twins (DT) have appeared as a significant tool in Industrial Internet of Things (IIoT) environments, allowing real-time monitoring, predictive maintenance, and maximizing device performance. However, integrating DTs with IIoT initiates serious security issues, specifically in the device’s authentication and authorization. The state-of-the-art mechanisms are exposed to insider threats, single points of failure, and privacy issues. Methods This study proposes a blockchain-based access control framework for cross-domain DTs. The blockchain (BC) integration eliminates reliance on the centralized authentication server. It uses platform verification from the manufacturer to validate IIoT device integrity and mitigate insider threats. Moreover, the authorization mechanism is implemented using smart contract and access control policies stored in BC. The proposed Non-Fungible Tokens enable role and permission delegation. Results and Discussion The integration of Hyperledger Fabric BC, platform hash verification, and NFT-based authorization in the proposed architecture enhanced its resilience against cyber-attacks i.e., replay, DoS/DDoS, insider, and spoofing attacks. Moreover, the proposed framework validates its viability with response times (approximately 300ms) for the authentication and authorization phases. Additionally, identity resolution attains 67 % depletion in latency compared to its counterpart.","author":[{"family":"Ali","given":"Gauhar"},{"family":"Shah","given":"Sajid"},{"family":"Elaffendi","given":"Mohammed"},{"family":"Ahmad","given":"Naveed"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fbloc.2025.1693926","URL":"https://doi.org/10.3389/fbloc.2025.1693926","source":"openalex"},{"id":"oa:W4413201753","type":"article-journal","title":"A Review of the Application of Ontologies and Semantic Web for Building Information Modelling and Digital Twins Based Construction Management","abstract":"As the construction industry is moving towards digitalisation, the integration of advanced technologies like Building Information Modelling (BIM) and digital twins has become essential for enhancing project efficiency. Currently, the industry has the capacity to operate at BIM Maturity stage 2 but faces challenges in achieving seamless data integration and interoperability. Progressing toward BIM Maturity Stage 3 could benefit from adopting semantic web and linked data technologies, which enable a more structured, machine-readable data environment. However, the path to this level of integration remains complex. At the heart of the semantic web lies ontologies, playing a pivotal role in structuring domain knowledge. Therefore, through a systematic literature review, this study explores the integration of ontologies and semantic web technologies in BIM or Digital Twin environments for construction management. This study provides a trend and theoretical analysis under different construction management use cases to identify how ontologies and semantic web technologies have been utilised during the construction execution phase. The study identified eight different use cases, including safety management, compliance checking, and construction planning and production control, among others. The findings emphasise that while there is great potential in using ontologies and the semantic web for data integration, significant barriers remain, such as data privacy concerns, scalability issues, and the complexity of ontology mapping. These findings underscore the importance of addressing these challenges to fully harness the capabilities of semantic web technologies within BIM environments, providing a potential roadmap toward realising BIM Maturity Stage 3 and to enhance collaboration and data exchange in the construction industry. This study provides a roadmap for future research and technological development in applying semantic web technologies to advance construction management.","author":[{"family":"Palihakkara","given":"Asha"},{"family":"Osorio-Sandoval","given":"Carlos"},{"family":"Tizani","given":"Walid"}],"issued":{"date-parts":[[2025]]},"DOI":"10.36680/j.itcon.2025.049","URL":"https://doi.org/10.36680/j.itcon.2025.049","source":"openalex"},{"id":"oa:W4410068942","type":"article-journal","title":"How Digital Orientation Affects Innovation Performance? Exploring the Role of Digital Capabilities and Environmental Dynamism","abstract":"Digital orientation has attracted significant attention from policymakers and researchers due to its potential to drive innovation success. While prior research has largely examined the impact of digital orientation on specific types of innovation from a static lens, a holistic and dynamic perspective on its relationship with firms’ overall innovation performance remains limited. Drawing on dynamic capabilities theory, this study aims to bridge this gap by developing a moderated mediation model that incorporates the mediating role of digital capabilities and the moderating effect of environmental dynamism in the relationship between digital orientation and firms’ overall innovation performance. Using survey data from 368 Chinese firms, this study employs hierarchical regression analysis and the bootstrap method to test the hypotheses. The results indicate that digital orientation promotes digital capabilities (encompassing digital sensing, digital integrative, and digital transforming capabilities), which in turn facilitates firms’ overall innovation performance. Also, the effect of digital capabilities on innovation performance is moderated by environmental dynamism. This study contributes to the existing literature by offering a holistic and dynamic lens to elucidate the link between digital orientation and innovation performance, while also providing managerial insights for firms seeking to adopt digital orientation to boost innovation success in the evolving digital environments.","author":[{"family":"Zhang","given":"Xian"},{"family":"Wang","given":"Zongjun"},{"family":"Luo","given":"Wenyi"},{"family":"Guo","given":"Feifei"},{"family":"Wang","given":"Peng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/systems13050346","URL":"https://doi.org/10.3390/systems13050346","source":"openalex"},{"id":"oa:W4407090597","type":"article-journal","title":"Digital technologies and circularity: trade-offs in the development of life cycle assessment","abstract":"Abstract Purpose This research aims to develop a critical understanding of the employment of digital technologies (DTs) for LCA studies, outlining both the opportunities and challenges associated with circular strategies. Two research questions are thus addressed: (1) What circular loops and aspects are addressed when digital technologies are integrated in the development of a Life Cycle Inventory? (2) Which trade-offs are revealed in the integration of digital technologies in Life Cycle Inventory development addressing circularity along a life cycle? Methods This study is based on the problematisation approach, which critically examines existing assumptions in the LCA literature, structured into six principles: defining a domain of investigation, articulating and evaluating assumptions, developing alternative perspectives, involving the audience through qualitative interviews, and assessing the alternative assumptions. A systematic literature review (SLR) and semi-structured interviews with experts were conducted to explore these issues and suggest future research directions. Results and discussion It emerges that the DTs are mainly integrated in the Life Cycle Inventory phase capturing closing and narrowing loops, whereas a limited number of cases investigate slowing loops with different aspects investigated. However, even if DTs can facilitate and improve the trustworthiness of the inventory, they can also lead to an increase in complexity because more competencies are needed, it is more difficult to control data collection and elaboration, and more social interactions along the supply chain are needed. At the same time, DTs can reduce flexibility because further improvements are blocked, interfaces can be rigid to connect, and technical and normative updates can be more difficult to implement. Conclusions DTs improve the development of the Life Cycle Inventory phase, particularly in the context of the circular economy. However, they also introduce new complexities and challenges. The use of blockchain, digital twins, and IoT sensors, for instance, has significantly improved data transparency and traceability, which are critical for circular economy practices, but complexity and training requirements can limit their benefits, so careful consideration must be given to their implementation to maximise benefits and minimise drawbacks.","author":[{"family":"Toniolo","given":"Sara"},{"family":"Pierli","given":"Giada"},{"family":"Bravi","given":"Laura"},{"family":"Liberatore","given":"Lolita"},{"family":"Murmura","given":"Federica"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s11367-025-02436-9","URL":"https://doi.org/10.1007/s11367-025-02436-9","source":"openalex"},{"id":"oa:W4413104445","type":"article-journal","title":"A Review of Artificial Intelligence Applications for Biorefineries and Bioprocessing: From Data-Driven Processes to Optimization Strategies and Real-Time Control","abstract":"This paper reviews the integration of artificial intelligence (AI) and machine learning in biorefineries and bioprocessing, with applications in biocatalysis, enzyme optimization, real-time monitoring, and quality assurance. AI contributes to predictive modeling and allows the precise forecasting of process outcomes, resource management, and energy utilization. AI models, including supervised, unsupervised, and reinforcement learning, support improvements in important bioprocess stages, such as fermentation, purification, and microbial biosynthesis. Digital twins and soft-sensing technologies enable real-time control and increase operational precision in complex bioprocess environments. Hybrid modeling integrates data-driven AI techniques with common scientific principles, improving scalability and adaptability under dynamic operational conditions. This review addresses challenges in AI implementation, such as data standardization, model transparency, and the need for interdisciplinary collaboration. The discussion concludes with future directions and sustainable AI strategies, highlighting the potential of AI to strengthen scalable, efficient, and environmentally sustainable biorefinery operations. These findings highlight how AI-driven methodologies improve operational efficiency, reduce resource waste, and facilitate sustainable innovation in bioprocesses, thereby strengthening sustainability within the bioeconomy.","author":[{"family":"Butean","given":"Alex"},{"family":"Cutean","given":"Iulia"},{"family":"Barbero","given":"Rubén"},{"family":"Enríquez","given":"Juan"},{"family":"Matei","given":"Alexandru"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/pr13082544","URL":"https://doi.org/10.3390/pr13082544","source":"openalex"},{"id":"oa:W4416409869","type":"article-journal","title":"Digital twin for the analog scoliometer: advancements in telehealth for paediatric spine deformity care","abstract":"In scoliosis care, a spine specialist will measure the lateral curvature of the spine from a radiograph and measure the torso rotation non-radiographically with an analog scoliometer directly on the patient at every surveillance appointment. While radiographs can be taken at any imaging centre and transferred to the treating spine clinic, the patient must visit in-person for monitoring the progression of structural rotation. Until now, distance measurement of the Angle of Trunk Rotation (ATR) has not been possible as no \"virtual\" scoliometer exists. This study describes the development of the first digital twin for the analog scoliometer to enable fast, gravity-independent, reliable and accurate digital ATR measurements from patient-specific 3D virtual models. It mimics the physical measurement process of the ATR using an analog scoliometer in a virtual environment. Validation of the tool showed excellent intra-user (< 0.95) and inter-user (< 0.95) reliability. The digital measurements had a high positive correlation (0.897) and agreement (92.7%) with the analog measurements made clinically. At 6° cut-off, the tool showed a high sensitivity of 90.24% and specificity of 92.31%. Larger device width was not shown to be an advantage. The development of this digital twin is significant for telehealth implementation in paediatric spine deformity management.","author":[{"family":"Suresh","given":"Sinduja"},{"family":"Stubbs","given":"Annabelle"},{"family":"Pulling","given":"Grace"},{"family":"Amiri","given":"Amir"},{"family":"Izatt","given":"Maree"},{"family":"Labrom","given":"Robert"},{"family":"Askin","given":"Geoffrey"},{"family":"Little","given":"JP"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-25023-2","URL":"https://doi.org/10.1038/s41598-025-25023-2","source":"europepmc"},{"id":"oa:W7160715466","type":"article-journal","title":"Utilizing Manufacturing Digital Twins for Sustainability Reporting","abstract":"The advance of digital technologies and the societal imperative to achieve sustainability exposes new pathways for businesses. The environmental and social impacts of industrial operations are well known and there are increasing demands to report impact through voluntary and mandatory corporate stakeholder reporting. The extensive live operations reporting is disconnected from corporate reports built retrospectively from aggregate enterprise data. This paper argues that the disconnect between operations and corporate reporting is a missed opportunity hindered by data integration, absence of frameworks to guide adoption and the missed value that comes from integrated reporting. By considering digital twin data and those of reporting standards such as from the EU’s Corporate Sustainability Reporting Directive, the two could be mapped. Once mapped, a digital twin could be created to generate reporting data and enable improvement evaluation. This paper uses literature and expert interviews to report the requirements for linking digital twins to sustainability reporting. In turn it proposes a framework to guide data mapping and model configuration to use to evaluate the business level impact of operational changes. A discussion on the utility of the framework precedes the conclusion with directions for future research.","author":[{"family":"Luo","given":"Yujia"},{"family":"Candia","given":"Juan"},{"family":"Ball","given":"Peter"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/978-3-032-21154-5_32","URL":"https://doi.org/10.1007/978-3-032-21154-5_32","source":"openalex"},{"id":"oa:W4411782466","type":"article-journal","title":"Applications of Building Information Modeling (BIM) and BIM-Related Technologies for Sustainable Risk and Disaster Management in Buildings: A Meta-Analysis (2014–2024)","abstract":"Sustainable risk and disaster management in the built environment has become a critical research focus amid escalating environmental challenges. Building Information Modeling (BIM) is recognized as a key digital tool for enhancing disaster resilience through simulation, data integration, and collaborative management. This study systematically reviews BIM applications in sustainable risk and disaster management from 2014 to 2024, employing the PRISMA framework, literature coding, and network analysis. Five primary research clusters are identified: (a) sustainable construction and life cycle assessment, (b) performance evaluation and implementation, (c) technology integration and digital innovation, (d) Historic Building Modeling (HBIM) and post-disaster reconstruction, and (e) project management and technology adoption. Despite increasing scholarly attention, the field remains dominated by conceptual studies, with limited empirical exploration of emerging technologies such as artificial intelligence (AI). Four key challenges are highlighted: weak foundational integration with structural risk research, technological bottlenecks in AI and digital applications, limited practical implementation, and insufficient linkage between sustainability and risk management. Future trends are expected to focus on achieving Industry 4.0 interoperability, advancing AI-driven intelligent disaster response, and adopting multi-objective optimization strategies balancing resilience, sustainability, and cost-effectiveness. This study provides a comprehensive overview of the field’s evolution and offers insights into strategic directions for future research and practical innovation.","author":[{"family":"Wang","given":"Jiao"},{"family":"Ma","given":"Yuchen"},{"family":"Li","given":"Rui"},{"family":"Zhang","given":"Suxian"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15132289","URL":"https://doi.org/10.3390/buildings15132289","source":"openalex"},{"id":"oa:W7131217370","type":"article-journal","title":"Digital Twin-Enabled Human–Robot Collaborative Assembly: A Review of Technical Systems, Application Evolution, and Future Outlook","abstract":"With the transition from Industry 4.0 to Industry 5.0, human–robot collaborative assembly (HRCA) has progressed from physical copresence to cognitive integration and knowledge sharing. Digital twins (DTs) serve as enabling technologies that connect physical and virtual spaces. Support is provided for dynamic, safe, and human-centered collaboration. This study presents a systematic review of the research progress and practical applications of DT-enabled HRCA. First, conceptual boundaries between HRCA and general human–robot collaboration (HRC) in manufacturing are defined. Core elements of DT-driven state perception, task planning, and constraint modeling are described. Second, four task-allocation paradigms are classified and summarized, including optimization-based, constraint satisfaction-based, data-driven intelligent, and large language model (LLM)-assisted approaches. Applicable scenarios are identified. Third, the effects of collaboration modes and interaction modalities on planning logic are analyzed. Collaboration modes are categorized as parallel, sequential, and tightly coupled. Interaction modalities are grouped into AR-based explicit interaction, implicit intention perception, and multimodal fusion. Fourth, cross-domain application characteristics and engineering bottlenecks are summarized. Target domains include precision assembly, disassembly and remanufacturing, and construction on-site operations. Finally, four core challenges are distilled, including dynamic uncertainty, multi-objective conflicts, human factor adaptation, and system integration. Four future directions are outlined: LLM-enabled adaptive planning, safety–efficiency co-optimization, personalized collaboration, and standardized integration. The proposed technology–application–challenge–outlook framework is intended to provide a theoretical reference and practical guidance for transitioning HRCA from laboratory prototypes to large-scale industrial deployment.","author":[{"family":"Nie","given":"Qingwei"},{"family":"Chen","given":"Jingtao"},{"family":"Liu","given":"Changchun"},{"family":"Zhao","given":"Zhen"},{"family":"Xu","given":"Haoxuan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/machines14030255","URL":"https://doi.org/10.3390/machines14030255","source":"openalex"},{"id":"oa:W4411472999","type":"article-journal","title":"Prioritising Critical Barriers to Digital Twins Implementation for Sustainable Smart Facility Management in the Built Environment: A Global Study","abstract":"Digital twins (DT) is a potent technology that could revolutionise the built environment towards sustainable smart facility management (FM). However, there are critical barriers that prior studies have not paid much attention to. Thus, this paper investigates the barriers to effective DT implementation for sustainable smart FM by exploring and prioritising them. This is achieved via a quantitative design comprising a literature review and a global expert survey. The design is further integrated with critical analysis and Pareto analysis. The study revealed an adequate level of agreement on the notion that DT if implemented effectively could achieve sustainable smart FM in the built environment. Further analysis revealed 30 critical barriers, of which 23 need to be prioritised, with the top four including “high cost of procuring hard digital technologies”, lack of technical know-how”, “lack of a systematic and comprehensive DT reference mode”, and “data safety and security”. Prioritising these critical barriers, professionals can become efficient decision-makers and policymakers in implementing DT for sustainable smart FM, realising the United Nations sustainable development goals 9, 11, 12, and 13. The study creates awareness of the critical barriers, generating an avenue for future researchers in the built environment to enhance the effective implementation of DT for sustainable smart FM. This could create a positive cost-benefit balance and unlock a future of operational excellence by carefully analysing DT’s unique needs and adopting a strategic measure to achieve sustainability in FM","author":[{"family":"Ghansah","given":"Frank"},{"family":"Udeaja","given":"Chika"},{"family":"Darko","given":"Amos"},{"family":"Lu","given":"Weisheng"},{"family":"Agyekummensah","given":"George"},{"family":"Antwi-Afari","given":"Prince"},{"family":"Twum-Ampofo","given":"Samuel"},{"family":"Ababio","given":"Benjamin"},{"family":"Debrah","given":"Caleb"}],"issued":{"date-parts":[[2025]]},"DOI":"10.7771/3067-4883.1911","URL":"https://doi.org/10.7771/3067-4883.1911","source":"openalex"},{"id":"oa:W4414676427","type":"article-journal","title":"Transforming resilience with predictive digital twin technologies","abstract":"This research examines the role of digital twin technology in enhancing disaster preparedness and response frameworks, with a focus on scenarios involving tsunamis, earthquakes, and floods. The primary objective was to evaluate how digital twins integrate real-time data, predictive modelling, and stakeholder engagement to enhance resilience. A systematic literature review was conducted in accordance with PRISMA guidelines, screening 342 studies and narrowing the selection to 120 high-quality sources that met the inclusion criteria. The analysis revealed that digital twin models improved forecast accuracy by an average of 28% compared to traditional disaster models, particularly in tsunami inundation mapping and urban flood simulations. Community engagement through interactive platforms was reported in 62% of the reviewed cases, with direct evidence of faster evacuation and resource allocation. Post-disaster recovery applications demonstrated measurable efficiency gains, reducing infrastructure restoration times by approximately 15%. However, data gaps and interoperability issues were identified as recurring limitations, contributing to an estimated error margin of 8–12% in predictive outputs. Overall, the findings confirm that digital twins offer a transformative pathway for proactive disaster management. While challenges in data quality and governance remain, their integration into national frameworks could significantly enhance both preparedness and resilience.","author":[{"family":"Elemure","given":"Ifeoluwa"},{"family":"Adeola","given":"Elizabeth"},{"family":"Ologun","given":"Adeyinka"},{"family":"Odesanya","given":"Owoade"},{"family":"Oluwasola","given":"Peter"}],"issued":{"date-parts":[[2025]]},"DOI":"10.30574/wjbphs.2025.23.3.0850","URL":"https://doi.org/10.30574/wjbphs.2025.23.3.0850","source":"openalex"},{"id":"oa:W4409905385","type":"article-journal","title":"Approach to implant monitoring and data processing with digital implant lifecycle management","abstract":"Reducing implant failure rates is a primary research objective, involving the development of monitoring methods, new treatment options, improved manufacturing strategies, and innovative implant designs. The goal is to enhance product efficiency across generations by using information from previous iterations to improve patient outcomes. This paper aims to create an information management framework for implant-related data to enhance lifecycle monitoring. Strategies from product lifecycle management, condition-based maintenance, and the digital twin are applied to medical implant monitoring. The proposed digital implant lifecycle management concept records and processes data throughout the implant's lifecycle, from design and manufacturing to use and disposal. Implemented using an XML-data structure in simulation software, the concept focuses on manufacturing and monitoring, using total knee arthroplasty as an example. A simulation study demonstrates that the digital twin of the implant can simulate various manufacturing scenarios to optimize process parameters, reducing planning efforts for individual implants by up to 28%. The presented concept significantly improves implant and patient monitoring, enhances communication among stakeholders, and allows for scenario simulations to predict implant behaviour and improve future generations.","author":[{"family":"Denkena","given":"Berend"},{"family":"Wichmann","given":"Marcel"},{"family":"Eggers","given":"Max"},{"family":"Emonde","given":"Crystal"},{"family":"Hurschler","given":"Christof"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-99975-w","URL":"https://doi.org/10.1038/s41598-025-99975-w","source":"europepmc"},{"id":"oa:W4416194326","type":"article-journal","title":"Development of a Hospital-at-Home Digital Twin for Patients With Frailty: Scoping Review","abstract":"Background: Increasing demand on health care systems requires innovative, transformative solutions for efficient, high-quality care. One promising approach is digital twin (DT) technology, which leverages real-time data to create dynamic, virtual representations of a physical entity (individuals or space) to anticipate future scenarios and support care decisions. Although DTs have been explored in various sectors, their application in hospital at home (HaH), which delivers acute-level care in home environments, remains unexplored. Objective: This review bridges a critical knowledge gap, examining existing evidence on DT-enabling tools to manage patients with frailty in home settings. This will identify the underpinning architectural components required to inform an HaH-DT system supporting clinical decision-making. Methods: We searched 6 electronic databases and gray literature for primary English-language studies published between January 2019 and September 2025. Included studies reported on the monitoring or management of patients with frailty within their own home. Information was charted on a predefined data collection form to answer the research objectives. Review articles, protocols, and conference abstracts were excluded. Results: We included 69 reports: 54% (37/69) used quantitative approaches, and 36% (25/69) were pilot or feasibility studies. Reports were analyzed for DT-enabling tools and systematically mapped across the proposed 5-layered DT architecture: sensing, communication, storage, analytics, and visualization. DT layer taxonomies, interconnections, and classifications of data types collected (eg, about the patient, home environment, use of medical equipment) are presented. This evidence identifies DT-enabling tools for a variety of functions and a range of sensing technologies (eg, wearable-based passive sensing, active physiological sensors, ambient sensors detecting motion or environmental changes). The most prevalent communication modes were wireless and network-based (36/112, 32.1%), the majority (12/36, 33%) using Bluetooth. Better understanding of data management, particularly secure storage, is required within local health care systems. The emerging potential of predictive and prescriptive analytics for risk prediction, clinical decision-making, or activation of alert-triggered health interventions by clinicians was mapped. Analytics methods are currently largely descriptive. Advanced methods such as prescriptive analytics for recommendations of an optimal course of action and diagnostic analytics that highlight why a situation has occurred are lacking. DT-enabling tools demonstrate patient-centered benefits, including enhanced motivation, reassurance, and personalized care. Concerns include device accuracy, user acceptability, and implications for carers and organizational workflows. Conclusions: This review is among the first to systematically map DT-enabling tools to inform a potential HaH DT for patients with frailty, organized by a 5-layered conceptual model. Understanding these architectural layers provides the foundations for stakeholders to advance research and development in areas where there are knowledge gaps and consider how an HaH DT can effectively operate within current health care systems. Leveraging technology-enabled care in complex home-based settings provides great potential to deliver safer, personalized, timely care.","author":[{"family":"Yahya","given":"Faiza"},{"family":"Cooper","given":"Matthew"},{"family":"Saif","given":"Wahib"},{"family":"Kassem","given":"Mohamad"},{"family":"Nazar","given":"Hamde"}],"issued":{"date-parts":[[2025]]},"DOI":"10.2196/81510","URL":"https://doi.org/10.2196/81510","source":"openalex"},{"id":"oa:W7134267770","type":"article-journal","title":"Digital Media Use and Child Health and Development","abstract":"Importance: This systematic review and meta-analysis synthesized global longitudinal studies to estimate associations between social media, video games, and other digital media use with health and developmental outcomes in children and adolescents. Objective: To provide a meta-analytic synthesis of evidence on digital media use and health and developmental outcomes among individuals aged 0 to 18 years. Data Sources: This review was preregistered with PROSPERO, MEDLINE, PsycINFO, EMBASE, and ERIC databases and gray literature were searched from 2000 to 2024. Study Selection: Inclusion criteria were English-language longitudinal studies of participants aged 0 to 18 years reporting quantitative associations between digital media use and health or developmental outcomes. Data Extraction and Synthesis: Following PRISMA guidelines, 153 studies (115 cohorts, 1072 effect sizes) from 18 933 articles met criteria for quantitative synthesis. Random-effects meta-analyses estimated pooled correlations (r) with 95% CIs. Heterogeneity and moderators (age, sex, measurement method, follow-up duration, year of exposure) were examined. Study quality was assessed using the National Institutes of Health's Quality Assessment Tool. These data were analyzed from February 2025 to August 2025. Main Outcomes and Measures: Primary outcomes were socialemotional, cognitive, physical and motor health, and development associations. Results: A total of 153 studies (115 cohorts, 1072 effect sizes) with 18 933 participants met criteria for quantitative synthesis. Study participant ages ranged from 2 to 19 (mean [SD], 12.81 [2.79]) years, with 53.8% female and 46.2% male. Most studies were conducted in Europe (62 [40.5%]) and North America (60 [39.2%]), followed by Asia (22 [14.4%]), Australia (5 [3.3%]), and Latin America (1 [0.7%]). Social media use was associated with higher depression, externalizing and internalizing behaviors, self-injurious thoughts, problematic internet use, and substance use (r = 0.09; 95% CI, 0.06-0.12 to r = 0.21; 95% CI, 0.13-0.29) and also with lower academic achievement, poorer self-perception, and less positive development (r = -0.14; 95% CI, -0.26 to -0.01 to r = -0.07; 95% CI, -0.11 to -0.02). Video gaming was associated with higher aggression and externalizing behaviors (r = 0.16; 95% CI, 0.09-0.23 and r = 0.17; 95% CI, 0.07-0.26, respectively) and higher attention/executive functioning (r = 0.10; 95% CI, 0.03-0.16). Other digital media use, including digital device use and messaging/communication media, was associated with depression (r = 0.05; 95% CI, 0.00-0.09 to r = 0.12; 95% CI, 0.02-0.22). Associations between social media and depression were stronger in early adolescence (β = 0.09) and with self or parent-reported outcomes (β = 0.09); associations between social media and positive development were stronger with objective exposure measurement (β = 0.08). More recent social media exposure years showed stronger associations with substance use (β = 0.10). Conclusions and Relevance: In this systematic review and meta-analysis, digital media use was consistently associated with risks to child and adolescent health and development, particularly for social media. These findings highlight the need for targeted, multifaceted policies and interventions to mitigate potential harms from digital media exposure.","author":[{"family":"Teague","given":"Samantha"},{"family":"Somoray","given":"Klaire"},{"family":"Shatte","given":"Adrian"},{"family":"Miller","given":"Daniel"},{"family":"Moss","given":"Kristian"},{"family":"Crawford","given":"Andrew"},{"family":"Wildman","given":"Harrison"},{"family":"Kayal","given":"Diana"},{"family":"Hutchinson","given":"DCS"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1001/jamapediatrics.2026.0085","URL":"https://doi.org/10.1001/jamapediatrics.2026.0085","source":"openalex"},{"id":"oa:W4407630304","type":"article-journal","title":"Digital servitization business typologies in the manufacturing sector","abstract":"Digital servitization business typologies in the manufacturing sectorManufacturing companies undergo a transformative journey in digital servitization, necessitating strategic, tactical, and operational shifts.The existing literature outlines the best practices on this process and examines challenges and opportunities through qualitative empirical evidence.We enrich the investigation through a quantitative explanatory research approach, employing a survey targeting manufacturing companies from multiple countries.Analyzing the responses using cluster analysis, we found three business typologies with specific behaviors related to digital servitization: digital experimentalists, strategic pioneers, and digital servitization novices.This research contributes valuable insights into the varied behaviors adopted by manufacturing firms in navigating the digital servitization landscape.","author":[{"family":"Arioli","given":"Veronica"},{"family":"Pezzotta","given":"Giuditta"},{"family":"Romero","given":"David"},{"family":"Tecnológico De Monterrey","given":"Mexico"},{"family":"Adrodegari","given":"Federico"},{"family":"Sala","given":"Roberto"},{"family":"Rapaccini","given":"Mario"},{"family":"Saccani","given":"Nicola"},{"family":"Marjanović","given":"Uglješa"},{"family":"Rakić","given":"Slavko"},{"family":"West","given":"Shaun"},{"family":"Stoll","given":"Oliver"},{"family":"Wiesner","given":"Stefan"},{"family":"Bertoni","given":"Marco"},{"family":"Odriozola","given":"Urko"},{"family":"Pirola","given":"Fabiana"},{"family":"Gaiardelli","given":"Paolo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.24867/ijiem-378","URL":"https://doi.org/10.24867/ijiem-378","source":"openalex"},{"id":"oa:W7128396232","type":"article-journal","title":"Prognosis prediction of patients with disorders of consciousness based on digital twin brain models","abstract":"BACKGROUND: The accurate prediction of prognosis in patients with disorders of consciousness (DOC) is a significant challenge in clinical practice. Some studies based on traditional electroencephalography (EEG) features have shown potential for DOC prognosis. However, the underlying mechanisms behind the recovery of patients with DOC still lack in-depth research. METHODS: In this study, we used mathematical tools to construct digital twin brain models (DTBM) for DOC patients with different outcomes. Then, we trained a support vector machine classifier using model parameters and modal controllability features to distinguish between DOC patients with different outcomes, and assessed the importance of these features. Finally, we used a support vector machine regressor to predict the Coma Recovery Scale-Revised (CRS-R) score at 6-month follow-up. RESULTS: The results showed that the prognosis model based on local model parameters and modal controllability features achieved better performance (AUC = 90.22%, F-score = 86.00%, SEN = 84.31%, SPE = 91.43%) than the prognosis models based on some traditional EEG features. Additionally, a positive prognosis is associated with lower levels of inhibitory gain, higher levels of excitatory gain and modal controllability, particularly in brain regions within the frontoparietal network. In 74% and 70% of UWS and MCS patients, the MAE between the predicted CRS-R score and the actual CRS-R score was less than 5. CONCLUSIONS: Overall, our study contributes to enriching the neuromarkers associated with DOC prognosis and further elucidates the neural mechanisms of consciousness recovery.","author":[{"family":"Yan","given":"Shaoting"},{"family":"Li","given":"Qing"},{"family":"Li","given":"Ruiqi"},{"family":"Zhang","given":"Lipeng"},{"family":"Zhang","given":"Rui"},{"family":"Chen","given":"Mingming"},{"family":"Li","given":"Meng"},{"family":"Li","given":"Runtao"},{"family":"Zhang","given":"Hui"},{"family":"Shi","given":"Li"},{"family":"Hu","given":"Y"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1186/s12984-026-01905-y","URL":"https://doi.org/10.1186/s12984-026-01905-y","source":"openalex"},{"id":"oa:W7125214116","type":"article-journal","title":"Dynamic Modeling and Calibration of an Industrial Delayed Coking Drum Model for Digital Twin Applications","abstract":"The increasing share of heavy and high-sulfur crude oils in refinery feed slates worldwide highlights the need for models of delayed coking units (DCUs) that are both physically meaningful and computationally efficient. In this study, we develop and calibrate a simplified yet dynamic one-dimensional model of an industrial coke drum intended for integration into digital twin frameworks. The model includes a three-phase representation of the drum contents, a temperature-dependent global kinetic scheme for vacuum residue cracking, and lumped descriptions of heat transfer and phase holdups. Only three physically interpretable parameters—the kinetic scaling factors for distillate and coke formation and an effective wall temperature—were calibrated using routinely measured plant data, namely the overhead vapor and drum head temperatures and the final coke bed height. The calibrated model reproduces the temporal evolution of the top head and overhead temperatures and the final bed height with mean relative errors of a few percent, while capturing the more complex bottom-head temperature dynamics qualitatively. Scenario simulations illustrate how the coking severity (represented here by the effective wall temperature) affects the coke yield, bed growth, and cycle duration. Overall, the results indicate that low-order dynamic models can provide a practical balance between physical fidelity and computational speed, making them suitable as mechanistic cores for digital twins and optimization tools in delayed coking operations.","author":[{"family":"Bukhtoyarov","given":"VV"},{"family":"Nekrasov","given":"Ivan"},{"family":"Gorodov","given":"Alexey"},{"family":"Tynchenko","given":"Yadviga"},{"family":"Коленчуков","given":"ОА"},{"family":"Buryukin","given":"FA"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/pr14020375","URL":"https://doi.org/10.3390/pr14020375","source":"openalex"},{"id":"oa:W4417282702","type":"article-journal","title":"IoT-Based Digital Twin for Freshwater Pollution Monitoring: A Use Case of River Derwent","abstract":"This paper presents an IoT-enabled digital twin framework designed to enhance real-time monitoring and management of freshwater pollution. The framework integrates distributed IoT sensors to collect high-resolution data on dissolved oxygen (DO), temperature, and pollution dynamics, enabling the timely detection of ecological stressors. A four-layer architecture, comprising device, virtualisation, aggregation, and service layers, facilitates scalable data processing, visualisation, and stakeholder engagement. Key contributions include empirical validation of the IoT-enabled digital twin framework to monitor fresh water pollution, a modular system for anomaly detection and historical trend analysis, and actionable insights derived from spatially distributed edge nodes. The results highlight the inverse correlation between temperature and DO levels, disrupted during storm events by abrupt oxygen crashes (e.g. below 4 mg/l) and the critical role of edge node deployment in the river bed. The digital twin monitoring, recollection, and predictive modules collectively support proactive water quality management, identifying pollution gradients and seasonal patterns. Testing and evaluation on the Derwent river shows the system’s practical efficacy in reducing environmental risks and informing sustainable interventions.","author":[{"family":"Jarwar","given":"Muhammad"},{"family":"Hasan","given":"Najam"},{"family":"Boisvert","given":"Charles"},{"family":"Wheway","given":"Paul"},{"family":"Faulks","given":"Michael"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/pimrc62392.2025.11274979","URL":"https://doi.org/10.1109/pimrc62392.2025.11274979","source":"openalex"},{"id":"oa:W4406481350","type":"article-journal","title":"Dynamic Dual‐Level Overcurrent Protection Scheme for Distributed Energy Resource Networks Using Digital Twins Technology","abstract":"The integration of distributed generators (DGs), particularly renewable energy sources, into conventional distribution networks (DNs) presents significant protection challenges. This study introduces a novel digital twins‐based overcurrent relay (OCR) protection scheme with dynamic dual‐level characteristic curves for microgrids. By utilizing advanced technologies such as digital‐twin technology and hardware‐in‐the‐loop (HIL) testing, the proposed scheme enhances fault management and relay coordination. Key contributions of this work include the integration of advanced technologies and dynamic OCR settings, using digital‐twin technology and HIL testing to provide real‐time insights and robust validation under practical conditions. Additionally, the research thoroughly examines protection strategies for both grid‐connected and islanded modes, ensuring reliable operation during faults or grid failures. The study’s findings show substantial improvements over traditional OCR methods. The traditional OCR recorded a total tripping time of 14.87 s, while the dual‐level OCR reduced it to 8.97 s. The results highlight the proposed scheme’s enhanced sensitivity, faster fault isolation capability, and overall superior performance, providing a robust and reliable protection scheme for modern power distribution systems. Further testing results for the digital‐twin OCR, comparing both the digital simulation twin relay and the physical twin relay for the traditional single‐level OCR scheme and the proposed dual‐level scheme, provide valuable insights into the performance and reliability of these protection strategies. The close alignment between the simulation and physical results highlights the robustness and precision of the dual‐level scheme.","author":[{"family":"Alasali","given":"Feras"},{"family":"Elnaily","given":"Naser"},{"family":"Mustafa","given":"Haytham"},{"family":"Loukil","given":"Hassen"},{"family":"Saad","given":"Saad"},{"family":"Saidi","given":"Abdelaziz"},{"family":"Holderbaum","given":"William"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1155/etep/9428867","URL":"https://doi.org/10.1155/etep/9428867","source":"openalex"},{"id":"oa:W4416226677","type":"article-journal","title":"Digital Regulatory Governance: The Role of RegTech and SupTech in Transforming Financial Oversight and Administrative Capacity","abstract":"Rapid digitalization is transforming how public and private institutions manage regulation, compliance, and supervision. This paper explores the rise of Regulatory Technology (RegTech) and Supervisory Technology (SupTech) as instruments of digital regulatory governance and examines their implications for administrative efficiency, defined as the optimization of regulatory and supervisory processes through automation and data-driven coordination, institutional capacity, and policy innovation. Using a systematic literature review of 59 peer-reviewed studies published between 2017 and 2025, the study identifies how RegTech enhances compliance management and risk control in financial institutions, while SupTech enables regulators to improve supervisory agility, transparency, and real-time oversight. The findings show that these technologies create significant administrative value by streamlining reporting, enhancing accountability, and strengthening governance networks across the public–private interface. However, adoption is constrained by cybersecurity vulnerabilities, algorithmic opacity, regulatory fragmentation, and organizational resistance. To address these issues, the study proposes an integrated governance framework that maps opportunities and barriers across compliance, risk, technology, and institutional coordination. By synthesizing fragmented evidence, this research contributes to the field of administrative sciences by positioning RegTech and SupTech not only as technical innovations but as transformative tools of digital public administration and regulatory modernization.","author":[{"family":"Bagherifam","given":"Niloufar"},{"family":"Naghdi","given":"Sajjad"},{"family":"Ahmadian","given":"Vahid"},{"family":"Fazlzadeh","given":"Alireza"},{"family":"Shishehgarkhaneh","given":"Milad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/ijfs13040217","URL":"https://doi.org/10.3390/ijfs13040217","source":"openalex"},{"id":"oa:W4410699681","type":"article-journal","title":"Digital twin-driven method for determining wind force coefficients of a bridge deck section","abstract":"Wind force coefficients are important parameters for aerostatic and aerodynamic analyses in wind-resistant design of a long-span bridge. Wind force coefficients of long-span bridges are currently obtained through wind tunnel tests or computational fluid dynamics (CFD) simulations. Given that limitations and uncertainties exist in both methods, this study proposes a digital twin-driven method for providing more accurate predictions of wind force coefficients of a streamlined bridge deck. The sectional model of the bridge deck tested in a wind tunnel is taken as a physical model, while its virtual model is established using CFD simulation. The test results collected from the physical model are fused with the virtual model using polynomial regression algorithms to update the virtual model into a digital twin. The developed digital twin is employed to conduct an in-depth analysis of blockage effects and provide more accurate wind force coefficients. A global digital twin is then developed based on individual digital twins and Kriging interpolation to provide continuous wind force coefficients within a range of wind attack angles from -12° to 12°. This global digital twin is finally applied for the aerostatic analyses of the bridge. The results show that the digital twin-driven method can provide more accurate prediction than wind tunnel tests or CFD simulations.","author":[{"family":"Li","given":"Hao"},{"family":"Xu","given":"You"},{"family":"Liao","given":"Haili"},{"family":"Huang","given":"Lin"},{"family":"Wang","given":"Qi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/19942060.2025.2501389","URL":"https://doi.org/10.1080/19942060.2025.2501389","source":"openalex"},{"id":"oa:W4414359196","type":"article-journal","title":"Leveraging FMMEA for Digital Twin Development: A Case Study on Intelligent Completion in Oil and Gas","abstract":"The implementation of Digital Twins (DTs) represents a significant advancement for the Oil and Gas (O&G) industry. A DT virtually replicates a physical asset, enabling the monitoring, diagnosis, prediction, and optimization of its outcomes. Since failures are undesirable outcomes, investigations into potential failure modes are often integrated into the development. Traditional methods, such as Failure Modes and Effects Analysis (FMEA) and Failure Mode, Effects, and Criticality Analysis (FMECA), are widely used to identify, assess, and mitigate risks. However, there is still a lack of specific guidelines for studying potential failures in complex systems. This article introduces a framework for Failure Modes, Mechanisms, and Effects Analysis (FMMEA) as a tool for identifying and assessing failures in early DT development. Exploring failure mechanisms is highlighted as essential for effective prediction and management We also propose adjustments to FMMEA for complex, predictable systems, such as using a DPR (Detectable Priority Risk) instead of RPN (Risk Priority Number) for prioritizing risks. A comprehensive case illustrates the framework's application in developing a DT for an intelligent completion system in a major O&G company. The approach enables mechanism-oriented failure analysis and more detailed prognostic health management, providing greater transparency in the failure identification process.","author":[{"family":"Silva","given":"Nelson"},{"family":"Pontes","given":"Flavia"},{"family":"Silva","given":"Mariana"},{"family":"Fialho","given":"Breno"},{"family":"Delesposte","given":"Jamile"},{"family":"Souza","given":"Dalton"},{"family":"Chaves","given":"Luiz"},{"family":"Cardoso","given":"Rodolfo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/s25185846","URL":"https://doi.org/10.3390/s25185846","source":"openalex"},{"id":"oa:W7117662435","type":"article-journal","title":"Digital‐Twin‐Enabled, Time‐Aware Anomaly Detection for Industrial Cyber‐Physical Systems","abstract":"ABSTRACT Industrial cyber‐physical systems (ICPS) operate under tight dynamics and strict safety constraints, where anomalous behaviour unfolds over time and requires operator‐actionable context. Although recent learning‐based detectors have improved point‐wise accuracy, deployment realism remains limited: evaluations often ignore temporal leakage, underreport event‐level performance and provide little support for situational awareness in the control room. This work introduces a digital‐twin‐enabled, time‐aware anomaly detection framework that couples a temporal LSTM–DNN classifier with data‐driven thresholding and an operator‐facing twin for live triage. The digital twin (web‐based React frontend with a Flask backend) mirrors plant state in real time to visualise alerts, hypothesise counterfactuals and accelerate response. Our aims are threefold: (i) detect attacks at the event level with low delay; (ii) surface explanations and sensor‐level rules that are actionable; and (iii) evaluate under realistic temporal protocols and imbalance. Methodologically, we combine sequence modelling with per‐sensor operating ranges learnt from unsupervised Isolation‐Forest analysis to capture abrupt shifts and multivariate inconsistencies; the twin surfaces both sequence scores and rule violations for human verification. On the SWaT benchmark, the system detected 31/41 attack events overall, including 22/23 SSSP (single‐stage single‐point), 3/6 SSMP (single‐stage multi‐point), 4/4 MSSP (multi‐stage single‐point) and 2/3 MSMP (multi‐stage multi‐point), demonstrating broad coverage across attack taxonomies. At the instance level, the classifier attained 94.6% accuracy, 99.8% precision, 94.8% recall and a 97.2% F1‐score on the held‐out test set, highlighting strong detection capability under class imbalance (specificity 18.4%). In sum, the contributions are (1) a digital‐twin‐enabled, time‐aware detection pipeline that integrates temporal learning with data‐driven operating envelopes; (2) event‐level evaluation and reporting aligned with operational practice; and (3) quantitative evidence that coupling sequence models with interpretable rules yields high precision and broad attack coverage while exposing residual specificity gaps that guide future cost‐sensitive calibration and threshold optimisation. Overall, DC‐GLNet (i) jointly exploits spectrogram‐level (SFEB) and ENF‐specific (ENFB) representations via a KAN classifier, (ii) incorporates robust harmonic selection and enhancement (RFA/HRFA) tailored to short, noisy clips and (iii) achieves > 90% accuracy on 5‐min clips, outperforming SVM, XGBoost and a NAS baseline by more than 7 percentage points on both SP‐CUP2016 and China‐Online‐Data benchmarks.","author":[{"family":"Mbasso","given":"Wulfran"},{"family":"Harrison","given":"Ambe"},{"family":"Dagal","given":"Idriss"},{"family":"Jangir","given":"Pradeep"},{"family":"Liu","given":"Zhe"},{"family":"Smerat","given":"Aseel"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/dgt2.70016","URL":"https://doi.org/10.1049/dgt2.70016","source":"openalex"},{"id":"oa:W4409449331","type":"article-journal","title":"Enhancing clinical outcome predictions through effective sample size evaluation in graph-based digital twin modeling","abstract":"Digital twins in healthcare offer an innovative approach to precision diagnosis, prognosis, and treatment. SynTwin, a novel computational methodology to generate digital twins using synthetic data and network science, has previously shown promise for improving prediction of breast cancer mortality. In this study, we validate SynTwin using population-level data for different cancer types from the Surveillance, Epidemiology, and End Results (SEER) program from the National Cancer Institute (USA). We assess its predictive accuracy across cancer types of varying sample sizes (n = 1,000 to 30,000 records), mortality rates (35% to 60%), and study designs, revealing insights into the strengths and limitations of digital twins derived from synthetic data in mortality prediction. We also evaluate the effect of sample size (n = 1,000 to 70,000 records) on predictive accuracy for selected cancers (non-Hodgkin lymphoma, bladder, and colorectal cancers). Our results indicate that for larger datasets (n > 10,000) including digital twins in the nearest network neighbor prediction model significantly improves the performance compared to using real patients alone. Specifically, AUROCs ranged from 0.828 to 0.884 for cancers such as cervix uteri and ovarian cancer with digital twins, compared to 0.720 to 0.858 when using real patient data. Similarly, among the selected three cancers, AUROCs using digital twins exceeded AUROCs using real patients alone by at least 0.06 with narrowing variance in performance as the sample size increased. These results highlight the benefit of network-based digital twins, while emphasizing the importance of considering effective sample size when developing predictive models like SynTwin.","author":[{"family":"Li","given":"Xi"},{"family":"Chang","given":"Jui"},{"family":"Venkatesan","given":"Mythreye"},{"family":"Wang","given":"Zhiping"},{"family":"Moore","given":"Jason"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1186/s13040-025-00446-9","URL":"https://doi.org/10.1186/s13040-025-00446-9","source":"openalex"},{"id":"oa:W4411545614","type":"article-journal","title":"Wheels turning: CHO cell modeling moves into a digital biomanufacturing era","abstract":"Recent advancements in biologics production using CHO cells have been partly driven by improved understanding of how variations in the cell culture environment influence cellular metabolism, productivity, and the attributes of the final product. In-silico models serve a valuable role in mapping the effects of various process parameters and media changes on cellular response. Advances in technologies such as data-driven analysis, self-learning systems, and digital twins are reinforcing progress toward smart manufacturing, enabling the real-time control of production processes. Furthermore, kinetic, and constraint-based mechanistic modeling, combined with omics approaches, are becoming increasingly incorporated into the bioprocess development and manufacturing innovation ecosystem. In this review, we cover CHO central metabolism as a foundation for mechanistic modeling and extend the discussion to include various mechanistic modeling approaches, highlighting the incorporation of glycosylation and secretory pathways. Multi-omics approaches provide a deeper understanding of intracellular processes and the dynamic interactions between product quality and pathways. In parallel, to achieve the Industry 4.0 vision of digitalization and machine learning techniques are finding wider adoption in biopharmaceutical development. We discuss the potential applications of these techniques for predictions, inference, optimization, and control. The role of big data analytics and artificial intelligence methods in reinforcing progress towards smart manufacturing and enabling real-time control of production processes is discussed. Finally, we summarize the application of machine learning and hybrid models to CHO bioprocesses, aiming to develop and manufacture drugs more efficiently and at a lower cost for patients.","author":[{"family":"Ranpura","given":"Sandeep"},{"family":"Maralingannavar","given":"Vishwanathgouda"},{"family":"Gheorghe","given":"Alexandra"},{"family":"Ma","given":"Edward"},{"family":"Morrissey","given":"James"},{"family":"Betenbaugh","given":"Michael"},{"family":"Demirhan","given":"Deniz"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.csbj.2025.06.035","URL":"https://doi.org/10.1016/j.csbj.2025.06.035","source":"openalex"},{"id":"oa:W4413352791","type":"article-journal","title":"Digital Twins and Big Data in the Metaverse: Addressing Privacy, Scalability, and Interoperability with AI and Blockchain","abstract":"This paper explores the integration of digital twin technologies and big data in the metaverse to improve urban traffic management. It highlights the importance of technology in mirroring and augmenting our physical and virtual worlds. This study examines how big data and digital twin technologies merge in the metaverse to improve traffic management. Our work applies artificial intelligence (AI) and blockchain technologies to address concerns about privacy, scalability, and interoperability. In a literature review and case study on traffic management, we outline how big data analytics and digital twins can increase operational and decision-making efficiency. This study aims to elucidate the transformative potential of such technologies for urban transport and postulates future areas of social, regulatory, and environmental research gaps.","author":[{"family":"Li","given":"Ruoxuan"},{"family":"Abdalla","given":"Hemn"},{"family":"Gheisari","given":"Mehdi"},{"family":"Rabieidastjerdi","given":"Hamidreza"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/ijgi14080318","URL":"https://doi.org/10.3390/ijgi14080318","source":"openalex"},{"id":"oa:W4411260577","type":"article-journal","title":"In silico estimation of thrombogenic risk after left atrial appendage excision: Towards digital twins in atrial fibrillation","abstract":"BACKGROUND & AIM: The left atrial appendage (LAA) is a highly variable, pouch-like structure in the left atrium prone to thrombus formation, especially in atrial fibrillation (AF) patients. In silico cardiac models can help characterize the LAA's complex morphology and hemodynamics, aiding in identifying pro-thrombotic areas. This study assessed atrial hemodynamics and thrombus formation risk after LAA excision and compared with optimal synthetic excisions and occluder placements in high thrombogenic-risk cases. METHODS: We included 33 patients from the MARK-AF study who had persistent AF and underwent excision of the LAA. We quantified the morphological characteristics of the post-excision LAA remnant. With patient-specific atrial geometries and boundary conditions, in silico blood flow simulations were performed. For each patient, we quantified multiple in silico indices to characterize blood flow patterns and identify thrombogenic regions. We performed an in silico comparison of different LAA treatment approaches. RESULTS: In our cohort, 25/33 (76 %) of patients had a post-excision, protruding LAA remnant (LAA depth >10 mm). In silico simulations indicated that patients with a protruding remnant more frequently showed unfavorable values for in silico indices associated with high thrombogenic risk at the excision site. However, a prominent LAA remnant was not the only factor associated with a high thrombogenic risk. An optimal excision or optimal occluder device placement reduced thrombus formation risk. CONCLUSION: The combination of LAA remnant morphology and hemodynamics contributed to thrombus formation risk. Advanced in silico simulations uniquely enabled the comparison of different therapies, until now only centered on device occluders, contributing to digital twins in AF.","author":[{"family":"Albors","given":"Carlos"},{"family":"Terreros","given":"Nerea"},{"family":"Saiz-Vivó","given":"Marta"},{"family":"Zappala","given":"Pietro"},{"family":"Terpstra","given":"MM"},{"family":"Olivares","given":"Andy"},{"family":"Planken","given":"RN"},{"family":"Boven","given":"Wim"},{"family":"Driessen","given":"Antoine"},{"family":"Groot","given":"Joris"},{"family":"Cámara","given":"Óscar"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.compbiomed.2025.110483","URL":"https://doi.org/10.1016/j.compbiomed.2025.110483","source":"openalex"},{"id":"oa:W4414317354","type":"article-journal","title":"Predicting Building Height from Footprint and Urban Planning information for Digital Twin Generation","abstract":"Abstract. Accurate building height data is essential for constructing realistic and analytically useful 3D city models within digital twin systems. However, such data are often incomplete, particularly in small to medium-sized cities. This study presents a machine learning-based approach to predict building heights by integrating multi-source urban data, including building footprints, zoning regulations, and roof-type classifications. To enhance prediction accuracy, we clustered zoning types by height profiles and trained models separately for each group. We evaluated three regression algorithms—Random Forest (RFR), Support Vector Regression (SVR), and XGBoost—using stratified sampling and cross-validation. Among them, RFR achieved the highest overall accuracy, particularly in homogeneous zoning areas (R2 = 0.67), while SVR showed lower generalizability. The proposed model has been implemented in an open-source “3D City Model Generation Simulator,” enabling automated LOD3-level urban model generation using only remote sensing and street-view inputs. This work contributes a scalable and cost-effective solution for urban digital twin applications in data-sparse environments.","author":[{"family":"Ma","given":"Jin"},{"family":"Zhao","given":"Chenbo"},{"family":"Ogawa","given":"Yoshiki"},{"family":"Sekimoto","given":"Yoshihide"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/isprs-archives-xlviii-4-w15-2025-107-2025","URL":"https://doi.org/10.5194/isprs-archives-xlviii-4-w15-2025-107-2025","source":"openalex"},{"id":"oa:W4410308092","type":"article-journal","title":"AiWatch: A Distributed Video Surveillance System Using Artificial Intelligence and Digital Twins Technologies","abstract":"The primary purpose of video surveillance is to monitor public indoor areas or the boundaries of secure facilities to safeguard them against theft, unauthorized access, fire, and various other potential threats. Security cameras, equipped with integrated video surveillance systems, are strategically placed throughout critical locations on the premises, allowing security personnel to observe all areas for specific behaviors that may signal an emergency or a situation requiring intervention. A significant challenge arises from the fact that individuals cannot maintain focus on multiple screens simultaneously, which can result in the oversight of crucial incidents. In this regard, artificial intelligence (AI) video analytics has become increasingly prominent, driven by numerous practical applications that include object identification, detection of unusual behavior patterns, facial recognition, and traffic management. Recent advancements in this technology have led to enhanced functionality, remarkable accuracy, and reduced costs for consumers. There is a noticeable trend towards upgrading security frameworks by incorporating AI into pre-existing video surveillance systems, thus leading to modern video surveillance that leverages video analytics, enabling the detection and reporting of anomalies within mere seconds, thereby transforming it into a proactive security solution. In this context, the AiWatch system introduces digital twin (DT) technology in a modern video surveillance architecture to facilitate advanced analytics through the aggregation of data from various sources. By exploiting AI and DT to analyze the different sources, it is possible to derive deeper insights applicable at higher decision levels. This approach allows for the evaluation of the effects and outcomes of actions by examining different scenarios, hence yielding more robust decisions.","author":[{"family":"Ferone","given":"Alessio"},{"family":"Maratea","given":"Antonio"},{"family":"Camastra","given":"Francesco"},{"family":"Ciaramella","given":"Angelo"},{"family":"Staiano","given":"Antonino"},{"family":"Lettiero","given":"Marco"},{"family":"Polizio","given":"Angelo"},{"family":"Lombardi","given":"Francesco"},{"family":"Spoleto","given":"Antonio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/technologies13050195","URL":"https://doi.org/10.3390/technologies13050195","source":"openalex"},{"id":"oa:W4412384892","type":"article-journal","title":"Early Warning of Infectious Disease Outbreaks Using Social Media and Digital Data: A Scoping Review","abstract":"Background and Aim: Digital surveillance, which utilizes data from social media, search engines, and other online platforms, has emerged as an innovative approach for the early detection of infectious disease outbreaks. This scoping review aimed to systematically map and characterize the methodologies, performance metrics, and limitations of digital surveillance tools compared to traditional epidemiological monitoring. Methods: A scoping review was conducted in accordance with the Joanna Briggs Institute and PRISMA-SCR guidelines. Scientific databases including PubMed, Scopus, and Web of Science were searched, incorporating both empirical studies and systematic reviews without language restrictions. Key elements analyzed included digital sources, analytical algorithms, accuracy metrics, and validation against official surveillance data. Results: The reviewed studies demonstrate that digital surveillance can provide significant lead times (from days to several weeks) compared to traditional systems. While performance varies by platform and disease, many models showed strong correlations (r > 0.8) with official case data and achieved low predictive errors, particularly for influenza and COVID-19. Google Trends and X (formerly Twitter) emerged as the most frequently used sources, often analyzed using supervised regression, Bayesian models, and ARIMA techniques. Conclusions: While digital surveillance shows strong predictive capabilities, it faces challenges related to data quality and representativeness. Key recommendations include the development of standardized reporting guidelines to improve comparability across studies, the use of statistical techniques like stratification and model weighting to mitigate demographic biases, and leveraging advanced artificial intelligence to differentiate genuine health signals from media-driven noise. These steps are crucial for enhancing the reliability and equity of digital epidemiological monitoring.","author":[{"family":"Liscano","given":"Yamil"},{"family":"Arrieta","given":"Luis"},{"family":"Montenegro","given":"John"},{"family":"Prieto-Alvarado","given":"Diego"},{"family":"Ordóñezllanos","given":"Jordi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/ijerph22071104","URL":"https://doi.org/10.3390/ijerph22071104","source":"openalex"},{"id":"oa:W4413411676","type":"article-journal","title":"Research on Value-Chain-Driven Multi-Level Digital Twin Models for Architectural Heritage","abstract":"As a national treasure, architectural heritage carries multiple value dimensions such as history, technology, art, and culture. With the increasing demand for architectural heritage protection and utilization, the traditional static digital model of architectural heritage based on geometric expression can no longer meet the practical application of multi-stage and multi-level scenarios. To this end, this paper proposes a value-chain-driven multi-level digital twin model of architectural heritage. Based on the three-stage logic of protection, management, and dissemination of value-chain classification, it integrates four types of models: geometry, physics, rules, and behavior. Combined with different hierarchical application levels, the digital model of architectural heritage is refined into a VCLOD (Value-Chain-Driven Level of Detail) detail hierarchy system to achieve a unified expression from spatial form restoration to intelligent response. Through the empirical application of three typical scenarios: the full-area guided tour of the Forbidden City, the exhibition curation of the central axis and the preventive protection of the Meridian Gate, the model shows the following specific results: (1) the efficiency of tourist guidance is improved through real-time personalized path planning; (2) the exhibition planning and visitor experience are improved through dynamic monitoring and interactive management of the exhibition environment; (3) the predictive analysis and preventive protection measures of structural safety are realized, effectively ensuring the structural safety of the Meridian Gate. The research results provide a theoretical basis and practical support for the systematic expression and intelligent evolution of digital twins of architectural heritage.","author":[{"family":"Wang","given":"Guoli"},{"family":"Wang","given":"Yaofeng"},{"family":"Guo","given":"Ming"},{"family":"Liang","given":"Xuanshuo"},{"family":"Fu","given":"Yang"},{"family":"Li","given":"Hongda"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15172984","URL":"https://doi.org/10.3390/buildings15172984","source":"openalex"},{"id":"oa:W4413791612","type":"article-journal","title":"Data-Driven Method for Robotic Trajectory Error Prediction and Compensation Based on Digital Twin","abstract":"In addressing the limited absolute positioning accuracy of industrial robots, which stems from the discrepancy between the nominal kinematic model and the physical entity, this paper proposes a novel paradigm for online compensation based on data-driven error prediction. The present study utilized a KUKA KR4 R600 robot as the experimental platform to construct a high-fidelity digital twin system capable of real-time synchronization. Within this framework, a new machine learning model, termed the Global Configuration-Error Forest (GCE-Forest), was developed and validated. The fundamental principle of GCE-Forest, based on the Random Forest algorithm, is its offline learning of the complex, highly non-linear mapping from the robot’s six-dimensional joint space configuration to its three-dimensional end-effector Cartesian error space. This facilitates online, feedforward, and predictive compensation for the nominal trajectory during robot operation. Through rigorous comparative experiments, the superiority of the proposed GCE-Forest was established. The final outcomes of dynamic trajectory tracking validation demonstrate that the system, by accurately predicting a mean nominal error of 0.1977 mm, successfully reduced the average spatial positioning error of the end-effector to 0.0845 mm, achieving an accuracy improvement of 57.25%. This research provides comprehensive validation of the method’s robust performance, offering a low-cost, non-invasive, and highly effective solution for significantly enhancing robotic accuracy.","author":[{"family":"Yang","given":"Shengnan"},{"family":"Jiang","given":"Wenping"},{"family":"Long","given":"Lin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/machines13090771","URL":"https://doi.org/10.3390/machines13090771","source":"openalex"},{"id":"oa:W4414449091","type":"article-journal","title":"Integrating 3D object detection with ontologies for accurate digital twin creation in manufacturing systems","abstract":"Abstract The digitization of manufacturing resources through digital twins (DTs) enhances operational efficiency and resource management. Ontologies play a key role in maintaining semantic consistency within DT systems. However, existing ontology-based approaches face challenges, including limited adaptability, integration of heterogeneous data—such as 3D images—and high manual effort in ontology development. These limitations hinder the scalability of DT implementations. Traditional 2D imaging often lacks spatial accuracy in complex manufacturing environments, causing inefficiencies and higher costs. Integrating richer data with intelligent frameworks is crucial for improving production and adaptability. The proposed study addresses these challenges by introducing a methodology that integrates existing ontologies with advanced 3D object detection models. The proposed approach employs two fully automated pipelines: one for detecting manufacturing resources from 3D images and another for mapping them into ontologies, ensuring seamless integration into DT frameworks. By leveraging established ontologies, the methodology enhances interoperability, reduces implementation complexity, and facilitates scalable deployment of DT systems across various industrial applications. Additionally, a comparative analysis of multiple advanced 3D detection models provides valuable insights to guide the selection of optimal solutions for diverse industrial settings. Experimental results show that YOLOv8 achieved the highest performance, with 91% classification accuracy, 86% precision, 81% recall, and the fastest inference time of 0.66 s. For ontology population, four machine labels—Robot, MillingMachine, BandSaw, and Lathe—were successfully integrated using a semantic similarity-based mapping strategy, enabling automated class creation and merging. This innovative framework sets a new benchmark for DT implementations, offering enhanced accuracy, efficiency, and semantic coherence in modern manufacturing.","author":[{"family":"Boroukhian","given":"Tina"},{"family":"Supyen","given":"Kritkorn"},{"family":"Samson","given":"J"},{"family":"Bashyal","given":"Atit"},{"family":"Wicaksono","given":"Hendro"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s00170-025-16548-x","URL":"https://doi.org/10.1007/s00170-025-16548-x","source":"openalex"},{"id":"oa:W4410702467","type":"article-journal","title":"Unpacking willingness in family firms facing the digital transformation","abstract":"Abstract Digital transformation introduces a new set of parameters for firm innovation. Existing literature has found that family firms vary on their willingness to innovate. However, explanations of the factors that lead to a family firm’s (un)willingness to act remain scarce. Even more scarce are studies exploring the family firm’s (un)willingness in the digital transformation. The digital transformation is a promising environmental stimulus to unpack family firm (un)willingness due to its disruptive nature. This research uses a comparative multiple case study of 14 manufacturing family firms. The novel findings identify a variety of dispositions that can be divided into willingness-enabling and willingness-suppressing . Willingness affects how family firms potentially (do not) take advantage of the opportunities provided by the digital transformation. The contributions are twofold. First, the importance of considering the heterogeneity of family firms’ willingness toward digital transformation is highlighted. Second, by identifying the role of dispositions and related mechanisms we unpack the heterogeneity of the willingness. In sum, we provide a much-needed explanation of family firms in the digital transformation.","author":[{"family":"Appleton","given":"Samuel"},{"family":"Mismetti","given":"Marco"},{"family":"Matt","given":"Dominik"},{"family":"Massis","given":"Alfredo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s11187-025-01057-8","URL":"https://doi.org/10.1007/s11187-025-01057-8","source":"openalex"},{"id":"doi:10.1080/27525783.2026.2613469","type":"article-journal","title":"Quality-centric digital twins in additive manufacturing: a review of the state-of-the-art, challenges, and future directions","abstract":"Additive Manufacturing (AM) transformed the production landscape, yet quality-related challenges continue to hinder its full potential. To address these issues, various approaches have been explored, including Design of Experiments (DOE), numerical simulations, data-driven methods, and the emerging technology of Digital Twin (DT) – a virtual replica of a physical entity enabling bi-directional data exchange and real-time interaction. It stands out by offering integrated monitoring, control, and predictive capabilities. Despite recent advancements, DTs in AM remain underdeveloped, especially in addressing quality concerns. This systematic review comprehensively focuses on DTs specifically designed to enhance AM part quality – an area overlooked in previous reviews. We examine critical DT development stages, including design, implementation, data processing and intelligence, and verification and validation. Our analysis reveals two key findings. First, only 16 studies from the literature meet the strict criteria for quality-centric, bi-directional DTs, highlighting the field’s immaturity and fragmentation. Second, most implementations are process-specific, with limited multitasking capabilities and over-reliance on sensor data, inadequately addressing critical quality attributes. Based on these findings, we propose six future research directions, namely establishing a comprehensive quality-focused DT framework, integrating multiscale modelling, enabling smarter DTs, creating a unified platform for diverse AM processes, improving data synchronisation, and enhancing data security.","author":[{"family":"Ehteshamfar","given":"Mohammad"},{"family":"Xu","given":"Xun"},{"family":"Yang","given":"Sheng"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/27525783.2026.2613469","URL":"https://doi.org/10.1080/27525783.2026.2613469","source":"openalex"},{"id":"doi:10.1080/27525783.2025.2507007","type":"article-journal","title":"Digital-twin-based dynamic flexible job shop scheduling problem via multi-agent proximal policy optimisation","abstract":"Despite advancements in optimisation techniques, existing flexible job shop problem (FJSP) models are reactive and struggle with dynamic scheduling. Digital twin (DT) technology offers a solution. This study integrates DT with deep reinforcement learning (DRL) for proactive dynamic scheduling. A digital twin-based framework with multi-agent proximal policy optimisation (PPO) was used to adapt scheduling strategies in real-time. The virtual environment simulates production, predicts disruptions, and enables proactive adjustment. The dynamic flexible job shop problem (DFJSP) is modelled as a Markov decision process (MDP) with agents introduced to optimise decisions using DRL. The state and action spaces for the machine and job agents were designed to capture the real-time states. The reward function combines global (makespan) and local (machine utilisation) rewards. Multi-agent PPO trains agents in a virtual environment based on DT interactions. Experiments show that the method outperforms traditional rules and genetic algorithms, particularly in large-scale problems. Additionally, a real-world case study proved its effectiveness in managing machine failures and ensuring on-time completion with minimal deviation in dynamic and uncertain environments.","author":[{"family":"Yuan","given":"Minghai"},{"family":"Zhang","given":"Zhen"},{"family":"Mao","given":"Kefu"},{"family":"Ye","given":"Yang"},{"family":"Pei","given":"Fengque"},{"family":"Yang","given":"Ye"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/27525783.2025.2507007","URL":"https://doi.org/10.1080/27525783.2025.2507007","source":"openalex"},{"id":"oa:W4415970680","type":"article-journal","title":"MODELING THERMODYNAMIC PROCESSES USING MATLAB PDE TOOLBOX FOR CREATING DIGITAL TWINS IN THE FOOD INDUSTRY","abstract":"The article discusses an approach to modeling thermodynamic processes in food industry production systems using MATLAB PDE Toolbox. The main goal of the research is to create digital twins that allow simulating thermal processes and optimizing production operations. The work focuses on the application of heat equations taking into account the Neumann and Dirichlet boundary conditions, which ensures the accuracy and reliability of modeling. The results of computational experiments demonstrating dynamic changes in temperature fields in 2D space are presented. The main attention is paid to the influence of physical parameters such as thermal conductivity, density and specific heat capacity on temperature distribution. The obtained data can be used to improve energy efficiency and quality of production processes in the food industry.As a result of the research, a model describing temperature fields was developed in the MATLAB PDE Toolbox. The developed model serves as a basis for further research in the field of digital twins and integration with industrial modeling tools such as SIEMENS NX, as well as PML platforms. During this study, various heat transfer coefficients and boundary conditions were tested, which made it possible to determine the optimal model parameters. The final result, presented at the end of the article, demonstrates a smooth and correct distribution of thermodynamic processes, confirming the effectiveness of the proposed approach. In the future, this approach can be used to create more complex virtual production systems that allow not only to analyze thermal processes, but also to develop intelligent heat treatment control systems, improving the adaptability and efficiency of technological processes.","author":[{"family":"Makhambetov","given":"K"},{"family":"Belgibaev","given":"Baurzhan"},{"family":"Kunicina","given":"Nadezhda"}],"issued":{"date-parts":[[2025]]},"DOI":"10.53360/2788-7995-2025-3(19)-5","URL":"https://doi.org/10.53360/2788-7995-2025-3(19)-5","source":"openalex"},{"id":"oa:W4411571939","type":"article-journal","title":"AnywhereXR: on-the-fly 3D environments as a basis for open source immersive digital twin applications","abstract":"Visualization has long been fundamental to human communication and decision making. Today, we stand at the threshold of integrating veridical, high-fidelity visualizations into immersive digital environments, alongside digital twinning techniques. This convergence heralds powerful tools for communication, co-design, and participatory decision-making. Our paper delves into the development of lightweight open-source immersive digital twin visualizations, capitalizing on the evolution of immersive technologies, the wealth of spatial data available, and advancements in digital twinning. Coined AnywhereXR, this approach ultimately seeks to democratize access to spatial information on a global scale. Utilizing the Netherlands as our starting point, we envision expanding this methodology worldwide, leveraging open data and software to address pressing societal challenges across diverse domains.HighlightsLightweight creation of high-fidelity, object-based 3D environments on-the-fly based on public data sets3D environments suitable for creating interactive and adaptble immersive experiences through AR and VRConnections to digital twin applicationsEvaluation and case studyEnable futuring and co-design using immersive digital twins","author":[{"family":"Klippel","given":"Alexander"},{"family":"Knuiman","given":"Bart"},{"family":"Zhao","given":"Jiayan"},{"family":"Wallgrün","given":"Jan"},{"family":"Grübel","given":"Jascha"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/17538947.2025.2520000","URL":"https://doi.org/10.1080/17538947.2025.2520000","source":"openalex"},{"id":"oa:W4414578030","type":"article-journal","title":"INNOVATIVE METHODS FOR ENSURING CYBERSECURITY OF TECHNOLOGICAL CONTROL SYSTEMS OF A DIGITAL TWIN OF A FOOD INDUSTRY ENTERPRISE","abstract":"Cybersecurity in digital twin environments for the food industry presents unique challenges due to the merging of cyber‐physical systems with legacy industrial control systems. Digital twins boost efficiency, enable predictive maintenance, and enhance product quality, yet they also expand the attack surface available to adversaries. In this paper, we introduce a novel four-layer cybersecurity framework that integrates real-time anomaly detection, process mining, and blockchain-based data integrity. Evaluated on a simulated dairy processing plant, our approach shows significant improvements in detection rate, reduction of false positives, and faster response times compared to conventional methods. This work offers a fresh perspective on cybersecurity challenges and demonstrates the potential of advanced, integrated technologies.","author":[{"family":"Адилжанова","given":"Салтанат"},{"family":"Amirkhanov","given":"Bauyrzhan"},{"family":"Amirkhanova","given":"Gulshat"},{"family":"Anuarbek","given":"A"}],"issued":{"date-parts":[[2025]]},"DOI":"10.32014/2025.2518-1726.360","URL":"https://doi.org/10.32014/2025.2518-1726.360","source":"openalex"},{"id":"oa:W4414658913","type":"article-journal","title":"Core technologies for hydropower digitalization within the Energy Internet framework: a mini-review","abstract":"Hydropower, a cornerstone renewable energy source globally, is undergoing a transformative evolution through digitalization technologies within the emerging Energy Internet paradigm. This review examines the critical role, applications, enabling architectures, security considerations, and future directions of hydropower digitalization. Digitalization optimizes resource allocation and accessibility, enabling enhanced operational oversight and integration. Key applications include smart monitoring via Internet of Things (IoT) sensors and big data analytics for predictive maintenance, digital twin implementation for equipment prognostics and optimized real-time dispatch, sophisticated water resource scheduling leveraging diverse datasets (meteorological, hydrological, grid demand) for maximized utilization efficiency, and ecological impact mitigation via intelligent flow control and habitat design simulation. Deployment necessitates robust security measures adhering to industrial control standards (e.g., IEC 62443) and often employs redundant network architectures (dual-active or independent operation) to ensure safety and continuity. Future advancement depends critically on progress in interoperability, next-generation predictive digital twins, edge computing, advanced communication infrastructure, and cybersecurity resilience. Collectively, the ongoing evolution of hydropower digitalization technologies represents a vital pathway toward realizing the goals of efficiency, stability, and sustainability within the global Energy Internet.","author":[{"family":"Cao","given":"Tingxiang"},{"family":"Gao","given":"Song"},{"family":"Shi","given":"Xiangjian"},{"family":"Li","given":"Mo"},{"family":"Zhang","given":"Bing"},{"family":"Zhu","given":"Jingan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/frwa.2025.1681345","URL":"https://doi.org/10.3389/frwa.2025.1681345","source":"openalex"},{"id":"oa:W4411091652","type":"article-journal","title":"Reducing Delivery Times by Utilising On-Site Wire Arc Additive Manufacturing with Digital-Twin Methods","abstract":"The increasing demand for smaller batch sizes and mass customisation in production poses considerable challenges to logistics and manufacturing efficiency. Conventional methodologies are unable to address the need for expeditious, cost-effective distribution of premium-quality products tailored to individual specifications. Additionally, the reliability and resilience of global logistics chains are increasingly under pressure. Additive manufacturing is regarded as a potentially viable solution to these problems, as it enables on-demand, on-site production, with reduced resource usage in production. Nevertheless, there are still significant challenges to be addressed, including the assurance of product quality and the optimisation of production processes with respect to time and resource efficiency. This article examines the potential of integrating digital twin methodologies to establish a fully digital and efficient process chain for on-site additive manufacturing. This study focuses on wire arc additive manufacturing (WAAM), a technology that has been successfully implemented in the on-site production of naval ship propellers and excavator parts. The proposed approach aims to enhance process planning efficiency, reduce material and energy consumption, and minimise the expertise required for operational deployment by leveraging digital twin methodologies. The present paper details the current state of research in this domain and outlines a vision for a fully virtualised process chain, highlighting the transformative potential of digital twin technologies in advancing on-site additive manufacturing. In this context, various aspects and components of a digital twin framework for wire arc additive manufacturing are examined regarding their necessity and applicability. The overarching objective of this paper is to conduct a preliminary investigation for the implementation and further development of a comprehensive DT framework for WAAM. Utilising a real-world sample, current already available process steps are validated and actual missing technical solutions are pointed out.","author":[{"family":"Sell","given":"Stefanie"},{"family":"Villani","given":"Kevin"},{"family":"Stautner","given":"Marc"},{"family":"Villani","given":"Kevin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/computers14060221","URL":"https://doi.org/10.3390/computers14060221","source":"openalex"},{"id":"oa:W7138594813","type":"article-journal","title":"Optimization of cold plates with asymmetric heat sources via a diffusion-model-driven digital twin","abstract":"Abstract The geometric design of liquid-cooled cold plates critically determines their thermal-hydraulic performance, influencing the efficiency and reliability of high-power electronic systems. This study presents a conditional diffusion model-assisted digital twin framework that integrates physics-based multi-objective topology optimization (TO) with generative AI to accelerate high-performance thermal management design. The study first employs multi-objective topology optimization to generate a diverse set of cold plate geometries, together with the corresponding thermal resistance ( $$R_{th}$$ R th ) and pressure drop ( $$\\Delta p$$ Δ p ) under asymmetric thermal loading. A conditional diffusion model is then trained to capture the underlying distribution of cold plate geometries under specified physical conditions, enabling rapid and diverse generation of new designs consistent with user-defined parameters. The new designs generated by diffusion model are evaluated using a surrogate model to predict their thermal-hydraulic performance, facilitating the quick selection of viable candidates without exhaustive full-order simulations. The final designs are validated through high-fidelity finite-element thermal-fluid simulations, confirming strong agreement with reference results. By integrating the predictive rigor of physics-based modeling with the speed and adaptability of generative AI, this work brings physics-informed predictive design off the supercomputer and into the operational world, establishing a scalable and intelligent digital twin paradigm for the design of next-generation thermal management systems.","author":[{"family":"Wu","given":"Hao"},{"family":"Coaty","given":"Jacob"},{"family":"Zong","given":"Yuwei"},{"family":"Azar","given":"Kaveh"},{"family":"Minary-Jolandan","given":"Majid"},{"family":"Tian","given":"Zhigang"},{"family":"Xu","given":"Y"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s00158-026-04292-z","URL":"https://doi.org/10.1007/s00158-026-04292-z","source":"openalex"},{"id":"oa:W4412168296","type":"article-journal","title":"Technological Innovation in Digital Brand Management: Leveraging Artificial Intelligence and Immersive Experiences","abstract":"The digital transformation has fundamentally reshaped brand management, moving from traditional mass communication to data-driven, interactive, and highly personalized strategies. With emerging technologies such as artificial intelligence (AI), augmented reality, and digital ecosystems, brands are now engaging consumers in innovative ways to enhance loyalty and gain a competitive advantage. This study examines how leading brands, such as Nike, Apple, and Coca-Cola, employ digital brand management strategies to enhance brand equity, boost consumer engagement, and maintain market leadership. A multiple-case study approach was employed to analyse this. Data was collected through archival research, social media analytics, and consumer sentiment analysis to assess the impact and effectiveness of these strategies. The study examines key digital branding elements, including direct-to-consumer (DTC) models, experiential marketing, and interactive campaigns. The findings reveal that Nike's DTC strategy fosters direct consumer relationships and strengthens brand equity. Apple's experiential marketing and storytelling foster emotional brand loyalty, while Coca-Cola's personalized and interactive digital campaigns drive consumer engagement and social media virality. These strategies demonstrate the growing importance of AI-driven personalization, omnichannel consistency, and consumer-centric engagement. The study concludes that brands prioritizing AI-powered personalization and immersive digital experiences achieve stronger consumer engagement and long-term brand growth. Practical implications suggest businesses integrate AI-driven analytics, invest in emerging technologies, and adopt consumer-focused digital strategies. Future research should investigate the long-term effects of AI-driven brand interactions and examine the role of Web3 and the Metaverse in shaping the future of digital brand management. © The Author(s) 2025. Published by RITHA Publishing. This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited maintaining attribution to the author(s) and the title of the work, journal citation and URL DOI.","author":[{"family":"Карпенко","given":"Віталій"},{"family":"Shkvyria","given":"Natalia"},{"family":"Yarova","given":"Nina"},{"family":"Terentieva","given":"Nataliia"}],"issued":{"date-parts":[[2025]]},"DOI":"10.57017/jorit.v4.2(8).06","URL":"https://doi.org/10.57017/jorit.v4.2(8).06","source":"openalex"},{"id":"oa:W4413886232","type":"article-journal","title":"Digital Transformation of the Ukrainian Construction Industry: Current Challenges and Prospects for Utilizing Global Experience","abstract":"The article is dedicated to analyzing the current state and prospects of digital transformation in the construction industry of Ukraine in the context of global trends. The three-stage model of digital transformation proposed by international researchers is considered, and the key problems hindering the digitalization of the Ukrainian construction sector are identified, including significant resource intensity, management inefficiency, outdated regulatory framework, high energy consumption, and object accident rate. The study aims to examine the problems and prospects of using international experience to accelerate the digitalization of the construction industry in Ukraine. The article employs methods such as analysis, synthesis, comparison, generalization, tabular, schematic, and logical methods. An overview of key digital technologies transforming the global construction industry is presented, such as BIM, IoT, artificial intelligence, automation, cloud computing, AR/VR, digital twins, drones, and 3D printing. The experience of leading countries in construction digital transformation (USA, Finland, Singapore, Denmark) is analyzed based on the Network Readiness Index (NRI) and the IMD World Digital Competitiveness Ranking. A low level of digital readiness in Ukraine is revealed, particularly in the technological component and the absence from global rankings. The first steps of Ukraine in the implementation of digital technologies are considered, including the creation of the Unified State Electronic System in the field of construction (ЄДЕССБ) and the fragmented use of BIM, digital twins, IoT, robotics, AR/VR, and 3D printing. The main factors hindering the digitalization of the construction industry in Ukraine are identified: technological backwardness, insufficient investment, staff shortage, and uncertainty in regulatory and legal regulation. Considering the urgent need for the reconstruction of Ukraine, a roadmap for the digital transformation of the construction industry for 2025-2030 is proposed.","author":[{"family":"Romanenko","given":"Olesia"},{"family":"Alaverdian","given":"Liudmyla"},{"family":"Yudicheva","given":"Olha"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/sist61657.2025.11139214","URL":"https://doi.org/10.1109/sist61657.2025.11139214","source":"openalex"},{"id":"oa:W4412040269","type":"article-journal","title":"Sustainability powered by digitalization? (Re-)politicizing the debate","abstract":"As ecological crises escalate, various stakeholders frame digitalization as a key solution for sustainability transformations. Besides incremental optimization, this promise has not materialized yet. We argue that digital solutions toward sustainability objectives are shaped by and reinforce power structures that effectively undermine sustainability outcomes. Academic discourse and governance are often dominated by a technology-centric framing in contrast to technologically informed, power-centric approaches. In this article, we develop an interdisciplinary framework to analyze three interconnected dimensions of power at the sustainability-digitalization-nexus and reveal how they obstruct sustainability. We locate power at the levels of environmental knowledge, governance, and technological materiality. First, digital technologies create representations of the environment that reinforce, reconfigure, or clash with preexisting ones, striving for more and better digital real-time data for technological control. Second, the spread of digital technologies is facilitated by emerging actor coalitions that promote digitalization while employing a reductionist understanding of sustainability. This narrows the policy space to optimization and incremental solutionism, which reproduces the status quo. Finally, the designs and material infrastructures of current digital technologies create path dependencies and lock-in effects while the underlying colonial resource and wealth flows remain hidden. We advocate for a (re-)politicization of digitalization across these dimensions to leverage its potential for sustainability transformations. We conclude that digitalization cannot spare us from political conflicts and deliberation processes about desirable sustainability futures. The debate should re-center fundamental questions about what kind of sustainable futures we want, where technology has a role to play, and where it does not.","author":[{"family":"Steig","given":"Florian"},{"family":"König","given":"Pascal"},{"family":"Marquardt","given":"Jens"},{"family":"Oels","given":"Angela"},{"family":"Radtke","given":"Jörg"},{"family":"Rehak","given":"Rainer"},{"family":"Weiland","given":"Sabine"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/15487733.2025.2521181","URL":"https://doi.org/10.1080/15487733.2025.2521181","source":"openalex"},{"id":"oa:W7138285949","type":"article-journal","title":"LUCIDiT: A Lean Urban Comfort Intelligent Digital Twin for Quick Mean Radiant Temperature Assessment","abstract":"The intensification of Global Warming and Urban Heat Island phenomena necessitates advanced, computationally effective tools for evaluating outdoor thermal comfort and microclimatic dynamics by means of Mean Radiant Temperature assessment. However, existing high-resolution physical models often suffer from prohibitive computational costs. This research proposes LUCIDiT (Lean Urban Comfort Intelligent Digital Twin), a physically based modeling framework implemented for a quick mean radiant temperature assessment inside complex urban morphologies. The method integrates a simplified balance of mutual radiative heat exchanges with recursive time-series filtering to account for the thermal inertia of different urban materials, alongside greenery heat exchange due to evapotranspiration. This architecture creates an operational urban comfort digital twin that reduces computational times by orders of magnitude for large-scale mappings, without sacrificing physical accuracy. Validation against drone-acquired thermographic data and the established Urban Multi-scale Environmental Predictor model demonstrates high reliability and coherence with the real physical phenomena and context. The application to an urban pilot site in Florence reveals that strategic interventions, such as substituting impervious surfaces with irrigated greenery and arboreal canopies, can mitigate radiant loads by up to 20 °C. Findings show that the proposed urban comfort digital twin can be a robust, scalable instrument for designing evidence-based climate adaptation strategies and quick testing mitigation scenarios to enhance urban resilience.","author":[{"family":"Baia","given":"Michele"},{"family":"Pierucci","given":"Giacomo"},{"family":"Balocco","given":"Carla"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/atmos17030305","URL":"https://doi.org/10.3390/atmos17030305","source":"openalex"},{"id":"oa:W4411220609","type":"article-journal","title":"Driving digital transformation in the oil and gas sector: unlocking AI’s potential in the UAE","abstract":"Purpose This study aims to examine the implementation of artificial intelligence (AI) in the UAE oil and gas sector, focusing on operational, project management and executive-level challenges. It addresses gaps in existing research, which predominantly originates from North America and Europe, and provides a regional perspective on the practical challenges of AI adoption. The study aims to guide future AI implementation projects in the UAE by offering a structured framework. Design/methodology/approach A three-phase qualitative study was conducted using an interpretivist methodology. Semi-structured interviews were carried out with operational engineers, project managers and senior executives in the UAE oil and gas sector. Data saturation was achieved, and thematic analysis was used to interpret the findings. Findings The study identifies the necessity of adopting a lessons-learnt approach, reflecting the emerging stage of AI in the sector. It emphasises the importance of structured change management methodologies to address gaps in digital transformation research. The findings also highlight the critical need for collaborative efforts to bridge skill gaps and expertise, despite challenges posed by the sector’s siloed organisational culture. Senior management support is identified as essential for fostering collaboration. A developed model was applied to an existing AI project and presented as a preliminary evaluation. Research limitations/implications This study contributes to the literature on AI implementation by providing a region-specific perspective for the UAE oil and gas sector. It identifies key challenges and offers actionable recommendations for practitioners and researchers, highlighting the importance of structured change management and collaboration in overcoming barriers to AI adoption. Originality/value This study presents a novel and impactful framework for implementing AI in the UAE oil and gas sector, effectively bridging both regional and practical research gaps. It highlights the critical importance of equipping engineers with the requisite skills to facilitate successful AI adoption and delivers a robust, practice-oriented model that can guide future initiatives and strategic decision-making within the industry.","author":[{"family":"Sulaity","given":"Iman"},{"family":"Yourston","given":"Douglas"},{"family":"Khassawneh","given":"Osama"},{"family":"Darwish","given":"Tamer"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1108/ijoa-01-2025-5145","URL":"https://doi.org/10.1108/ijoa-01-2025-5145","source":"openalex"},{"id":"oa:W7123960015","type":"article-journal","title":"Artificial Intelligence-Driven Transformation of Pediatric Diabetes Care: A Systematic Review and Epistemic Meta-Analysis of Diagnostic, Therapeutic, and Self-Management Applications","abstract":"The limitations of conventional diabetes management are increasingly evident. As a result, both type 1 and 2 diabetes in pediatric populations have become major global health concerns. As new technologies emerge, particularly artificial intelligence (AI), they offer new opportunities to improve diagnostic accuracy, treatment outcomes, and patient self-management. A PRISMA-based systematic review was conducted using PubMed, Web of Science, and BIREME. The research covered studies published up to February 2025, where twenty-two studies met the inclusion criteria. These studies examined machine learning algorithms, continuous glucose monitoring (CGM), closed-loop insulin delivery systems, telemedicine platforms, and digital educational interventions. AI-driven interventions were consistently associated with reductions in HbA1c and extended time in range. Furthermore, they reported earlier detection of complications, personalized insulin dosing, and greater patient autonomy. Predictive models, including digital twins and self-learning neural networks, significantly improved diagnostic accuracy and early risk stratification. Digital health platforms enhanced treatment adherence. Nonetheless, the barriers included unequal access to technology and limited long-term clinical validation. Artificial intelligence is progressively reshaping pediatric diabetes care toward a predictive, preventive, personalized, and participatory paradigm. Broader implementation will require rigorous multiethnic validation and robust ethical frameworks to ensure equitable deployment.","author":[{"family":"Valdespino-Saldaña","given":"Estefania"},{"family":"Altamirano-Bustamante","given":"Nelly"},{"family":"Calzada-León","given":"Raúl"},{"family":"Revilla-Monsalve","given":"Cristina"},{"family":"Altamirano-Bustamante","given":"Myriam"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/ijms27020802","URL":"https://doi.org/10.3390/ijms27020802","source":"openalex"},{"id":"oa:W7167515016","type":"article-journal","title":"Integrated energy-efficiency assessment of a geothermal well doublet digital twin for oil and gas fields","abstract":"Purpose. The research aims to develop and validate an integrated approach to assessing the digital twin of a geothermal well doublet system, which, within a single computational scheme, combines inter-well filtration, heat transfer within the wellbore, pump flow rates and the realistic low-temperature cogeneration potential. In addition, the purpose of research is to form a model suitable for operational decision-making and preliminary technical-economic assessments in conditions where electricity cogeneration is treated as a derivative component of heat extraction, limited by allowable drawdown and the heat-transfer fluid circulation mode in oil-and-gas-type collectors. Methods. An integrated modelling methodology was employed, comprising a radially generalized filtration model based on Darcy’s law, a modified Shukhov’s model for assessing heat losses in the wellbore column taking into account a velocity correction, as well as an energy module for determining pump power and a model for assessing the electrical power of low-temperature cogeneration. A parametric analysis was performed for a series of calculation scenarios, based on which an empirical multiplicative dependence of useful thermal power was identified and a dimensionless integral efficiency criterion was formed for constructing stable operating ranges. Findings. It has been found that the useful thermal power of a geothermal doublet varies between 0.2-0.99 MW, while the potential for electricity cogeneration is 15-75 kW, or about 4-7% of the thermal power. It is shown that maximizing debit is not equivalent to maximizing useful energy due to the rapid growth in pump flow rates and heat losses in the wells. It has been determined that the optimal operating modes of the doublet should be based on an integral energy criterion, and not only on hydrodynamic parameters. Originality. An integrated thermohydraulic-energy core for a geothermal doublet digital twin has been developed and validated, in which filtration, heat transfer, heat losses, pump flow rates and cogeneration are combined into a single analytically consistent model. For the first time, a multiplicative empirical formula for assessing useful thermal power has been synthesized, and an energy-consistent criterion for selecting operating modes of a geothermal doublet system has been proposed. Practical implications. The proposed approach forms an engineering-appropriate basis for the rapid selection of debits, well depths, and nominal drainage radii, which make it possible to determine stable operating modes of geothermal doublets, reduce energy losses, limit pumping loads, and reasonably assess the thermal potential of oil and gas conversion projects.","author":[{"family":"Fyk","given":"Мykhailo"},{"family":"Fyk","given":"Ilya"},{"family":"Fyk","given":"Оleksandr"},{"family":"Fyk","given":"Illia"}],"issued":{"date-parts":[[2026]]},"DOI":"10.33271/mining20.02.054","URL":"https://doi.org/10.33271/mining20.02.054","source":"openalex"},{"id":"oa:W4415499644","type":"article-journal","title":"Towards Digital Transformation in Building Maintenance and Renovation: Integrating BIM and AI in Practice","abstract":"Digital transformation powered by Building Information Modeling (BIM) and Artificial Intelligence (AI) is reshaping renovation practices by addressing persistent challenges such as fragmented records, scheduling disruptions, regulatory delays, and inefficiencies in stakeholder coordination. This study explores the integration of these technologies through a case study of a Catholic church renovation (2022–2023) in Hong Kong, supplemented by insights from 10 comparable projects. The research proposes a practical framework for incorporating digital tools into renovation workflows that focuses on diagnosing challenges, defining objectives, selecting appropriate BIM/AI tools, designing an integrated system, and combining implementation, monitoring, and scaling into a cohesive iterative process. Key technologies include centralized BIM repositories, machine learning-based predictive analytics, Internet of Things (IoT) sensors, and robotic process automation (RPA). The findings show that these tools significantly improve data organization, proactive planning, regulatory compliance, stakeholder collaboration, and overall project efficiency. While qualitative in nature, this study offers globally relevant insights and actionable strategies for advancing digital transformation in renovation practices, with a focus on scalability, continuous improvement, and alignment with regulatory frameworks.","author":[{"family":"Wong","given":"Philip"},{"family":"Lo","given":"Kim"},{"family":"Long","given":"Haitao"},{"family":"Lai","given":"Joseph"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app152111389","URL":"https://doi.org/10.3390/app152111389","source":"openalex"},{"id":"oa:W4417486417","type":"article-journal","title":"An Agentic AI-based Architecture for Digital Twins Specialized in Predictive Maintenance: Application to Ball Mills","abstract":"Mining operations are increasingly confronted with a multitude of challenges, including price volatility, declining ore grades, and escalating energy costs. These challenges are exacerbated by variations in mineral hardness, which contribute to accelerated wear on critical equipment. Among this machinery, ball mills are particularly susceptible to wear and component failures, leading to unplanned maintenance, costly downtime, and disruptions in production. This research seeks to enhance the capabilities of predictive maintenance (PdM), with a concentrated emphasis on Anomalous Behavior Detection (ABD) and Digital Twin (DT) technologies, specifically tailored for ball mill applications within a multi-agent AI system (MAS) framework. We present a novel architectural design that synergizes DT and ABD through a semi-autonomous multi-agent AI system comprising two primary agents: the PdM agent and the Quality Assurance Agent. The primary function of the PdM agent is to identify anomalous behavior, while the Quality Assurance Agent is tasked with assessing the implications of parameter modifications on mill efficiency. Furthermore, we described the principal challenges related to data quality, system integration, and real-time responsiveness that must be systematically addressed to facilitate successful implementations in the future.","author":[{"family":"Collao","given":"Claudio"},{"family":"Akhtar","given":"Humza"},{"family":"Toro","given":"Carlos"},{"family":"Ocampomartínez","given":"Carlos"},{"family":"Schor","given":"Raphael"},{"family":"Prieto","given":"Rami"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.ifacol.2025.12.403","URL":"https://doi.org/10.1016/j.ifacol.2025.12.403","source":"openalex"},{"id":"oa:W4412691132","type":"article-journal","title":"Mixed Reality-based Digital Twinning of Building Circularity: A Co-Design Approach for Sustainable Buildings","abstract":"Sustainability in construction practices is becoming the need of the day, and the construction sector is getting adoptive to the integration of digital tools to explore the opportunities for enhancing sustainability and circular economy applications, offering significant benefits to both industry and society. To achieve this goal, this article discusses a sustainability framework combining Digital Twin (DT), Mixed Reality (MR), and Life-Cycle Assessment (LCA) to align with circular economy principles in building construction.A case study of a single-family house in Kelowna, BC, Canada is conducted to demonstrate the potential of this integration for comprehensive LCA of buildings.The LCA analysis of the building is performed using OneClick LCA-an LCA platform.The results of LCA account for the embodied carbon, improved material circularity, life cycle cost efficiency, etc.A DT Dashboard (DTD) of the building's circularity model is also developed, which monitors and optimizes the whole life cycle of the building.The DTD is then deployed to MR hardware -Microsoft HoloLens for enabling onsite circularity analysis of the building.This not only allows for immersive visualization of LCA data but also enhances stakeholders' collaboration and decisionmaking.This way the study showcases how immersive DT can potentially be a game-changer for sustainable construction and provides an industrially replicable model.","author":[{"family":"Su","given":"Bo"},{"family":"Fawad","given":"Muhammad"},{"family":"Chen","given":"Qian"},{"family":"Salamak","given":"Marek"}],"issued":{"date-parts":[[2025]]},"DOI":"10.22260/isarc2025/0208","URL":"https://doi.org/10.22260/isarc2025/0208","source":"openalex"},{"id":"oa:W4411460439","type":"article-journal","title":"Digital Twin Technology in Precision Medicine and Public Health: Transforming Patient Care and Epidemiological Forecasting","abstract":"Healthcare providers use digital twins to tailor health-related interventions to personal, genetic, lifestyle, and environmental factors as against the one-size-fits-all model. This is primarily because of its ability to facilitate individualized treatment plans while enhancing clinical decision-making. This study examines the role of digital twin in precision medicine and public health, with a focus on the revolutionizing capacity in patient care and epidemiological forecasting. Using multiple empirical and case studies, the impact of this technology on informing public health strategies and optimizing patient management will be assessed. Despite its transformative potential, the integration of digital twin technology presents challenges such as data interoperability issues and standardization concerns, which hinder effective implementation. Nonetheless, digital twin technology holds promise for improving public health outcomes as it continues to evolve.","author":[{"family":"Olatunde","given":"Ronke"},{"family":"Gyasiwaa","given":"Millicent"},{"family":"Ayangeakaa","given":"Ayange"},{"family":"Usman","given":"Muhammad"},{"family":"Olorundare","given":"Timothy"},{"family":"Akpughe","given":"Ome"}],"issued":{"date-parts":[[2025]]},"DOI":"10.38124/ijisrt/25jun719","URL":"https://doi.org/10.38124/ijisrt/25jun719","source":"openalex"},{"id":"oa:W4411062771","type":"article-journal","title":"Designing digital health interventions with causal inference and multi-armed bandits: a review","abstract":"Recent statistics from the World Health Organization show that non-communicable diseases account for 74% of global fatalities, with lifestyle playing a pivotal role in their development. Promoting healthier behaviors and targeting modifiable risk factors can significantly improve both life expectancy and quality of life. The widespread adoption of smartphones and wearable devices enables continuous, in-the-wild monitoring of daily habits, opening new opportunities for personalized, data-driven health interventions. This paper provides an overview of the advancements, challenges, and future directions in translating principles of lifestyle medicine and behavior change into AI-powered mobile health (mHealth) applications, with a focus on Just-In-Time Adaptive Interventions. Considerations for the design of adaptive interventions that leverage wearable and contextual data to dynamically personalize behavioral change strategies in real time are discussed. Bayesian multi-armed bandits from reinforcement learning are exploited as a framework for tailoring interventions, with causal inference methods used to incorporate structural assumptions about the user's behavior. Furthermore, strategies for evaluation at both individual and population levels are presented, with causal inference tools to further guide unbiased estimates. A running example of a simple real-world scenario aimed at increasing physical activity through digital interventions is used throughout the paper. With input from domain experts, the proposed approach is generalizable to a wide range of behavior change use cases.","author":[{"family":"Švihrová","given":"Radoslava"},{"family":"Rossi","given":"Andrew"},{"family":"Marzorati","given":"Davide"},{"family":"Tzovara","given":"Athina"},{"family":"Faraci","given":"Francesca"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fdgth.2025.1435917","URL":"https://doi.org/10.3389/fdgth.2025.1435917","source":"openalex"},{"id":"oa:W7128367552","type":"manuscript","title":"Advances in Emerging Digital Technologies for Sustainable Agriculture: Applications and Future Perspectives","abstract":"Sustainable agriculture is under increasing pressure due to climate variability, resource scarcity, and the need to reduce environmental impacts without compromising productivity. This study aimed to systematically analyze recent advances in emerging digital technologies applied to sustainable agriculture. The PRISMA protocol was applied to Scopus and Web of Science, considering publications from 2020 to 2025, which were analyzed using RStudio 4.5.10 and VOSviewer 1.6.20, resulting in 101 relevant articles. The findings indicate that multisensor monitoring and precision agriculture enable high-resolution characterization of soil–crop variability, supporting site-specific irrigation, fertilization, and phytosanitary management. Likewise, machine learning-based predictive models improve decision-making by forecasting yield, water stress, nutrient deficiencies, and disease outbreaks. In addition, edge computing and autonomous systems enhance operational efficiency and reduce labor dependency. Blockchain strengthens transparency and sustainability certification through secure traceability, while digital twins optimize management strategies through prior simulation. Despite these advances, limitations remain, including platform fragmentation, limited interoperability, uneven adoption among smallholders, and challenges in model generalization across heterogeneous agroecosystems. Therefore, further progress toward integrated and interoperable digital ecosystems is recommended.","author":[{"family":"Yparraguirre","given":"Carlos"},{"family":"Rodríguez-Yparraguirre","given":"Abel"},{"family":"Rodriguez","given":"Wendy"},{"family":"Saavedra-Vera","given":"Janet"},{"family":"Lopez-Carranza","given":"Atilio"},{"family":"Olivares-Espino","given":"Iván"},{"family":"Rojo","given":"Cesar"},{"family":"Epifania-Huerta","given":"Andrés"},{"family":"Guarniz-Vásquez","given":"Elías"},{"family":"Maco-Vásquez","given":"Wilson"}],"issued":{"date-parts":[[2026]]},"DOI":"10.20944/preprints202602.0211.v1","URL":"https://doi.org/10.20944/preprints202602.0211.v1","source":"openalex"},{"id":"oa:W4408950092","type":"article-journal","title":"Smart port city: Digital interfaces for enhancing RoPax port and city co-existence","abstract":"The transition towards smart cities demands a multifaceted approach, which becomes particularly challenging in port cities, where urban life intersects with global logistics. While ports serve as critical logistic nodes, they hold the potential for diverse urban uses beyond mere ship traffic. This study investigates the integration of physical and digital infrastructures in port cities, focusing on the area where urban space expands towards RoPax terminals that combine wheeled cargo and passenger transport. The study is designed as a case study of a Baltic Sea port city undergoing significant infrastructural changes, including the construction of a new passenger terminal and rearrangement of the area surrounding the port. We explore the development of digital infrastructure to facilitate the coexistence of a liveable city and efficient transport connections. Our analysis is based on the dimensions of a smart city and related interfaces. The findings identify key digital interfaces between the city and its port, highlighting five types of such interfaces and the unique challenges and opportunities in balancing the smart city goals of urban and port authorities. This study contributes to the literature on smart cities by demonstrating the critical role of ports in the formation of smart cities, with implications for similar urban contexts.","author":[{"family":"Tsvetkova","given":"Anastasia"},{"family":"Wahlström","given":"Irina"},{"family":"Edelman","given":"Kristel"},{"family":"Franzén","given":"Riikka"},{"family":"Zhou","given":"Yiran"},{"family":"Hellström","given":"Magnus"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.cities.2025.105936","URL":"https://doi.org/10.1016/j.cities.2025.105936","source":"openalex"},{"id":"oa:W7160093829","type":"article-journal","title":"Digital twins of ex vivo human lungs enable accurate and personalized evaluation of therapeutic efficacy","abstract":"Digital twins are an emerging concept in healthcare that envisions integration of molecular, physiological, functional and clinical data to create computational models of biological systems such as cells, organs and individuals. However, the lack of large, multimodal datasets has so far precluded the realization of comprehensive digital twins in medicine. Ex vivo lung perfusion (EVLP) allows the study of human lungs outside the body under physiological conditions and generates multimodal data from imaging, physiologic monitoring and molecular assays. Here we report lung digital twins developed from the largest known clinical EVLP dataset. We show that the digital twin framework accurately models >75 parameters spanning lung physiology, biochemistry, radiography, transcriptomics, metabolomics and proteomics. Furthermore, direct comparison to experimental data on EVLP lungs treated with alteplase demonstrates that digital twins can precisely assess therapeutic efficacy. Together, these results establish human lung digital twins developed using EVLP as a data-rich approach to improve the evaluation of therapeutic effects.","author":[{"family":"Zhou","given":"Xuanzi"},{"family":"Wang","given":"Bo"},{"family":"Wei","given":"Yiyang"},{"family":"Hacker","given":"Serena"},{"family":"Kim","given":"Sumin"},{"family":"Borrillo","given":"T"},{"family":"Mccaig","given":"Abby"},{"family":"Ahmed","given":"Haaniya"},{"family":"Ren","given":"Youxue"},{"family":"Hough","given":"Olivia"},{"family":"Orsini","given":"Luca"},{"family":"Chao","given":"BT"},{"family":"Mcinnis","given":"Micheal"},{"family":"Cypel","given":"Marcelo"},{"family":"Liu","given":"Mingyao"},{"family":"Yeung","given":"Jonathan"},{"family":"Sorbo","given":"Lorenzo"},{"family":"Keshavjee","given":"Shaf"},{"family":"Sage","given":"Andrew"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41587-026-03121-4","URL":"https://doi.org/10.1038/s41587-026-03121-4","source":"openalex"},{"id":"oa:W4414252439","type":"article-journal","title":"Subparsec Acceleration and Collimation of NGC 4261’s Twin Jets","abstract":"Abstract We report the first robust evidence for a cospatial subparsec acceleration and collimation zone (ACZ) in the twin jets of the nearby low-luminosity active galactic nucleus NGC 4261. This result is derived from multifrequency Very Long Baseline Array imaging, combined with the frequency-dependent properties of the radio core (core shift and core size) and jet kinematics determined from the jet-to-counterjet brightness ratio. By applying multiple analysis methods and incorporating results from the literature, we identify a parabolic-to-conical structural transition in both the jet and counterjet, with the transition occurring at (1.23 ± 0.24) pc or (8.1 ± 1.6) × 103 R s (Schwarzschild radii) for the jet and (0.97 ± 0.29) pc or (6.4 ± 1.9) × 103 R s for the counterjet. We also derive the jet velocity field at distances of ∼(103–2 × 104) R s. While local kinematic variations are present, the jet shows an overall acceleration to relativistic speeds from ∼103 to ∼8 × 103 R s, with a maximum Lorentz factor of Γ max ≈ 2.6 . Beyond this region, the jet gradually decelerates to subrelativistic speeds. These findings support the existence of a subparsec-scale (≲1.5 pc) ACZ in NGC 4261, where the jet is accelerated via magnetic-to-kinetic energy conversion while being confined by external pressure. A brief comparison with M87 suggests that the ACZ in NGC 4261 may represent a scaled-down analog of that in M87. These results point toward a potential diversity in jet ACZ properties, emphasizing the importance of extending such studies to a broader AGN population to elucidate the physical mechanisms at play.","author":[{"family":"Yan","given":"Xi"},{"family":"Cui","given":"Lang"},{"family":"Hada","given":"Kazuhiro"},{"family":"Frey","given":"S"},{"family":"Lu","given":"Ru"},{"family":"Chen","given":"Liang"},{"family":"Xu","given":"Wancheng"},{"family":"Fariyanto","given":"Elika"},{"family":"Ho","given":"Luis"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3847/1538-4357/adf84c","URL":"https://doi.org/10.3847/1538-4357/adf84c","source":"openalex"},{"id":"oa:W4414552827","type":"article-journal","title":"Conceptual development and implementation of a digital twin model for managing saltwater intrusion of an island coastal aquifer","abstract":"Abstract Saltwater intrusion (SWI) poses a significant environmental challenge for coastal aquifers in Pacific Island nations, including Port Vila, Vanuatu. This study utilised a 3D numerical simulation model to evaluate SWI in the Tagabe coastal aquifer under current pumping regimes. To address SWI, optimal pumping patterns were identified through machine learning-based surrogate ensemble models and a simulation-optimisation (S–O) management model. A digital twin (DT) framework of the Tagabe coastal aquifer was developed, incorporating a 3D numerical model, surrogate ensemble models, and the S–O approach. The DT framework, linked with illustrative field data, was used to generate and analyse five illustrative scenarios based on varying salt concentrations (0.45, 0.55, 0.75, 0.90, and 1.15 kg/m 3 ; Scenarios 1 to 5, respectively). The results indicated that scenario 3 (salt concentration of 0.75 kg/m 3 ) led to the highest pumping rates from production wells (17,317 m 3 /d) and the lowest from barrier wells (202 m 3 /d), while scenario 5 showed maximum pumping of 31,676 m 3 /d from production wells and 5000 m 3 /d from barrier wells. The S–O model results were validated with less than 10% relative error compared to the numerical model outputs. To the author’s best knowledge, the application of DT in managing SWI has not been applied before. This study is the first to apply a DT framework for managing SWI in coastal aquifers, showcasing its potential for predicting future scenarios and optimising water management strategies. The results from the study indicated that DT can be successfully employed in a coastal aquifer for managing the SWI. The methodology developed and implemented in this study is of global significance and could be used to manage water resources wisely. The study demonstrated that with the help of the S–O approach, the DT is vital in predicting future scenarios, changes in pumping patterns, and other uncertainties.","author":[{"family":"Sharan","given":"Ashneel"},{"family":"Datta","given":"Bithin"},{"family":"Roy","given":"Dilip"},{"family":"Lal","given":"Alvin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s10661-025-14553-x","URL":"https://doi.org/10.1007/s10661-025-14553-x","source":"openalex"},{"id":"oa:W7166735839","type":"article-journal","title":"Toward Secure Software-Defined Industrial Networks Through Asset Administration Shell Digital Twins","abstract":"Industrial digitalization is moving from Industry 4.0 toward Industry 5.0’s emphasis on resilience, human-centric operation, and sustainability. This shift is enabled by the convergence of Operational Technology and Information Technology, but this integration also broadens the exposure of industrial infrastructures to cyber threats targeting communication integrity and process continuity. Mitigating these risks requires network control that is both programmable and aware of each asset’s operational context. However, there is still a lack of operational interfaces that translate the semantics of industrial assets into programmable, runtime-enforceable network behavior. In this paper, following a Design Science Research methodology, we introduce an asset-aware, closed-loop network control abstraction in which the industrial network itself is modeled as a managed asset through Asset Administration Shells. Asset state, lifecycle phase, and operational intent are translated into network policies enforced at runtime on programmable data planes, while in-network telemetry is exposed at the asset level and correlated with operational metrics. We validate the abstraction on a hybrid testbed that combines virtualized components with industrial-grade hardware and virtualized 5G connectivity, through three security-oriented use cases: (i) asset-driven customization of forwarding policies; (ii) human-centric secure maintenance with controlled remote access over 5G; and (iii) anomaly detection and isolation based on cross-layer telemetry correlation. The results show that asset-level operations can drive programmable network enforcement and make network telemetry available at the asset layer. Finally, the work outlines a first step toward standardizing network-oriented asset submodels by separating control-plane operations from data-plane state and telemetry.","author":[{"family":"Bacca","given":"Riccardo"},{"family":"Melis","given":"Andrea"},{"family":"Rinieri","given":"Lorenzo"},{"family":"Girau","given":"Roberto"},{"family":"Prandini","given":"Marco"},{"family":"Callegati","given":"Franco"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/fi18070347","URL":"https://doi.org/10.3390/fi18070347","source":"openalex"},{"id":"oa:W7113899863","type":"article-journal","title":"Context-aware Drift Detection for Quality-aware Data-Driven Smart City Digital Twins","abstract":"As urban environments become more complex, Smart Cities will increasingly depend on the integration of Internet of Things (IoT) devices and Digital Twin (DT) technologies to enable real-time monitoring, simulation, and predictive analytics, to ultimately improve quality of life. Data-driven approaches play a crucial role in optimizing city operations, but their effectiveness is hampered by data drift, shifts in data distributions over time that can degrade model performance. Frequent model retraining is a common solution, but it can be ineffective or lead to high computational costs. Alternatively, drift-driven approaches are often vulnerable to false detections caused by noisy IoT data, hardware failures, or cyber threats. To address that problem, we propose a context-aware drift detection algorithm that takes advantage of local correlations between data sources to detect actual real drifts while avoiding false positives. Furthermore, we present a decentralized layered architecture for embedding drift detection within the Smart City ecosystem and evaluate our approach by using a real-world dataset. Our approach demonstrates the viability of context-aware distributed drift detection, enhancing the reliability and efficiency of ML-driven Smart City applications.","author":[{"family":"Serfilippi","given":"Luca"},{"family":"Bujari","given":"Armir"},{"family":"Corradi","given":"Antonio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1145/3748699.3749824","URL":"https://doi.org/10.1145/3748699.3749824","source":"openalex"},{"id":"oa:W4411829077","type":"article-journal","title":"Smart Water Management: Governance Innovation, Technological Integration, and Policy Pathways Toward Economic and Ecological Sustainability","abstract":"Smart water management (SWM) represents a transformative shift in urban water governance, integrating advanced digital technologies—including the Internet of Things (IoT), Artificial Intelligence (AI), big data analytics, and digital twin modeling—to enable real-time monitoring, predictive analytics, and adaptive decision-making. While drawing extensively on a structured literature review to build its theoretical foundation, this manuscript is primarily presented as a research paper that combines conceptual analysis with empirical insights derived from comparative case studies, rather than a standalone comprehensive review. A five-layer system architecture—encompassing data sensing, transmission, processing, intelligent analysis, and decision support—is introduced to evaluate how technological components interact across operational layers. The model is applied to two representative cases: Singapore’s Smart Water Grid and selected pilot programs in Chinese cities (Shenzhen, Hangzhou, Beijing). These cases are analyzed for their level of digital integration, policy alignment, and performance outcomes, offering insights into both mature and emerging smart water implementations. Findings indicate that the transition from manual to intelligent governance significantly enhances system performance and robustness, particularly in response to climate-induced disruptions. Despite benefits such as reduced non-revenue water and improved pollution control, challenges including high initial investment, data interoperability issues, and cybersecurity risks remain critical barriers to widespread adoption. Policy recommendations focus on establishing national standards, promoting cross-sectoral data sharing, encouraging public–private partnerships, and investing in workforce development to support the long-term sustainability and scalability of smart water initiatives.","author":[{"family":"Dai","given":"Youjin"},{"family":"Huang","given":"Zhengwei"},{"family":"Khan","given":"Naveed"},{"family":"Labbo","given":"Muwaffaq"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/w17131932","URL":"https://doi.org/10.3390/w17131932","source":"openalex"},{"id":"oa:W4409715428","type":"article-journal","title":"A Systematic Review on the Combination of VR, IoT and AI Technologies, and Their Integration in Applications","abstract":"The convergence of Virtual Reality (VR), Artificial Intelligence (AI), and the Internet of Things (IoT) offers transformative potential across numerous sectors. However, existing studies often examine these technologies independently or in limited pairings, which overlooks the synergistic possibilities of their combined usage. This systematic review adheres to the PRISMA guidelines in order to critically analyze peer-reviewed literature from highly recognized academic databases related to the intersection of VR, AI, and IoT, and identify application domains, methodologies, tools, and key challenges. By focusing on real-life implementations and working prototypes, this review highlights state-of-the-art advancements and uncovers gaps that hinder practical adoption, such as data collection issues, interoperability barriers, and user experience challenges. The findings reveal that digital twins (DTs), AIoT systems, and immersive XR environments are promising as emerging technologies (ET), but require further development to achieve scalability and real-world impact, while in certain fields a limited amount of research is conducted until now. This review bridges theory and practice, providing a targeted foundation for future interdisciplinary research aimed at advancing practical, scalable solutions across domains such as healthcare, smart cities, industry, education, cultural heritage, and beyond. The study found that the integration of VR, AI, and IoT holds significant potential across various domains, with DTs, IoT systems, and immersive XR environments showing promising applications, but challenges such as data interoperability, user experience limitations, and scalability barriers hinder widespread adoption.","author":[{"family":"Kostadimas","given":"Dimitris"},{"family":"Kasapakis","given":"Vlasios"},{"family":"Kotis","given":"Konstantinos"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/fi17040163","URL":"https://doi.org/10.3390/fi17040163","source":"openalex"},{"id":"oa:W4411420590","type":"article-journal","title":"What Kind of Rural Digital Configurations Contribute to High County-Level Economic Growth? A Study Conducted in China’s Digital Village Pilot Counties","abstract":"The digitalization of rural areas has emerged as a crucial strategy for promoting economic development, yet the phenomenon of “digital suspension” poses a challenge, where the lack of digital integration in certain sectors may hinder economic progress. This study delves into this issue by identifying multiple configurations that drive county-level economic growth. More specifically, this study aims to explore how rural digitalization contributes to county-level economic growth through different combinations of environmental and subject-level factors. To address this issue, this study applies the fuzzy-set qualitative comparative analysis method, guided by systems thinking and ecological systems theory. The analysis is based on 89 case samples selected from China’s digital village pilot counties, using data from the China County-level Digital Rural Index Research Report jointly released by Peking University and Ali Research Institute, published in 2022, and other county-level statistical data. The study explores the complex causal mechanisms and configuration paths through which rural digitalization empowers county-level economic growth. This study found that (1) the conditions necessary to generate high county-level economic growth do not exist in the process of rural digitalization (at least not within the digital village pilot); (2) four configurations facilitate high county-level economic growth: digital governance-led configuration, dual promotion of digital governance and digital infrastructure, dual promotion of digital life and digital infrastructure, and dual promotion of digital life and digital economy; and (3) two configurations yield non-high county-level economic growth and exhibit asymmetrical relationships with those configurations conducive to high growth. These research findings not only broaden the application of systems thinking and ecological systems theory in the realm of rural digitalization but also offer practical insights into strategies for enhancing county-level economic growth.","author":[{"family":"Xie","given":"Guojie"},{"family":"Tian","given":"Yu"},{"family":"Huang","given":"Lijuan"},{"family":"Li","given":"Muyun"},{"family":"Blenkinsopp","given":"John"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/systems13060488","URL":"https://doi.org/10.3390/systems13060488","source":"openalex"},{"id":"oa:W7128481497","type":"article-journal","title":"Hybrid Digital Twin Framework for Real-Time Indoor Air Quality Monitoring and Filtration Optimization","abstract":"This study presents a hybrid digital twin system designed for real-time indoor air quality (IAQ) monitoring and filtration optimization within a residential environment. Using a network of low-cost sensors, physics-based simulations, and machine learning models, the system dynamically replicates the indoor environment to enable continuous assessment and optimization of key pollutants, including particulate matter, volatile organic compounds, and carbon dioxide. The system architecture integrates mass balance and decay models, computational fluid dynamics simulations, regression models, and neural network algorithms, all evaluated under both filtering and non-filtering conditions. A graphical user interface allows users to interact with the system, test air purifier placements, and visualize air quality dynamics in real time. The results demonstrate that, within this system, simpler models, such as linear regression, outperform more complex architectures under data-limited conditions, achieving test-set coefficients of determination ranging from 0.97 to 0.99 across multiple IAQ parameters. At the same time, the hybrid modelling approach enhances interpretability and robustness. Overall, this digital twin system contributes to smart building management by offering a scalable, interpretable, and cost-effective solution for proactive IAQ control and personalized decision-making.","author":[{"family":"Petrić","given":"Valentino"},{"family":"Strbad","given":"Dejan"},{"family":"Račić","given":"Nikolina"},{"family":"Hussein","given":"Tareq"},{"family":"Kecorius","given":"Simonas"},{"family":"Mureddu","given":"Francesco"},{"family":"Lovrić","given":"Mario"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/atmos17020184","URL":"https://doi.org/10.3390/atmos17020184","source":"openalex"},{"id":"oa:W4409535435","type":"article-journal","title":"Digital Transformation in Aftersales and Warranty Management: A Review of Advanced Technologies in I4.0","abstract":"This research examines how Industry 4.0 technologies such as artificial intelligence (AI), the Internet of Things (IoT), and digital twins (DT) are used in the digital transformation process of warranty management. This research focuses on converting traditional warranty management practices from reactive systems to predictive and proactive ones, improving operational performance and customer experiences. Based on an already established eight-phase framework for warranty management, this paper reviews machine learning (ML), natural language processing (NLP), and predictive analytics, among other advanced technologies, to enhance warranty optimization processes. Best practices in the automotive sector, as well as in the railway and aeronautics industries, have experienced substantial achievements, including optimized resource utilization and savings, together with tailored services. This study describes the limitations of capital investments, labor training requirements, and data protection issues. Therefore, it suggests implementation sequencing and staff education approaches as solutions. In addition to the current evolution of Industry 4.0, this research’s conclusion highlights how digital warranty management advancements optimize resources and reduce costs while adhering to international standards and ethical data practices.","author":[{"family":"González-Prida","given":"Vicente"},{"family":"Parra","given":"Carlos"},{"family":"Viveros","given":"Pablo"},{"family":"Kristjanpoller","given":"Fredy"},{"family":"Márquez","given":"Adolfo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/a18040231","URL":"https://doi.org/10.3390/a18040231","source":"openalex"},{"id":"oa:W4411969184","type":"article-journal","title":"Workflow based on GANs and CNNs towards a digital twin for the 3D morphological characterization of latex aggregates","abstract":"This paper presents a workflow for estimating the 3D morphological characteristics of latex aggregates from 2D in-situ images using deep learning and stochastic geometry models. The method includes automatic image segmentation using a Convolutional Neural Network (CNN), 3D object generation using a Generative Adversarial Network (GAN), and estimation of 3D characteristics. Validation with synthetic datasets shows effective size, shape, and texture characterization, with the Mean Absolute Percentage Error (MAPE) for morphological characteristics of generated objects being around 5% at most. Application to real in-situ images demonstrates feasibility and consistency with experimental observations, successfully generating a digital twin of the latex aggregate population. The method’s flexibility and efficiency make it suitable for real-time industrial applications, offering potential for process monitoring and quality control. Future work will focus on enhancing model performance and adapting to different particle types for broader applicability in various industrial settings.","author":[{"family":"Théodon","given":"Léo"},{"family":"Coufortsaudejaud","given":"Carole"},{"family":"Debayle","given":"Johan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.powtec.2025.121286","URL":"https://doi.org/10.1016/j.powtec.2025.121286","source":"openalex"},{"id":"oa:W4415134092","type":"article-journal","title":"ANALISIS LITERATUR MENGENAI PERAN AI AGENT DALAM EFISIENSI AUTOMASI DIGITAL","abstract":"Perkembangan teknologi kecerdasan buatan (Artificial Intelligence/AI) telah mendorong lahirnya AI Agent sebagai komponen kunci dalam mendukung efisiensi dan automasi digital di berbagai sektor. AI Agent berfungsi sebagai sistem cerdas yang mampu melakukan tugas-tugas secara otonom dan adaptif, mulai dari chatbot hingga sistem multi-agent berbasis pembelajaran mesin. Penelitian ini bertujuan untuk menganalisis kontribusi AI Agent terhadap efisiensi operasional dan produktivitas kerja organisasi, serta mengevaluasi tantangan dan potensi pengembangannya di masa depan. Pendekatan penelitian dilakukan melalui Systematic Literature Review (SLR) dengan merujuk pada metodologi Kitchenham, yang mencakup proses pencarian, seleksi, dan evaluasi terhadap 31 artikel ilmiah dari tahun 2017–2025, dengan 28 artikel memenuhi kriteria inklusi. Pencarian literatur dilakukan melalui lima database ilmiah utama, yaitu IEEE Xplore, ResearchGate, SpringerLink, Scopus, dan arXiv, dengan kata kunci terkait AI Agent dan efisiensi automasi digital. Hasil analisis menunjukkan bahwa penerapan AI Agent dapat meningkatkan efisiensi operasional hingga 40% dan mengurangi waktu produksi sebesar 30%. Teknologi pendukung seperti Large Language Models (LLM), Internet of Things (IoT), dan arsitektur multi-agent turut memperkuat kemampuan adaptasi AI Agent dalam konteks industri kompleks. Namun, integrasi teknologi ini masih menghadapi kendala, seperti kurangnya kesiapan SDM, hambatan struktural organisasi, serta isu etika dan transparansi sistem. Sebagai usulan riset lanjutan, studi ini merekomendasikan pengembangan model evaluasi kinerja AI Agent lintas sektor, integrasi dengan teknologi emerging seperti digital twin dan edge computing, serta analisis kesiapan organisasi dalam implementasi sistem AI. Dengan demikian, penelitian ini memberikan landasan strategis untuk optimalisasi AI Agent yang berkelanjutan dan bertanggung jawab dalam mendukung transformasi digital di berbagai sektor.","author":[{"family":"Fathoni","given":"Fathoni"},{"family":"Robani","given":"Muhammad"},{"family":"Aderiyana","given":"Fakih"},{"family":"Manahan","given":"Nico"},{"family":"Wilantara","given":"Muhammad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.35145/joisie.v9i1.4964","URL":"https://doi.org/10.35145/joisie.v9i1.4964","source":"openalex"},{"id":"oa:W4412170338","type":"article-journal","title":"Automated District-Level Energy Demand Modeling Using EnergyPlus Empowered by Digital Twin Technology","abstract":"Abstract. The global shift toward decentralization and decarbonization in the energy sector demands robust tools for accurately simulating building energy demand at the district scale. Although EnergyPlus is well-regarded for its detailed building-level modeling, it poses challenges when extended to larger districts with diverse building typologies. This paper presents both a conceptual architecture and a working prototype of an automated pipeline that addresses these limitations. Leveraging open-access geo-spatial and non-spatial data from the Netherlands—including over 10 million buildings—the pipeline seamlessly scales EnergyPlus simulations to the district level. The system employs the OGC 3D Tiles standard for efficient streaming and real-time visualization of simulation results across a nationwide 3D Tileset. Implemented in Python and tested on local machines, the pipeline is poised for cloud-based deployment to further enhance scalability and performance. By integrating a digital twin for real-time monitoring and scenario testing, the approach enables efficient bulk operations, interactive decision support, and clearer insights into urban-scale energy consumption patterns. The resulting automation and scalable workflows offer valuable contributions to sustainable urban planning, ensuring that efficiency opportunities can be quickly identified and acted upon at multiple spatial scales.","author":[{"family":"Jalilzadeh","given":"Amin"},{"family":"Rafiee","given":"Azarakhsh"},{"family":"Graaf","given":"Stefan"},{"family":"Konstantinou","given":"Thaleia"},{"family":"Oosterom","given":"Peter"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/isprs-annals-x-g-2025-397-2025","URL":"https://doi.org/10.5194/isprs-annals-x-g-2025-397-2025","source":"openalex"},{"id":"oa:W7131116382","type":"article-journal","title":"Co-Creating Climate-Resilient Streets: Digital Twin-Based Simulations for Outdoor Thermal Comfort","abstract":"Rapid urbanization and climate change are intensifying heat exposure in cities, making effective adaptation strategies essential. This study presents a streamlined digital twin modeling framework for simulating the impact of nature-based solutions (NBSs) on outdoor thermal comfort, developed within the Intelligent Communities Lifecycle (ICL) software suite. The approach automates the import of urban geometry from OpenStreetMap and integrates geolocated weather data, enabling users to efficiently test scenarios involving NBSs and surface material modifications. Outdoor thermal comfort is quantified using the Universal Thermal Climate Index (UTCI), with results visualized through an interactive cloud-based 3D platform to support participatory urban planning. The methodology is demonstrated in Meunierstraat, Leuven (Belgium), where three planning alternatives are compared across seasonal extremes. Simulations show that targeted NBS interventions, particularly temporary participatory measures, can improve thermal comfort under extreme heat. However, the benefits are seasonally dependent and spatially heterogeneous, emphasizing the value of high-resolution, scenario-based analysis. This integrated workflow enhances both technical evidence and stakeholder engagement. While the tool is capable of linking outdoor comfort improvements with building energy performance and carbon emissions, the present paper focuses solely on the outdoor thermal comfort results, leaving indoor–outdoor coupling analysis as a direction for future work.","author":[{"family":"Urrutia-Azcona","given":"Koldo"},{"family":"Bonetti","given":"Valentina"},{"family":"Mizanur","given":"Mohammad"},{"family":"Janssen","given":"Nele"},{"family":"Buckley","given":"Niall"},{"family":"Wit","given":"Mark"},{"family":"Murray","given":"Kieran"},{"family":"Byrne","given":"Niall"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/smartcities9020039","URL":"https://doi.org/10.3390/smartcities9020039","source":"openalex"},{"id":"oa:W7117105230","type":"article-journal","title":"Time Series Models of the Human Heart in Patients with Heart Failure: Toward a Digital Twin Approach","abstract":"Digital Twins (DTs) are digital replicas of physical entities. The use of DTs in healthcare is a growing area of research. With DTs, there is potential to revolutionize healthcare with the assistance of Artificial Intelligence. This can lead to achieving precision, personalization, and value addition in healthcare. Contributing to this field, we present one of the first attempts of uncovering time series models of decompensation of heart failure. This was performed using some of the first data collected from the pilot phase of the SmartHeart study, in which an at-home, wearable, wireless sensor-based digital self-monitoring system for people with heart failure was tested.","author":[{"family":"Wickramasinghe","given":"Nilmini"},{"family":"Ulapane","given":"Nalika"},{"family":"Zhang","given":"Yuxin"},{"family":"Jansons","given":"Paul"},{"family":"Cedersund","given":"Gunnar"},{"family":"Maddison","given":"Ralph"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/s26010082","URL":"https://doi.org/10.3390/s26010082","source":"europepmc"},{"id":"oa:W4406384338","type":"article-journal","title":"Design and Implementation of a Virtual Hoisting System: A Digital Twin Approach for Early Warning and Fault Detection","abstract":"Mine hoists are vital for efficiently transporting materials and personnel between surface and underground mining operations, making their safety and reliability paramount. However, conventional monitoring approaches, which rely on distributed sensors or video surveillance, are limited in their ability to capture the global dynamics of the system, leading to suboptimal decision-making and potential safety risks. This research introduces the integration of digital twin technology into the monitoring and management of mine hoists to address these challenges. This study uses Unity-based modeling to create a virtual system capable of real-time synchronization with its physical counterpart. The digital twin simulates dynamic load changes, predicts potential faults, and optimizes operational parameters through intelligent algorithms. A robust monitoring framework was developed, consisting of a multi-layered architecture that integrates physical systems, real-time data collection, and virtual simulations. Field tests on a multi-rope friction hoist verified the system’s performance, with results demonstrating improved stability, accuracy, and predictive capabilities. A health evaluation model further enhances safety by categorizing the hoist’s operational state into health levels such as ‘healthy,’ ‘sub-healthy,’ ‘warning,’ and ‘fault.’ This model identifies critical risks, such as wire rope tension anomalies, and provides early warnings, ensuring timely interventions.","author":[{"family":"Basher","given":"Md"},{"family":"Islam","given":"Md"},{"family":"Ahmed","given":"Mushtaq"},{"family":"Joarder","given":"Akash"}],"issued":{"date-parts":[[2025]]},"DOI":"10.54536/ajise.v4i1.4098","URL":"https://doi.org/10.54536/ajise.v4i1.4098","source":"openalex"},{"id":"oa:W4415545132","type":"article-journal","title":"Res publica digitalis: The uneven digital transformation of the European public sector and the impact of policy disparities on governance, service efficiency, and socioeconomic inclusion","abstract":"Research background: Digital transformation has become a central pillar of public sector modernisation in the European Union (EU), with initiatives focusing on digital infrastructure, e-government services, human capital development, and research and innovation. The EU’s long-term strategy for digital advancement is aimed at narrowing performance gaps and fostering inclusive progress among member states. However, regional disparities, stagnation in certain countries, and inconsistent investments in research and public services reveal the complex nature of digital convergence. The COVID-19 crisis further exposed structural weaknesses while simultaneously accelerating digital transitions across the EU. Purpose of the article: This article aims to assess the development and inequality of public sector digitalisation across EU–27 countries. It focuses on identifying trends, regional shifts, and performance dynamics based on multidimensional evaluation. The study seeks to determine whether digital convergence is taking place, which countries are leading or lagging, and what policy implications emerge from the observed trajectories. Methods: The research employs a multi-method approach combining the Analytic Hierarchy Process (AHP), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and the Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE) method, Lorenz curve, Gini coefficient analysis, k-means clustering with PCA transformation, sensitivity analysis, and scenario modelling. A total of 24 criteria reflecting the digital maturity of the public sector, such as broadband access, digital skills, e-government services, and research and development (R&D) activity, were used. This comprehensive framework enables robust comparisons of performance levels, structural inequalities, and resilience to weight variations in composite indicators. Findings & value added: The analysis reveals a measurable decline in digital inequality within the EU, as shown by a steady reduction in the Gini coefficient over time. Countries like Austria, Cyprus, and Croatia demonstrated significant upward mobility, driven by strategic investment and consistent policy support. Conversely, countries such as Romania and Belgium experienced relative decline due to stagnation in innovation and public service quality. Sensitivity testing confirmed the robustness of the applied model, while scenario analysis highlighted the transformative potential of targeted interventions. The value added of this research lies in its integrated analytical framework, which not only maps digital progress but also identifies structural challenges and policy leverage points essential for achieving a more cohesive digital Europe.","author":[{"family":"Valášková","given":"Katarína"},{"family":"Nagy","given":"Marek"},{"family":"Figura","given":"Marcel"},{"family":"Rousek","given":"Pavel"}],"issued":{"date-parts":[[2025]]},"DOI":"10.24136/oc.3866","URL":"https://doi.org/10.24136/oc.3866","source":"openalex"},{"id":"oa:W4409564591","type":"article-journal","title":"A Smart Metrology Laboratory Environmental Monitoring and Recognition Method Based on Digital Twin and Improved Transformer","abstract":"ABSTRACT Aiming at the problems of poor reliability and low visualization in the monitoring of power metrology laboratories, a smart power metrology laboratory environmental monitoring and recognition method based on digital twins and improved Transformer is proposed. Firstly, a smart power metrology laboratory architecture is designed based on digital twin technology, achieving comprehensive perception of the laboratory through the interaction between physical entities and virtual platforms. Then, the large kernel block module is added to the Swin Transformer model to enhance the representation ability between cross—modal feature information, and the improved Swin Transformer model is deployed in the intelligent layer of the laboratory architecture. Finally, the improved model is used to analyse the laboratory monitoring information, and multi‐source information is fused for decision‐making to obtain reliable identification results of personnel behaviour and metrology device status. Experimental analysis of this method based on a virtual smart power metrology laboratory scenario shows that this method can effectively identify various behaviours of personnel. The recognition accuracy of sleeping behaviour reaches 96.74%, and the average recognition accuracy of metrology device status is 91.74%. Meanwhile, the study also points out the limitations of the current system in detecting some failure modes, providing more comprehensive theoretical and technical references for the construction of smart power metrology laboratories.","author":[{"family":"Wang","given":"Zuo"},{"family":"Kai","given":"Cuiying"},{"family":"Li","given":"Qi"},{"family":"Liu","given":"Huiying"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/tje2.70069","URL":"https://doi.org/10.1049/tje2.70069","source":"openalex"},{"id":"oa:W7123341649","type":"article-journal","title":"A Digital Twin Approach Integrating IoT and AI for Monitoring and Assessing Roof Degradation in Historic Buildings","abstract":"The EN-HERITAGE project aims to define and prototype an integrated digital platform for the management of virtual models of buildings belonging to the historic built heritage, with a particular focus on slate roofing systems. The platform integrates IoT technologies for environmental monitoring, architectural surveys carried out using laser scanning and photogrammetry, HBIM models, and artificial intelligence algorithms for the analysis of degradation phenomena. The pilot application was conducted on the Albergo dei Poveri complex in Genoa, providing a replicable methodology for the planned conservation of the historic built environment. Preliminary results highlight the effectiveness of the platform in integrating heterogeneous data, providing stakeholders involved in the management of extensive architectural heritage with concrete support for decision-making processes and greater efficiency in planning maintenance and restoration interventions on historic buildings.","author":[{"family":"Valentini","given":"Margherita"},{"family":"Brotto","given":"Paolo"},{"family":"Campana","given":"Paolo"},{"family":"Capponi","given":"Miguel"},{"family":"Colli","given":"Matteo"},{"family":"Rapuzzi","given":"Andrea"},{"family":"Rosso","given":"Paolo"},{"family":"Zani","given":"Sara"},{"family":"Vecchiattini","given":"Rita"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/iic2010002","URL":"https://doi.org/10.3390/iic2010002","source":"openalex"},{"id":"oa:W7128924543","type":"article-journal","title":"Digital Twin-Driven Operational Management Framework for Real-Time Decision-Making in Smart Factories","abstract":"To improve operational efficiency, adaptability, and sustainability in an intelligent factory within the Industry 4.0 era, decision-making must happen in real-time. This paper presents a framework that relies on Digital Twin-Driven Operational Management to IoT, AI-driven analytics, and edge computing for cost, time, data-driven and real-time decision-making in manufacturing environments. The framework utilizes real-time sensor data, predictive modeling, and optimization algorithms for enhanced allocation of resources, production scheduling and effective fault recognition. A case study conducted in a smart manufacturing facility validates the framework, resulting in remarkable improvements in operational efficiency, system adaptability, and cost reduction compared to traditional models. The results of the experiment are increased accuracy in decision-making, decreased downtime, and optimized energy consumption, establishing the framework as a feasible solution for next generation smart factories. This study helps provide a better balance between ever-growing theoretical advancements and industrial application of the theory, leading to more resilient, autonomous and data-driven manufacturing ecosystems.","author":[{"family":"Clark","given":"Logan"},{"family":"Garcia","given":"Benjamin"},{"family":"Harris","given":"Sophia"}],"issued":{"date-parts":[[2025]]},"DOI":"10.66096/jigbp.v1.3","URL":"https://doi.org/10.66096/jigbp.v1.3","source":"openalex"},{"id":"oa:W4415673229","type":"article-journal","title":"Precision mapping of equilibrium disclination strain in pentagonally twinned nanostructures","abstract":"Pentatwinned nanostructures are key to understanding the mechanical, chemical, and structural behavior of nanomaterials owing to their unique fivefold symmetry and lattice strain from a 7.35° disclination gap between {111} twin boundaries. However, the precise equilibrium strain distributions have remained unclear because of heterogeneity among individual particles, requiring statistical analysis across large sample populations. Here, we use nanobeam four-dimensional scanning transmission electron microscopy (4D-STEM) to extract averaged strain profiles from uniformly sized, shape-identical particles, achieving high-resolution, statistically robust insights beyond single-particle noise. The strain profiles reveal how tensile, shear, and rotational components collectively compensate for the angular deficit, with particle shape-dependent local variations highlighting the importance of morphological control in synthesis. By integrating in situ heating with 4D-STEM, we captured a previously unobserved strain relaxation pathway involving the formation of periodic partial dislocations that stabilizes the strain-relieved equilibrium state. This study establishes a quantitative framework for equilibrium strain in fivefold-twinned nanostructures and offers strain engineering strategies for tailored properties.","author":[{"family":"Cheng","given":"Zhihua"},{"family":"Shi","given":"Chuqiao"},{"family":"Zhao","given":"Kaijie"},{"family":"Engel","given":"Michael"},{"family":"Jones","given":"Matthew"},{"family":"Han","given":"Yimo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1126/sciadv.aea9781","URL":"https://doi.org/10.1126/sciadv.aea9781","source":"openalex"},{"id":"oa:W7118123856","type":"article-journal","title":"The Automatic Packing Box Positioning of Production Line in Digital Twin Logistics System Based on YOLOv8","abstract":"ABSTRACT As Industry 4.0 advances, the application of digital technologies is increasingly being popularised in the logistics and warehousing sector. For digital twins, the accurate and efficient collection of real‐time data from the physical world significantly impacts the accuracy of modelling. With the enhancement of computer processing power, the application of computer vision as an information acquisition module is becoming increasingly widespread. This paper proposes a novel method in which YOLOv8 object detection is applied to locate and track packing boxes on the production line. At the same time, the digital twin model is updated in real time to synchronise the positions of the boxes. In the system, high‐definition industrial cameras are used to capture the production line, and the YOLOv8 keypoint estimation model is utilised to calculate the pose of each packing box in every frame. The results are then mapped to the coordinate system of the digital twin model through perspective transformation and coordinate conversion algorithms. Data exchange between the vision algorithm and the digital twin model is performed in real time via a Redis database. The feasibility of the system was verified in the diverging and converging areas of a small experimental production line. Compared with the traditional approach of using photoelectric sensors to detect the positions of packing boxes, the proposed system overcomes two major limitations: the inability to distinguish between different types of boxes and the failure to continuously track and locate them. The results demonstrate that the proposed method outperforms conventional techniques. It shows notable superiority in accurately simulating the motion posture and trajectory of packing boxes within a digital twin system. Such capabilities hold great significance for enhancing the monitoring and management of production logistics.","author":[{"family":"Li","given":"Jiashun"},{"family":"Song","given":"Rongrong"},{"family":"Liu","given":"Haitao"},{"family":"Zhao","given":"Erxun"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1049/dgt2.70022","URL":"https://doi.org/10.1049/dgt2.70022","source":"openalex"},{"id":"oa:W4414317351","type":"article-journal","title":"Evaluating and Enhancing Georeferencing Accuracy in BIM and 3D GIS Models for Built Environment Digital Twins","abstract":"Abstract. The integration of Building Information Modelling (BIM) and Geographic Information Systems (GIS) through open standard models such as IFC and CityGML is fundamental to the development of a comprehensive digital twins for the built environment projects. Accurate georeferencing of these models is essential for performing reliable geospatial analyses, particularly in projects that employ a custom Coordinate Reference System (CRS) or are affected by significant distortion due to map projection. Although a considerable number of studies addressed georeferencing in the context of BIM-GIS data integration, limited attention has been given to the assignment of custom CRSs to both IFC and CityGML models. Moreover, the impact of BIM modelling and different georeferencing approaches on the final positional accuracy of the models remains under-investigated. This study addresses these gaps by proposing a methodology to enhance georeferencing accuracy through the assignment of custom CRS to both IFC and CityGML models, while also practically examining how BIM modelling practices and georeferencing approaches impact the overall positional quality of the models. The results demonstrate the effectiveness of the proposed methodology in enhancing georeferencing accuracy of IFC and CityGML models, offering a practical guideline for ensuring the spatial accuracy of the 3D models in the digital twin environment.","author":[{"family":"Mohammed","given":"Peshawa"},{"family":"Behan","given":"Avril"},{"family":"O'sullivan","given":"Dympna"},{"family":"Mcauley","given":"Barry"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/isprs-annals-x-4-w6-2025-161-2025","URL":"https://doi.org/10.5194/isprs-annals-x-4-w6-2025-161-2025","source":"openalex"},{"id":"oa:W7154958262","type":"article-journal","title":"A Lightweight Web3D Digital Twin Framework for Real-Time ESG Monitoring Using IoT Sensors","abstract":"Existing Environmental, Social, and Governance (ESG) monitoring approaches rely primarily on static reports and dashboard-based interfaces, limiting real-time analysis and interactive exploration of sustainability data in complex built environments. In addition, current digital twin systems often lack integration with IoT-based sensing or depend on cloud-based rendering infrastructures, increasing deployment complexity and restricting accessibility. This study proposes a lightweight Web3D-based digital twin framework for real-time ESG monitoring in smart buildings. The system integrates an independently developed IoT sensor network with a browser-native 3D visualization platform, enabling real-time monitoring of ESG indicators—including electricity consumption—without requiring proprietary software or dedicated rendering hardware. ESG indicators are derived using a rule-based classification aligned with the WELL Building Standard v1. The framework was validated through a 12-month real-world deployment involving 60 IoT sensors. Results demonstrate stable performance, achieving 66 FPS rendering, 78 ms system latency, and 98% sensor data consistency based on cross-sensor agreement. The system also enabled timely detection of environmental anomalies, leading to measurable improvements in air quality and lighting conditions. Unlike prior digital twin systems, the proposed framework delivers a fully browser-native, lightweight architecture that integrates real-time IoT sensing, adaptive Web3D visualization, and structured ESG monitoring within a single deployable system. This approach provides a practical solution with potential for broader deployment in real-time sustainability monitoring for smart buildings.","author":[{"family":"Sinthamrongruk","given":"Thepparit"},{"family":"Dahal","given":"Keshav"},{"family":"Harnpornchai","given":"Napat"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/electronics15081736","URL":"https://doi.org/10.3390/electronics15081736","source":"openalex"},{"id":"oa:W7119206616","type":"article-journal","title":"A Knowledge Graph-Guided and Multimodal Data Fusion-Driven Rapid Modeling Method for Digital Twin Scenes: A Case Study of Bridge Tower Construction","abstract":"Establishing digital twin scenes facilitates the understanding of geospatial phenomena, representing a significant research focus for GIS scientists and engineers. However, current research on digital twin scenes modeling relies on manual intervention or the overlay of static models, resulting in low modeling efficiency and poor standardization. To address these challenges, this paper proposes a knowledge graph-guided and multimodal data fusion-driven rapid modeling method for digital twin scenes, using bridge tower construction as an illustrative example. We first constructed a knowledge graph linking the three domains of “event-object-data” in bridge tower construction. Guided by this graph, we designed a knowledge graph-guided multimodal data association and fusion algorithm. Then a rapid modeling method for bridge tower construction scenes based on dynamic data was established. Finally, a prototype system was developed, and a case study area was selected for analysis. Experimental results show that the knowledge graph we built clearly captures all elements and their relationships in bridge tower construction scenes. Our method enables precise fusion of 5 types of multimodal data: BIM, DEM, images, videos, and point clouds. It improves spatial registration accuracy by 21.83%, increases temporal fusion efficiency by 65.6%, and reduces feature fusion error rates by 70.9%. Local updates of the 3D geographic scene take less than 30 ms, supporting millisecond-level digital twin modeling. This provides a practical reference for building geographic digital twin scenes.","author":[{"family":"Zhang","given":"Yongtao"},{"family":"Wang","given":"Yongwei"},{"family":"Guo","given":"Zhihao"},{"family":"Zhu","given":"Jun"},{"family":"Huang","given":"Fanxu"},{"family":"Zhu","given":"Hao"},{"family":"Chen","given":"Yuan"},{"family":"Kang","given":"Yajian"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/ijgi15010027","URL":"https://doi.org/10.3390/ijgi15010027","source":"openalex"},{"id":"oa:W7133696306","type":"article-journal","title":"Multi-Agent Systems and Digital Twins as a Basis for Smart Buildings with Integrated Sustainable Efficient Ventilation","abstract":"Ventilation management is a key component of smart building performance, directly affecting indoor air quality, occupant comfort, and energy consumption during operation. The increasing complexity of building systems and variability in occupancy and environmental conditions challenge conventional static or centralised ventilation strategies. This study presents a conceptual and methodological framework for intelligent ventilation management based on the integration of distributed environmental sensorisation, multi-agent systems, and digital twins. The proposed approach focuses on structuring the architecture and decision-making mechanisms that enable adaptive and predictive ventilation strategies, including multi-source air intake selection (6D ventilation). Rather than providing experimental or simulation-based validation, the study defines a coherent framework intended to support future quantitative evaluation and implementation. The expected benefits of the approach, in terms of improved energy efficiency, indoor environmental quality, and life-cycle performance, are discussed in relation to existing research. The framework contributes to the development of smart buildings by providing a structured basis for advanced, adaptive, and sustainable ventilation management.","author":[{"family":"Rizo-Maestre","given":"Carlos"},{"family":"Flores-Moreno","given":"José"},{"family":"Nebot-Sanz","given":"Amor"},{"family":"Huesca-Tortosa","given":"José"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/buildings16051026","URL":"https://doi.org/10.3390/buildings16051026","source":"openalex"},{"id":"oa:W4413811233","type":"article-journal","title":"Benchmarking Control Strategies for Multi-Component Degradation (MCD) Detection in Digital Twin (DT) Applications","abstract":"Digital Twins (DTs) have become central to intelligent asset management within Industry 4.0, enabling real-time monitoring, diagnostics, and predictive maintenance. However, implementing Prognostics and Health Management (PHM) strategies within DT frameworks remains a significant challenge, particularly in systems experiencing multi-component degradation (MCD). MCD occurs when several components degrade simultaneously or in interaction, complicating detection and isolation processes. Traditional data-driven fault detection models often require extensive historical degradation data, which is costly, time-consuming, or difficult to obtain in many real-world scenarios. This paper proposes a model-based, control-driven approach to MCD detection, which reduces the need for large training datasets by leveraging reference tracking performance in closed-loop control systems. We benchmark the accuracy of four control strategies—Proportional-Integral (PI), Linear Quadratic Regulator (LQR), Model Predictive Control (MPC), and a hybrid model—within a Digital Twin-enabled hydraulic system testbed comprising multiple components, including pumps, valves, nozzles, and filters. The control strategies are evaluated under various MCD scenarios for their ability to accurately detect and isolate degradation events. Simulation results indicate that the hybrid model consistently outperforms the individual control strategies, achieving an average accuracy of 95.76% under simultaneous pump and nozzle degradation scenarios. The LQR model also demonstrated strong predictive performance, especially in identifying degradation in components such as nozzles and pumps. Also, the sequence and interaction of faults were found to influence detection accuracy, highlighting how the complexities of fault sequences affect the performance of diagnostic strategies. This work contributes to PHM and DT research by introducing a scalable, data-efficient methodology for MCD detection that integrates seamlessly into existing DT architectures using containerized RESTful APIs. By shifting from data-dependent to model-informed diagnostics, the proposed approach enhances early fault detection capabilities and reduces deployment timelines for real-world DT-enabled PHM applications.","author":[{"family":"Barimah","given":"Atuahene"},{"family":"Jahanzeb","given":"Akhtar"},{"family":"Niculita","given":"Octavian"},{"family":"Cowell","given":"Andrew"},{"family":"Mcglinchey","given":"Don"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/computers14090356","URL":"https://doi.org/10.3390/computers14090356","source":"openalex"},{"id":"oa:W4412765872","type":"article-journal","title":"Mapping the nexus between open innovation and circular economy: a decade of bibliometric evidence","abstract":"The urgency of environmental and resource-related challenges has elevated the importance of integrating Open Innovation and Circular Economy into sustainability-driven strategies. While these domains have independently matured, their intersection remains under examined, particularly from a quantitative, science-mapping perspective. This study employs bibliometric analysis on 98 articles published in academic journals between 2015 and 2025, which were screened according to specific criteria, using the Scopus and Web of Science databases. The performance analysis and science mapping were conducted using R and VOSviewer to understand the intellectual organization, changing themes, and influential researchers in the Open Innovation–Circular Economy field. The results contribute theoretically to how Open Innovation mechanisms can facilitate Circular Economy transitions by highlighting underutilized theoretical perspectives, such as stronger innovation capability, better engagement with all stakeholders, and greater organizational capability, and practically, it offers insights for organizations, policymakers, and other ecosystem actors seeking to implement circular strategies through open and collaborative innovation. Conversations are now shifting from theory to more practical and digitally driven approaches that apply to entire ecosystems. Technologies such as artificial intelligence, the Internet of Things, and digital twins are increasingly instrumental in supporting circular models and real-time decision-making. This study utilizes the Scopus and Web of Science databases, which may result in the exclusion of grey literature and studies from specific regions that are not indexed. In the future, research should include data from different sectors, develop designs such as Open Circular Platforms, and test concepts such as Circular Openness and Innovation Density.","author":[{"family":"Surya","given":"Djoni"},{"family":"Rahim","given":"Rano"},{"family":"Hamsal","given":"Mohammad"},{"family":"Candra","given":"Sevenpri"},{"family":"Gunadi","given":"Willy"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/frsus.2025.1638284","URL":"https://doi.org/10.3389/frsus.2025.1638284","source":"openalex"},{"id":"oa:W4412922294","type":"article-journal","title":"Integrating blockchain with digital product passports for managing reverse supply chain","abstract":"• First comprehensive review of ML models for end-of-life product return predictions. • Integration of PRISMA systematic review with network and meta -analysis methods. • Key factors influencing ML prediction accuracy in reverse supply chains. • Six future research directions for AI-enhanced circular-economy logistics. The evolution of the circular economy has led to the adoption of circular supply chains, where efficient management of the reverse supply chain enhances resource utilization, minimizes waste, and fosters a circular supply chain. However, managing reverse supply chains presents numerous challenges including a lack of information transparency and traceability, inconsistent cooperation among stakeholders, and uncertainty in recycling process, such as variations in quantity, quality, and timing. To address these challenges, an information sharing framework that integrates blockchain technology with digital product passports (DPPs) is designed to manage reverse supply chain information. Subsequently, a system dynamics model is applied to evaluate the potential impacts and feasibility of this framework within the reverse supply chain and its implications for the forward supply chain. The results indicate that the application of the proposed framework enhance the legal recycling market, reduces the negative environmental impact of illegal recycling activities, mitigates the bullwhip effect within the forward supply chain, and improves market fulfillment rate. The proposed information sharing framework can be employed to enhance the information efficiency of the reverse supply chain, aid in the recovery of end-of-life products and critical resources utilization, thereby supporting the transition to a circular economy.","author":[{"family":"Xia","given":"Hanbing"},{"family":"Li","given":"Jiahong"},{"family":"Li","given":"Qian"},{"family":"Milisavljevic-Syed","given":"Jelena"},{"family":"Salonitis","given":"Konstantinos"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.tre.2025.104336","URL":"https://doi.org/10.1016/j.tre.2025.104336","source":"openalex"},{"id":"oa:W7155388149","type":"article-journal","title":"Formal Integration of ISO/IEC Digital Twin Standards: A Layered Compliance Model with Uncertainty Quantification","abstract":"Digital Twin (DT) implementations in electrical and industrial systems are governed by fragmented ISO/IEC and IEC standards spanning terminology, architecture, interoperability, lifecycle management, and cybersecurity. This paper proposes a mathematical framework that integrates these standards into a unified compliance model. A layered DT architecture is defined as a finite set of functional abstractions, and standards are linked to layers through a multivalued mapping and an incidence matrix. Traceability, interoperability, fidelity, and security/governance indicators are normalized and aggregated through a bounded weighted functional to obtain a deterministic compliance score. The model is then extended by treating selected indicators as random variables, which enables probabilistic maturity classification and Monte Carlo-based robustness analysis. The resulting functional is bounded, monotone, and stable under bounded perturbations. Numerical experiments on a synthetic portfolio illustrate deterministic scoring and uncertainty effects. The framework provides a proof-of-concept basis for structured DT compliance assessment across heterogeneous electrical systems; however, broader empirical validation is still required before operational deployment.","author":[{"family":"Bălan","given":"George"},{"family":"Serea","given":"Elena"},{"family":"Sălceanu","given":"Alexandru"},{"family":"Lucache","given":"Dorin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/math14091425","URL":"https://doi.org/10.3390/math14091425","source":"openalex"},{"id":"oa:W4412005859","type":"article-journal","title":"C6.1 - Toward a Digital Twin of Hydrogen Pressure Vessels Enabled by Distributed Fiber Optic Sensors","abstract":"We present a digital replica of a hydrogen pressure vessel enabled by distributed fiber optic sensors (DFOS).This digital replica dynamically displays and updates the vessel's structural condition by calculating strain residuals defined as the difference between the measured DFOS strain and the expected strain based on pressure data.As an example, we show the ability of the DFOS to detect and localize damage caused by drilling six holes into the vessel's body.This digital replica represents a foundational step toward a fully integrated digital twin for predictive maintenance and remaining lifetime prognosis.","author":[{"family":"Karapanagiotis","given":"Christos"},{"family":"Schukar","given":"Marcus"},{"family":"Breithaupt","given":"Mathias"},{"family":"Hicke","given":"Konstantin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5162/smsi2025/c6.1","URL":"https://doi.org/10.5162/smsi2025/c6.1","source":"openalex"},{"id":"oa:W7124164678","type":"article-journal","title":"Towards a digital cancer cell twin: External pharmacological validation of a mechanistic A549 electrophysiology model","abstract":"Abstract Computational electrophysiology models are beginning to emerge as digital‐twin–oriented representations of cancer cells, offering mechanistic insights that complement traditional patch‐clamp experiments. In this study, we evaluate the ability of the earliest in‐silico cancer electrophysiology model, an ion channel model based on Hidden Markov state transitions, to reproduce drug‐modulated current densities in A549 lung adenocarcinoma cells. Using independent experimental data from Glaser et al. (2021), we characterised Ca 2 + ‐activated K + channels, KCa1.1 and KCa3.1, in wild‐type (WT) and erlotinib‐resistant (ER) A549 cells under baseline conditions, as well as after activation with 1‐EBIO (3‐ethyl‐1H‐benzimidazol‐2‐one) and inhibition with paxilline and senicapoc. The in‐silico model reproduced the qualitative order of current responses under all pharmacological conditions, quantitatively matching the paxilline‐ and senicapoc‐blocked states while remaining within biologically reasonable channel expression limits. Reproducing 1‐EBIO activation required higher‐than‐physiological effective channel numbers, indicating that ligand‐dependent gating is not fully represented. Nevertheless, the model captured the overall electrophysiological behaviour of both WT and ER cells and successfully distinguished their phenotypes. In summary, the in‐silico model already enables mechanistic interpretation of electrophysiological phenotypes and drug‐modulated responses. With continued refinement, including the incorporation of ligand‐modulated gating, improved calcium‐feedback dynamics, and formal uncertainty quantification, this model has the potential to evolve into a predictive digital twin platform supporting ion‐channel pharmacology, therapy optimisation and precision oncology.","author":[{"family":"Desoyer","given":"Celine"},{"family":"Ruf","given":"Martin"},{"family":"Baumgärtner","given":"Christian"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1002/ctd2.70112","URL":"https://doi.org/10.1002/ctd2.70112","source":"openalex"},{"id":"oa:W4406741888","type":"article-journal","title":"Symbiopersonal intelligence towards symbiotic and personalized digital medicine","abstract":"In this perspective, we introduce the concept of Symbiopersonal Intelligence (SymAI)-a specialized form of artificial intelligence designed to facilitate and optimize symbiotic interactions between individuals and intelligent devices in digital medicine. SymAI represents a new frontier in personalized intelligent systems, adaptively learning from and catering to individual needs and behaviors. We explore its emergence and potential implementation in both personal and public healthcare, encompassing telemedicine, precision medicine, surgical assistance, chronic disease management, and policy optimization. Key technological frameworks and hardware enablers are outlined, with a particular emphasis on multimodal data retrieval, transmission, and processing, as well as personalized interventions delivered via wearable and implantable devices. By integrating artificial intelligence into sensor technologies and addressing barriers in flexible electronics, SymAI holds the potential to revolutionize digital health, offering more responsive, tailored care and improved health outcomes.","author":[{"family":"Mensah","given":"Alfred"},{"family":"Bao","given":"Qiwen"},{"family":"Zhang","given":"Zhaonan"},{"family":"Ya","given":"Chen"},{"family":"Jiang","given":"Qing"},{"family":"Cai","given":"Pingqiang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.fmre.2025.01.009","URL":"https://doi.org/10.1016/j.fmre.2025.01.009","source":"openalex"},{"id":"oa:W4411473200","type":"article-journal","title":"Put out fires in Facility Management through the Digital Twin adoption: outcomes from Italy","abstract":"The Architecture, Construction, Engeneering and Operation (AECO) industry is benefitting from the digitalisation spread. Several digital technologies, including Artificial Intelligence (AI) and Digital Twin (DT) are revolutioning the industry’s operations. Especially, the technological innovation of the Operation and Maintenance (O&M) phase of building life cycle has the potential to optimise the managing of buildings through more efficient, transparent, and sustainable practices. The academic literature, that focuses on the O&M digital innovation, identifies the DT as the main technology to support the digitalisation of facility management (FM) practices in buildings. These potentials, described in terms of improvements in operational time and costs, are not embraced by the market, which seems unready to introduce this innovation. Issues increase in those markets that are not identified as innovator leaders, such as Italy, which is considered a moderate innovator in the European panorame, presenting a very fragmented AECO industry of small-medium enterprises and a scarse innovation boost. With the objective to highlight the market’s willingness to embrace digital innovation, the present study discusses the degree to which digital technologies, and especially DT, are adopted in the Italian market. Thus, after identifing the potential benefits in the academic literature, and report the results of a previous studies on the Italian market perspective in digital innovation, this study discusses digital technologies’ adoption with FM operators. Assessing the real application of digital technologies and DT, the paper reasons about improvements in building performance and operational efficiency introduced by real-time monitoring and predicting building behaviour. The research shows that operators encounter difficulties with data handling and practical application of these technologies. This is also caused by a knowledge gap of the Italian market, which sees few companies that support the adoption of DT.","author":[{"family":"Signorini","given":"Martina"},{"family":"Pomè","given":"Alice"},{"family":"Spagnolo","given":"Sonia"}],"issued":{"date-parts":[[2025]]},"DOI":"10.7771/3067-4883.1985","URL":"https://doi.org/10.7771/3067-4883.1985","source":"openalex"},{"id":"oa:W7128774248","type":"manuscript","title":"Digital Enablers of the Circular Economy: A Bibliometric and Gender-Inclusive Review of Business and Management Research (2015–2025)","abstract":"Digital transformation has become a cornerstone of circular economy (CE) strategies, yet the intersection between digital innovation and women’s entrepreneurship remains poorly understood. This study examines how digital enablers such as IoT, AI, blockchain, data analytics and platform technologies are represented in CE-related business and management research, while assessing the visibility of gender-inclusive and women-entrepreneurship perspectives. Using a bibliometric design, we retrieved and merged Scopus and Web of Science records (2015–2025), applied de-duplication and relevance screening, and conducted performance analysis and science mapping through bibliometrix (R) and VOSviewer to identify core themes, leading journals, influential authors, collaboration networks and thematic clusters. The findings show a sharp rise of digital-CE scholarship after 2018, dominated by technological perspectives on smart manufacturing, circular supply chains, digital product passports and blockchain-enabled traceability. Four stable clusters emerged: digital circular manufacturing, circular business model innovation, waste and resource management, and policy–social aspects. However, gender-related terms appear in only 1.35% of the corpus, revealing a substantial gap between academic research and EU policy priorities for inclusive digital and circular transitions. The study contributes by integrating a gender-inclusive lens into digital-CE scholarship and outlining a future research agenda that positions women entrepreneurs as critical—yet currently overlooked—actors in shaping digital circular ecosystems.","author":[{"family":"Tankova","given":"Eleonora"},{"family":"Moneva","given":"Iva"},{"family":"Krasteva-Hristova","given":"Radosveta"},{"family":"Pencheva","given":"Miglena"},{"family":"Ivanova","given":"Antonina"}],"issued":{"date-parts":[[2026]]},"DOI":"10.20944/preprints202602.1031.v1","URL":"https://doi.org/10.20944/preprints202602.1031.v1","source":"openalex"},{"id":"oa:W4415219167","type":"article-journal","title":"ELiOT: End‐to‐end LiDAR odometry with transformers harnessing real‐world, simulated, and digital twin","abstract":"Abstract The development of smart cities depends on intelligent systems that integrate data from diverse environments. In this work, we present ELiOT , an end‐to‐end LiDAR odometry framework with transformer architecture designed to utilize real‐world data, simulations, and digital twins. ELiOT leverages high‐fidelity simulators and digital twin environments to enable sim‐to‐real applications, training on the real‐world KITTI odometry dataset while benefiting from simulated data for improved generalization. Our self‐attention‐based flow embedding network eliminates the need for traditional 3D‐2D projections by implicitly modeling motion from sequential LiDAR scans. The framework incorporates a 3D transformer encoder‐decoder to extract rich geometric and semantic features. By integrating digital twin environments and simulated data into the training process, ELiOT bridges the gap between simulation and real‐world applications, offering robust and scalable solutions for urban navigation challenges. This work underscores the potential of combining real‐world and virtual data to advance LiDAR odometry and highlights its role for the future smart cities.","author":[{"family":"Lee","given":"Daegyu"},{"family":"Nam","given":"Hyunwoo"},{"family":"Jang","given":"In‐sung"},{"family":"Shim","given":"David"}],"issued":{"date-parts":[[2025]]},"DOI":"10.4218/etrij.2025-0011","URL":"https://doi.org/10.4218/etrij.2025-0011","source":"openalex"},{"id":"oa:W4411736072","type":"article-journal","title":"Editorial: Human-centric innovation in the built environment","abstract":"Human-centric innovation in the built environmentThe shift from traditional system-centred approaches to human-centred designs in building environments is not just a change in methodology.It completely rethinks how we design, build and use our spaces.While traditional methods have focused mainly on efficiency, quality improvement and cost reduction, Industry 5.0 (I5.0) bring a new perspective.They highlight the importance of human well-being, social interactions and cultural contexts in technology development (Lu et al., 2022;Motiei et al., 2024;Resendiz-Villasenor et al., 2025;Yitmen et al., 2025).This transformation focuses on improving how people experience the built environment in several ways.Construction and design are social and technical systems.They involve how technology is used, how people behave and the cultural factors that come into play.These elements connect in complex ways.Instead of considering people as just technology users, this approach recognises them as active participants.Their views, choices, and interactions influence how built environment innovations succeed and last (Nair et al., 2025).The human element appears in many areas, from individual worker safety and comfort to community changes.It includes different cultural work habits and raises concerns about privacy in smart cities.Specifically, this involves understanding how people perceive and adopt new technologies, how their backgrounds and cultures shape collaboration, and how the design of the environment has a direct impact on human health and ecological sustainability (Najafi and Rahimian, 2024).Further, using advanced technologies in Construction 5.0, like IoT, AI and digital twins (DTs) (Najafi et al., 2025) requires careful attention to how people interact with them.These systems create a lot of data about how people act and how the environment functions.This raises another important question about privacy, user control and how to balance what technology can do with designs that focus on people.However, the main challenge is not only to create smart technologies but also to design systems that improve human experience and support well-being.This special collection presents 17 empirical studies that explore the human dimensions of built environment innovation across diverse contexts, from worker safety and technology adoption to cross-cultural collaboration and smart city privacy concerns.Each paper contributes essential insights into how behavioural, social, and cultural factors shape the success of sustainable and resilient construction practices, demonstrating that practical innovation requires understanding both technical capabilities and human experience.In their study, Nazari et al. (2025) uses the NSGA-II optimisation algorithm to compare window and shading designs for office buildings in Tehran and Auckland, two cities with similar latitudes but in different hemispheres.The research finds that slat number and wall distance are the most important shading variables in both cities, with Auckland providing better thermal comfort while Tehran receives more daylight and can achieve greater energy savings through proper shading and window-to-wall ratios.The study provides the first hemispheric comparison of these design parameters, offering practical guidance for architects and a methodology for researchers studying building performance optimisation across different climates.Abdul Ghafar and Ibrahim (2025) compare cross-cultural productivity between Malaysian and UK AEC professionals in industrialised building projects using cognitive organisational theory protocols tested in SimVision®.The research finds that BIM technology intervention improves exception handling, coordination and decision-making, while national culture Smart and Sustainable Built Environment 883","author":[{"family":"Najafi","given":"Mina"},{"family":"Rahimian","given":"Farzad"},{"family":"Akanmu","given":"Abiola"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1108/sasbe-06-2025-567","URL":"https://doi.org/10.1108/sasbe-06-2025-567","source":"openalex"},{"id":"oa:W4416893686","type":"article-journal","title":"Cryogenic nano-twinning engineering to mitigate the strength–hydrogen embrittlement trade-off in a high-entropy alloy","abstract":"High-strength alloys are vulnerable to hydrogen embrittlement (HE), showing a trade-off between mechanical strength and HE resistance. In this work, a cryogenic nano-twinning strategy was proposed to overcome this trade-off relationship in a CoCrFeMnNi high-entropy alloy. The approach combines pre-straining at 77 K, which induces stable nanotwins, with recovery annealing at 773 K to decrease dislocation density. The nanotwin-engineered alloy exhibits ∼2.2-fold higher yield strength than fully recrystallized samples while retaining HE resistance. This cryo-twin engineering as a viable pathway to break the strength–HE resistance in HEAs, offering a design route for advanced structural materials in hydrogen environments.Impact statement This cryogenic nano-twinning engineering, which combines pre-straining at 77 K and heat treatment, can achieve superior synergy of mechanical strength and hydrogen embrittlement resistance.","author":[{"family":"Kim","given":"Rae"},{"family":"Choi","given":"Jumi"},{"family":"Lee","given":"Ho"},{"family":"Koo","given":"Bon‐wook"},{"family":"Lee","given":"Shi"},{"family":"Son","given":"Sujung"},{"family":"Ha","given":"Hyojeong"},{"family":"Lee","given":"Do"},{"family":"Suh","given":"Dong‐woo"},{"family":"Kim","given":"Hyoung"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/21663831.2025.2596162","URL":"https://doi.org/10.1080/21663831.2025.2596162","source":"openalex"},{"id":"oa:W4417485977","type":"article-journal","title":"Developing provider digital twins for personalized provider-patient communication via a RAG-based conversational framework","abstract":"Digital twins have emerged as a paradigm in precision and personalized medicine, enabling data-driven modeling of individuals to support tailored interventions. While most existing work focuses on patient-oriented twins, little attention has been given to modeling the provider's role, particularly in clinical communication. In this study, we present GRACE (Generalized RAG-Enhanced Conversation Framework), a framework for constructing a provider digital twin (ProDT) that emulates key aspects of clinicians' communicative and cognitive behavior. GRACE integrates three modules: a physician-informed dialog script generation and optimization module for provider-patterned conversation, a Retrieval-Augmented Generation (RAG) pipeline for factual grounding and timely knowledge updating, and an LLM-based conversational interface that enables interactive, context-aware exchanges. Using HPV vaccination counseling as a representative use case, GRACE was evaluated with HealthBench and a structured user study involving clinician feedback. The results demonstrate its feasibility, trustworthiness, and adaptability for proactive provider-patient communication, marking a conceptual step toward safe, scalable, and cognitively grounded digital twins in healthcare.","author":[{"family":"Li","given":"Pengze"},{"family":"Hu","given":"Yutong"},{"family":"Li","given":"Jianfu"},{"family":"Gemeinhardt","given":"Garit"},{"family":"Li","given":"Fang"},{"family":"Amith","given":"Muhammad"},{"family":"Cui","given":"Licong"},{"family":"Forte","given":"Antonio"},{"family":"Tao","given":"Cui"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.csbj.2025.12.007","URL":"https://doi.org/10.1016/j.csbj.2025.12.007","source":"openalex"},{"id":"oa:W4415781909","type":"article-journal","title":"Generative AI in clinical (2020–2025): a mini-review of applications, emerging trends, and clinical challenges","abstract":"Generative artificial intelligence (G-AI) has moved from proof-of-concept demonstrations to practical tools that augment radiology, dermatology, genetics, drug discovery, and electronic-health-record analysis. This mini-review synthesizes fifteen studies published between 2020 and 2025 that collectively illustrate three dominant trends: data augmentation for imbalanced or privacy-restricted datasets, automation of expert-intensive tasks such as radiology reporting, and generation of new biomedical knowledge ranging from molecular scaffolds to fairness insights. Image-centric work still dominates, with GANs, diffusion models, and Vision-Language Models expanding limited datasets and accelerating diagnosis. Yet narrative (EHR) and molecular design domains are rapidly catching up. Despite demonstrated accuracy gains, recurring challenges persist: synthetic samples may overlook rare pathologies, large multimodal systems can hallucinate clinical facts, and demographic biases can be amplified. Robust validation, interpretability techniques, and governance frameworks therefore, remain essential before G-AI can be safely embedded in routine care.","author":[{"family":"Fahad","given":"Nafiz"},{"family":"Rabbi","given":"Riadul"},{"family":"Hasan","given":"Sumayea"},{"family":"Prity","given":"Fariya"},{"family":"Ahmed","given":"Rasel"},{"family":"Ahmed","given":"Farhana"},{"family":"Hossen","given":"Md"},{"family":"Liew","given":"Tze"},{"family":"Sayeed","given":"Md"},{"family":"Goh","given":"Michael"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fdgth.2025.1653369","URL":"https://doi.org/10.3389/fdgth.2025.1653369","source":"openalex"},{"id":"oa:W4413868583","type":"article-journal","title":"An explainable digital twin framework for skin cancer analysis using early activation meta-learner","abstract":"Skin cancer is among the most common cancers globally, which calls for timely and precise diagnosis for successful therapy. Conventional methods of diagnosis, including dermoscopy and histopathology, are significantly dependent on expert judgment and therefore are time-consuming and susceptible to inconsistencies. Deep learning algorithms have shown potential in skin cancer classification but tend to consume a substantial amount of computational resources and large training sets. To overcome these issues, we introduce a new hybrid computer-aided diagnosis (CAD) system that integrates Stem Block for feature extraction and machine learning for classification. The International Skin Imaging Collaboration (ISIC) skin cancer dermoscopic images were collected from Kaggle, and essential features were collected from the Stem Block of a deep learning (DL) algorithm. The selected features, which were standardized using StandardScaler to achieve zero mean and unit variance, were then classified using a meta-learning classifier to enhance precision and efficiency. In addition, a digital twin framework was introduced to simulate and analyze the diagnostic process virtually, enabling real-time feedback and performance monitoring. This virtual replication aids in continuous improvement and supports the deployment of the CAD system in clinical environments. To improve transparency and clinical reliability, explainable artificial intelligence (XAI) methods were incorporated to visualize and interpret model predictions. Compared to state-of-the-art approaches, our system reduced training complexities without compromising high classification precision. Our proposed model attained an accuracy level of 96.25%, demonstrating its consistency and computationally efficient status as a screening tool for detecting skin cancer.","author":[{"family":"Sampath","given":"Pradeepa"},{"family":"Gopika","given":"S"},{"family":"Vimal","given":"S"},{"family":"Kang","given":"Yoonje"},{"family":"Seo","given":"Sanghyun"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fcomp.2025.1646311","URL":"https://doi.org/10.3389/fcomp.2025.1646311","source":"openalex"},{"id":"oa:W4411832820","type":"article-journal","title":"Digital Transition as a Driver for Sustainable Tailor-Made Farm Management: An Up-to-Date Overview on Precision Livestock Farming","abstract":"The increasing integration of sensing devices with smart technologies, deep learning algorithms, and robotics is profoundly transforming the agricultural sector in the context of Farming 4.0. These technological advancements constitute critical enablers for the development of customized, data-driven farming systems, offering potential solutions to the challenges of agricultural intensification while addressing societal concerns associated with the emerging paradigm of “farming by numbers”. The Precision Livestock Farming (PLF) systems enable the continuous, real-time, and individual sensing of livestock in order to detect subtle change in animals’ status and permit timely corrective actions. In addition, smart technology implementation within the housing environment leads the whole farming sector towards enhanced business rentability and food security as well as increased animal health and welfare conditions. Looking to the future, the collection, processing, and analysis of data with advanced statistic methods provide valuable information useful to design predictive models and foster the insight on animal welfare, environmental sustainability, farming productivity, and profitability. This review highlights the significant potential of implementing advanced sensing systems in livestock farming, examining the scientific foundations of PLF and analyzing the main technological applications driving the transition from traditional practices to more modern and efficient farming models.","author":[{"family":"Losacco","given":"Caterina"},{"family":"Pugliese","given":"Gianluca"},{"family":"Forte","given":"Lucrezia"},{"family":"Tufarelli","given":"Vincenzo"},{"family":"Maggiolino","given":"Aristide"},{"family":"Palo","given":"Pasquale"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/agriculture15131383","URL":"https://doi.org/10.3390/agriculture15131383","source":"openalex"},{"id":"oa:W4406049199","type":"article-journal","title":"Construction of a Real-Scene 3D Digital Campus Using a Multi-Source Data Fusion: A Case Study of Lanzhou Jiaotong University","abstract":"Real-scene 3D digital campuses are essential for improving the accuracy and effectiveness of spatial data representation, facilitating informed decision-making for university administrators, optimizing resource management, and enriching user engagement for students and faculty. However, current approaches to constructing these digital environments face several challenges. They often rely on costly commercial platforms, struggle with integrating heterogeneous datasets, and require complex workflows to achieve both high precision and comprehensive campus coverage. This paper addresses these issues by proposing a systematic multi-source data fusion approach that employs open-source technologies to generate a real-scene 3D digital campus. A case study of Lanzhou Jiaotong University is presented to demonstrate the feasibility of this approach. Firstly, oblique photography based on unmanned aerial vehicles (UAVs) is used to capture large-scale, high-resolution images of the campus area, which are then processed using open-source software to generate an initial 3D model. Afterward, a high-resolution model of the campus buildings is then created by integrating the UAV data, while 3D Digital Elevation Model (DEM) and OpenStreetMap (OSM) building data provide a 3D overview of the surrounding campus area, resulting in a comprehensive 3D model for a real-scene digital campus. Finally, the 3D model is visualized on the web using Cesium, which enables functionalities such as real-time data loading, perspective switching, and spatial data querying. Results indicate that the proposed approach can effectively get rid of reliance on expensive proprietary systems, while rapidly and accurately reconstructing a real-scene digital campus. This framework not only streamlines data harmonization but also offers an open-source, practical, cost-effective solution for real-scene 3D digital campus construction, promoting further research and applications in twin city, Virtual Reality (VR), and Geographic Information Systems (GIS).","author":[{"family":"Gao","given":"Rui"},{"family":"Yan","given":"Guanghui"},{"family":"Wang","given":"Yingzhi"},{"family":"Yan","given":"Tianfeng"},{"family":"Niu","given":"Ruiting"},{"family":"Tang","given":"CM"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/ijgi14010019","URL":"https://doi.org/10.3390/ijgi14010019","source":"openalex"},{"id":"oa:W4410068249","type":"article-journal","title":"Industry 5.0 and Human-Centered Energy System: A Comprehensive Review with Socio-Economic Viewpoints","abstract":"Industry 5.0 transforms industrial ecosystems via artificial intelligence (AI), human–machine collaboration, and sustainability-focused innovations. This systematic literature review examines Industry 5.0′s role in energy transition through digital transformation, sustainable supply chains, and energy efficiency strategies. Key findings highlight AI-driven smart grids, blockchain-enabled energy transactions, and digital twin simulations as enablers of low-carbon, adaptive industrial operations. This review uniquely integrates technological, managerial, and policy perspectives, providing actionable insights for policymakers and industry leaders. Industry 5.0 enhances innovative energy management, renewable energy integration, and flexible energy distribution, strengthening resilience and sustainability. It fosters environmental responsibility, social impact, and circular economy principles, laying the foundation for a low-carbon economy and accelerating the global energy transition.","author":[{"family":"Hu","given":"Jin‐li"},{"family":"Li","given":"Yang"},{"family":"Chew","given":"J"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/en18092345","URL":"https://doi.org/10.3390/en18092345","source":"openalex"},{"id":"oa:W7134182786","type":"article-journal","title":"Human-Centered optimization through Digital Twins, and Motion Capture Technologies of a manual activity in the logistics sector","abstract":"Industry 4.0 has enabled significant technological advances for industrial applications, creating new business opportunities but often neglecting how operators interact with increasingly complex systems. In contrast, Industry 5.0 emphasizes a human-cantered approach, highlighting the role of operators and their interaction with automation in modern industrial environments. Despite technological progress, many industrial sectors, such as logistics, continue to rely on fully manual tasks. These workstations are frequently poorly optimized, ergonomically inadequate, and not inclusive of diverse operators. The repetitive and physically demanding nature of such tasks can lead to fatigue, stress, and increased risk of injury, negatively impacting both operator well-being and productivity.This paper proposes an innovative methodology to optimize manual operations in the logistics sector through advanced technologies and a human-centered design approach. The goal is to enhance inclusivity, reduce physical loads, and minimize injury risks associated with repetitive or hazardous activities. To this end, motion capture systems (MoCap) and digital human simulation software were employed to develop a digital twin of both operators and workstations. This virtual model enabled the analysis of the current situation and the simulation of multiple optimization scenarios. By using this risk-free environment, alternative automation solutions were evaluated, and the most effective configurations were identified based on performance, efficiency, and safety.A comprehensive ergonomic evaluation complemented the analysis, assessing key indicators to define the optimal task distribution between human operators and automated systems. This ensured minimized physical load on operators while maximizing operational efficiency. Virtual reality (VR) technology was integrated into the validation process, allowing operators to interact directly with proposed solutions in a virtual setting. The proposed methodology was applied to a real logistics process to validate its practicality and effectiveness. Preliminary results confirmed its potential in industrial applications, demonstrating improvements in ergonomics, inclusivity, and productivity. These findings are further detailed and discussed in the final version of the paper.Additionally, a dedicated study was conducted on the number of sensors required in MoCap acquisitions. The objective was to determine the minimum number of sensors necessary to accurately reproduce operator motion, while exploiting the posture prediction capabilities of a digital human simulation software IPS IMMA. This analysis is important due to the fact that reducing the number of sensors directly lowers acquisition time, system complexity, and implementation costs, thereby making the methodology more practical and scalable for industrial deployment. By identifying an optimal compromise between sensor quantity and motion fidelity, the study contributes to the efficient and sustainable use of advanced motion capture technologies in industrial contexts.Overall, this work highlights the importance of integrating ergonomic considerations and human factors into industrial automation strategies. By placing the operator at the center of system design, the study demonstrates how logistics operations can be optimized not only for efficiency but also for inclusivity, safety, and operator well-being. These findings provide practical insights for the transition toward Industry 5.0, where human–machine collaboration is essential for sustainable productivity and improved job satisfaction.","author":[{"family":"Vargas","given":"Manuela"},{"family":"Cibrario","given":"Valerio"},{"family":"Tumiotto","given":"Denise"},{"family":"Bertoli","given":"Annalisa"},{"family":"Fantuzzi","given":"Cesare"}],"issued":{"date-parts":[[2026]]},"DOI":"10.54941/ahfe1007157","URL":"https://doi.org/10.54941/ahfe1007157","source":"openalex"},{"id":"oa:W7134983805","type":"article-journal","title":"A closed-loop framework integrating robotic inspection and digital twins for fatigue prognosis of in-service steel bridges","abstract":"Fatigue cracking threatens the safety of orthotropic steel decks (OSDs) in long-span bridges, yet current manual inspection lacks predictive depth. We present a closed-loop framework integrating autonomous robotic inspection, vision-based quantification, and finite-element fracture mechanics to enable adaptive fatigue prognosis. In laboratory validation, the robotic platform achieved a mean localization accuracy of 2.7 ± 0.8 cm, meeting structural precision requirements. Field deployment on an in-service cable-stayed bridge demonstrated that automated inspection reduced average time per girder from 124.6 to 50.4 minutes-a 59.6% reduction. Identified cracks were assimilated into a digital twin for adaptive state updating. Analysis of discrepancies between simulated and observed propagation paths-interpreted via stress intensity factor fields-highlighted significant mixed-mode fracture effects, particularly elevated Mode-II (shear) contributions, as a primary source of predictive uncertainty under in-service conditions. This integration of robotics and digital twins provides a scalable solution for automated maintenance. Beyond labor reduction, the framework establishes a data-driven path toward proactive life-cycle management, enhancing the structural resilience and long-term safety of critical transportation infrastructure.","author":[{"family":"Li","given":"Xiaodong"},{"family":"Fu","given":"ZQ"},{"family":"Guo","given":"Hongbin"},{"family":"Ji","given":"Bohai"},{"family":"Xu","given":"Zhaodong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s44172-026-00637-0","URL":"https://doi.org/10.1038/s44172-026-00637-0","source":"openalex"},{"id":"oa:W7123456014","type":"article-journal","title":"Achieving clinically meaningful outcomes in digital health: a six-step, cyclical precision engagement framework (ENGAGE)","abstract":"By leveraging everyday technologies such as mobile apps, wearables, and AI-enabled tools, digital health interventions (DHIs) offer new pathways to integrate self-management and intervention programs into the fabric of daily life, while bridging gaps in care through continuous, context-aware support. Yet many tools underperform clinically because digital engagement (\"screen time\") is conflated with impact, while behavioral science is retrofitted, if applied at all. We propose the ENGAGE Framework: a cyclical, six-step model of precision engagement that integrates user needs, behavioral science, and adaptive personalization to transform initial curiosity into sustained real-world habits. By leveraging available data, users can be segmented according to their need (Step 1: Enroll & Segment), targeted with the most relevant and engaging message to increase micro-engagement (Step 2: Nudge & Hook), and persuaded to engage in real-world health behavior change (Step 3: Guide Behavior). From this macro-engagement step, additional core behavioral science principles are used to reinforce the real-world behaviors long enough to positively impact health outcomes (Step 4: Anchor Habits), while measuring progress (Step 5: Generate Evidence) to inform adaptive and optimized engagement strategies (Step 6: Expand & Evolve with AI) for tailored interventions and communications based on user characteristics, context, and clinical data for both new and existing users. Each step of the ENGAGE Framework maps to evidence-based techniques, implementation tactics (e.g., integration pathways and operational deployment strategies), and metrics that help translate superficial engagement into long-lasting behavior change and measurable clinical outcomes. We synthesize relevant engagement literature, identify gaps and challenges (e.g., measurement heterogeneity, lack of focus on macro-engagement, product development challenges, ecosystem barriers), and offer a practical checklist for innovators. By focusing on who needs what support, when and why, ENGAGE aims to help DHI developers and researchers design interventions that are effective, equitable, and empirically testable.","author":[{"family":"Eiselt","given":"Anne‐kathrin"},{"family":"Kirkendall","given":"Suzanne"},{"family":"Xiong","given":"Engelina"},{"family":"Langner","given":"David"},{"family":"Goldfarb","given":"Micah"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fdgth.2025.1713334","URL":"https://doi.org/10.3389/fdgth.2025.1713334","source":"openalex"},{"id":"oa:W4417113999","type":"article-journal","title":"A Dual Digital Twin Framework for Reinforcement Learning: Bridging Webots and MuJoCo with Generative AI and Alignment Strategies","abstract":"Deep reinforcement learning (DRL) has shown potential for robotic training in virtual environments; however, challenges remain in bridging simulation and real-world deployment. This paper introduces an extended reinforcement learning framework that advances beyond traditional single-environment approaches by proposing a dual digital twin concept. Specifically, we suggest creating a digital twin of the robot in Webots and a corresponding twin in MuJoCo, enabling policy training in MuJoCo’s optimized physics engine and subsequent transfer back to Webots for validation. To ensure consistency across environments, we introduce a digital twin alignment methodology, synchronizing sensors, actuators, and physical model characteristics between the two simulators. Furthermore, we propose a novel testing framework that conducts controlled experiments in both virtual environments to quantify and manage divergence, thereby improving robustness and transferability. To address the cost and complexity of maintaining two high-fidelity models, we leverage generative AI agents to automate the creation of the secondary digital twin, significantly reducing engineering overhead. The proposed framework enhances scalability, accelerates training, and improves the reliability of sim-to-real transfer, paving the way for more efficient and adaptive robotic systems.","author":[{"family":"Laukaitis","given":"Algirdas"},{"family":"Šareiko","given":"Andrej"},{"family":"Mažeika","given":"Dalius"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/electronics14244806","URL":"https://doi.org/10.3390/electronics14244806","source":"openalex"},{"id":"oa:W4411890354","type":"article-journal","title":"Transport System Digitalization in the Mining Industry","abstract":"The mining industry faces increasing pressure to improve efficiency, reduce operational costs, and adapt to modern technological trends. Central to these challenges is digitalization. This paper compares the level of digitalization in the mining industry internationally and in Slovakia, raising the question of the feasibility of implementing digitalization tools in small-scale Slovak mining operations. The presented case study demonstrates the creation of a simulation model and 3D animation for the development of small and medium-sized open pit mines, using Tecnomatix Plant Simulation software version 2302.0004, empirical data collection, and programming with SimTalk 2.0. Internationally, digitalization through modeling and simulation is already at a much higher level, with advanced solutions such as digital twins. In contrast, digitalization in Slovak mining operations is limited to basic simulation approaches, with only a few documented attempts, highlighting substantial opportunities for further development. The simulation model developed in this study enables more efficient planning and management of logistics and transportation processes, with potential benefits for operational improvements, safety, and sustainability. Adopting digitalization, even in small-scale operations, can drive the future development of the Slovak mining industry.","author":[{"family":"Ondov","given":"Marek"},{"family":"Šaderová","given":"Janka"},{"family":"Sofrankova","given":"Andrea"},{"family":"Horizral","given":"Lukáš"},{"family":"Kačmáry","given":"Peter"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17136038","URL":"https://doi.org/10.3390/su17136038","source":"openalex"},{"id":"oa:W4415598584","type":"article-journal","title":"Digital Twins in the Cloud: A Modular, Scalable and Interoperable Framework for Accelerating Verification and Validation of Autonomous Driving Solutions","abstract":"Abstract Verification and validation (V&V) of autonomous vehicles (AVs) is critical to ensure operational safety, reliability, and regulatory compliance. This typically requires exhaustive testing across a variety of operating environments and driving scenarios including rare, extreme, or hazardous situations that might be difficult or impossible to capture in reality. Additionally, physical V&V methods such as track-based evaluations or public-road testing are often constrained by time, cost, and inherent safety issues, which motivates the need for virtual proving grounds. However, the fidelity and scalability of simulation-based V&V methods can quickly turn into a bottleneck, given the sheer amount of test cases that need to be executed. In such a milieu, this work proposes a framework that flexibly scales digital twin simulations within high-performance computing clusters (HPCCs) and automates the V&V process. Here, digital twins enable the creation of high-fidelity virtual representations of the AV and its operating environments, allowing extensive scenario-based testing in precisely controlled yet realistic simulations. Meanwhile, cloud-based HPCC infrastructure brings substantial advantages in terms of computational power and scalability, enabling rapid iterations of simulations, processing and storage of massive amounts of data, and deployment of large-scale test campaigns, thereby reducing the time and cost associated with the V&V process. We demonstrate the efficacy of this approach through a case study on variability analysis of a candidate autonomy algorithm to identify vulnerabilities in its perception, planning, and control sub-systems. The modularity, scalability, and interoperability of the proposed framework are demonstrated by deploying a test campaign comprising 256 test cases on two different HPCC architectures to ensure continuous operation in a publicly shared resource setting. The findings highlight the ability of the proposed framework to accelerate and streamline the V&V process by significantly compressing (∼ 30×) the timeline.","author":[{"family":"Samak","given":"Tanmay"},{"family":"Samak","given":"Chinmay"},{"family":"Martino","given":"Giovanni"},{"family":"Nair","given":"Pranav"},{"family":"Krovi","given":"Venkat"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1115/detc2025-163799","URL":"https://doi.org/10.1115/detc2025-163799","source":"openalex"},{"id":"oa:W4412201802","type":"article-journal","title":"A Novel Energy Control Digital Twin System with a Resource-Aware Optimal Forecasting Model Selection Scheme","abstract":"As global energy demand intensifies across industrial, commercial, and residential domains, efficient and accurate energy management and control become crucial. Energy Digital Twins (EDTs), leveraging sensor measurement data and precise time-series forecasting models, offer promising monitoring, prediction, and optimization solutions for such services. Edge computing enables EDTs to deliver real-time management services placed closer to users. However, the existing energy management methodologies may fail to consider the limited resources of edge environments, which may cause service delays and reduced accuracy in management services. To solve this problem, we propose a novel energy control digital twin system with a resource-aware optimal forecasting mode selection scheme. The system dynamically selects optimal forecasting models by integrating statistical features of the input time series with available resources. It employs a two-stage approach: first, it identifies promising models through similarity detection in past time series; second, this initial recommendation is refined by considering the available computing resources to pinpoint the optimal forecasting model. This mechanism enhances adaptability and responsiveness in resource-constrained environments. Utilizing real-world LPG consumption data from 887 sensors, the proposed system achieves forecasting accuracy comparable to previous methods while reducing latency by up to 19 times in low-resource settings.","author":[{"family":"Kwon","given":"Jin"},{"family":"Rubab","given":"Anwar"},{"family":"Kim","given":"Won"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15147738","URL":"https://doi.org/10.3390/app15147738","source":"openalex"},{"id":"oa:W7164159410","type":"article-journal","title":"Glasgow Public and Private 5G Performance Dataset (2025): Acquisition and Comparative Analysis","abstract":"Abstract The rollout of 5G promised gigabit speeds and sub-10 ms latency for smart cities and IoT, but real-world urban performance in the United Kingdom remains poorly documented, with few openly accessible multi-provider datasets at neighbourhood resolution. We present a publicly released dataset of 720 outdoor 5G measurements collected across 15 Glasgow neighbourhoods over three consecutive days (6–8 April 2025), using all four major UK operators (EE, Vodafone, O2, Sky Mobile) and two consumer devices (Samsung Galaxy S24 Ultra and Google Pixel 9 Pro). This dataset was collected as part of the Ayrshire 5G Innovation Region (5GIR) project to serve as a real-world urban benchmark, providing a reference for what mature public 5G performance looks like in a comparable Scottish city, against which future Ayrshire public connectivity can be assessed. City-wide averages were 670.63 Mbps download, 165.05 Mbps upload, 21.62 ms ping, and −77.85 dBm SS-RSRP. Individual download measurements ranged from 47.84 to 1248.95 Mbps, with a coefficient of variation of 45.7%, reflecting the high variability characteristic of shared urban 5G spectrum. O2 recorded the highest median download speed (744.9 Mbps), and suburban neighbourhoods consistently outperformed the urban core. Signal strength showed negligible correlation with throughput ( r = 0.02), highlighting the complexity of real-world 5G performance. The dataset is permanently archived and openly available under CC-BY 4.0 on Zenodo 1 and is intended for reuse in urban propagation modelling, coverage prediction, smart-city planning, digital twinning, and as a 2025 baseline for 6G benchmarking.","author":[{"family":"Hart","given":"Ahren"},{"family":"Sturley","given":"Hamish"},{"family":"Mclean","given":"Paul"},{"family":"Salvá-García","given":"Pablo"},{"family":"Shakir","given":"Muhammad"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41597-026-07600-w","URL":"https://doi.org/10.1038/s41597-026-07600-w","source":"openalex"},{"id":"oa:W7130646650","type":"article-journal","title":"Autonomous Energy Management Systems for Port and Maritime Electrical Infrastructure Using Digital-Twin-Driven Architectures","abstract":"This study examines the evolving role of intelligent, data-centric energy management frameworks in addressing the growing operational, environmental, and governance complexities of modern port and maritime electrical infrastructure. As ports transition toward highly electrified and interconnected systems, conventional supervisory approaches are increasingly constrained by non-stationary demand, distributed energy resources, and heightened resilience requirements. The purpose of this study is to investigate how the integration of real-time system representation, advanced analytics, and learning-based control can support adaptive, secure, and sustainable energy operations within maritime environments. The study adopts a comprehensive analytical approach grounded in an extensive synthesis of interdisciplinary literature spanning energy systems engineering, digital modelling, artificial intelligence, cybersecurity, and infrastructure governance. Conceptual architectural analysis is employed to examine how real-time data acquisition, simulation, optimisation and autonomous decision-making can be coherently integrated within operational energy management frameworks. Particular attention is given to socio-technical considerations, including regulatory compliance, workforce capability and institutional readiness, which critically influence system performance and acceptance. The analysis reveals that digitally mediated energy management frameworks enable a shift from reactive, asset-level control toward proactive, system-level optimisation. Key findings indicate that predictive and learning-based analytics enhance operational resilience, improve energy efficiency and support emissions reduction when embedded directly into control workflows. However, the study also identifies persistent challenges related to model standardisation, validation of autonomous decisions, cybersecurity assurance and the integration of emerging energy carriers. The study concludes that intelligent energy management frameworks offer a viable pathway for achieving resilient, environmentally responsible and economically efficient port energy operations. It recommends continued interdisciplinary research, the development of robust governance and certification mechanisms, and sustained investment in human capital to ensure safe, trustworthy and scalable deployment across diverse maritime contexts.","author":[{"family":"Shittu","given":"Habeeb"},{"family":"Adeniji","given":"Ibukun"},{"family":"Oteri","given":"Oghenemaero"},{"family":"Shittu","given":"Mujeeb"}],"issued":{"date-parts":[[2026]]},"DOI":"10.62225/2583049x.2026.6.1.5740","URL":"https://doi.org/10.62225/2583049x.2026.6.1.5740","source":"openalex"},{"id":"oa:W7147194776","type":"article-journal","title":"Healthcare digital twins: A methodological literature review on integrating iot and AI for personalized medicine and predictive care","abstract":"Digital Twin (DT) technology has the potential to revolutionize healthcare delivery and enhance patient outcomes through personalized and precision medicine, simulation models for operations and interventions, and drug discovery. However, successful implementation of DTs in Internet of Things (IoT) and artificial intelligence (AI) healthcare is contingent upon addressing key challenges such as privacy, ethics, and robust data security. This paper presents a methodological literature review of DT applications in healthcare, systematically analyzing the current state of research, key enabling technologies, and implementation challenges. The review summarizes DT categorization approaches (application-based, technology-based, and real-time function-based); delineates core DT components such as sensors, data pipelines, AI/ML capabilities, security and governance measures; and surveys data collection and sensing technologies spanning EHRs, wearable/IoMT devices, and medical imaging. It further synthesizes diverse case studies across hospital management, diagnosis and treatment, patient monitoring and management, personalized therapies, and medical devices, highlighting both performance gains and translational gaps. Based on the corpus, the review identifies data integration and interoperability across heterogeneous healthcare systems as the foundational barrier to widespread DT adoption; without standardized protocols and semantics for multi-source data fusion and real-time exchange, the promise of adaptive, personalized, and predictive care remains largely unrealized. Finally, we outline actionable directions including standards-aligned data models, privacy-preserving learning (for example, federated or split learning), measurable clinical validation, and workflow-aware user experience design to accelerate translation from prototypes to routine clinical practice.","author":[{"family":"Shahnazinia","given":"Sara"},{"family":"Tavasoli","given":"Mahsa"},{"family":"Sarrafzadeh","given":"Abdolhossien"},{"family":"Karimoddini","given":"Ali"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.teler.2026.100325","URL":"https://doi.org/10.1016/j.teler.2026.100325","source":"openalex"},{"id":"oa:W7165152461","type":"article-journal","title":"Digital empowerment for green: the impact of supply chain digitalization and enterprise energy efficiency","abstract":"Improving energy efficiency in the supply chain is now a crucial component in advancing sustainable development. As a motivational force, digital technology offers new opportunities to optimise energy consumption throughout the supply chain. Based on the data of Chinese A-share listed enterprises from 2010 to 2022, this paper takes the supply chain digitalization pilot policy as an exogenous shock and uses the difference-in-difference method to thoroughly investigate the impact of supply chain digitalization on enterprise’s supply chain energy efficiency (SCEE). The research finds that supply chain digitalization can significantly improve an enterprise’s SCEE, and its promoting effect is more pronounced in non-heavily polluting, capital-intensive, and technology-intensive enterprises. In addition, the mechanism analysis results show that by enhancing the industrial concentration and innovation capability, supply chain digitalization can effectively promote the improvement of SCEE. Further analysis shows that firms’ productivity plays a positive moderating role, while environmental uncertainty plays a negative moderating role. Our findings offer enterprises a theoretical framework for advancing the sustainable transformation.","author":[{"family":"Qin","given":"Qi"},{"family":"Chen","given":"XP"},{"family":"Zhang","given":"Tianyi"},{"family":"Tan","given":"Linfang"},{"family":"Gao","given":"Da"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1057/s41599-026-07969-4","URL":"https://doi.org/10.1057/s41599-026-07969-4","source":"openalex"},{"id":"oa:W7123341275","type":"article-journal","title":"“That’s the dream, right?”: reflections on the co-design of an environmental digital twin by flood risk management professionals","abstract":"A Digital Twin (DT) dynamically represents the near-real-time status of a system, allowing users to visualise its current and forecasted status, and test interventions. Emerging technologies, such as DTs, could be transformative for working practices in environmental risk management. However, the development of DTs for environmental management and disaster risk reduction involves extensive challenges. Within Flood Risk Management (FRM), this process is complicated by the involvement of multiple professional stakeholders with diverse statutory responsibilities, priorities, and needs. There is also no formal method for the design of DTs or established method of accounting for end user needs. Processes tend to be top-down and technology driven, rather than bottom-up and user focused. This paper presents one of the first attempts to explore user co-design within the development of a DT. It stems from FLOODTWIN - an interdisciplinary DT demonstrator project for FRM in Hull and the East Riding of Yorkshire (United Kingdom), a region with complex, compound flood risk. Using data from participatory workshops and interviews, we explore the project’s co-creation process with professional FRM stakeholders, mapping emerging opportunities and challenges in the development of DTs and their interfaces from a qualitative, ethnographic perspective. We reflect on the diverse perspectives of professional users, how they engage with emerging technologies, the politics of data-sharing, and the role of academic research in shaping future development of DTs in FRM practice. We present a new evidence-base to inform future research on the co-creation of digital tools in multi-agency decision-making for FRM and wider environmental management. The paper proposes a research planning framework for navigating co-design processes in future projects to develop environmental DTs. In so doing, the paper also illustrates ways in which sub-optimal water risk management is socially constructed, and not merely a technical challenge to be surmounted.","author":[{"family":"Underhill","given":"Helen"},{"family":"Mcewen","given":"Lindsey"},{"family":"Coulthard","given":"Thomas"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fenvs.2025.1724250","URL":"https://doi.org/10.3389/fenvs.2025.1724250","source":"openalex"},{"id":"oa:W4406233782","type":"article-journal","title":"Data-Driven Technologies for Energy Optimization in Smart Buildings: A Scoping Review","abstract":"Data-driven technologies in smart buildings offer significant opportunities to enhance energy efficiency, sustainability, and occupant comfort. However, the existing literature often lacks a holistic examination of the technological advancements, adoption barriers, and business models necessary to realize these benefits. To address this gap, this scoping review synthesizes current research on these technologies, identifies factors influencing their adoption, and examines supporting business models. Inspired by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a structured search of the literature across four major databases yielded 112 relevant studies. The key technologies identified included big data analytics, Artificial Intelligence, Machine Learning, the Internet of Things, Wireless Sensor Networks, Edge and Cloud Computing, Blockchain, Digital Twins, and Geographic Information Systems. Energy optimization is further achieved through integrating renewable energy resources and advanced energy management systems, such as Home Energy Management Systems and Building Energy Management Systems. Factors influencing adoption are categorized into social influences, individual perceptions, cost considerations, security and privacy concerns, and data quality issues. The analysis of business models emphasizes the need to align technological innovations with market needs, focusing on value propositions like cost savings and efficiency improvements. Despite the benefits, challenges such as high initial costs, technical complexities, security risks, and user acceptance hinder their widespread adoption. This review highlights the importance of addressing these challenges through the development of cost-effective, interoperable, secure, and user-centric solutions, offering a roadmap for future research and industry applications.","author":[{"family":"Billanes","given":"Joy"},{"family":"Ma","given":"Zheng"},{"family":"Jôrgensen","given":"Bo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/en18020290","URL":"https://doi.org/10.3390/en18020290","source":"openalex"},{"id":"oa:W7127633690","type":"article-journal","title":"Simultaneous Digital Twin: Chaining Climbing-Robot, Defect Segmentation, and Model Updating for Building Facade Inspection","abstract":"The rapid deterioration of building facades presents substantial safety hazards in urban environments, necessitating advanced, automated inspection solutions. While computer vision (CV) and deep learning (DL) techniques have shown promise for defect analysis, critical gaps remain in achieving real-time, quantitative, and generalizable damage assessment suitable for robotic deployment. Current methods often lack precise metric quantification, struggle with diverse material appearances, and are computationally intensive for on-site processing. To address these limitations, this paper introduces a fully automated, end-to-end inspection framework integrating a wall-climbing robot, a real-time vision-based analysis system, and a digital twin management platform. The primary contributions are threefold: (1) a novel, fully integrated robotic framework for autonomous navigation, multi-sensor data collection, and real-time analysis; (2) a lightweight, synthetic data-augmented DL model for real-time defect segmentation and metric quantification, achieving a mean Average Precision (mAP) of 0.775 for segmentation, an average defect length error of 1.140 cm, and an average center position error of 0.826 cm; (3) a cloud-based digital twin platform enabling quantitative defect visualization, spatiotemporal traceability, and data-driven project management, with the on-site inspection cycle demonstrating a responsive latency of 2.8–4.8 s. Validated through laboratory tests and real building projects, the framework demonstrates significant improvements in inspection efficiency, quantitative accuracy, and decision support over conventional methods.","author":[{"family":"Song","given":"Changhao"},{"family":"Lü","given":"Chang"},{"family":"Shi","given":"Yilong"},{"family":"He","given":"Aili"},{"family":"Lin","given":"Jia‐rui"},{"family":"Ma","given":"Zhiliang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/buildings16030646","URL":"https://doi.org/10.3390/buildings16030646","source":"openalex"},{"id":"oa:W4416716941","type":"article-journal","title":"An IoT-Enabled Digital Twin Architecture with Feature-Optimized Transformer-Based Triage Classifier on a Cloud Platform","abstract":"It is essential to assign the correct triage level to patients as soon as they arrive in the emergency department in order to save lives, especially during peak demand. However, many healthcare systems estimate the triage levels by manual eyes-on evaluation, which can be inconsistent and time consuming. This study creates a full Digital Twin-based architecture for patient monitoring and automated triage level recommendation using IoT sensors, AI, and cloud-based services. The system can monitor all patients’ vital signs through embedded sensors. The readings are used to update the Digital Twin instances that represent the present condition of the patients. This data is then used for triage prediction using a pretrained model that can predict the patients’ triage levels. The training of the model utilized the synthetic minority over-sampling technique, combined with Tomek links to lessen the degree of data imbalance. Additionally, Lagrange element optimization was applied to select those features of the most informative nature. The final triage level is predicted using the Tabular Prior-Data Fitted Network, a transformer-based model tailored for tabular data classification. This combination achieved an overall accuracy of 87.27%. The proposed system demonstrates the potential of integrating digital twins and AI to improve decision support in emergency healthcare environments.","author":[{"family":"Mutashar","given":"Haider"},{"family":"Abu-Alsaad","given":"Hiba"},{"family":"Mahmoud","given":"Sawsan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/iot6040073","URL":"https://doi.org/10.3390/iot6040073","source":"openalex"},{"id":"oa:W7110901057","type":"article-journal","title":"Features of assessment and prediction of the condition of ship heat exchangers in the operation system based on digital twin technology","abstract":"One of the main directions for improving marine power plants is to increase their efficiency in the processes of heat energy conversion within individual system components. These processes are governed by the laws of thermodynamics, fluid dynamics, and heat and mass transfer, and they determine the efficiency coefficient of the installation, the amount of heat and harmful emissions, service life, as well as the compactness and overall performance of the systems. Heat exchangers, as essential components of power plants, play a crucial role in shaping these indicators. The need for improvement of ship power plant equipment and heat exchangers has been substantiated, which defines the practical demand for the development, enhancement, and implementation of scientific and technical solutions aimed at intensifying heat transfer processes under ship operating conditions. The features of assessment and prediction of the state of marine heat exchangers in operation are justified and systematically considered, based on the digital twin technology of cargo vessels and ship power plants. A model and an information-based complex system have been developed for addressing the research tasks. This allows further investigation through an aggregated model representing the digital twin of an intelligent management system for the operation of cargo vessels and ship power plants. The theoretical and experimental justification for the studied application has been provided, focusing on practical methods for forming a digital twin to represent the performance of ship heat exchange equipment under real operating conditions. An example of applying this method to an actual ship heat exchanger is presented","author":[{"family":"Gritsuk","given":"IV"},{"family":"Khudyakov","given":"IV"},{"family":"Pogorletskyi","given":"DS"},{"family":"Chernenko","given":"VV"},{"family":"Kotov","given":"AI"},{"family":"Zadorozhnii","given":"VK"}],"issued":{"date-parts":[[2025]]},"DOI":"10.31498/2225-6733.51.2025.344965","URL":"https://doi.org/10.31498/2225-6733.51.2025.344965","source":"openalex"},{"id":"oa:W7154510119","type":"article-journal","title":"Autonomous Supply Chains: Integrating Artificial Intelligence, Digital Twins, and Predictive Analytics for Intelligent Decision Systems","abstract":"Autonomous supply chains (ASC) are the next generation of digitally empowered logistics and operations systems that can make adaptive, data-driven, and intelligent decisions. Innovations in artificial intelligence (AI), digital twins (DT), and predictive analytics (PA) are transforming traditional supply chains into integrated and interactive networks to detect disruptions, simulate the future, and automatically modify operational decisions. This paper reviews the ASC mechanism and summarizes the increasing literature on the technologies and analytical capabilities available to support intelligent supply chain decision systems. A structured literature review was conducted using Scopus, Web of Science, and Google Scholar, resulting in 52 relevant studies after screening and eligibility assessment. The paper discusses the recent advances in AI-based forecasting, simulation environments using digital twins, data integration using the Internet of Things (IoT), and predictive analytics. These technologies can help an organization gain real-time visibility of the supply chain networks. They improve the precision of demand forecasting, optimize inventory and production planning, and dynamically coordinate logistics operations. Digital twins allow the development of virtual models of supply chain ecosystems, which could be used to test scenarios, analyze risks, and plan strategies. These capabilities combined can be used to create predictive and self-adaptive supply networks capable of being responsive to uncertainty and market volatility. Besides examining the technological foundations, the paper also tracks key challenges related to the move towards autonomous supply chains, such as data governance, system interoperability, cybersecurity risks, algorithm transparency, and the necessity of successful human-AI collaboration in decision-making. The synthesis leads to a multi-layered framework that integrates data acquisition, analytics, simulation, and execution for autonomous decision-making in supply chains. Future research directions in relation to resilient supply networks, intelligent automation, and adaptive supply chain ecosystems are also provided in the study. Through integrating existing information on the new forms of intelligent technology and how it can be incorporated into the supply chain systems, this review contributes to the literature on next-generation supply chains. It will also offer information to both researchers and practitioners aiming at designing autonomous as well as data-driven supply networks.","author":[{"family":"Shamsuddoha","given":"Mohammad"},{"family":"Zimmerman","given":"Honey"},{"family":"Nasir","given":"Tasnuba"},{"family":"Sakib","given":"Md"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/info17040371","URL":"https://doi.org/10.3390/info17040371","source":"openalex"},{"id":"oa:W7124763352","type":"article-journal","title":"Continued use of virtual commissioning models: A novel approach toward digital twins for automated production systems","abstract":"Abstract Virtual Commissioning (VC) is an increasingly integral practice in the engineering of production systems, evidenced by growing research and industrial adoption. Advancements in VC model fidelity, computational performance, and automated generation are improving the validation of complex production systems and point toward further applicability beyond conventional control software validation. In industrial practice, however, VC models are still confined to their original use. While emerging applications for VC models in the operational phase highlight the potential for model reuse, a structured method for transforming these valuable engineering assets into Digital Twins (DTs) is still absent. This paper addresses this gap through three main contributions: first, by clarifying the VC/DT boundary within production contexts and identifying open research questions; second, by introducing a novel six-phase transformation method; and third, by identifying industrially-derived use cases and their specific requirements. The proposed method adopts the Design Science Research (DSR) methodology to systematically structure the problem space, derive actionable objectives, and design the iterative development process. Initial results include a set of industrial use cases with their corresponding requirements, as well as the exemplary execution of one development cycle. Finally supplemented by a qualitative cost-benefit analysis, this work offers practical guidance for realizing VC-based DTs that support operational tasks in production environments.","author":[{"family":"Ferle","given":"Felix"},{"family":"Chen","given":"Shengjian"},{"family":"Kuhn","given":"Alexander"},{"family":"Klingel","given":"Lars"},{"family":"Schenke","given":"Christer"},{"family":"Tekouo","given":"William"},{"family":"Verl","given":"Alexander"},{"family":"Ihlenfeldt","given":"Steffen"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s00170-025-17195-y","URL":"https://doi.org/10.1007/s00170-025-17195-y","source":"openalex"},{"id":"oa:W4413348638","type":"article-journal","title":"Cohort Profile Update: The Norwegian Mother, Father and Child Cohort (MoBa)","abstract":"The Norwegian Mother, Father and Child Cohort Study (MoBa) is a large population-based cohort and biobank for research on health and development. MoBa includes data on 94 834 mothers, 75 229 fathers, and 113 632 children (currently aged 15–25 years) recruited during pregnancy between 1999 and 2008, with continuing follow-up from a life-course perspective. Up to 25 years of follow-up with linkages to national registries provides unique research opportunities. Recent data collections among children aged 13–25 years and parents aged 32–86 years include questionnaires on health, lifestyle, fertility, COVID-19, cognitive tests, and clinical measurements. Genotyped data are available for 225 667 MoBa participants, including ∼30 000 full mother–father–child trios. The biodata resource also offers large-scale datasets (n > 10 000) on the epigenome and metabolome and smaller datasets (n = 100–10 000) on biomarkers from blood, plasma, urine, and serum. MoBa data access is given through helsedata.no; see https://www.fhi.no/en/ch/studies/moba/for-forskere-artikler/research-and-data-access/. New collaborations are welcome. The Norwegian Mother, Father and Child Cohort Study (MoBa), initially named the Norwegian Mother and Child Study, was launched in the 1990s by epidemiologists at the Norwegian Institute of Public Health, studying pregnancy outcomes from the Medical Birth Registry of Norway [1]. The primary aim was to identify causes of diseases by collecting comprehensive exposure and outcome data from fetal life onwards [2]. Recruitment began in 1999 with a postal invitation and the first questionnaire was sent prior to the routine ultrasound examination in the 17th week of pregnancy. Biological material was collected during the ultrasound appointment. In 2008, the goal of recruiting 100 000 pregnancies was achieved and recruitment concluded, with the last MoBa baby born in July 2009. Previous MoBa cohort profiles have described the initial sampling and waves of data collection up to 2016 [2, 3]. Since 2016, data-collection efforts in MoBa have been initiated to update and enrich existing datasets, providing crucial information on further development and health outcomes, particularly in the offspring generation. Adolescence and early adulthood are life stages characterized by significant social, physical, and emotional changes that can impact lifelong health and wellbeing. The new data collections among MoBa teens (aged 16–17 years) and young adults (aged 18–25 years) encompass a wide range of topics, including physical and mental health, pubertal development, health behaviors, pain, career and family plans, living situations, and social media use. Through a collaboration with the Norwegian University of Science and Technology, MoBa has, for the first time, included a web-based neuropsychological test battery as part of the new data collection to provide reliable measures of cognitive function [4, 5]. The fertility rate has decreased substantially, both in Norway and globally, over the past few decades [6], making the causes and consequences of childlessness important fields of research. Data on reproductive health indicators in young adulthood are being collected through questionnaires and clinical examinations to gain insights into the status of reproductive health in young adults today and into factors influencing fertility, such as hormonal status, environmental exposures, and lifestyle factors. When the COVID-19 pandemic hit in early 2020, billions of people were affected by the infection and by national and regional strategies to prevent its spread. A biweekly data collection in MoBa was initiated in March 2020 and invitations were sent to all mothers and fathers as well as to 16- to 17-year-olds, to monitor symptoms and to study potential impacts of the pandemic. Additional blood samples were collected in 2020, 2021, and 2023. Important research questions included the effects of vaccination and COVID-19 infection on short- and lo","author":[{"family":"Brandlistuen","given":"Ragnhild"},{"family":"Kristjansson","given":"Dana"},{"family":"Alsaker","given":"Elin"},{"family":"Valen","given":"Ragnhild"},{"family":"Birkeland","given":"Even"},{"family":"Røyrvik","given":"Ellen"},{"family":"Page","given":"Christian"},{"family":"Aamelfot","given":"Maria"},{"family":"Vangbæk","given":"Sille"},{"family":"Ask","given":"Helga"},{"family":"Havdahl","given":"Alexandra"},{"family":"Brantsæter","given":"Anne"},{"family":"Rørtveit","given":"Guri"},{"family":"Håberg","given":"Siri"},{"family":"Magnus","given":"Per"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1093/ije/dyaf139","URL":"https://doi.org/10.1093/ije/dyaf139","source":"openalex"},{"id":"oa:W7164910563","type":"article-journal","title":"Approaching the Twin Transition in the Tire Industry","abstract":"Considering its resource-intensive production, complex global supply chains and substantial environmental impact, the tire industry provides a critical context for twin transition research. Using an in-depth qualitative research design, this study explores how sustainability and digitalization are jointly embedded within the strategic and operational practices of a premium tire manufacturer. The study reveals an integrated life-cycle approach that combines circular material innovation, energy transition, supplier governance, and artificial intelligence-enabled digitalization. The study illustrates the firm’s engagement in the twin transition, marked by systemic tradeoffs between environmental performance, cost efficiency and market competitiveness. Both managerial- and literature-related implications are discussed.","author":[{"family":"Grosu","given":"Raluca"},{"family":"Sava","given":"Ștefan"},{"family":"Francu","given":"Cristian"},{"family":"Amicarelli","given":"Vera"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/15332969.2026.2688330","URL":"https://doi.org/10.1080/15332969.2026.2688330","source":"openalex"},{"id":"oa:W4408477851","type":"article-journal","title":"Going digital to boost safe and sustainable materials innovation markets. The digital safe-and-sustainability-by-design innovation approach of the PINK project","abstract":"Hub, as the user Interface to the platform, finally guides the user through the complete AdMas&Chems development process from idea creation to market introduction. Guided by two Developmental Case Studies, the process of building of the PINK Platform is iterative, ensuring industry readiness to implement and apply it. Additionally, the Industrial Demonstrator programme will be introduced as part of the final project phase, which allows industry partners and especially small and medium enterprises (SMEs) to become part of the PINK consortium. Feedback from the Demonstrators as well as other stakeholder-engagement activities and collaborations will shape the platform's final look and feel and, even more important, activities to assure long-term technical sustainability.","author":[{"family":"Exner","given":"Thomas"},{"family":"Dokler","given":"Joh"},{"family":"Friedrichs","given":"Steffi"},{"family":"Seitz","given":"Christian"},{"family":"Bleken","given":"Francesca"},{"family":"Friis","given":"Jesper"},{"family":"Hagelien","given":"Thomas"},{"family":"Mercuri","given":"Francesco"},{"family":"Costa","given":"Anna"},{"family":"Furxhi","given":"Irini"},{"family":"Sarimveis","given":"Haralambos"},{"family":"Afantitis","given":"Antreas"},{"family":"Marvuglia","given":"Antonino"},{"family":"Larreagallegos","given":"Gustavo"},{"family":"Serchi","given":"Tommaso"},{"family":"Serra","given":"Angela"},{"family":"Greco","given":"Dario"},{"family":"Nymark","given":"Penny"},{"family":"Himly","given":"Martin"},{"family":"Wiench","given":"Karin"},{"family":"Watzek","given":"Nico"},{"family":"Schillinger","given":"Eva"},{"family":"Gavillet","given":"Jérôme"},{"family":"Lynch","given":"Iseult"},{"family":"Karwath","given":"Andreas"},{"family":"Haywood","given":"Alexe"},{"family":"Gkoutos","given":"Georgios"},{"family":"Hischier","given":"Roland"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.csbj.2025.03.019","URL":"https://doi.org/10.1016/j.csbj.2025.03.019","source":"openalex"},{"id":"oa:W4411153268","type":"article-journal","title":"Democratizing Digital Transformation: A Multisector Study of Low-Code Adoption Patterns, Limitations, and Emerging Paradigms","abstract":"Low-code development platforms (LCDPs) have emerged as transformative tools for accelerating digital transformation across industries by enabling rapid application development with minimal hand-coding. This paper synthesizes existing research and industry practices to explore the adoption, benefits, challenges, and future directions of low-code technologies in key sectors: automotive, equipment manufacturing, aerospace, electronics, and energy. Drawing on academic literature, industry reports, and case studies, this review highlights how low-code bridges the gap between IT and domain experts while addressing sector-specific demands. The study emphasizes the significant impact of LCDPs on operational efficiency, innovation acceleration, and the democratization of software development. However, it also identifies critical challenges related to customization, interoperability, security, and usability. The paper concludes with a discussion of emerging trends, including enhanced AI/ML integration, edge computing, open-source ecosystems, and sector-specific platform evolution, which are poised to shape the future of low-code development. Ultimately, this research underscores the potential of low-code platforms to drive sustainable digital transformation while addressing the complex needs of modern industries.","author":[{"family":"Shi","given":"Zhengwu"},{"family":"Dong","given":"Junyu"},{"family":"Gan","given":"Yanhai"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15126481","URL":"https://doi.org/10.3390/app15126481","source":"openalex"},{"id":"oa:W4409381785","type":"article-journal","title":"Digital Transformation in Healthcare Management: From Artificial Intelligence to Blockchain","abstract":"The digital transformation of healthcare is revolutionizing the management of medical institutions, improving operational efficiency, patient outcomes, and data security. With the increasing complexity of healthcare systems, the integration of cutting-edge technologies such as Artificial Intelligence. The COVID-19 pandemic significantly accelerated digital transformation, compelling healthcare institutions to adopt telemedicine, AI-assisted diagnostics, and cloud-based medical records to meet growing patient demands and resource constraints. The rapid digital transformation of healthcare is driven by advancements in Artificial Intelligence (AI), blockchain, the Internet of Things (IoT), and Big Data. This review article aims to analyze the objectives and implications of digital transformation in medical institutions, focusing on the integration of AI, blockchain, and IoT in hospital management. The methodological approach for this review article focuses on synthesizing existing literature to examine the role of Artificial Intelligence (AI), blockchain, the Internet of Things (IoT), and Big Data in the digital transformation of healthcare management. The integration of Artificial Intelligence (AI), Blockchain, Internet of Things (IoT), and Big Data has demonstrated significant improvements in healthcare management, enhancing efficiency, patient outcomes, and data security.","author":[{"family":"Krotkiewicz","given":"Marcin"},{"family":"Szynkaruk","given":"Agata"},{"family":"Stachyra","given":"Alina"}],"issued":{"date-parts":[[2025]]},"DOI":"10.36740/wlek/202445","URL":"https://doi.org/10.36740/wlek/202445","source":"openalex"},{"id":"oa:W7133948753","type":"article-journal","title":"A digital twin framework for predicting and simulating type 2 diabetes onset using retrospective lifestyle data","abstract":"Introduction: Type 2 Diabetes Mellitus (T2DM) is a rising global health concern, heavily influenced by modifiable lifestyle and psychosocial factors. However, most predictive tools focus on biomedical markers and rely on real-time data from wearables or electronic health records, limiting their scalability in resource-constrained settings. This study presents a novel digital twin (DT) framework that uses retrospective lifestyle, behavioral, and psychosocial data to forecast T2DM onset and simulate the estimated effects of preventive interventions. Methods: Data were drawn from 19,774 participants in the UK Biobank cohort, followed for up to 17 years. A penalized Cox proportional hazards model was employed to estimate individual time-to-event risk trajectories based on 90 candidate predictors. Predictors were selected through univariate screening, multicollinearity assessment, and variance filtering, yielding a final model with 14 significant variables. Causal inference techniques, including directed acyclic graphs (DAGs) and counterfactual simulations, were used to explore intervention effects on disease progression. Results: 0.004). Psychosocial stressors such as loneliness, insomnia, and poor mental health emerged as strong independent predictors and were associated with estimated increases in absolute T2DM risk of approximately 35 percentage points individually and nearly 78 percentage points when combined, under the modeled assumptions. These effects were partly reinforced through diet, with high intake of processed meat, salt, and sugary cereals acting as risk amplifiers within the modeled causal pathways. Cheese intake was protective overall, but its estimated benefit was attenuated under psychosocial stress, where reduced consumption produced a small, directionally harmful mediation effect. Counterfactual simulations suggested that improvements in psychosocial conditions could reduce estimated T2DM risk by approximately 11.6 percentage points within the modeled cohort, with protective dietary patterns such as cheese consumption re-emerging as psychosocial stress was alleviated. The model also revealed pronounced ethnic disparities, with South Asian, African, and Caribbean participants exhibiting significantly higher estimated risk than White counterparts within this cohort. These findings highlight the potential of integrated, stress-informed prevention strategies that address both psychosocial and dietary pathways. Conclusion: This study introduces a transparent, simulation-enabled DT framework for estimating T2DM risk and exploring behavioral intervention scenarios without reliance on real-time data streams. It enables interpretable, personalized prevention planning and supports exploration of scalable deployment in public health, particularly in underserved or low-infrastructure environments. The integration of psychosocial and lifestyle data represents an important step toward more equitable and behaviorally informed digital health solutions.","author":[{"family":"Kiran","given":"Mahreen"},{"family":"Xie","given":"Ying"},{"family":"Ball","given":"Graham"},{"family":"Schutte","given":"Rudolph"},{"family":"Anjum","given":"Nasreen"},{"family":"Pierścionek","given":"Barbara"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fdgth.2026.1710829","URL":"https://doi.org/10.3389/fdgth.2026.1710829","source":"openalex"},{"id":"oa:W7135169554","type":"article-journal","title":"Design of a Virtual LiDAR System Simulation Training Platform for Port Automation Equipment Based on Digital Twin","abstract":"As the core sensing method for port automation equipment, LiDAR is widely used in spatial distance measurement, three-dimensional positioning, and environmental perception. However, its ranging mechanism, parameter configuration, and role in complex port operations are relatively abstract, making traditional training difficult to achieve intuitive understanding and efficient application. To address this issue, this paper proposes a virtual LiDAR simulation training platform based on digital twin technology. The platform constructs a virtual environment highly consistent with real port operation processes, designs a virtual LiDAR module with adjustable horizontal/vertical field of view, resolution, channel count, and ranging distance, and achieves bidirectional synchronization of data and control signals between physical and twin spaces. Using a bulk cargo handling machine as the verification object, consistency comparison experiments were conducted on point cloud density, ranging accuracy, and geometric similarity. The results show that the virtual point clouds generated by the platform are highly consistent with real point clouds in key indicators, featuring low cost, high flexibility, and scalability, and can provide reliable support for operation training, algorithm testing, equipment deployment assessment, and operational safety analysis of port automation equipment.","author":[{"family":"Zhang","given":"Yujie"},{"family":"Man","given":"Xintai"},{"family":"He","given":"Mengjie"},{"family":"Mi","given":"Chao"},{"family":"Postolache","given":"Octavian"},{"family":"Shen","given":"Yang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/978-981-95-6911-3_46","URL":"https://doi.org/10.1007/978-981-95-6911-3_46","source":"openalex"},{"id":"oa:W4410359613","type":"article-journal","title":"Microalgae and circular economy: unlocking waste to resource pathways for sustainable development","abstract":"The growing environmental crises demands an urgent transition from a linear to a circular economy. Microalgae are photosynthetic microorganisms that offer exceptional potential due to their rapid growth, high CO₂ fixation capacity, and ability to remove nutrients and pollutants from wastewater, producing both clean water and valuable biomass. Such characteristics have attracted interest in developing circular systems that transform wastes into resources such as biomaterials, biofertilisers, biofuels and bioactive compounds. However, various challenges hinder their industrial application, including technical, economic, environmental, commercial and political barriers. Technical limitations such as inefficient culture systems, low productivity and contamination risks, can be addressed by using genetic engineering tools to develop superior strains, and by developing bioreactors coupled with emerging technologies (AI, Digital Twin). Additionally, it was found that studies using wastewater for microalgae cultivation and a biorefinery approach to recover low and high value bioproducts were found to be energetically, environmentally and economically viable. Several projects and studies demonstrating microalgae-based circular economy models were highlighted. Finally, the implementation of clear regulations and guidelines for wastewater composition in microalgae systems is recommended to facilitate market acceptance and consumer trust in microalgae-derived products.","author":[{"family":"Santos","given":"BCD"},{"family":"Freitas","given":"Filomena"},{"family":"Sobral","given":"AJFN"},{"family":"Encarnação","given":"Telma"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/19397038.2025.2501488","URL":"https://doi.org/10.1080/19397038.2025.2501488","source":"openalex"},{"id":"oa:W4411436694","type":"article-journal","title":"Active Fabric Origami Enabled by Digital Embroidery of Magnetic Yarns","abstract":"Active fabrics can perform deformations such as contraction, expansion, and bending when exposed to external stimuli. Origami, the ancient art of paper folding, transforms a 2D sheet into a complex 3D structure. However, integrating origami-inspired designs into active fabrics presents significant challenges, including the large-scale production of stimuli-responsive yarns that can be processed using standard textile techniques to achieve intricate origami patterns with high precision and versatility. In this work, the large-scale fabrication of magnetic yarns featuring high magnetic susceptibility, mechanical strength, and flexibility is reported, which is enabled by processing magnetic polymer composites with a series of textile engineering processes. Utilizing digital embroidery, these magnetic yarns are programmed into origami patterns with predefined yarn alignments on flexible fabrics to create various active fabric origami structures that are mechanical durable and functional consistent. These structures can reversibly transform among shapes in response to specific magnetic fields, enabling a range of functionalities such as altering surface roughness, delivering linear actuation, mimicking flower blooming, and providing switchable thermal insulation. The novel active fabric origami provides promising smart platforms across areas as diverse as smart textiles, soft robotics, wearable devices, and fashion.","author":[{"family":"Li","given":"Haiqiong"},{"family":"Zhang","given":"Han"},{"family":"Zha","given":"Xiang‐jun"},{"family":"Pu","given":"Jun‐hong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/adma.202503948","URL":"https://doi.org/10.1002/adma.202503948","source":"openalex"},{"id":"oa:W4409919505","type":"article-journal","title":"Designing Innovative Digital Solutions in the Cultural Heritage and Tourism Industry: Best Practices for an Immersive User Experience","abstract":"Digital transformation is reshaping business strategies and driving innovation across various industries including Cultural Heritage (CH) and tourism. Digital technologies, such as eXtended Reality (XR) and the Internet of Things (IoT), are increasingly being adopted to enhance visitors’ experiences, foster interactive engagement, and promote cultural knowledge. Despite the growing number of digital solutions proposed in the CH sector, several challenges remain in differentiating digital products and services, including matching industry needs and user expectations. This aspect is of particular interest when dealing with small and medium enterprises (SMEs), which often suffer from limited resources. Therefore, to design an effective digital solution, like a cloud-based platform for tourism and heritage applications, it is essential to first identify the key requirements, expectations, and preferences of SMEs and customers. This study presents the findings of a survey-based analysis conducted among 122 CH and tourism professionals, focusing on the most relevant features, services, and functionalities that such platforms should integrate. Results indicate a strong demand for cloud-based solutions that incorporate XR, IoT, sensors, and smart devices to collect context data and deliver personalized, immersive, and context-aware experiences. These insights suggest valuable practices for the development of digital tools that effectively support cultural organizations in engaging visitors.","author":[{"family":"Vecchio","given":"Vito"},{"family":"Lazoi","given":"Mariangela"},{"family":"Marche","given":"Claudio"},{"family":"Mettouris","given":"Christos"},{"family":"Montagud","given":"Mario"},{"family":"Specchia","given":"Giorgia"},{"family":"Ali","given":"Mostafa"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15094935","URL":"https://doi.org/10.3390/app15094935","source":"openalex"},{"id":"oa:W7119470489","type":"article-journal","title":"Roots and the rhizosphere: a perspective on the hidden engine of regenerative, antifragile, and digitally enabled agriculture","abstract":"For decades, agricultural optimization has focused primarily on aboveground yield and external inputs while neglecting the complexity and functional integrity of belowground processes. The rhizosphere, the dynamic zone surrounding roots, has long been investigated through isolated components but rarely in a holistic framework, despite its critical role in agroecosystem productivity, soil fertility, and sustainability. Moreover, the translation of this knowledge into routine farm-scale practice remains quite limited. This perspective argues for repositioning the rhizosphere at the center of agricultural innovation. In this view, roots and their microbial partners are not only fundamental for crop performance but also drivers of antifragility, enabling farming systems to withstand and even improve under environmental stresses, while sustaining productivity. Integrating advances in root biology, soil chemistry, microbial ecology, and agronomics, this review shows that rhizosphere processes drive key biogeochemical functions such as carbon sequestration, nutrient cycling, and stress adaptation. Critical gaps include limited integration of root-microbiome traits in crop breeding, lack of field-ready rhizosphere diagnostics, and variable performance of microbial inoculants across soils and climates. Addressing these challenges is essential to operationalize rhizosphere science at field scale and support reduced-input, climate-resilient farming systems. Looking forward, emerging technologies ranging from high-resolution imaging and spectroscopy to artificial intelligence offer unprecedented insight into belowground complexity and a unique opportunity to bridge the gap between experimental insights and real-world farming. Ultimately, the review calls for a paradigm shift embedding rhizosphere processes into crop breeding, farming system design, and management strategies. Recognizing the rhizosphere as a primary entry point for innovation is essential for translating science into practical levers for regenerative, antifragile, and sustainable agriculture. • Roots and microbes form dynamic alliances that drive nutrient cycles and soil health. • The rhizosphere is central to antifragile, climate-smart, and regenerative farming. • Root exudates shape microbial recruitment and enhance plant stress adaptability. • AI, imaging, and sensors unlock real-time insights into rhizosphere functionality. • Redesigning agriculture from below connects breeding, management, and microbiomes.","author":[{"family":"Cesco","given":"Stefano"},{"family":"Zuluaga","given":"Monica"},{"family":"Cavani","given":"Luciano"},{"family":"Borruso","given":"Luigimaria"},{"family":"Laudicina","given":"Vito"},{"family":"Mazzetto","given":"Fabrizio"},{"family":"Mimmo","given":"Tanja"},{"family":"Pii","given":"Y"},{"family":"Terzano","given":"Roberto"},{"family":"Astolfi","given":"Stefania"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.farsys.2026.100199","URL":"https://doi.org/10.1016/j.farsys.2026.100199","source":"openalex"},{"id":"oa:W4416593640","type":"article-journal","title":"Giga‐Voxel Multiscale Composite Architecture Mirrored Through a Data‐to‐Model Closed‐Loop Digital Twin","abstract":"Giga-voxel digital models offer abundant geometric detail; however, no mainstream method currently exists to efficiently distribute individual voxels across massive image volumes, and designing complex anisotropic composite materials remains infeasible due to the absence of promising methods. Herein, we propose a systematic digital twin workflow tailored for generating high-fidelity virtual representations of anisotropic composite microstructures and giga-voxel meso-structural models, leveraging a harmonious integration of top-down image-based modeling and bottom-up data-driven generation. Our study demonstrates the efficacy of micro-digital representations as foundational building blocks within a continuum of digital assembly processes tailored for mesostructural models. Utilizing 3D image data, specifically X-ray tomography, our data-driven modeling meticulously characterizes the geometric attributes of the experimentally observed objects, thereby facilitating the creation of digital unit twins, each endowed with distinct identities assigned through a random seed generation. The closed-loop system provides feedback mechanism between data and model to ensure the 3D quality of the generated models. For hierarchical organization at the giga-voxel level, the digital unit twins are methodically expanded into cohesive 3D architectures based on assembly relationship at length scales of more than four orders of magnitude. Remarkably, this hierarchical model provides intricate insight into micro-to-macro geometrics while preserving the intrinsic microstructure.","author":[{"family":"Yu","given":"Siwon"},{"family":"Jang","given":"Seungsoo"},{"family":"Cho","given":"Young"},{"family":"Park","given":"Seunggyu"},{"family":"Hwang","given":"Jun"},{"family":"Hong","given":"Soon"},{"family":"Marrow","given":"TJ"},{"family":"Lee","given":"Kang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/adma.202510559","URL":"https://doi.org/10.1002/adma.202510559","source":"europepmc"},{"id":"oa:W4415769242","type":"article-journal","title":"Quality by digital design in action: a workflow for crystallisation and isolation","abstract":"This paper exemplifies a Quality by Digital Design (QbDD) workflow for the crystallisation and isolation of active pharmaceutical ingredients (APIs). QbDD uses a digital first approach to improve manufacturability and sustainability whilst assuring product quality within practical constraints. This study uses three exemplar compounds (ibuprofen, lamivudine, and AZD0837), each of which presents a different challenge for crystallisation; these include agglomeration, solid state form, and slow growth rates, respectively. These cases are used to evaluate the benefits of the QbDD approach and identify gaps for future research. Results of this work show that the QbDD workflow reduces the number of physical experiments by 28% and the API material usage by 52-65% when compared to comparable API development processes not using this approach. This approach provides a route to practically implement and exploit the benefits of digital tools and overcome digital skill shortages. By exploiting digital tools for process simulation and optimisation, the workflow improves efficiency, even in complex cases where multiple workflow iterations are required. This workflow, therefore, paves the way for more sustainable and cost-effective API production and it promotes future standardisation of digital design in pharmaceutical development.","author":[{"family":"Houson","given":"Ian"},{"family":"Siddique","given":"Humera"},{"family":"Chong","given":"Magdalene"},{"family":"Robertson","given":"Murray"},{"family":"Turner","given":"Alice"},{"family":"Nordon","given":"Alison"},{"family":"Osman","given":"Amal"},{"family":"Galindo","given":"Amparo"},{"family":"Dunn","given":"Andrew"},{"family":"Johnson","given":"Blair"},{"family":"Benyahia","given":"Brahim"},{"family":"Brown","given":"Cameron"},{"family":"Mustoe","given":"Chantal"},{"family":"Price","given":"C"},{"family":"Reilly","given":"Chris"},{"family":"Adjiman","given":"Claire"},{"family":"Jackson","given":"George"},{"family":"Prasad","given":"Elke"},{"family":"Halbert","given":"Gavin"},{"family":"Feilden","given":"Helen"},{"family":"Šefčık","given":"Ján"},{"family":"Mcginty","given":"John"},{"family":"Robertson","given":"John"},{"family":"Smith","given":"Ken"},{"family":"Al-Attili","given":"Mais"},{"family":"Mcgowan","given":"Mark"},{"family":"Siddique","given":"Mariam"},{"family":"Pathan","given":"Momina"},{"family":"Rajoub","given":"Nazer"},{"family":"Hamilton","given":"NG"},{"family":"Feeney","given":"Rachel"},{"family":"Brown","given":"Scott"},{"family":"Urwin","given":"Stephanie"},{"family":"Bernet","given":"Thomas"},{"family":"Pickles","given":"Thomas"},{"family":"Li","given":"Wei"},{"family":"Florence","given":"Alastair"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.ijpharm.2025.126343","URL":"https://doi.org/10.1016/j.ijpharm.2025.126343","source":"openalex"},{"id":"oa:W4414745885","type":"article-journal","title":"CAD-guided 6D pose estimation with deep learning in digital twin for industrial collaborative robot manipulation","abstract":"6D pose estimation in the bin-picking task has attracted increasing attention from researchers. CAD model-based method have been proposed, demonstrating its effectiveness. However, most existing research relies on point cloud registration from the RGB-D camera, which is often not robust to noise and low-light conditions, leading to degraded point cloud quality and reduced accuracy. Thereby, the method accuracy is significantly affected. Moreover, detecting objects correctly plays a vital role in multiple objects. Supervised deep learning takes consideration into this task, but it typically requires a large amount of labeled data. In industrial environments, sample collection and model retraining are limited. To address these challenges, we introduce the potential approach that integrates the zero-shot learning YOLOE and DEFOM-Stereo model. The YOLOE detects and localizes the object without requiring object-specific training, while DEFOM-Stereo generates point clouds for the CAD model-based pose estimation. Extensive experiments demonstrate that the proposed approach achieves high accuracy in pose estimation, which is essential for grasp planning and manipulation tasks in robotics. Furthermore, the proposed approach is applied in a Unity3D-based digital twin, enabling enhanced virtual representation of a physical pickup target with an estimated pose. Hence, the research result supports more accurate and responsive digital twins for robotics toward the development of smart manufacturing systems.","author":[{"family":"Dong","given":"Quang"},{"family":"Pham","given":"Thu"},{"family":"Nguyen","given":"Tuan"},{"family":"Tran","given":"Chi"},{"family":"Tran","given":"Hoang"},{"family":"Tan","given":"Desney"},{"family":"Nguyen","given":"Khang"},{"family":"Ngyuyen","given":"Quang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.4108/airo.9676","URL":"https://doi.org/10.4108/airo.9676","source":"openalex"},{"id":"oa:W7116764415","type":"article-journal","title":"A Digital Twin-Enhanced KJ-Kano Framework for User-Centric Conceptual Design of Underwater Rescue Robots","abstract":"To address the increasing complexity and diversity of user requirements in underwater rescue equipment, this study proposes a Digital Twin (DT)-enhanced KJ-Kano conceptual design framework. It systematically closes the feedback loop between requirement prioritization and experiential validation. Unlike traditional approaches, this framework orchestrates KJ clustering, Kano analysis, and mission-aware DT simulation in a domain-adapted, iterative workflow, enabling dynamic validation of user needs under high-risk, simulated rescue scenarios. Functional expectations and preferences were clustered and prioritized, then instantiated in a modular DT prototype for navigation, manipulation, and perception tasks. To evaluate design effectiveness, 55 participants operated the robot DT model and its control interfaces in virtual rescue missions. User satisfaction across functionality, interactivity, intelligence, and appearance was assessed with a five-point Likert scale, and the results showed high reliability (Cronbach’s α = 0.86) and positive evaluations (overall mean = 3.83). Intelligent experience scored highest (3.95), while ease of operation was lowest (3.60), suggesting potential for interface optimization. The framework effectively transforms heterogeneous, context-specific user requirements into validated design solutions, offering a replicable, data-driven methodology for early-stage conceptual design of underwater rescue robots and other safety-critical human–machine systems, bridging the gap between generic design methods and high-risk domain application.","author":[{"family":"Niu","given":"Xiaojing"},{"family":"Ye","given":"Jingying"},{"family":"Chen","given":"Liling"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app16010135","URL":"https://doi.org/10.3390/app16010135","source":"openalex"},{"id":"doi:10.1007/978-3-032-09040-9_9","type":"article-journal","title":"Digital Twin for Datacenter: HPC4AI UniTO Case Study","abstract":"Abstract The HPC4AI (High-Performance Computing for Artificial Intelligence) datacenter at the University of Turin’s Computer Science Department was established to meet the rapidly growing computational demands of interdisciplinary AI research. HPC4AI innovates by redefining the traditional roles of Cloud and High-Performance Computing (HPC) systems, where the Cloud provides a modern interface for HPC, and HPC acts as an accelerator for Cloud applications. To date, it has supported over 40 research projects spanning diverse fields such as astronomy, medicine, and human sciences. Additionally, HPC4AI serves as a research and development platform for exploring, developing, and testing novel datacenter technologies. It features a variety of experimental computing platforms and the first prototype of a two-phase evaporative server cooling system. This work outlines the operational management of HPC4AI, highlighting challenges, lessons learned, and key opportunities related to digital twins for datacenters.","author":[{"family":"Vaccaro","given":"Viviana"},{"family":"Birke","given":"Robert"},{"family":"Meschini","given":"Silvia"},{"family":"Tagliabue","given":"Lavinia"},{"family":"Rabellino","given":"Sergio"},{"family":"Legazpi","given":"Pablo"},{"family":"Andinucci","given":"Marco"},{"family":"Aldinucci","given":"Marco"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/978-3-032-09040-9_9","URL":"https://doi.org/10.1007/978-3-032-09040-9_9","source":"openalex"},{"id":"oa:W4410975468","type":"article-journal","title":"Digital Intelligence in Building Lifecycle Management: A Mixed-Methods Approach","abstract":"The rapid evolution of information technology has positioned digital intelligence as a transformative force across socio-economic domains, necessitating rigorous scholarly examination of its applications and implications. This paper systematically explores the digital intelligence empowerment in Building Lifecycle Management (BLM) under the framework of Construction 4.0. Employing a mixed-methods approach, the research combines a systematic literature review with bibliometric visualization analysis using CiteSpace to map the intellectual landscape, identify key technological drivers (for example, Building Information Modeling, Internet of Things, artificial intelligence, and blockchain), and elucidate integration mechanisms across planning, design, construction, and operational phases. A comparative case study of BLM adoption further demonstrates the transformative impacts of digital intelligence on project efficiency, sustainability, and safety. The research highlights the role of digital intelligence in addressing industry challenges, including resource waste (global construction generates 30% of total waste), safety risks, and stagnant productivity, while fostering innovation and sustainable development. This study advances a holistic model for digital transformation in BLM, offering actionable insights for stakeholders to bridge the academia–industry divide and prioritize strategic investments in interoperable systems, workforce upskilling, and governance frameworks.","author":[{"family":"Lai","given":"JS"},{"family":"Wan","given":"Runnan"},{"family":"Chong","given":"Heap‐yih"},{"family":"Liao","given":"Xiaofeng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17115121","URL":"https://doi.org/10.3390/su17115121","source":"openalex"},{"id":"oa:W4413286518","type":"article-journal","title":"VisFactory: Adaptive Multimodal Digital Twin with Integrated Visual-Haptic-Auditory Analytics for Industry 4.0 Engineering Education","abstract":"Industry 4.0 has intensified the skills gap in industrial automation education, with graduates requiring extended on boarding periods and supplementary training investments averaging USD 11,500 per engineer. This paper introduces VisFactory, a multimedia learning system that extends the cognitive theory of multimedia learning by incorporating haptic feedback as a third processing channel alongside visual and auditory modalities. The system integrates a digital twin architecture with ultra-low latency synchronization (12.3 ms) across all sensory channels, a dynamic feedback orchestration algorithm that distributes information optimally across modalities, and a tripartite student model that continuously calibrates instruction parameters. We evaluated the system through a controlled experiment with 127 engineering students randomly assigned to experimental and control groups, with assessments conducted immediately and at three-month and six-month intervals. VisFactory significantly enhanced learning outcomes across multiple dimensions: 37% reduction in time to mastery (t(125) = 11.83, p < 0.001, d = 2.11), skill acquisition increased from 28% to 85% (ηp2=0.54), and 28% higher knowledge retention after six months. The multimodal approach demonstrated differential effectiveness across learning tasks, with haptic feedback providing the most significant benefit for procedural skills (52% error reduction) and visual–auditory integration proving most effective for conceptual understanding (49% improvement). The adaptive modality orchestration reduced cognitive load by 43% compared to unimodal interfaces. This research advances multimedia learning theory by validating tri-modal integration effectiveness and establishing quantitative benchmarks for sensory channel synchronization. The findings provide a theoretical framework and implementation guidelines for optimizing multimedia learning environments for complex skill development in technical domains.","author":[{"family":"Lin","given":"Tsung"},{"family":"Chiu","given":"Cheng‐nan"},{"family":"Wang","given":"Po"},{"family":"Fang","given":"Li"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/multimedia1010003","URL":"https://doi.org/10.3390/multimedia1010003","source":"openalex"},{"id":"oa:W4414292676","type":"article-journal","title":"Development of Digital/Visual Twin for Real‐Time Leak Detection in Gas Pipelines Under Multiphase Flow Conditions","abstract":"ABSTRACT Leak detection (LD) in gas pipelines (GPs) is critical for ensuring operational safety and environmental protection. This study presents a novel digital/visual twin for detecting single‐ and multiple leaks in GPs under both single‐ and multiphase flow conditions. The framework of the digital twin leverages experimental data from a multiphase flow‐testing loop and synthetic data generated using OLGA software to validate and optimize machine learning (ML) models for leak detection and localization. Several ML models, including random forest (RF), support vector machine (SVM), k ‐nearest neighbors ( k ‐NNs), decision tree regression (DTR), and eXtreme gradient boosting (XGBoost), were tested individually for their ability to classify leak conditions and localize leaks. Initial results showed moderate performance for individual models, with accuracies ranging from 42% to 57%. However, a significant improvement was observed through the use of advanced techniques such as stacking models, feature engineering, and data averaging. The final stacking regressor model, which combined the strengths of RF, k ‐NN, and SVM, outperformed the individual models, achieving R 2 values exceeding 0.96 with an accuracy of 90% in complex multiple leak scenarios. The digital twin system integrates this ML framework with real‐time data visualization, allowing operators to visualize offshore pipeline conditions, detect leaks, and localize leak positions using a virtual twin representation of the physical pipeline. The virtual twin provides an interactive, high‐fidelity interface that enables users to monitor and analyze leak events as they occur, enhancing situational awareness and decision‐making capabilities. The combination of advanced ML techniques and digital twin technology provides a robust and accurate solution for real‐time LD in offshore pipelines. It significantly improves detection performance in multiphase flow conditions. This innovative approach sets a new benchmark for offshore pipeline monitoring systems, offering superior LD capabilities under a range of operational conditions. The system is readily adaptable for integration with SCADA platforms and pipeline monitoring infrastructures, supporting deployment in offshore oil and gas operations, industrial gas distribution networks, and critical energy corridors where early LD is essential.","author":[{"family":"Alammari","given":"Wahib"},{"family":"Sleiti","given":"Ahmad"},{"family":"Hamilton","given":"Matthew"},{"family":"Ferroudji","given":"Hicham"},{"family":"Gomari","given":"Sina"},{"family":"Hassan","given":"Ibrahim"},{"family":"Hasan","given":"Rashid"},{"family":"Hussein","given":"Ibnelwaleed"},{"family":"Rahman","given":"Mohammad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/ghg.2379","URL":"https://doi.org/10.1002/ghg.2379","source":"openalex"},{"id":"oa:W7135020744","type":"article-journal","title":"Digital and sustainable agricultural futures: sociotechnical imaginaries of twin transitions and emerging roles for science","abstract":"Introduction Recently, the concept of twin transitions gained momentum in policy and scientific discourse about agrifood systems. In twin transitional processes, digital tools are leveraged to drive sustainability transformations, while sustainability thinking guides the development, diffusion, and use of digital technology. However, these transitions are characterized by high uncertainty about the futures they will lead agriculture into. Methods In the present study, following a sociotechnical imaginaries perspective and using data from a workshop attended by Greek researchers, farmers, and farm advisors, we pursued two objectives. First, to delineate the futures that these transitions might shape for agriculture. Second, to identify the roles that science has to play in these futures. Results Our results reveal the multiplicity of agri-digital and sustainable transitions, picturing futures that range from idealized states, where digital technology continuously supports the achievement of sustainability targets, to less optimistic scenarios, in which digitalization fails to improve agricultural sustainability or even to deliver on its promise to provide tangible benefits at the farm level. Discussion Science is called to respond to these futures by contributing to technology upgrading, developing low-end digital tools, monitoring and assessing the sustainability performance of agricultural digitalization, informing policy-making, and co-shaping problematizations about digitalization with societal actors.","author":[{"family":"Lioutas","given":"Evagelos"},{"family":"Charatsari","given":"Chrysanthi"},{"family":"Rosa","given":"MD"},{"family":"Pagnani","given":"Tiziana"},{"family":"Aidonis","given":"Dimitrios"},{"family":"Bartoli","given":"Luca"},{"family":"Achillas","given":"Charisios"},{"family":"Folinas","given":"Dimitrios"},{"family":"Michailidis","given":"Anastasios"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fsufs.2026.1746682","URL":"https://doi.org/10.3389/fsufs.2026.1746682","source":"openalex"},{"id":"oa:W7125598625","type":"article-journal","title":"Relatedness and regional specialization in green, digital, and twin economic activities: evidence from the UK","abstract":"Abstract This paper examines the geography and relatedness of green, digital, and twin (both green and digital) economic activities across UK local authorities, contributing to debates on whether the two domains are truly synergistic. Using an innovative web-based real-time industry classification dataset covering about 200,000 firms, we identify regional specializations and compute industry-relatedness from firm-level co-occurrence patterns. Spatial mapping and urban scaling analyses reveal interesting patterns: digital industries tend to concentrate in large urban centres, while green and twin industries are more dispersed. Furthermore, regression models show that relatedness in one domain (e.g. green) is positively associated with specialization in the other (e.g. digital), with twin industries exerting the strongest mutual influence on both green and digital domains. These results provide empirical support that capabilities in one domain can facilitate diversification into the other, and that twin activities act as a bridge linking them. By explicitly identifying activities that are simultaneously green and digital, and by quantifying their relatedness to other industries, this paper offers new insights into the structural interdependencies underpinning the twin transition and its geography.","author":[{"family":"Cicerone","given":"Gloria"},{"family":"Losacker","given":"Sebastian"},{"family":"Ortega-Argilés","given":"Raquel"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s00168-025-01445-8","URL":"https://doi.org/10.1007/s00168-025-01445-8","source":"openalex"},{"id":"oa:W4413912072","type":"article-journal","title":"Achieving Cultural Heritage Sustainability Through Digital Technology: Public Aesthetic Perception of Digital Dunhuang Murals","abstract":"Against the backdrop of rapid digitization of cultural heritage, assessing the public’s genuine perception of digital heritage has become a critical issue in the study of cultural sustainability and communication. This study takes the “Digital Dunhuang Museum” exhibition in Guangzhou as a case, focusing on the differences and underlying mechanisms in public aesthetic perception of digital Dunhuang murals. Integrating eye-tracking experiments, subjective image evaluations, and semi-structured interviews, the research innovatively introduces multimodal visual behaviour and physiological data as core indicators in the field of digital cultural heritage. It systematically compares the explicit attitudes and implicit responses of audiences with different artistic backgrounds during the aesthetic perception process. The results reveal that participants with an art-related background show significantly higher scores in subjective dimensions such as pleasure, attraction, and visiting intention. They also demonstrate stronger visual engagement and emotional arousal in physiological dimensions, including the number of fixations, total fixation duration, and pupil diameter changes. This study constructs a mechanism of aesthetic perception for digital cultural heritage based on “visual attention–cognitive processing–emotional arousal”, enriching the public’s understanding of digital cultural heritage conservation and communication from both cognitive and emotional perspectives. The findings provide empirical support for the design of digital exhibitions of cultural heritage and expand the methodological and cognitive approaches in cultural sustainability research, offering important theoretical and practical implications.","author":[{"family":"Chen","given":"Yuxin"},{"family":"Peng","given":"Yuxian"},{"family":"Tan","given":"Yuanjun"},{"family":"Luo","given":"Guang"},{"family":"Wang","given":"Min"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17177887","URL":"https://doi.org/10.3390/su17177887","source":"openalex"},{"id":"oa:W7159868150","type":"article-journal","title":"Human digital twins in sports and rehabilitation: a systematic review","abstract":"Digital twins are increasingly shaping how humans interact with complex representations of the body in sport and rehabilitation, yet the design, use, and evaluation of Human Digital Twins in these domains remain fragmented and insufficiently characterised from a Human–Computer Interaction perspective. This study presents a systematic literature review aimed at analysing how Human Digital Twins have been designed, implemented, and evaluated in these domains. Following the PRISMA 2020 protocol, 32 papers were analysed with respect to application domains, system goals, technologies, interaction modalities, user involvement, and the role of artificial intelligence. The results reveal a prevalence of rehabilitation-oriented applications, while sports-related studies remain less consolidated. Wearable sensors, inertial measurement units, and vision systems are the most commonly adopted technologies, and the majority of interfaces rely on expert-oriented dashboards. User involvement is limited, with only two studies reporting participation during design and most evaluations involving fewer than 20 participants. AI techniques are employed in 23 out of 32 studies (72%), although their implementation is often only briefly described. The findings highlight significant gaps in participatory design practices, interaction diversity, and methodological maturity, suggesting the need for more human-centred, transparent, and robust approaches to the development of Human Digital Twins in sports and rehabilitation.","author":[{"family":"Barricelli","given":"Barbara"},{"family":"Cerutti","given":"Federico"},{"family":"Morzenti","given":"Stefano"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/0144929x.2026.2660222","URL":"https://doi.org/10.1080/0144929x.2026.2660222","source":"openalex"},{"id":"oa:W7125651156","type":"article-journal","title":"Data-Driven Operational Assessment Method and Digital Twin System for Unmanned Surface Vehicles","abstract":"To address the challenge of effectively leveraging multi-source data for automated operational assessment of Unmanned Surface Vehicles (USVs) and utilizing digital technologies for monitoring and control, this paper proposes a data-driven state assessment method for surface unmanned systems and develops a digital twin system tailored for USVs. First, a dual-channel feature modeling mechanism is constructed by integrating physically interpretable statistical features with temporal convolutional features. Second, a complementary modeling strategy is adopted using CatBoost for static classification and GRU for dynamic modeling, while a Covariance Intersection (CI) fusion strategy is introduced to enhance the classification performance and adaptability of the model. Finally, a digital twin system is designed that incorporates Position Estimation, Attitude Estimation, and State Evaluation, enabling real-time monitoring and multidimensional visualization of USV operational states. Experimental results demonstrate that the proposed method outperforms baseline approaches in terms of accuracy, F1-score, and other key metrics, exhibiting strong generalization capability and promising potential for practical deployment.","author":[{"family":"Bai","given":"Yuting"},{"family":"Hu","given":"Jiyuan"},{"family":"Tursun","given":"Eziz"},{"family":"Yimit","given":"Hurxida"}],"issued":{"date-parts":[[2026]]},"DOI":"10.62762/tmi.2025.444910","URL":"https://doi.org/10.62762/tmi.2025.444910","source":"openalex"},{"id":"oa:W7164667332","type":"article-journal","title":"Fostering sustainability with digital twins and gamification: a systematic review","abstract":"Abstract This systematic review investigates how digital twin technologies are combined with gamification to support sustainability across different domains. Using the PRISMA 2020 framework, we retrieved 122 records from three databases. After screening, 23 papers satisfying the inclusion criteria were analyzed in depth. Each one was examined along nine dimensions: application domain, motivation, case study, use of real-time data synchronization, digital twin type, gamification elements, visualization and interaction modalities, user involvement, and alignment with the United Nations Sustainable Development Goals. The results reveal a research landscape that is still emerging, characterized by heterogeneous methodologies, limited maturity of digital twin implementations, and a predominant use of basic gamification strategies. The findings of this review informed a set of design implications and the formulation of a conceptual framework to guide the design of gamified digital twins that foster sustainability in its various forms.","author":[{"family":"Samiepour","given":"Maryam"},{"family":"Barricelli","given":"Barbara"},{"family":"Fogli","given":"Daniela"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s11042-026-21730-8","URL":"https://doi.org/10.1007/s11042-026-21730-8","source":"openalex"},{"id":"oa:W4414612878","type":"article-journal","title":"DESIGN AND VERIFICATION OF AN INNOVATIVE CERAMIC LUMBAR INTERBODY FUSION CAGE USING DIGITAL TWINS","abstract":"Lumbar interbody fusion (LIF) is the gold standard to treat severe lumbar interbody disk pathologies. Standard cages in titanium and peek exhibit certain limitations, including the potential for subsidence and pseudoarthrosis. This suggests an unmet need for the development of innovative implants, exploiting new materials, such as b.Bone™ (GreenBone Ortho, Italy), a biphasic ceramic obtained through a biomorphic transformation from rattan wood. A biodegradable interbody cage can both induce bone formation and be completely resorbed over time. However, the mechanical resistance of such brittle material becomes a critical aspect to be considered during the design process. Digital twins (DT) allow to save both time and costs compared to standard experimental try-and-error approaches, obtaining directly the optimized geometry to be manufactured and tested. This work presents a DT-driven cage geometry optimization exploiting a fully-parametric lumbar spine model (J Biomech. 2024 Feb:164:111951) and LIF surgery simulations. The design process' final goal is the optimized cage prototype manufacturing and test, according to standard ISO 23089-2:2021. A lateral approach (LLIF) was selected and simulated through detailed finite element model considering 3 steps: (i) site preparation and vertebrae distraction, (ii) cage insertion and posterior fixation and (iii) application of complex loading conditions combining follower load with a bending movement in flexion, extension, axial rotation and lateral bending. Cage design was iteratively optimized to minimize failed volume and bone-cage interface strains (indicating subsidence). This involved adjusting cage medio-lateral width and incorporating variable holes for instrumentation accommodation and graft placement. Optimized designs were digitally tested against ISO23089-2 standards (axial compression, torsion, shear and subsidence) before manufacturing. All cage designs led to a reduction up to 98% in the range of motion, ensuring an effective fixation. In terms of cage mechanical resistance, flexion was the most critical loading condition. Nevertheless, the optimized cage design presented a failed volume below 10% for every simulated task. As expected, the surrounding bone was highly strained, similar or lower than what it is typically observed for standard titanium and peek cages. DT allow deep investigation of the mechanical response of the ceramic cage once implanted in human lumbar spine and the interaction between cage and bone. The iterative process allowed a cage design optimization leading to rapid manufacturing of prototypes, which was preceded by a DT of the mechanical tests prescribed by the standard ISO23089-2, to further reduce the number of tested prototypes.","author":[{"family":"Ninarello","given":"Davide"},{"family":"Brambilla","given":"Giorgia"},{"family":"Crivellaro","given":"Camilla"},{"family":"Barbera","given":"Luigi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1302/1358-992x.2025.8.054","URL":"https://doi.org/10.1302/1358-992x.2025.8.054","source":"openalex"},{"id":"oa:W4415280908","type":"article-journal","title":"Towards Evolving Actor–Network Ontologies: Enabling Reflexive Digital Twins for Cultural Heritage","abstract":"This paper introduces the concept of evolving actor–network ontologies (EANO) as a new paradigm for cultural digital twins. Building on actor–network theory, EANO reframes ontologies from static representations into reflexive, dynamic structures in which semantic interpretations are continuously negotiated among heterogeneous actors. We propose a five-layer architecture that operationalizes this principle, embedding reflexivity, actor salience, and systemic parameters such as resistance and volatility directly into the ontological model. To illustrate this approach, we present minimal simulations that demonstrate how different actor constellations and systemic conditions lead to distinct patterns of semantic evolution, ranging from expert erosion to contested equilibria and balanced coexistence. Rather than serving as predictive models, these simulations exemplify how EANO captures semantic plurality and contestation within a transparent and interpretable framework. The contribution of this work is thus twofold: it provides a conceptual foundation for evolving ontologies in digital heritage and a lightweight demonstration of how such models can be instantiated and explored computationally.","author":[{"family":"Pavlidis","given":"George"},{"family":"Arampatzakis","given":"Vasileios"},{"family":"Sevetlidis","given":"Vasileios"},{"family":"Koutsoudis","given":"Anestis"},{"family":"Arnaoutoglou","given":"Fotis"},{"family":"Ioannakis","given":"George"},{"family":"Kiourt","given":"Chairi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/info16100892","URL":"https://doi.org/10.3390/info16100892","source":"openalex"},{"id":"oa:W4408070838","type":"article-journal","title":"Research on Water Resource Management in Yellow River Irrigation Areas Based on Digital Twins","abstract":"With the swift progress of information technology, the deployment of digital twin technology in water resources management within the Yellow River Irrigation District (YRID) demonstrates considerable promise.This study seeks to investigate the effectiveness of digital twin technology in addressing issues such as water scarcity, the imbalance between supply and demand, insufficient scientific data support and intelligent decision-making systems, as well as the challenges associated with water fee collection and management.By developing a digital twin model, accurate simulation, efficient data analysis, and intelligent decision support for the water resources in YRID were achieved, significantly enhancing the scientific basis and accuracy of water resource management.The findings indicate that the implementation of digital twin technology can lead to approximately a 15% reduction in water resource waste, a 20% improvement in water resource utilization efficiency, and optimization of the water fee collection and management processes to lower overall management costs.These outcomes not only offer innovative solutions for water resource management in the Yellow River Irrigation District but also provide valuable lessons for managing water resources in other irrigation areas.","author":[{"family":"Liu","given":"Zhen"},{"family":"Li","given":"Guozheng"},{"family":"Dong","given":"Fang"},{"family":"Hui","given":"Zhenxing"}],"issued":{"date-parts":[[2025]]},"DOI":"10.2991/978-94-6463-658-1_34","URL":"https://doi.org/10.2991/978-94-6463-658-1_34","source":"openalex"},{"id":"oa:W4415280535","type":"article-journal","title":"Reliability Assessment of High-Speed Train Gearbox Based on Digital Twin and WHO-WPHM","abstract":"The gearbox is essential for power transmission in high-speed trains, and its reliability directly impacts operational safety. Accurate monitoring data and effective assessment methods are crucial for accurately assessing its reliability. This study is based on digital twin (DT) technology, precisely deploying virtual sensors to collect vibration data from critical measurement points accurately. By integrating the Wild Horse Optimizer (WHO) and the Weibull Proportional Hazards Model (WPHM), it achieved reliability assessment for a high-speed train gearbox. First, a DT framework for the high-speed train gearbox was established. Taking the gear pair, a critical power transmission component in the gearbox, as an example, a DT model of the gear pair was built on Ansys Twin Builder, virtual sensors were deployed at critical measurement points, and vibration acceleration data was collected. Then, a WPHM reliability assessment model was established, and the WHO was used to estimate and optimize the WPHM parameters. Finally, the response covariates reduced by the Local Tangent Space Alignment (LTSA) were used as model inputs, and the WPHM was applied to assess the reliability of critical parts based on the collected data. The web-deployed DT model was delivered within 13 s. This achieved a simulation acceleration factor of 2.35 × 104, compared to traditional methods. The number of iterations for the WOA was reduced by 62.9% compared to the WHO and by 48.1% compared to the HHO. The reliability assessment results align with the actual operating mileage status of the gear pair, thus validating the effectiveness and feasibility of this method.","author":[{"family":"Wang","given":"Tengfei"},{"family":"Chen","given":"Yun"},{"family":"Li","given":"Siying"},{"family":"Lv","given":"Jinhe"},{"family":"Liu","given":"Yumei"},{"family":"Yang","given":"Jinyu"},{"family":"Yan","given":"Qiushi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/s25206418","URL":"https://doi.org/10.3390/s25206418","source":"openalex"},{"id":"oa:W4417324965","type":"article-journal","title":"Digital twin management platform integrating multi-agent system for resource utilisation of crop-livestock waste and its applications","abstract":"To address the issues in traditional crop-livestock waste recycling, such as low resource utilisation efficiency and insufficient management effectiveness, this study proposes a digital twin-based management method incorporating multi-agent system. Firstly, the key factors influencing crop-livestock waste recycling were analysed, and a hierarchical five-tiered management architecture was proposed to achieve closed-loop coordination across the entire production process. Secondly, a dual data-model driven strategy was adopted to construct digital twin models of the production system. This approach deeply integrates the distributed decision-making advantages of multi-agent system with the simulation and predictive capabilities of digital twin, enabling multi-dimensional simulation, multi-objective optimisation, and prospective production capacity forecasting for all elements of the production process. Additionally, a virtual-real bidirectional interactive verification mechanism enhances prediction accuracy and resource allocation efficiency, forming an innovative application model of ‘digital pre-evaluation–parameter optimisation–physical validation’. Ultimately, case validation demonstrates that this platform reduces raw material transportation cost by about 15%, decreases unplanned equipment downtime by over 50%, and effectively improves resource utilisation efficiency. It offers practical value and broad application prospects for advancing green and low-carbon agricultural development.","author":[{"family":"Chen","given":"Zhaoming"},{"family":"Yin","given":"Zhao"},{"family":"Xu","given":"Zeyu"},{"family":"Yin","given":"Fengjun"},{"family":"Cheng","given":"Song"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/27525783.2025.2598492","URL":"https://doi.org/10.1080/27525783.2025.2598492","source":"openalex"},{"id":"oa:W4407898368","type":"article-journal","title":"Leveraging Digital Twins for Stratification of Patients with Breast Cancer and Treatment Optimization in Geriatric Oncology: Multivariate Clustering Analysis","abstract":"Background: Defining optimal adjuvant therapeutic strategies for older adult patients with breast cancer remains a challenge, given that this population is often overlooked and underserved in clinical research and decision-making tools. objectives: This study aimed to develop a prognostic and treatment guidance tool tailored to older adult patients using artificial intelligence (AI) and a combination of clinical and biological features. Methods: A retrospective analysis was conducted on data from women aged 70+ years with HER2-negative early-stage breast cancer treated at the French Léon Bérard Cancer Center between 1997 and 2016. Manifold learning and machine learning algorithms were applied to uncover complex data relationships and develop predictive models. Predictors included age, BMI, comorbidities, hemoglobin levels, lymphocyte counts, hormone receptor status, Scarff-Bloom-Richardson grade, tumor size, and lymph node involvement. The dimension reduction technique PaCMAP was used to map patient profiles into a 3D space, allowing comparison with similar cases to estimate prognoses and potential treatment benefits. Results: Out of 1229 initial patients, 793 were included after data refinement. The selected predictors demonstrated high predictive efficacy for 5-year mortality, with mean area under the curve scores of 0.81 for Random Forest Classification and 0.76 for Support Vector Classifier. The tool categorized patients into prognostic clusters and enabled the estimation of treatment outcomes, such as chemotherapy benefits. Unlike traditional models that focus on isolated factors, this AI-based approach integrates multiple clinical and biological features to generate a comprehensive biomedical profile. Conclusions: This study introduces a novel AI-driven prognostic tool for older adult patients with breast cancer, enhancing treatment guidance by leveraging advanced machine learning techniques. The model provides a more nuanced understanding of disease dynamics and therapeutic strategies, emphasizing the importance of personalized oncology care.","author":[{"family":"Heudel","given":"Pierre‐etienne"},{"family":"Ahmed","given":"Mashal"},{"family":"Renard","given":"Félix"},{"family":"Attyé","given":"Arnaud"}],"issued":{"date-parts":[[2025]]},"DOI":"10.2196/64000","URL":"https://doi.org/10.2196/64000","source":"openalex"},{"id":"oa:W4413245925","type":"article-journal","title":"Multiplayer Virtual Labs for Electronic Circuit Design: A Digital Twin-Based Learning Approach","abstract":"The rapid development of digital technologies is opening up new avenues for transforming education, particularly in fields that require practical training, such as electronic circuit design. In this context, this paper presents the development of a multiplayer virtual learning platform that makes use of digital twins technology to offer a realistic, collaborative experience in a simulated environment. Users can interact in real time through synchronized avatars, voice communication, and multiple viewing angles, simulating a physical classroom. Evaluation of the platform with undergraduate students showed positive results in terms of usability, collaboration, and learning effectiveness. Despite the limitations of the sample, the findings reinforce the prospect of virtual laboratories as a modern tool in technical education.","author":[{"family":"Sakkas","given":"Konstantinos"},{"family":"Ntagka","given":"Niki"},{"family":"Spyridakis","given":"Michail"},{"family":"Μιλτιάδους","given":"Ανδρέας"},{"family":"Glavas","given":"Euripidis"},{"family":"Tzallas","given":"Alexandros"},{"family":"Γιαννακέας","given":"Νικόλαος"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/electronics14163163","URL":"https://doi.org/10.3390/electronics14163163","source":"openalex"},{"id":"oa:W4415874488","type":"article-journal","title":"Using a digital twin and smart services to enable automatic generation of context-sensitive instructions","abstract":"The increasing diversity and shorter life cycles of technical products pose significant challenges for manufacturing companies, particularly in the context of providing specific and context-sensitive instructions to employees, especially in domains including maintenance, assembly and disassembly. This challenge holds significant importance in the context of the current skilled worker shortage. This paper proposes a solution by leveraging digital twin technology and smart services to automate the generation of context-sensitive instructions. The research outlines the development of a smart service system that uses real-time data from digital twins to create and deliver adaptive and user-specific instructions via smart devices. A conceptual design of the smart service system, a prototypical implementation using a rolling mill maintenance task, and the verification and validation of the developed system were carried out. The results indicate that the proposed system effectively addresses the challenges of traditional manual instructions, enhancing efficiency, accuracy, and user satisfaction. • Leverages digital twin technology for context-sensitive manufacturing instructions. • Smart services generate adaptive, user-specific guidance in real-time. • Validated system improves efficiency, accuracy, and user satisfaction in industrial applications. • Demonstrates reduced errors and faster task execution in a rolling mill maintenance case study.","author":[{"family":"Lossie","given":"Karl"},{"family":"Hellmich","given":"Jan"},{"family":"Liang","given":"Junjie"},{"family":"Baum","given":"Jonas"},{"family":"Göppert","given":"Amon"},{"family":"Grunert","given":"Dennis"},{"family":"Schmitt","given":"Robert"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jmsy.2025.10.007","URL":"https://doi.org/10.1016/j.jmsy.2025.10.007","source":"openalex"},{"id":"oa:W7131071926","type":"article-journal","title":"Digital materials ecosystem: from databases to AI agents for autonomous discovery","abstract":"The concept of a digital materials ecosystem represents a new paradigm in materials research, where data, theory, and automation are integrated into a unified and iterative framework. By combining reliable databases, physical frameworks, and intelligent data analysis, materials discovery is evolving from empirical exploration toward a systematic and predictive science. The rapid growth of data and artificial intelligence (AI) has enabled the identification of complex structure-property relationships, while advances in automated synthesis and high-throughput characterization are closing the loop between prediction and validation. Looking forward, the field must focus on building trustworthy and benchmarked datasets, developing interpretable and high-precision models, and designing AI tools that embody human scientific reasoning. Equally important is ensuring standardization and consistency between digital inputs and experimental responses. Together, these efforts will transform materials discovery from data accumulation into genuine knowledge generation, paving the way for an autonomous and self-improving research ecosystem that accelerates both fundamental understanding and technological innovation.","author":[{"family":"Zhang","given":"Di"},{"family":"Jia","given":"Xue"},{"family":"Wang","given":"Yuhang"},{"family":"Liu","given":"Heng"},{"family":"Wang","given":"Qian"},{"family":"Jang","given":"Seong‐hoon"},{"family":"Shah","given":"Daksh"},{"family":"Ye","given":"Songbo"},{"family":"Tran","given":"Hung"},{"family":"Li","given":"Hao"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1039/d5sc09229a","URL":"https://doi.org/10.1039/d5sc09229a","source":"openalex"},{"id":"oa:W4414192589","type":"article-journal","title":"Using digital twins to understand environmental health impacts","abstract":"The growth of Internet of Things (IoT) and wearable sensors has advanced digital twin (DT) technology in urban planning, utility management, and healthcare by providing real-time data. Researchers, public health officials, and first responders can leverage DTs to understand the complex interactions between people and the environment and to model the impacts of the built environment and population density on local temperature and air quality, as well as the health impacts of these exposures. The combination of environmentally aware human DTs and smart cities (including agricultural land) could provide better strategies for forecasting vector-borne or environmentally driven diseases, which are predicted to increase over the next decades because of warmer temperatures and more contact between people, animals, and insects caused by higher population densities. This research brief discusses the current state of environmentally aware DTs and highlights areas where the technology needs to improve, such as the need to establish data and metadata standards for IoT and wearable sensors, the use of edge computing resources to achieve scaling and rapidly communicate results better, and access to labeled data. Improving environmentally aware DT technology could help establish more effective forecasting and mitigation strategies to reduce the loss of human life from natural disasters and disease outbreaks.","author":[{"family":"International","given":"Rti"},{"family":"Hegartycraver","given":"Meghan"},{"family":"Gaur","given":"Pooja"},{"family":"Daviswilson","given":"Hope"},{"family":"Temple","given":"D"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3768/rtipress.2025.rb.0043.2509","URL":"https://doi.org/10.3768/rtipress.2025.rb.0043.2509","source":"openalex"},{"id":"oa:W7133817371","type":"article-journal","title":"Digital Twin-Enabled Thermal Energy Management System for Sustainable Manufacturing Process Optimization","abstract":"Manufacturing processes consume substantial thermal energy, yet siloed management approaches cannot exploit facility-wide synergies. This study develops and validates an integrated Digital Twin (DT) that fuses physics-based thermal models with machine-learning forecasts and multi-objective optimization to coordinate process heat, waste-heat recovery, thermal storage, and on-site renewables in real-time. Deployed across four heterogeneous manufacturing facilities, the DT generated operator-ready knee-point recommendations that balanced energy use, operating cost, and emissions under changing production and weather conditions. Across sites, deployment produced substantial, sustained gains in thermal-energy efficiency and marked reductions in carbon intensity (approximately 27% higher efficiency and about one-third lower emissions in aggregate), demonstrating that system-level orchestration outperforms isolated component upgrades. Novelty lies in plant-scale, real-time co-optimization of process heat, waste-heat recovery, thermal storage, and on-site renewables using a hybrid physics–ML digital twin with uncertainty-aware multi-objective control, field-validated across four heterogeneous manufacturing sites.","author":[{"family":"Mukhitdinov","given":"Otabek"},{"family":"Jumanazarov","given":"Doniyor"},{"family":"Xudaynazarov","given":"Egambergan"},{"family":"Umarov","given":"AV"},{"family":"Alsayah","given":"Ahmed"}],"issued":{"date-parts":[[2026]]},"DOI":"10.24867/ijiem-401","URL":"https://doi.org/10.24867/ijiem-401","source":"openalex"},{"id":"oa:W4416254488","type":"manuscript","title":"Digital Twins as Funhouse Mirrors: Five Key Distortions","abstract":"Scientists and practitioners are increasingly moving to deploy digital twins--LLM-based models of real individuals--across social science and policy research. We conduct 19 pre-registered studies spanning 164 diverse outcomes (e.g., attitudes toward hiring algorithms, intentions to share misinformation), comparing human responses to those of their corresponding digital twins, which are trained on each individual's prior responses to over 500 questions. We establish an empirical benchmark for digital twin performance: their predictions are only modestly more accurate than those of a homogeneous base LLM and exhibit weak correlation with human responses (average $r = 0.20$). To inform future development, we identify five systematic distortions in digital twin behavior: (i) insufficient individuation, (ii) stereotyping, (iii) representation bias, (iv) ideological bias, and (v) hyper-rationality. Finally, we release our full dataset and code as a standardized testbed for evaluating and improving digital twin methodologies. Together, our findings caution against premature deployment while laying the groundwork for a transparent, replicable, and iterative science of responsible digital twin development.","author":[{"family":"Peng","given":"Tianyi"},{"family":"Gui","given":"George"},{"family":"Brucks","given":"Melanie"},{"family":"Merlau","given":"Daniel"},{"family":"Fan","given":"Grace"},{"family":"Sliman","given":"Malek"},{"family":"Johnson","given":"Eric"},{"family":"Althenayyan","given":"Abdullah"},{"family":"Bellezza","given":"Silvia"},{"family":"Donati","given":"Dante"},{"family":"Fong","given":"Hortense"},{"family":"Friedman","given":"Elizabeth"},{"family":"Guevara","given":"Ariana"},{"family":"Hussein","given":"Mohamed"},{"family":"Jerath","given":"Kinshuk"},{"family":"Kogut","given":"Bruce"},{"family":"Kumar","given":"Akshit"},{"family":"Lane","given":"Kristen"},{"family":"Li","given":"H"},{"family":"Morwitz","given":"Vicki"},{"family":"Netzer","given":"Oded"},{"family":"Perkowski","given":"Patryk"},{"family":"Toubia","given":"Olivier"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2509.19088","URL":"https://doi.org/10.48550/arxiv.2509.19088","source":"openalex"},{"id":"oa:W7134037253","type":"article-journal","title":"Digital Twins in Europe: Driving Sustainable Innovation and Sovereignty","abstract":"Abstract Digital twins are emerging as a key technological enabler for Europe’s industrial future. As high-fidelity virtual replicas of physical systems, digital twins harness advances in artificial intelligence, connectivity, and the growing availability of data to enable real-time monitoring, simulation, and optimization. Their impact spans diverse domains, including manufacturing, healthcare, energy, logistics, and smart cities, playing a pivotal role in driving the green and digital transition.This chapter explores the foundational principles and strategic relevance for digital twins within the European context, with particular emphasis on the contributions of the AI, Data, and Robotics Association (ADRA). It outlines state-of-the-art technical approaches and highlights prominent use cases in this critical field.","author":[{"family":"Ramos","given":"Victor"},{"family":"García","given":"Gema"},{"family":"Romero","given":"Iria"},{"family":"Requeni","given":"Celia"},{"family":"Gusmeroli","given":"Sergio"},{"family":"Bante","given":"Iddo"},{"family":"Sierra","given":"José"},{"family":"Nikolakis","given":"Nikolaos"},{"family":"Koeva","given":"Mila"},{"family":"Kovacs","given":"Katalin"},{"family":"Aguirre","given":"Gorka"},{"family":"Ocaña","given":"I"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/978-3-032-10561-5_4","URL":"https://doi.org/10.1007/978-3-032-10561-5_4","source":"openalex"},{"id":"oa:W7125490305","type":"article-journal","title":"Advancing Modern Power Grid Planning Through Digital Twins: Standards Analysis and Implementation","abstract":"The increasing complexity of modern electrical networks poses significant challenges in terms of monitoring, maintenance, and operational efficiency. However, current planning approaches often lack a unified integration of real-time data and predictive modeling. In this context, Digital Twins (DTs) emerge as a promising solution, as they enable the creation of virtual replicas of physical assets. This research addresses the lack of standardized technical frameworks by proposing a novel mathematical optimization model for grid planning based on DTs. The proposed methodology integrates comprehensive architecture (frontend/backend), specific data standards (IEC 61850), and a linear optimization formulation to minimize operational costs and enhance reliability. Case studies such as DTEK Grids and American Electric Power are analyzed to validate the approach. The results demonstrate that the proposed framework can reduce planning errors by approximately 15% and improve fault prediction accuracy to 99%, validating the DTs as a key tool for the digital transformation of the energy sector towards Industry 5.0.","author":[{"family":"Gómez-Luna","given":"Eduardo"},{"family":"Murillo-Becerra","given":"Marlon"},{"family":"Garibello-Narváez","given":"David"},{"family":"Vasquez","given":"Juan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19020556","URL":"https://doi.org/10.3390/en19020556","source":"openalex"},{"id":"oa:W4412939567","type":"article-journal","title":"Asynchronous Deep Reinforcement Learning for Semantic Communication and Digital-Twin Deployment in Transportation Networks","abstract":"The dynamically evolving and technologically-driven hybrid landscape of transportation networks integrated with advanced edge computing capabilities has demonstrated efficient communication and computation techniques to guarantee robust quality of services (QoS) to vehicles. However, conventional communication systems in the Internet of Vehicles (IoV) still encounter challenges in providing meaningful low-latency communication and AI-assisted real-time synchronization on the edge. One reason is that it has exhausted the Shannon limit by utilizing cellular, NOMA, and Wi-Fi technologies. Therefore, we present an integrated approach leveraging Semantic Communication (SC), and Digital Twin (DT) deployment to tackle the challenges caused by high-dimensional data exchanges and resource spectrum crunch leading to inevitable latency constraints. SC stimulates meaningful transmission of data to high-mobility vehicles by providing a relevant knowledge base (KB) and DT deployment. In this paper, we established the vehicular SC (VSC) model, and DT deployment strategy. We formulate a multi-objective optimization problem (MOP) to maximize the overall QoS of the system by jointly optimizing VSC and DT deployment. Compared to traditional deep-reinforcement learning (DRL) schemes, we propose a Digital Twin Semantic Sensing using the Multi-vehicle DRL ($DTS^{2}$-MVDL) algorithm which addresses the MOP and persistent issues of multi-dimensional, continuous, and discrete nature of the vehicular environment. Lastly, we employ age of Information (AoI), latency, and QoS as the performance metrics to determine the algorithmic efficiency.","author":[{"family":"Rawlley","given":"Oshin"},{"family":"Gupta","given":"Shashank"},{"family":"Panwar","given":"Jatin"},{"family":"Sharma","given":"Pushpendra"},{"family":"Rathore","given":"Shailendra"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/tits.2025.3593038","URL":"https://doi.org/10.1109/tits.2025.3593038","source":"openalex"},{"id":"oa:W4407764223","type":"manuscript","title":"Integrated Sensing and Communication for 6G Holographic Digital Twins","abstract":"With the advent of 6G networks, offering ultra-high bandwidth and ultra-low latency, coupled with the enhancement of terminal device resolutions, holographic communication is gradually becoming a reality. Holographic digital twin (HDT) is considered one of key applications of holographic communication, capable of creating virtual replicas for real-time mapping and prediction of physical entity states, and performing three-dimensional reproduction of spatial information. In this context, integrated sensing and communication (ISAC) is expected to be a crucial pathway for providing data sources to HDT. This paper proposes a four-layer architecture assisted by ISAC for HDT, integrating emerging paradigms and key technologies to achieve low-cost, high-precision environmental data collection for constructing HDT. Specifically, to enhance sensing resolution, we explore super-resolution techniques from the perspectives of parameter estimation and point cloud construction. Additionally, we focus on multi-point collaborative sensing for constructing HDT, and provide a comprehensive review of four key techniques: node selection, multi-band collaboration, cooperative beamforming, and data fusion. Finally, we highlight several interesting research directions to guide and inspire future work.","author":[{"family":"Zhang","given":"Haijun"},{"family":"Zhang","given":"Ziyang"},{"family":"Liu","given":"Xiangnan"},{"family":"Li","given":"Wei"},{"family":"Li","given":"Hongmin"},{"family":"Sun","given":"Chen"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2502.13352","URL":"https://doi.org/10.48550/arxiv.2502.13352","source":"openalex"},{"id":"oa:W4416849156","type":"article-journal","title":"Digital Twins for Cryogenic Hydrogen Safety: Integrating Computational Fluid Dynamics and Machine Learning","abstract":"The global transition toward low-carbon energy and transportation systems positions hydrogen as a key clean and versatile energy carrier. However, ensuring the safe handling and storage of hydrogen—particularly in its liquid form LH2)—remains a critical challenge to large-scale deployment. Accidental releases of LH2 can lead to rapid dispersion, cryogenic hazards, and increased risks of ignition or detonation due to hydrogen’s low ignition energy and wide flammability limits. This review synthesizes recent advances in the understanding and modelling of LH2 safety scenarios, emphasizing the complementary roles of Computational Fluid Dynamics (CFD) and Machine Learning (ML). The paper first outlines the fundamental physical processes governing cryogenic hydrogen leaks, spills, and jet releases, followed by an overview of current storage and sensing technologies. Special consideration is given to safety implications arising from the differences between open and enclosed environments and the fact that existent sensing technologies present deficiencies at low temperatures. CFD-based studies are reviewed to illustrate how these methods capture complex flow and dispersion dynamics under diverse operational and environmental conditions, supported by a summary of existing experimental investigations used for model validation. The emerging role of ML is then examined, focusing on its integration with CFD simulations and sensor networks for predictive risk assessment, real-time leak detection, and the development of digital twins. Finally, integrated CFD–ML-sensor systems are discussed as a pathway toward a physics-informed, data-driven framework for advancing hydrogen safety and reliability.","author":[{"family":"Vogiatzaki","given":"Konstantina"},{"family":"Tretola","given":"Giovanni"},{"family":"Cesmat","given":"Laurie"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/hydrogen6040110","URL":"https://doi.org/10.3390/hydrogen6040110","source":"openalex"},{"id":"oa:W4414314904","type":"article-journal","title":"Effectiveness of Digital Twin Framework for Collaborative Robotic Manipulation","abstract":"This work examines the effectiveness of a digital twin (DT) framework using an industrial pick-and-place case study with a collaborative robotics arm. The problem addressed is the need for improved production process planning and visualization in robotics. The employed method involves creating a DT and evaluating its fidelity to a physical robotic system performing a pick-and-place task. Evaluations included comparing the digital and real robot trajectories, utilizing ISO 9283 performance testing, and analyzing metrics like RMSE, MAPE, and R2. The evaluation shows initial positive results indicating that the proposed DT framework fits the real data well, thus, demonstrates feasibility of this approach. The results can be used to improve the planning and visualization of the production process for collaborative robot arm with 3D printers or adapted for more complex industrial machine tools. These improvements can support the enterprises to spot potential problems before they occur, optimize performance and reduce costs.","author":[{"family":"Dong","given":"Quang"},{"family":"Nguyen","given":"Tuan"},{"family":"Tran","given":"Chi"},{"family":"Pham","given":"Thi"},{"family":"Do","given":"Duc"},{"family":"Nguyen","given":"Khang"},{"family":"Nguyen","given":"Quang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.54644/jte.2025.1835","URL":"https://doi.org/10.54644/jte.2025.1835","source":"openalex"},{"id":"oa:W7126274310","type":"article-journal","title":"Sustainable building’s energy management with artificial intelligence and machine learning: A decadal scoping review (2014–2024)","abstract":"Artificial Intelligence (AI) and Machine Learning (ML) are transforming energy management in buildings by enabling data-driven prediction, optimization, and real-time control. This scoping review synthesized the state of the art in this field over the past decade (2014–2024), based on a structured search of peer-reviewed studies. The review classified AI/ML applications, according to features like: forecasting horizons, algorithm families (classical ML, deep learning, hybrid/ensemble, reinforcement learning), building categories (residential, commercial, healthcare), and integration levels (standalone, IoT-enabled, microgrid-enabled). The analysis of 100+ comparative studies showed that ensemble and hybrid methods frequently outperform single algorithm methods, however, performance gains vary considerably depending on data quality, forecasting horizon, and building operational characteristics. Key challenges remain in data standardization, balance between model complexity and interpretability, privacy, and scalability from individual buildings to urban districts. Emerging opportunities were highlighted at the intersection of AI with digital twins, IoT, and transfer learning, which support small data contexts and real time adaptation. By bridging technical advances with practical challenges, this work aims at informing the scientific community, working towards intelligent, sustainable, and efficient energy management in buildings, by supporting with a clear classification of AI/ML techniques and their most promising applications across different building types.","author":[{"family":"Ahmed","given":"Nouman"},{"family":"Ding","given":"Yuemin"},{"family":"Canti","given":"Guido"},{"family":"Anglani","given":"Norma"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.egyr.2026.109082","URL":"https://doi.org/10.1016/j.egyr.2026.109082","source":"openalex"},{"id":"oa:W4417118656","type":"article-journal","title":"Design of a digital twin for NB-IoT satellite constellations","abstract":"The deployment of Low Earth Orbit satellite constellations is challenging due to the dynamic nature of these networks, intermittent connections, and power limitations. To better understand and anticipate the system’s behaviour under new conditions, Digital Twins (DTs) has been studied as a valuable tool for simulation and analysis. DTs enable satellite operators to perform real-monitoring, anomaly detection, and forecasting studies of software updates or orbital changes. The present work sets forth a DT architecture that integrates real-time satellite data with AI-powered forecasting. This facilitates real-time, continuous monitoring of the constellation performance, enabling performance forecasting and the detection of anomalies. To conclude, different forecasting models are presented to overcome the discontinuity and interruption on satellite communications, as well as the results obtained that illustrate the errors of the different forecasting models. Presenting a framework for a DTs architecture dedicated to manage any satellite constellation, while the Distributed system Simulator can model satellite contacts, aiming to enhance global connectivity and efficiency.","author":[{"family":"Dolz-Puig","given":"Arnau"},{"family":"Fusté","given":"Oriol"},{"family":"Pérez-Portero","given":"Adrián"},{"family":"Fraire","given":"Juan"},{"family":"Ruiz-De-Azua","given":"Joan"},{"family":"Calveras","given":"Anna"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/icp.2025.4045","URL":"https://doi.org/10.1049/icp.2025.4045","source":"openalex"},{"id":"oa:W4412177096","type":"article-journal","title":"Inversion model of stress state reconstruction for geological hazard pipelines based on digital twin","abstract":"Abstract Due to the frequent occurrence of geological disasters worldwide, which pose a serious threat to infrastructure such as pipelines, accurately assessing the stress state of pipelines has become an urgent issue to be addressed. To improve the real-time and prediction accuracy of underground pipeline stress monitoring in the context of geohazards, the study constructs a dynamic closed-loop pipeline stress state reconstruction and inversion framework based on digital twin technology. The mechanical state of the physical pipeline is mapped in real time by the digital twin, the numerical simulation and multi-source monitoring data are integrated, and the parameters of the twin model are dynamically optimized by combining the optimization algorithms of Particle Swarm Optimization (PSO) and Support Vector Machine (SVM), so as to realize the real-time prediction of the pipeline stress state and the dynamic updating of the disaster scenario. The experiment showed that the numerical simulation model could accurately simulate the stress-strain response of pipelines under geological hazards, which was basically consistent with the actual monitoring data. The accuracy of the inversion model was 95.14%, which was an average improvement of 11.06% compared to other models. The calculation time was 5.62 s, which was an average reduction of 18.95%. Under the three geological disasters of earthquakes, mudslides, and landslides, the root mean square error of the model’s predictions was below 3 GPa, and the accuracy remained above 94%. The results indicate that the research model has high prediction accuracy and efficiency and can effectively handle the problem of predicting pipeline stress states under different geological disasters, providing a reliable method for evaluating pipeline stress states in geological disasters.","author":[{"family":"Luning","given":"Xue"},{"family":"Mingliang","given":"Tian"},{"family":"Juncheng","given":"Zhao"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s42452-025-07435-x","URL":"https://doi.org/10.1007/s42452-025-07435-x","source":"openalex"},{"id":"oa:W4411633476","type":"article-journal","title":"Digital-twin imaging based on descattering Gaussian splatting","abstract":"Three-dimensional imaging through scattering media is important in medical science and astronomy. We propose a digital-twin imaging method based on Gaussian splatting to observe an object behind a scattering medium. A digital twin model built through data assimilation, emulates the behavior of objects and environmental changes in a virtual space. By constructing a digital twin using point clouds composed of Gaussians and simulating the scattering process through the convolution of a point spread function, three-dimensional objects behind a scattering medium can be reproduced as a digital twin. In this study, a high-contrast digital twin reproducing a three-dimensional object was successfully constructed from degraded images, assuming that data were acquired from wavefronts disturbed by a scattering medium. This technique reproduces objects by integrating data processing with image measurements.","author":[{"family":"Shimomura","given":"Suguru"},{"family":"Yamanouchi","given":"Kazuki"},{"family":"Tanida","given":"Jun"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1364/oe.564226","URL":"https://doi.org/10.1364/oe.564226","source":"openalex"},{"id":"oa:W4409441952","type":"article-journal","title":"Thermal Digital Twin of LH2 Aircraft Storage Tank","abstract":"The decarbonization of the economy is impacting all activities and sectors worldwide. Transport, particularly aircraft transport, is involved in this endeavor; shifting to H2-powered aircraft is one of the identified options for decarbonization, which implies the need for the effective implementation of complex cryogenic LH2 storage. Modeling tank storage via a Digital Twin (DTwin) is of paramount relevance to facilitate the design process (gains, operating scenarios) and for the extrapolation of experimental measurements on a particular set-up to future tanks with other materials or dimensions. The present paper contributes to this issue, presenting the model under development as part of the H2ELIOS project and the preliminary model results.","author":[{"family":"Oliet","given":"C"},{"family":"Mosqueda-Otero","given":"Marcial"},{"family":"Schillaci","given":"Eugenio"},{"family":"Amani","given":"Ahmad"},{"family":"Rigola","given":"Joaquim"},{"family":"González","given":"Jesús"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/engproc2025090097","URL":"https://doi.org/10.3390/engproc2025090097","source":"openalex"},{"id":"oa:W7124288947","type":"article-journal","title":"DIGITAL TWINS IN INDUSTRY: ARCHITECTURE, APPLICATION AND ECONOMIC EFFICIENCY","abstract":"The article provides a comprehensive analysis of the concept of digital twins and their practical application in modern industry. The study covers the architectural features of digital twins, including the physical layer, the data and integration layer, the modeling layer, and the service layer. The technologies underlying digital twins are considered in detail: IoT sensors, cloud platforms, machine learning and physical and mathematical modeling. Using a practical example of forecasting the maintenance of a pumping station, the advantages of switching from planned to predictive maintenance are demonstrated. The results of the study show that the introduction of digital twins can reduce maintenance costs by 20-30% by preventing unplanned downtime and optimizing resources. The article is valuable for specialists in the field of industrial automation, digital transformation and management of production assets.","author":[{"family":"Tyunina","given":"A"},{"family":"Kukueva","given":"D"},{"family":"Kondusova","given":"V"},{"family":"Zolnikov","given":"Konstantin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.58168/ppspm2025_199-204","URL":"https://doi.org/10.58168/ppspm2025_199-204","source":"openalex"},{"id":"oa:W4414603442","type":"article-journal","title":"Digital Twin-Based Reinforcement Learning for Energy Exchange Among Electric Vehicles and Base Stations in a Disaster-Affected Region","abstract":"The cellular base stations (BSs) have backup batteries to maintain uninterrupted power supply. Recent studies have shown that a backup battery may have some spare energy to act as a flexible resource. Similarly, electric vehicles (EVs) are also capable to give surplus energy stored in their batteries to other consumers or back to the grid. Therefore, both BSs and EVs can share energy among themselves through Telecom-to-Vehicle (T2V) and Vehicle-to-Telecom (V2T) exchange. However, the energy exchange is challenging in a disaster-affected region due to connectivity failures, power disruption and damaged routes. This paper proposes an energy exchange solution among BSs and EVs in a post disaster situation. We propose a digital-twin (DT) based solution which utilizes Artificial Intelligence (AI) algorithms to estimate energy consumption of BSs and EVs and identifies their role as energy buyers or sellers. It also models power disruption and disaster-affected blocked routes as Markov processes with parameters derived from real historic data of floods. Then, a reinforcement learning (RL) algorithm is proposed to match BSs and EVs which can feasibly take part in either T2V or V2T exchange. Performance of the proposed solution is compared with independent RL without DT and assisted by federated learning. Simulations show that energy exchanged by RL algorithm doubles with the utilization of DT.","author":[{"family":"Ayaz","given":"Ferheen"},{"family":"Nekovee","given":"Maziar"},{"family":"Sheng","given":"Zhengguo"},{"family":"Saeed","given":"Nagham"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/tits.2025.3607305","URL":"https://doi.org/10.1109/tits.2025.3607305","source":"openalex"},{"id":"oa:W4407164910","type":"article-journal","title":"Development of a digital twin for the diagnosis of cardiac perfusion defects","abstract":"Abstract Myocardial Blood Flow (MBF) is a key indicator of myocardial perfusion, typically assessed through additional clinical tests like dynamic CT perfusion under stress. This study introduces a digital twin designed to enhance coronary artery disease diagnosis by predicting MBF using data from routine CT images and clinical measurements. The digital twin employs AI methods to reconstruct coronary and myocardial geometries and integrates a computational model, featuring 3D coronary arteries and a three-compartment myocardial model, blindly calibrated with data from six representative patients. Validation on 28 additional patients showed MBF predictions consistent with experimental and clinical measurements. Confusion matrix analysis assessed the twin’s ability to classify at-risk patients (averaged MBF < 230 ml/min/100g) versus non-at-risk patients, yielding a recall of 0.77, with precision and accuracy at 0.72. This work represents the first attempt to predict and validate MBF on such a large cohort, paving the way for future clinical applications.","author":[{"family":"Criseo","given":"Elisabetta"},{"family":"Baggiano","given":"Andrea"},{"family":"Pelagi","given":"Giovanni"},{"family":"Nannini","given":"Guido"},{"family":"Redaelli","given":"Alberto"},{"family":"Pontone","given":"Gianluca"},{"family":"Vergara","given":"Christian"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1101/2025.02.04.25321638","URL":"https://doi.org/10.1101/2025.02.04.25321638","source":"openalex"},{"id":"oa:W7119097930","type":"article-journal","title":"A Hierarchical Framework Leveraging IIoT Networks, IoT Hub, and Device Twins for Intelligent Industrial Automation","abstract":"Industrial Internet of Things (IIoT) networks, Microsoft Azure Internet of Things (IoT) Hub, and device twins (DvT) are increasingly recognized as core enablers of adaptive, data-driven manufacturing. This paper proposes a hierarchical IIoT framework that integrates industrial IoT networking, DvT for asset-level virtualisation, system-level digital twins (DT) for cell orchestration, and cloud-native services to support the digital transformation of brownfield, programmable logic controller (PLC)-centric modular automation (MA) environments. Traditional PLC/supervisory control and data acquisition (SCADA) paradigms struggle to meet interoperability, observability, and adaptability requirements at scale, motivating architectures in which DvT and IoT Hub underpin real-time orchestration, virtualisation, and predictive-maintenance workflows. Building on and extending a previously introduced conceptual model, the present work instantiates a multilayered, end-to-end design that combines a federated Message Queuing Telemetry Transport (MQTT) mesh on the on-premises side, a ZigBee-based backup mesh, and a secure bridge to Azure IoT Hub, together with a systematic DvT modelling and orchestration strategy. The methodology is supported by a structured analysis of relevant IIoT and DvT design choices and by a concrete implementation in a nine-cell MA laboratory featuring a robotic arm predictive-maintenance scenario. The resulting framework sustains closed-loop monitoring, anomaly detection, and control under realistic workloads, while providing explicit envelopes for telemetry volume, buffering depth, and latency budgets in edge-cloud integration. Overall, the proposed architecture offers a transferable blueprint for evolving PLC-centric automation toward more adaptive, secure, and scalable IIoT systems and establishes a foundation for future extensions toward full DvT ecosystems, tighter artificial intelligence/machine learning (AI/ML) integration, and fifth/sixth generation (5G/6G) and time-sensitive networking (TSN) support in industrial networks.","author":[{"family":"Bădoi","given":"Cornelia"},{"family":"Çetin","given":"Bilge"},{"family":"Cetin","given":"Kamil"},{"family":"Karataş","given":"Çağdaş"},{"family":"Özbek","given":"Mehmet"},{"family":"Şahin","given":"Savaş"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/app16020645","URL":"https://doi.org/10.3390/app16020645","source":"openalex"},{"id":"oa:W7116663310","type":"article-journal","title":"Bio-Circular Economy and Digitalization: Pathways for Biomass Valorization and Sustainable Biorefineries","abstract":"This review examines how the integration of circular bioeconomy principles with digital technologies can drive climate change mitigation, improve resource efficiency, and facilitate sustainable biorefinery development. This highlights the urgent need to transition away from fossil fuels and introduces the bio-circular economy as a regenerative model focused on biomass valorization, reuse, recycling, and biodegradability. This study compares linear, circular, and bio-circular approaches and analyzes key policy frameworks in Europe, Latin America, and Asia linked to several UN Sustainable Development Goals. A central focus is the role of digitalization, particularly artificial intelligence (AI), the Internet of Things (IoT), and blockchain. Examples include AI-based biomass yield prediction and biorefinery optimization, IoT-enabled real-time monitoring of material and energy flows, and blockchain technology for supply chain traceability and transparency. Applications in agricultural waste valorization, bioplastics, bioenergy, and nutraceutical extraction are also discussed in this review. Sustainability tools, such as automated life-cycle assessment (LCA) and Industry 4.0 integration, are outlined. Finally, future perspectives emphasize autonomous smart biorefineries, biotechnology–nanotechnology convergence, and international collaboration supported by open data platforms.","author":[{"family":"Coronado-Contreras","given":"Sergio"},{"family":"Ibarra-Manzanares","given":"Zaira"},{"family":"Casas-Rodríguez","given":"AD"},{"family":"Pastrana-Pastrana","given":"Álvaro"},{"family":"Sepúlveda","given":"L"},{"family":"Rodríguez-Herrera","given":"Raúl"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/biomass6010001","URL":"https://doi.org/10.3390/biomass6010001","source":"openalex"},{"id":"oa:W7117244283","type":"article-journal","title":"Development of Digital Twins for Library Information System Simulation","abstract":"The creation of digital twins for Library Information Systems (LIS) simulation models provides new insights into the automation, management, efficiency, and user experience of modern-day libraries. A digital twin captures metrics from its real-world counterpart in real time, enabling analysis, monitoring, and optimization. The research is focused on LIS digital twin designs and implementations within the context of IoT, data analytics, and machine learning. Digital twins can simulate user behavior, resource usage, and subsystem interactions, offering great potential to enhance cataloging, circulation, space management, and personal service delivery, thereby augmenting advanced services. The research presents a schema that corresponds to the tangible assets within the library, including books and users, along with the infrastructure for their virtual representations. This enables predictive maintenance of the assets, automated inventory monitoring, and scenario testing. The development supports changing interface elements and user-operated control recommendation systems based on real-time usage data. Initial simulation results suggest improvements in library service delivery and decision-making capabilities within the library ecosystem. This paper addresses major concerns in data harmonization, vulnerability, privacy, and strategies for achieving effective twin deployment. The findings explain how the application of the digital twin disrupts library systems to provide responsive and user-centered information services.","author":[{"family":"Jabborov","given":"Xazrat"},{"family":"Kholikulov","given":"Akhmadjon"},{"family":"Norkulova","given":"Nargiza"},{"family":"Fallah","given":"Mohammad"},{"family":"Sobirovich","given":"Nabiev"},{"family":"Khaydarov","given":"Izzatilla"}],"issued":{"date-parts":[[2025]]},"DOI":"10.51983/ijiss-2026.16.1.33","URL":"https://doi.org/10.51983/ijiss-2026.16.1.33","source":"openalex"},{"id":"oa:W7124682775","type":"article-journal","title":"Barriers to Implementing Digital Twin Technologies in Industrial Settings","abstract":"Recent review articles highlight an exponential rise in publications on Digital Twin (DT) technology.Despite its recognised potential, DTs have yet to achieve widespread practical use.Following a presentation of the state of the art and an original conceptual diagram illustrating the technology, this work presents the key factors contributing to the gap between conception and implementation.Using experimental data from a laboratory water system and a reliability-based perspective, this analysis examines the practical limitations of DT application.The findings indicate that broader use of DTs depends on the technological maturity and reliability of all system components, which still require further development.","author":[{"family":"Wiora","given":"Józef"},{"family":"Wiora","given":"Alicja"},{"family":"Saleem","given":"Faisal"}],"issued":{"date-parts":[[2025]]},"DOI":"10.21014/tc6-2025.037","URL":"https://doi.org/10.21014/tc6-2025.037","source":"openalex"},{"id":"oa:W4417166352","type":"article-journal","title":"Adoption of digital technologies in asset management: a bibliometric and text analysis","abstract":"The introduction of digital technologies has gained considerable momentum in the field of asset management. To identify the research characteristics and development trends in the fields of digital technologies and asset management, a bibliometric analysis was conducted using the Scopus database. The analysis covers the period from 2004 to 2024 to capture the digital era and the evolving field of asset management. A total of 1,493 publications were extracted and analysed using the VOSviewer and CiteSpace. Additionally, Voyant Tools, an open-source web-based application for text analysis, was used to examine the corpus of abstracts of all publications previously analysed through the bibliometric analysis. The analysis revealed that promising technologies such as machine learning (ML), the Internet of Things (IoT), artificial intelligence (AI), digital twin (DT), blockchain, etc. are mainly used in the field of asset management. In addition, building information modelling (BIM) and geographic information systems (GIS) are commonly used tools in asset management, which shows the potential of their integration and connection with digital technologies. The results of this study contribute to the literature and practice by providing insights into trends in the use of digital technologies in asset management.","author":[{"family":"Maletič","given":"Damjan"},{"family":"Trojanowska","given":"Justyna"},{"family":"Maletič","given":"Matjaž"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/15732479.2025.2598801","URL":"https://doi.org/10.1080/15732479.2025.2598801","source":"openalex"},{"id":"oa:W4417333744","type":"article-journal","title":"A Conceptual Model of a Digital Twin Driven Co-Pilot for Speed Coordination in Congested Urban Traffic","abstract":"Digital Twins (DTs) are increasingly used to support real-time decision making in connected mobility systems, where network latency and uncertainty limit the effectiveness of conventional control strategies. This paper proposes a conceptual model for a DT-driven Co-Pilot designed to provide adaptive speed recommendations in congested urban traffic. The system combines live data from a mobile client with a prediction engine that executes multiple short-horizon SUMO simulations in parallel, enabling the DT to anticipate local traffic evolution faster than real time. A lightweight clock-alignment mechanism and latency evaluation over LAN, Cloudflare-tunneled connections, and 4G/5G networks demonstrate that the Co-Pilot can operate reliably using existing communication infrastructures. Experimental results show that moderate speeds (35–50 km/h) yield throughput and delay performance comparable to higher speeds, while improving flow stability—an important property for safe platooning and collaborative driving. The parallel execution of ten SUMO instances completes within 2–3 s for a 600 s simulation horizon, confirming the feasibility of embedding domain-specific ITS logic into a predictive DT architecture. The findings demonstrate that Digital Twin–based anticipatory simulation can compensate for communication latency and support real-time speed coordination, providing a practical pathway toward scalable, deployable DT-enabled traffic assistance systems.","author":[{"family":"Olteanu","given":"Adrian"},{"family":"Nicolae","given":"Maximilian"},{"family":"Alexe","given":"Bianca"},{"family":"Mocanu","given":"Ştefan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/fi17120572","URL":"https://doi.org/10.3390/fi17120572","source":"openalex"},{"id":"oa:W4412092543","type":"article-journal","title":"Digital twins for the sustainable maintenance of ageing waterway infrastructure","abstract":"Abstract. A substantial part of the ageing waterway infrastructure in Europe, including locks, quay walls, and coastal protection structures, is approaching the end of its service life, necessitating either replacement or extensive repairs to prevent hazards. The integration of digital twins offers transformative opportunities for the complete digitalization of these assets, enhancing structural inspections and maintenance processes. This paper explores methods and solutions developed through the 3D HydroMapper, port_AI, and Port:Evolution research projects funded by the Federal Ministry for Digital and Transport, Germany from 2018 to 2027. By utilizing mobile platforms for geodata collection, both above and below water, and employing technologies such as sonar, photogrammetry, and laser scanning, comprehensive and precise surface scans and images of infrastructure can be achieved. These scans enable early detection of damage, facilitating timely repair measures and extending the service life of structures. The fusion of diverse georeferenced data types within a cloud portal ensures efficient sharing and lifecycle management, contributing to sustainable infrastructure maintenance.This paper provides a full workflow from the acquisition of waterway infrastructure below and above water to the planning of its maintenance.","author":[{"family":"Jost","given":"Berit"},{"family":"Holste","given":"Karsten"},{"family":"Hesse","given":"Christian"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/isprs-archives-xlviii-2-w10-2025-147-2025","URL":"https://doi.org/10.5194/isprs-archives-xlviii-2-w10-2025-147-2025","source":"openalex"},{"id":"oa:W4416868477","type":"article-journal","title":"Enhancing safety in urban mobility with female digital twins","abstract":"A ‘human digital twin’ (HDT) is a representation of a human from the physical world in the digital world that includes several dimensions, such as physical, behavioural, social, physiological, cognitive and biological aspects. HDTs are an emerging field of study, emerging serendipitously from wearable devices in various fitness and wellness applications, and have become increasingly relevant in precision medicine, as hyper-personalised digital human twins. Today, moreover, real-time biometric data is helping health and fitness care in relation to prevention and prediction. In the same vein, human physiological parameters present in emotions, such as fear, could help in the context of women's mobility safety in urban areas. A human digital twin could be created that evolves throughout a woman's life, providing her with guidance and safety suggestions for her mobility, and assistance in case of need in emergency situations. In this article we present AngelaDT, a custom-designed Human Digital Twin to improve the safety of women's mobility in urban areas. In addition, the platform supporting the digital human twin and its life cycle are also described.","author":[{"family":"Marina","given":"Paloma"},{"family":"Fernández","given":"Dolores"},{"family":"Alonso","given":"Almudena"},{"family":"Sánchez","given":"Belén"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s00146-025-02762-4","URL":"https://doi.org/10.1007/s00146-025-02762-4","source":"openalex"},{"id":"oa:W7128698828","type":"article-journal","title":"Principles for Applying AI to Address the Challenges of Scaling Digital Twins","abstract":"ABSTRACT Despite the increasing affordability of data processing and storage and the enhancement of artificial intelligence (AI) and digital technologies in recent years, scalability and adoption continue to be a challenge when it comes to digital twins (DTs). Common challenges that are often cited include the effort of designing and building DTs, high customisation, the cost to operate and maintain DTs, interoperability between DT components and DTs, and the extensive analysis and effort required to turn DT outputs into useful insights. AI has seen significant advancements and growth lately, driven by the release of popular AI products such as ChatGPT, Google Gemini and DeepSeek's R1. Many of the recent developments have the potential to address the challenges of scaling and adopting DTs. This paper examines the intersection of AI and DTs and explores how AI can be used to address some of the challenges of scaling and adopting DTs. It concludes with a set of principles that aim to apply to most DT applications, regardless of use case or industry, and proposes AI methods and techniques that can potentially be used for each principle. These principles are (1) reduce effort, cost and/or time; (2) optimise resource and system efficiency; (3) improve interaction and outcome and (4) improve interoperability, reusability and maintainability.","author":[{"family":"Chen","given":"Christine"},{"family":"Wagg","given":"David"},{"family":"Girolami","given":"Mark"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1049/dgt2.70025","URL":"https://doi.org/10.1049/dgt2.70025","source":"openalex"},{"id":"oa:W7153094587","type":"article-journal","title":"Digital twin transition for intelligent and resilient industrial systems","abstract":"Digital twins (DTs) are a vital technology transforming industrial systems by linking the physical and digital realms through real-time, bidirectional data flow and intelligent analysis. This special issue of the International Journal of Production Research presents 14 original contributions that advance both the theoretical framework and practical applications of digital twins in diverse industrial settings, such as production control, process monitoring, human-machine collaboration, supply chains, maintenance, and value-based deployment. The articles are grouped into three key themes: (i) DT architectures, modelling principles, and trustworthy development; (ii) smart production management, process optimisation, and digital integration; and (iii) human-centered applications, supply chain support, and industrial value creation. Collectively, they offer a comprehensive overview of digital twins as a transformative technology enabling adaptive and resilient industrial operations. The editorial concludes with a discussion of major open challenges and promising research directions to promote wider adoption of digital twins across various industrial sectors.","author":[{"family":"Finco","given":"Serena"},{"family":"Bao","given":"Ji"},{"family":"Jackson","given":"Ilya"},{"family":"Lu","given":"Yuqian"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/00207543.2026.2655025","URL":"https://doi.org/10.1080/00207543.2026.2655025","source":"openalex"},{"id":"oa:W7154732563","type":"article-journal","title":"Reframing BIM and Digital Twins for Intelligent Built Environments","abstract":"The integration of Building Information Modeling [BIM] and Digital Twins [DT] has emerged as a central driver of digital transformation in the architecture, engineering, and construction sector. Yet, its systemic impact remains constrained by conceptual fragmentation and uneven institutional adoption. This study synthesizes contemporary BIM–DT scalability and each to identify dominant technological and application dimensions, examine the governance conditions shaping scalability, and develop an analytical framework that advances understanding beyond technology-centered syntheses. A two-stage analytical design was employed, combining bibliometric keyword co-occurrence analysis of 1295 Scopus-indexed records with systematic qualitative synthesis of 56 peer-reviewed journal articles published between 2020 and 2025, following PRISMA guidelines. Six interrelated analytical dimensions characterize the current BIM–DT research landscape: BIM–DT integration advancements and applications; interoperability and visualization; safety enhancement; energy efficiency; data-driven decision making; and stakeholder collaboration. Across these dimensions, a persistent misalignment emerges between technological capability and organizational readiness, with deficiencies in standards, governance, and sociotechnical coordination constituting the principal barriers to large-scale deployment. The findings reframe BIM–DT convergence not as a discrete technological upgrade but as the emergence of a coordinated socio-technical information ecosystem spanning the full building lifecycle. By foregrounding governance conditions, data stewardship, and institutional coordination, this study extends understanding of how digital twins expand BIM from design coordination to operational governance and establishes a foundation for more systematic implementation of intelligent, resilient, and sustainable built-environment systems.","author":[{"family":"Muhudin","given":"Abdullahi"},{"family":"Shafiullah","given":"Md"},{"family":"Al-Ramadan","given":"Baqer"},{"family":"Zami","given":"Mohammad"},{"family":"Zamani","given":"Mohammad"},{"family":"Herzallah","given":"Lazhari"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/smartcities9040071","URL":"https://doi.org/10.3390/smartcities9040071","source":"openalex"},{"id":"oa:W4415338952","type":"article-journal","title":"Collaborative Structural Health Monitoring for Bridge Digital Twins","abstract":"Structural Health Monitoring (SHM) is an effective tool that not only reduces reliance on periodic inspections but also enhances them by analyzing the current state of a structure based on the latest structural data. Collaborative SHM, which integrates various SHM systems within the scope of bridge digital twins (BDTs), enhances infrastructure resilience and maintenance strategies. However, it faces challenges in integrating distributed sensor networks and requires interdisciplinary collaboration. In this work, various aspects of enhancing collaborative SHM with BDTs are presented. As a pilot project, the Nibelungen Bridge in Worms (NBW), Germany, is introduced. Based on specific stakeholder and project requirements, various SHM systems have been installed on this bridge. To address these challenges, goal-oriented solutions have been developed and elaborated. Finally, conclusions and future outlooks are presented.","author":[{"family":"Kang","given":"Chongjie"},{"family":"Herrmann","given":"Ralf"},{"family":"Eisermann","given":"Cedric"},{"family":"Marx","given":"Steffen"}],"issued":{"date-parts":[[2025]]},"DOI":"10.12783/shm2025/37546","URL":"https://doi.org/10.12783/shm2025/37546","source":"openalex"},{"id":"oa:W4415644077","type":"article-journal","title":"Application of Digital Twin Platform for Prefabricated Assembled Superimposed Stations Based on SERIC and IoT Integration","abstract":"Prefabricated stations utilizing digital modeling techniques demonstrate significant advantages over traditional cast-in-place methods, including improved dimensional accuracy, reduced environmental impact, and minimized material waste. To maximize these benefits, this study develops a digital twin platform for prefabricated assembled superimposed stations through the integration of Digital Twin Scene–Entity–Relationship–Incident–Control (SERIC) modeling with IoT technology. The platform adopts a “1+5+N” architecture that implements model-data separation, lightweight processing, and model-data association for SERIC model management, while IoT-enabled data acquisition facilitates lifecycle data sharing. By integrating BIM models, engineering data, and IoT sensor inputs, the platform employs multi-source analytics to monitor construction progress, enhance safety surveillance, ensure quality control, and optimize designs. Implementation at Jinan Metro Line 8’s prefabricated underground station confirms the SERIC-IoT digital twin’s efficacy in advancing sustainable, high-quality rail transit development. Results demonstrate the platform’s capacity to improve construction efficiency and operational management, aligning with urban rail objectives prioritizing sustainability and technological innovation. This study establishes that integrating SERIC modeling with IoT in digital twin frameworks offers a robust approach to modernizing prefabricated station construction, with scalable applications for future smart transit infrastructure.","author":[{"family":"Lu","given":"Linhai"},{"family":"Liu","given":"Jiahai"},{"family":"Bingbing","given":"Hu"},{"family":"Gao","given":"Yu"},{"family":"Xu","given":"Qianwei"},{"family":"Lu","given":"Yanyun"},{"family":"Huang","given":"GH"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15213856","URL":"https://doi.org/10.3390/buildings15213856","source":"openalex"},{"id":"oa:W4410969370","type":"article-journal","title":"Digital Twins: A Solution Under the Standard k-ε Model in Industrial CFD, to Predict Ideal Conditions in a Sugar Dryer","abstract":"Currently, emerging technologies such as digital twins, through the application of frontier techniques, have achieved physics-based simulations that reduce time and costs. Hence, its application is of the utmost importance in the industry, mainly in the sugar drying process of sugar mills for an updated version of the process. Sugar mills lack process control, leading to unexpected issues. Sugar mills with poor process control cause operational problems. This article presents significant innovation in the field of industrial process optimisation through the integration of digital twins with the k-ε standard model in computational fluid dynamics (CFD). The primary objective of this publication is to predict the ideal conditions of a centrifugal sugar dryer using CFD through the k-ε standard model to analyse the aerodynamic behaviour of the ambient air by applying heat through heat exchangers to obtain a suitable mass flow. The mathematical model was carried out under an energy balance to the thermodynamic system to study the behaviour through a simulation in MATLAB R2017 and an air-fluid simulation of drying with software CFD 2015. The results proved that the model of the thermal system and frontier conditions, when applying CFD, carried our simulation and remained stable. The ideal operating conditions of the centrifugal sugar dryer can be predicted effectively, with an energy saving of 4.25%.","author":[{"family":"Guerrero-Hernández","given":"Verónica"},{"family":"Reyes-Morales","given":"Guillermo"},{"family":"Lima","given":"Violeta"},{"family":"Ortega-Moody","given":"Jorge"},{"family":"Bertel","given":"Quelbis"},{"family":"Rodríguez","given":"Gerardo"},{"family":"Sánchez","given":"Blanca"},{"family":"Ceballos-Díaz","given":"Claudia"},{"family":"Herazo","given":"Luis"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/fluids10060146","URL":"https://doi.org/10.3390/fluids10060146","source":"openalex"},{"id":"oa:W7117155701","type":"article-journal","title":"Digital divide and income inequality: causal evidence from Italian provinces","abstract":"Abstract The digital economy can function either as a catalyst to stimulate economic growth or else as a driver of socioeconomic inequality when its benefits are unevenly distributed. This study investigates the effect of rural digital connectivity on income inequality in Italy. Utilizing NUTS 3 panel data spanning 2014–2022, we conduct a counterfactual Difference-in-Differences approach with continuous treatment intensity to estimate the impact of introducing rural broadband coverage at speeds of 30 and 100 Mbps on multiple measures of income distribution, including the Gini, Theil, and Atkinson indices. The empirical framework incorporates a comprehensive set of socioeconomic controls, as well as provincial and time fixed effects, to account for unobserved heterogeneity and regional path dependencies. Our findings indicate that broadband expansion is significantly associated with increasing inequality, suggesting that access alone does not guarantee inclusive outcomes, particularly in localities characterized by structural fragility and limited human capital. Additional heterogeneity and spatial analyses demonstrate that these inequality effects are more evident in southern provinces and localities with a higher concentration of inner areas, where the digital divide remains more pronounced. These findings accentuate the dual role of digitalization and highlight the necessity of coordinated policy interventions that combine infrastructure investment with digital skills development, institutional capacity-building, and spatially integrated governance strategies.","author":[{"family":"Bergantino","given":"Angela"},{"family":"Fusco","given":"Giulio"},{"family":"Intini","given":"Mario"},{"family":"Monturano","given":"Gianluca"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s00168-025-01440-z","URL":"https://doi.org/10.1007/s00168-025-01440-z","source":"openalex"},{"id":"oa:W4411452550","type":"article-journal","title":"Digital Economy, Green Finance, and Carbon Emissions: Evidence from China","abstract":"This paper investigates the role of the digital economy in reducing carbon emissions, with a particular focus on the moderating and threshold effects of green finance. An analysis of data from 30 Chinese provinces shows that the digital economy significantly reduces carbon emission intensity by restructuring energy consumption and promoting green technological innovation. Green finance plays a crucial moderating role by alleviating financial barriers to digital transformation and supporting the implementation of emission-reducing technologies. The study reveals a nonlinear relationship, with green finance exhibiting a “strong initial, weak subsequent” threshold effect. At the same time, the digital economy’s impact on carbon reduction strengthens over time as technological development progresses. These findings contribute to understanding how digitalisation and green finance can work synergistically to drive sustainable low-carbon development.","author":[{"family":"Jin","given":"Weibo"},{"family":"Wang","given":"Yiming"},{"family":"Yan","given":"Yi"},{"family":"Zhou","given":"Hongyan"},{"family":"Xu","given":"Longyu"},{"family":"Zhang","given":"Yi"},{"family":"Xu","given":"Yao"},{"family":"Zhang","given":"Yuqi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17125625","URL":"https://doi.org/10.3390/su17125625","source":"openalex"},{"id":"oa:W7131278121","type":"article-journal","title":"Overcoming synchronization challenges in machining digital twins: transpiling legacy NC dialects to enhance interoperability","abstract":"Abstract Digital Twin (DT) technology is a key enabler of smart manufacturing, with extensive research devoted to virtual replicas of physical assets in both subtractive and additive processes. In this context, numerical control (NC) programs are central to synchronizing physical and virtual twins, yet they are typically based on G-code, a low-level language introduced in the 1960s. Although standardized at its core, G-code has been widely extended by CNC system developers, leading to multiple dialects and significant interoperability issues across heterogeneous machines. These differences hinder effective synchronization, particularly due to the difficulty of aligning timestamps among NC programs. This study proposes a methodology to improve synchronization and interoperability by transpiling NC dialects into a higher-level abstraction based on a comprehensive and fine-grained set of machining functions. The methodology is implemented as an extensible object-oriented framework. Validation through the successful transpilation of a legacy NC dialect demonstrates the ability to compute accurate event timelines, providing a foundation for the development of robust Digital Twins for G-code-based manufacturing processes.","author":[{"family":"Aguiar","given":"Francisco"},{"family":"Rebeyka","given":"Claudimir"},{"family":"Costa","given":"Dalberto"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s00170-026-17723-4","URL":"https://doi.org/10.1007/s00170-026-17723-4","source":"openalex"},{"id":"oa:W4412690924","type":"article-journal","title":"A Digital Twin-based System for the Indoor Environmental Quality Monitoring in Off-Site Construction Facilities","abstract":"Off-site construction (OSC) is a well-established paradigm for achieving productivity, safety, and sustainability in construction.The key factor in its success is the efficiency of the workforce transforming blueprints into actual buildings and building elements.This has driven efforts to improve working conditions at the production facility, paving the way towards humancentric construction manufacturing.Achieving a safe and healthy indoor environmental quality (IEQ) is among the most critical aspects of this endeavor.Given the dynamic nature of IEQ in OSC facilities, there is a need for realtime performance monitoring as a means of identifying any deviations from IEQ standards and regulations.As such, the objective of this study is to develop a digital twin-based system for real-time monitoring of the IEQ of OSC facilities with continuous management and alerting features.The proposed O-IEQ Alert System encompasses four phases: (1) IEQ metrics identification, (2) data acquisition, (3) digital modelling, and (4) development of the IEQ alerting component.The system is successfully applied in a case study of a wall-production manufacturing facility.A web-based alert system is developed that presents real-time monitoring of the IEQ indices, including Air Quality Index, thermal comfort Predicted Mean Vote Index, and the Sound Level Index for each workstation along with the time-series trends.In case any of the indices does not fall within the defined threshold, an alert is issued to management to take the necessary corrective and preventive measures.The ultimate aim is to provide a safe, healthy, and productive working environment in OSC facilities.","author":[{"family":"Assaf","given":"Sena"},{"family":"Assaf","given":"Mohamed"},{"family":"Li","given":"Xinming"},{"family":"Bouferguène","given":"Ahmed"},{"family":"Alhussein","given":"Mohamed"}],"issued":{"date-parts":[[2025]]},"DOI":"10.22260/isarc2025/0115","URL":"https://doi.org/10.22260/isarc2025/0115","source":"openalex"},{"id":"oa:W7118939551","type":"article-journal","title":"Plant Digital Twins: The Fusion of Biology and Artificial Intelligence","abstract":"The speed of the convergence between biological sciences and artificial intelligence is changing how we perceive, observe and regulate plant systems. Nowadays, the agricultural sector is on the verge of a technological revolution, a revolution in which virtual plant replicas, or plant digital twins, provide unprecedented data on patterns of growth, stress tolerance, nutrient interactions, disease forecasting, and yield optimization. Plant Digital Twins: The Fusion of Biology and Artificial Intelligence is a book that is written as a referral book by students, researchers, scientists, and innovators who would be interested in venturing into this transformative field. It also combines the basics of biology and advanced algorithms and demonstrates that digital twins have the potential to transform modern agriculture, climate resilience, herbal studies, precision farming, and sustainable crop development. The book bridges the gap between theory and practice relating to plant physiology, IoT-enabled sensing, cloud computing, data analytics, AI-driven modelling, and simulation sciences. In every chapter, there are good insights, case studies, and technological trends that are influencing the future of plant science. It is meant to empower the readers with not only the conceptual but also practical relevance to prepare them in the following era of intelligent, smart, and sustainable agriculture.","author":[{"family":"Sinha","given":"Aashna"},{"family":"Shukla","given":"Geetanjali"},{"family":"Parveen","given":"Fraiz"},{"family":"Gehlot","given":"Anita"},{"family":"Singh","given":"Rajesh"}],"issued":{"date-parts":[[2025]]},"DOI":"10.55938/wlp.v2i7.302","URL":"https://doi.org/10.55938/wlp.v2i7.302","source":"openalex"},{"id":"oa:W4413416164","type":"article-journal","title":"SYNTHUA-DT: A Methodological Framework for Synthetic Dataset Generation and Automatic Annotation from Digital Twins in Urban Accessibility Applications","abstract":"Urban scene understanding for inclusive smart cities remains challenged by the scarcity of training data capturing people with mobility impairments. We propose SYNTHUA-DT, a novel methodological framework that integrates unmanned aerial vehicle (UAV) photogrammetry, 3D digital twin modeling, and high-fidelity simulation in Unreal Engine to generate annotated synthetic datasets for urban accessibility applications. This framework produces photo-realistic images with automatic pixel-perfect segmentation labels, dramatically reducing the need for manual annotation. Focusing on the detection of individuals using mobility aids (e.g., wheelchairs) in complex urban environments, SYNTHUA-DT is designed as a generalized, replicable pipeline adaptable to different cities and scenarios. The novelty lies in combining real-city digital twins with procedurally placed virtual agents, enabling diverse viewpoints and scenarios that are impractical to capture in real life. The computational efficiency and scale of this synthetic data generation offer significant advantages over conventional datasets (such as Cityscapes or KITTI), which are limited in accessibility-related content and costly to annotate. A case study using a digital twin of Curitiba, Brazil, validates the framework’s real-world applicability: 22,412 labeled images were synthesized to train and evaluate vision models for mobility aids user detection. The results demonstrate improved recognition performance and robustness, highlighting SYNTHUA-DT’s potential to advance urban accessibility by providing abundant, bias-mitigating training data. This work paves the way for inclusive computer vision systems in smart cities through a rigorously engineered synthetic data pipeline.","author":[{"family":"Romero","given":"Santiago"},{"family":"Souza","given":"Mauren"},{"family":"Serpa-Andrade","given":"Luis"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/technologies13080359","URL":"https://doi.org/10.3390/technologies13080359","source":"openalex"},{"id":"oa:W4413217460","type":"article-journal","title":"Physics‐Informed Digital Twins: Enhancing Concrete Structural Assessment Based on Point Cloud Data","abstract":"Finite element modeling is widely regarded as an effective method for simulating structural responses, but maintaining geometrical consistency with damaged physical structures remains insufficiently explored. This paper proposes a new physics‐informed digital twin framework for concrete structure modeling and implements the twinning/synchronization process between the physical model and its counterpart finite element analysis (FEA) model. This framework starts with point cloud scanning for damage and point cloud processing. Subsequently, a direct mapping method called Voxel–Node–Element (VNE) is proposed, which can improve mapping efficiency and reduce mapping errors. Furthermore, a multiscale modeling method is adopted to enhance digital twin modeling updates, dramatically reducing the number of elements and improving computational efficiency. An experimental case study was conducted to evaluate this method, showing good alignment between point cloud and physics models with a geometric error of less than 5%. Additionally, computational efficiency was improved by 95% compared to traditional methods. This method can also be used for full‐scale structure modeling, which was validated in the case of damage updates for large bridges. This study enables a highly accurate and efficient method for updating digital twin models. This capability was validated through damage updates applied to large‐scale bridge structures.","author":[{"family":"Song","given":"Honghong"},{"family":"Zhu","given":"Xiaofeng"},{"family":"Li","given":"Haijiang"},{"family":"Yang","given":"Gang"},{"family":"Zhang","given":"Tian"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1155/stc/5605927","URL":"https://doi.org/10.1155/stc/5605927","source":"openalex"},{"id":"oa:W7134177810","type":"article-journal","title":"AI-Driven Fault Detection and O&M for Wind Turbine Drivetrains: A Review of SCADA, CMS and Digital Twin Integration","abstract":"The rapid expansion of wind energy has increased the operational complexity of wind turbines, where component degradation, environmental variability, and maintenance decisions are tightly coupled. Artificial intelligence (AI) has been widely applied to support fault detection and operation and maintenance (O&M), yet many existing studies remain fragmented and insufficiently address practical challenges such as heterogeneous data, sparse fault labels, and cross-site generalization. This review provides an engineering-oriented synthesis of AI-based methods for wind turbine fault detection and O&M, focusing on drivetrain diagnostics as a representative application. The literature is organized along an end-to-end O&M workflow, including SCADA-based condition monitoring, component-level fault diagnosis, health assessment and remaining useful life estimation, multi-modal blade inspection, and DT (Digital Twin) integration. Traditional ML (machine learning), ensemble methods, deep learning, physics-informed learning, and transfer learning are reviewed with respect to their data requirements, operational assumptions, and deployment constraints. Beyond algorithmic performance, this review discusses data governance, alarm design, model updating, and interpretability, and summarizes public datasets and emerging data resources. The aim is to bridge methodological advances and practical O&M requirements, supporting reliable and deployable AI applications in wind energy systems.","author":[{"family":"Jia","given":"Ning"},{"family":"Feng","given":"Jiangzhe"},{"family":"Zuo","given":"Zongyou"},{"family":"Liu","given":"Zhiyi"},{"family":"Wang","given":"Tengyuan"},{"family":"Cai","given":"Chang"},{"family":"Li","given":"Qingan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19051370","URL":"https://doi.org/10.3390/en19051370","source":"openalex"},{"id":"oa:W7163003874","type":"article-journal","title":"Digital twin federation for urban mobility assessment: Definition, pillars, and a human-in-the-loop functional architecture","abstract":"Urban mobility systems face growing challenges. While various smart mobility solutions have been proposed, there is still a lack of comprehensive tools for assessing the impact of these solutions in a dynamic and iterative manner. Recent literature increasingly adopts the Digital Twin (DT) concept. However, DTs have conventionally been framed around automating solutions, which often conflict with the requirements of human-driven planning in socio-technical systems, leading to ambiguities in how DTs should be defined and operationalised for mobility planning. To fill this gap, this paper presents the concept of a Digital Twin Federation (FedDT) designed for comprehensive urban mobility assessments. Firstly, a definition of the FedDT concept is established based on four conceptual pillars, including physical & digital system exchange, system monitoring & planning, outcome evaluation & immersive experience, and human-in-the-loop control. Building on the concept and 5 stakeholder co-design sessions, we present a functional FedDT architecture that enables iterative, bidirectional data exchange between the physical and digital mobility systems, thereby supporting a data-driven decision-making process while ensuring the interests of stakeholders are continuously integrated. Finally, we demonstrate how the FedDT architecture can be instantiated through a proof-of-concept application framework. This framework serves as a research agenda that guides and links the development of separate modules to reduce private vehicle dependency in Amsterdam, the Netherlands. Overall, this work lays a conceptual and architectural foundation for FedDT, advancing the implementation of integrated digital twin solutions for sustainable mobility systems.","author":[{"family":"Li","given":"Jingjun"},{"family":"Grübel","given":"Jascha"},{"family":"Nadi","given":"Ali"},{"family":"Snelder","given":"Maaike"},{"family":"Arem","given":"Bart"},{"family":"Gao","given":"Jie"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.tra.2026.105086","URL":"https://doi.org/10.1016/j.tra.2026.105086","source":"openalex"},{"id":"oa:W4415349124","type":"article-journal","title":"Lost in translation: why digital twins thrive in research but falter in politics and public administration","abstract":"Abstract Since 2017, Digital Twins (DTs) have gained prominence in academic research, with researchers actively conceptualising, prototyping, and implementing DT applications across disciplines. The transformative potential of DTs has also attracted significant private sector investment, leading to substantial advancements in their development. However, their adoption in politics and public administration remains limited. While governments fund extensive DT research, their application in governance is often seen as a long-term prospect rather than an immediate priority, hindering their integration into decision-making and policy implementation. This study bridges the gap between theoretical discussions and practical adoption of DTs in governance. Using the Technology Readiness Level (TRL) and Technology Acceptance Model (TAM) frameworks, we analyse key barriers to adoption, including technological immaturity, limited institutional readiness, and scepticism regarding practical utility. Our research combines a systematic literature review of DT use cases with a case study of Germany, a country characterised by its federal governance structure, strict data privacy regulations, and strong digital innovation agenda. Our findings show that while DTs are widely conceptualised and prototyped in research, their use in governance remains scarce, particularly within federal ministries. Institutional inertia, data privacy concerns, and fragmented governance structures further constrain adoption. We conclude by emphasising the need for targeted pilot projects, clearer governance frameworks, and improved knowledge transfer to integrate DTs into policy planning, crisis management, and data-driven decision-making.","author":[{"family":"Richter","given":"Friederike"},{"family":"Campbell","given":"Kirsty"},{"family":"Riedl","given":"Jasmin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1017/dap.2025.10027","URL":"https://doi.org/10.1017/dap.2025.10027","source":"openalex"},{"id":"oa:W4412040917","type":"article-journal","title":"A systematic literature review on integrating AI-powered smart glasses into digital health management for proactive healthcare solutions","abstract":"AI-powered smart glasses are emerging as a highly promising advancement in the field of digital health management, owing to their capabilities in real-time monitoring, chronic disease management, and personalized treatment planning. To comprehensively understand the current state of development, we systematically searched multiple databases, including Web of Science, PubMed, and IEEE Xplore, to collect relevant literature. This paper provides a systematic analysis of the current applications of smart glasses in healthcare, focusing on their potential benefits and limitations. Key issues discussed include user engagement, treatment adherence, data privacy, standardization, battery efficiency, clinical validation, and medical ethics. Our findings suggest that, supported by emerging clinical evidence, smart glasses have demonstrated significant improvements in areas such as assisted medical services, health management, anxiety alleviation in children, and telemedicine. By integrating multi-modal sensors, these devices are capable of accurately tracking certain physiological indicators and synchronizing real-time visual input, thereby enhancing the accuracy and timeliness of health interventions and medical services. Notably, some cutting-edge smart glasses have adopted advanced artificial intelligence algorithms, particularly large language models (LLMs) with context awareness and human-like interaction capabilities. These AI-powered glasses can offer real-time, personalized dietary and health management recommendations tailored to users' daily life scenarios. Building on these findings, this study further proposes a conceptual framework for proactive health management using smart glasses and explores future directions in technological development and practical applications. Overall, AI-enhanced smart glasses show great potential as a critical interface between healthcare providers and patients, poised to play a vital role in the future of personalized medicine and continuous health management.","author":[{"family":"Wang","given":"Boyuan"},{"family":"Zheng","given":"Ying"},{"family":"Han","given":"Xihao"},{"family":"Kong","given":"Liang"},{"family":"Xiao","given":"Gexin"},{"family":"Xiao","given":"Zunxiong"},{"family":"Chen","given":"Shanji"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41746-025-01715-x","URL":"https://doi.org/10.1038/s41746-025-01715-x","source":"openalex"},{"id":"oa:W7128736234","type":"article-journal","title":"In-situ digital twinning of induction machines via sensitivity-based genetic algorithm parameter estimation","abstract":"This paper presents a novel, non-invasive methodology for creating a high-fidelity digital twin using only steady-state operational data. The proposed approach employs a fourstep workflow with two-stage parameter identification algorithm. First, a grid-based sensitivity analysis is conducted to establish robust and constrained search boundaries. Subsequently, a genetic algorithm performs a precise search within these boundaries to identify the final T-equivalent circuit parameters. The methodology was validated on a 1.5 kW induction motor. All but core loss identified parameters demonstrated similarity with those obtained from standard offline tests, and the resulting digital twin accurately reproduced the machine?s behaviour when compared to experimental measurements.","author":[{"family":"Filipović","given":"Filip"},{"family":"Stojiljkovic","given":"Andjela"},{"family":"Mitrović","given":"Nebojša"},{"family":"Banković","given":"Bojan"},{"family":"Petronijević","given":"Milutin"},{"family":"Kostić","given":"Vojkan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.2298/fuee2601285f","URL":"https://doi.org/10.2298/fuee2601285f","source":"openalex"},{"id":"oa:W4410985655","type":"article-journal","title":"A Digital Twin-based condition monitoring system to detect and resolve web slip at traction rollers in a web processing machine","abstract":"Slippage of web material over rollers is an undesirable phenomenon in web processing applications, causing damage to the web material. This leads to compromised quality and increased waste. While web slippage is commonly observed at high web speeds due to air entrapment on freely rotating rollers, it also occurs at lower web speeds at the traction rollers, which are designed to drive the web through the machine. Installing web speed sensors to detect such web slippage on multiple traction rollers in large-scale web processing machines is expensive. This work presents a novel Digital Twin methodology for online condition monitoring and fault detection to identify web slip at the traction rollers. The Digital Twin uses the contact forces between the web and the traction roller to detect web slippage, greatly reducing the need for web speed sensors and thereby cutting costs and time. Additionally, in response to detected web slip, the newly proposed Digital Twin further acts to resolve the slip. Experimental results demonstrate the effectiveness of the Digital Twin in detecting and resolving web slippage on three different web materials.","author":[{"family":"Mathivanan","given":"Arulkumaran"},{"family":"Kooning","given":"Jeroen"},{"family":"Stockman","given":"Kurt"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jmsy.2025.05.001","URL":"https://doi.org/10.1016/j.jmsy.2025.05.001","source":"openalex"},{"id":"oa:W4409804912","type":"article-journal","title":"From Digital to Real: Optimised and Functionally Integrated Shotcrete 3D Printing Elements for Multi-Storey Structures","abstract":"The construction industry is facing a dual challenge: an increasing demand for new buildings on the one hand and the urgent need to drastically reduce emissions and waste on the other. One promising field of research to face these challenges comprises additive manufacturing (AM) technologies. Through these advanced methods, digital workflows between design and fabrication can be implemented to optimise the form and structure, unlocking new architectural freedom while ensuring sustainability and efficiency. However, to drive this transformation in construction, the new technologies must be investigated in large-scale applications. One of these fast-emerging AM techniques is Shotcrete 3D Printing (SC3DP). The present research documents the 1:1 scale manufacturing process, from digital to real, of a building section utilising SC3DP. A workflow and production steps, spanning from design over manufacturing to assembly, are introduced. The architectural design, reinforced by computational methods, was iteratively refined to adapt to manufacturing constraints. The paper also emphasises the importance of a digital twin in ensuring seamless data integration and real-time adjustments during construction. By incorporating reinforcement techniques such as short rebar insertion and robotic fibre winding, this study demonstrates the structural capabilities achievable with SC3DP. In summary, the implementation of comprehensive digital workflows utilising computational design, automated data acquisition and data flow, as well as robotic fabrication is presented to demonstrate the potential of AM methods in construction. Furthermore, this paper provides a perspective on potential future research paths and opportunities inherent in leveraging the innovative SC3DP technique.","author":[{"family":"Dörrie","given":"Robin"},{"family":"Gantner","given":"Stefan"},{"family":"Amiri","given":"Fatemeh"},{"family":"Lachmayer","given":"Lukas"},{"family":"David","given":"Martin"},{"family":"Rothe","given":"Tom"},{"family":"Freund","given":"Niklas"},{"family":"Nouman","given":"Ahmad"},{"family":"Mawas","given":"Karam"},{"family":"Oztoprak","given":"Oguz"},{"family":"Rennen","given":"Philipp"},{"family":"Ekanayaka","given":"Virama"},{"family":"Hürkamp","given":"André"},{"family":"Kollmannsberger","given":"Stefan"},{"family":"Hühne","given":"Christian"},{"family":"Raatz","given":"Annika"},{"family":"Dröder","given":"Klaus"},{"family":"Lowke","given":"Dirk"},{"family":"Hack","given":"Norman"},{"family":"Kloft","given":"Harald"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15091461","URL":"https://doi.org/10.3390/buildings15091461","source":"openalex"},{"id":"oa:W7106504365","type":"article-journal","title":"A sustainability-oriented KPI framework for digital twin adoption in the sugar industry: ISM–MICMAC approach","abstract":"Purpose The sugar industry is always pressured to be suitable and enhance its operational effectiveness. Digital twin (DT) has the potential to transform this industry. However, the lack of industry-specific key performance indicator (KPI) frameworks makes it challenging to implement them. This study provides a hierarchical KPI model for DT adoption in the sugar sector, interconnecting the United Nations' sustainable development goals (SDGs). Design/methodology/approach It has two phases: the first is an intense literature review, which identifies 24 relevant KPIs for DT adoption and sets the procedure for expert validation. Second, hierarchical relationships were identified through interpretive structural modeling (ISM) and MICMAC was used to classify KPIs based on driving and reliant power. The developed framework has several dimensions: technology, environmental, strategic, operational, financial and security. Findings Operational and environmental KPIs relate to important factors; however, environmental, social and governance (ESG) tracking, stakeholder satisfaction, governance, social and environmental factors, and reduction of defects were also critical outcomes. Key drivers came after technological studies, such as integrating old legacy systems, data integration and return on investment, or digital investment. The KPI hierarchy establishes the structural relationship that ensures DT investments align with sustainability goals, including cutting carbon emissions, maximizing resource usage and reducing water consumption. Research limitations/implications Likewise, earlier studies, the existing paper is also not free from limitations. We consulted experts from emerging economies like India to develop ISM modeling and collect data. However, the experts' opinions may change from country to country, impacting results. Also, the proposed research is applicable in the sugar sector. Originality/value Developing the DT adoption KPIs in the sugar sector using ISM and MICMAC is a unique contribution of this research. In addition, all KPI frameworks are also interconnected with the United Nations sustainability goals.","author":[{"family":"Pandey","given":"Satish"},{"family":"Virmani","given":"Naveen"},{"family":"Bhandari","given":"Dimple"},{"family":"Jagtap","given":"Sandeep"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1108/jadee-08-2025-0392","URL":"https://doi.org/10.1108/jadee-08-2025-0392","source":"openalex"},{"id":"oa:W7134940461","type":"article-journal","title":"Mapping Urban Digital Twins Across Regions: An Exploratory Study of Maturity, Implementation Status, and Authority","abstract":"An increasing number of municipalities are adopting urban digital twins (UDTs) to improve urban management. Although the models differ widely, municipalities face similar challenges in their implementation. Therefore, sharing insights on UDTs provides an opportunity for collective growth. To facilitate this growth, the present exploratory study maps the characteristics, challenges, and potentials of 99 UDTs in Europe, North America, and Asia. We first estimate the UDT readiness based on established features, along with contextual and local authority involvement indicators. Next, we conduct semi-structured interviews with key individuals from eight selected cities to contextualize the review findings. The mapping results indicate that most UDTs in our sample operate at the municipal level, and that over half (57%) are not in series operation. The reviewed UDTs are mid-level in maturity, and local authority involvement is a key driver of scalability. We infer that UDT progress depends as much on common frameworks, organizational readiness, governance capacity, and relevant data as on technology. Collaborations with private companies and researchers can play a central role in the long-term sustainment and growth of UDT infrastructures.","author":[{"family":"Hiller","given":"Jasmin"},{"family":"Mansour","given":"Mohamed"},{"family":"Kremer","given":"Noemi"},{"family":"Crampen","given":"David"},{"family":"Behren","given":"Sascha"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/smartcities9030049","URL":"https://doi.org/10.3390/smartcities9030049","source":"openalex"},{"id":"oa:W4414239176","type":"article-journal","title":"Policy-Driven Digital Health Interventions for Health Promotion and Disease Prevention: A Systematic Review of Clinical and Environmental Outcomes","abstract":"Objectives: This systematic review investigates clinical and environmental outcomes associated with policy-driven digital health interventions for health promotion and disease prevention. Methods: Following PRISMA 2020 guidelines, six databases (Scopus, Web of Science, PubMed, IEEE Xplore, ScienceDirect, and MDPI) were systematically searched for empirical studies published between January 2020 and June 2025, using keywords including “digital health,” “telemedicine,” “mHealth,” “wearable,” “AI,” “environmental impact,” and “sustainability.” From 1038 unique records screened, 68 peer-reviewed studies met inclusion criteria and underwent qualitative thematic synthesis. Results: Results show digital health interventions such as telemedicine, mobile health (mHealth) apps, wearable devices, and artificial intelligence (AI) platforms improve healthcare accessibility, chronic disease management, patient adherence, and clinical efficiency. Environmentally, these interventions significantly reduce carbon emissions, hospital energy consumption, and medical waste. Conclusion: The studies lacked standardized environmental metrics and predominantly originated from high-income regions. Future research should prioritize the development of uniform sustainability indicators, broaden geographic representation, and integrate rigorous life-cycle assessments. Policymakers are encouraged to embed environmental considerations into digital health strategies to support resilient, sustainable healthcare systems globally.","author":[{"family":"Faizan","given":"Muhammad"},{"family":"Han","given":"Chaeyoon"},{"family":"Lee","given":"Seung"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/healthcare13182319","URL":"https://doi.org/10.3390/healthcare13182319","source":"openalex"},{"id":"oa:W7116104720","type":"article-journal","title":"Digital twins in computational medicine with a specific focus on nuclear oncology. Where do we stand?","abstract":"In medicine, digital twins (DTs) serve as computational models that replicate biological and physiological characteristics of a specific individual — whether a patient, an organ, or even a single cell — and simulate virtual biomedical experiments. DT-based simulations hold the potential to identify the most beneficial intervention at any given moment. A range of technological approaches has been explored across various medical fields, with oncology being one of the most suitable areas of application in view of the necessity of timely and personalized treatment decisions. Medical imaging, and especially nuclear medicine, might have a central role in the development of DTs. In this review we define digital twins, examine current evidence, and discuss opportunities that digital twins can offer in computational nuclear oncology. We also briefly summarize the state-of-the-art of DTs in other fields.","author":[{"family":"Cavinato","given":"Lara"},{"family":"Sollini","given":"Martina"},{"family":"Papp","given":"Laszlo"},{"family":"Shi","given":"Kuangyu"},{"family":"Visvikis","given":"Dimitris"},{"family":"Chiti","given":"Arturo"},{"family":"Kirienko","given":"Margarita"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.eanmi.2025.100022","URL":"https://doi.org/10.1016/j.eanmi.2025.100022","source":"openalex"},{"id":"oa:W7161681803","type":"article-journal","title":"Power Hardware-in-the-Loop validation of digital twin-enabled dynamic analysis and assessment of distribution networks","abstract":"The development of accurate equivalent models of distribution networks (DNs) is of primary significance for power system dynamic analysis and control applications. Advances in measurement infrastructure and information and communication technologies have enabled the development of data-driven DN simulation models and digital twins. Despite the numerous modeling approaches proposed, their majority have not been tested under real-world conditions, leading to poor assessment of their efficacy in representing DN dynamics. This study aims to derive and validate reduced-order DN equivalent models that serve as digital counterparts of physical components connected to the network across discrete operating scenarios. Real-time simulations are performed using a Power Hardware-in-the-Loop experimental framework. Within this framework, the model structure selection and the accuracy of the developed digital replicas are evaluated under close to real-world conditions. The results demonstrate the effectiveness of the developed models and their applicability for dynamic simulations, offering a practical alternative without compromising accuracy.","author":[{"family":"Barzegkarntovom","given":"Georgios"},{"family":"Kontis","given":"Eleftherios"},{"family":"Papadopoulos","given":"Theofilos"},{"family":"Feng","given":"Zhiwang"},{"family":"Burt","given":"Graeme"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.epsr.2026.113311","URL":"https://doi.org/10.1016/j.epsr.2026.113311","source":"openalex"},{"id":"oa:W7154227605","type":"article-journal","title":"A hybrid self-evolving edge-AI framework for scalable digital process twins in enterprise systems","abstract":"Edge-centric digital process twins struggle with slow adaptation and real-time compliance. We propose a self-evolving Edge-AI architecture with five components. The Hierarchical Neuro-Symbolic Verification Graph integrates symbolic rules and neural graphs, reducing latency by 35% while maintaining over 97% compliance. Federated Evolutionary Drift Adaptation improves drift response by 28% and F1 score by 15% using evolutionary operators. The Multi-Resolution Spatio-Temporal Causal Inference Network enables 40% earlier fault detection via causal separation. The Quantum-Inspired Edge Reinforcement Optimiser speeds convergence by 30% and boosts effectiveness by 12%. The Cross-Layer Digital Twin Consistency Ledger ensures tamper-proof state integrity with <0.5% violations at 10k+ transactions/s, enabling secure, adaptive automation.","author":[{"family":"Naresh","given":"P"},{"family":"Sardar","given":"Tanvir"},{"family":"Ramityal","given":"Bharti"},{"family":"Almusharraf","given":"Ahlam"},{"family":"Jain","given":"Vipul"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/17517575.2026.2653241","URL":"https://doi.org/10.1080/17517575.2026.2653241","source":"openalex"},{"id":"oa:W7133231232","type":"article-journal","title":"Modelling vat photopolymerization: a comprehensive review and perspectives on digital twinning and advancing multi-wavelength processes","abstract":"Vat photopolymerization (VPP) is a high-precision additive manufacturing technology that selectively cures photosensitive resins to create complex 3D structures. The emergence of multi-wavelength VPP – enabling capabilities such as wavelength-selective multi-material printing and photo-inhibition-aided processes – introduces new challenges in modelling and process control. Conventional single-wavelength models often fail to capture the coupled optical, thermal, chemical, and mechanical phenomena underlying material interactions and dynamic process behaviours, limiting predictive accuracy and optimisation. This review critically evaluates the state of VPP modelling, encompassing physics-based and data-driven approaches, and highlights their strengths, limitations, and challenges for both single- and multi-wavelength systems. Building on this analysis, an AI-driven digital twin framework is proposed, that integrates multiscale, multi-physics simulations with in-situ sensor data and machine learning–based surrogate models. This approach enables real-time monitoring, prediction, and adaptive control, improving process efficiency, material utilisation, and print quality. It also provides a pathway for designing and testing sustainable, multi-functional materials tailored for next-generation VPP systems. By combining high-fidelity simulations with adaptive AI, this work establishes a roadmap for intelligent, scalable, and sustainable VPP technologies, supporting high-resolution, multi-material, and multifunctional additive manufacturing across diverse industrial applications.HighlightsReview evaluates modelling methods for single- and multi-wavelength VPP.Framework integrates optical, thermal, kinetic and mechanical multi-physics models.AI-driven digital twin enables adaptive, real-time monitoring and process control.Hierarchical modelling links physics-based simulations with data-driven learning.Roadmap advances intelligent, sustainable, and multi-material VPP technologies.","author":[{"family":"Zhao","given":"Xiayun"},{"family":"Bensouda","given":"Yousra"},{"family":"Alam","given":"Md"},{"family":"Wang","given":"Yiquan"},{"family":"Zhang","given":"Heyang"},{"family":"Zhang","given":"Yue"},{"family":"Zhang","given":"Haolin"},{"family":"Rosen","given":"David"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/17452759.2026.2632491","URL":"https://doi.org/10.1080/17452759.2026.2632491","source":"openalex"},{"id":"oa:W7125945291","type":"article-journal","title":"From digital tools to sustainable change: How change agents enable the twin transition in hospitality","abstract":"This study explores how change agents drive sustainable service change in hospitality networks through engagement in the twin transition—combining digitalization and sustainability. Using a multi-level sensemaking framework (extraorganizational, intraorganizational, intraindividual), we analyze the role of a local hoteliers’ association promoting a business intelligence solution (BIS) to support this transition. Drawing on a case study of 43 hotels in northeastern Italy, supplemented by a simulation study, we examine how twin transition engagement mediates the effects of social capital, category-based sensemaking, and stewardship on sustainable service change. Findings show that structural and cognitive social capital influence sustainability directly, but not twin transition engagement, underscoring the critical role of the change agent. Category-based sensemaking is fully mediated, while stewardship affects sustainability but not digital adoption. The study contributes to hospitality research by linking sensemaking and stewardship to digital–sustainability innovation, and highlights simulation as a useful method to validate findings in data-constrained environments.","author":[{"family":"Cappiello","given":"Giuseppe"},{"family":"Casoli","given":"Debora"},{"family":"Tuan","given":"Annamaria"},{"family":"Visentin","given":"Marco"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.ijhm.2026.104591","URL":"https://doi.org/10.1016/j.ijhm.2026.104591","source":"openalex"},{"id":"oa:W4413153278","type":"article-journal","title":"Digital Twins and AI in Infrastructure Engineering: A Global Review of Risk-Informed Design, Operations, and Maintenance","abstract":"As global infrastructure systems become increasingly complex and vulnerable, the integration of Digital Twins (DT) and Artificial Intelligence (AI) has emerged as a transformative strategy for risk-informed design, operations, and maintenance. However, a significant research gap remains in understanding the global patterns, integration challenges, and practical impact of DT-AI systems across different infrastructure sectors. This systematic review, guided by the PRISMA framework, synthesizes findings from 126 peer-reviewed studies sourced from Scopus, Web of Science, and IEEE Xplore. Analysis revealed that 68% of implementations focus on predictive maintenance and real-time monitoring, while only 12% address early-stage design optimization highlighting an imbalance in lifecycle focus. Furthermore, projects that applied AI-enhanced DTs achieved up to 30% reduction in unplanned maintenance events and improved infrastructure lifespan predictions by an average of 22%. Case studies from Singapore, the UK, Norway, and the US demonstrate real-world benefits in city planning, structural health monitoring, and transportation. Despite these successes, key barriers persist, including data interoperability, cybersecurity vulnerabilities, high implementation costs, and insufficient regulatory standards. This review underscores the need for cross-sectoral collaboration, global policy frameworks, and inclusive innovation strategies to fully leverage DT-AI capabilities in building resilient, adaptive infrastructure.","author":[{"family":"Ogunleye","given":"Emmanuel"},{"family":"Anyaene","given":"Kingsley"},{"family":"Oladetan","given":"Jeremiah"},{"family":"Lawal","given":"Aliu"},{"family":"Okeke","given":"Francis"},{"family":"Ogunbule","given":"Olutoyin"},{"family":"Eromosele","given":"Eric"}],"issued":{"date-parts":[[2025]]},"DOI":"10.69739/sjet.v2i2.808","URL":"https://doi.org/10.69739/sjet.v2i2.808","source":"openalex"},{"id":"oa:W4410382109","type":"article-journal","title":"The translational power of Alzheimer’s-based organoid models in personalized medicine: an integrated biological and digital approach embodying patient clinical history","abstract":"Alzheimer’s disease (AD) is a complex neurodegenerative condition characterized by a multifaceted interplay of genetic, environmental, and pathological factors. Traditional diagnostic and research methods, including neuropsychological assessments, imaging, and cerebrospinal fluid (CSF) biomarkers, have advanced our understanding but remain limited by late-stage detection and challenges in modeling disease progression. The emergence of three-dimensional (3D) brain organoids (BOs) offers a transformative platform for bridging these gaps. BOs derived from patient-specific induced pluripotent stem cells (iPSCs) mimic the structural and functional complexities of the human brain. This advancement offers an alternative or complementary approach for studying AD pathology, including β-amyloid and tau protein aggregation, neuroinflammation, and aging processes. By integrating biological complexity with cutting-edge technological tools such as organ-on-a-chip systems, microelectrode arrays, and artificial intelligence-driven digital twins (DTs), it is hoped that BOs will facilitate real-time modeling of AD progression and response to interventions. These models capture central nervous system biomarkers and establish correlations with peripheral markers, fostering a holistic understanding of disease mechanisms. Furthermore, BOs provide a scalable and ethically sound alternative to animal models, advancing drug discovery and personalized therapeutic strategies. The convergence of BOs and DTs potentially represents a significant shift in AD research, enhancing predictive and preventive capacities through precise in vitro simulations of individual disease trajectories. This approach underscores the potential for personalized medicine, reducing the reliance on invasive diagnostics while promoting early intervention. As research progresses, integrating sporadic and familial AD models within this framework promises to refine our understanding of disease heterogeneity and drive innovations in treatment and care.","author":[{"family":"Dolciotti","given":"Cristina"},{"family":"Righi","given":"Marco"},{"family":"Grecu","given":"Eleonora"},{"family":"Trucas","given":"Marcello"},{"family":"Maxia","given":"Cristina"},{"family":"Murtas","given":"Daniela"},{"family":"Diana","given":"Andrea"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fncel.2025.1553642","URL":"https://doi.org/10.3389/fncel.2025.1553642","source":"openalex"},{"id":"oa:W4411345500","type":"article-journal","title":"An Overview of Critical Success Factors for Digital Shipping Corridors: A Roadmap for Maritime Logistics Modernization","abstract":"Digital Shipping Corridors (DSCs) are gaining traction as integrated models for increasing transparency, efficiency, and sustainability in maritime logistics. Yet, the enabling conditions for their effective implementation remain insufficiently explored. This study employs a qualitative thematic review approach, analyzing the academic literature, global policy documents, and selected case studies to identify and synthesize the critical success factors for DSC development. The analysis reveals seven interdependent factors: technological infrastructure, economic feasibility, regulatory frameworks, logistical efficiency, logistical security, stakeholder collaboration, and environmental sustainability. These factors are not independent but interact dynamically, requiring coordinated development across technical, institutional, and environmental domains. This study proposes a dynamic interaction framework that illustrates how progress in one area (e.g., digital infrastructure) depends on readiness in others (e.g., governance and cross-sector collaboration). The outcomes contribute both conceptually and practically. The framework offers a system-level understanding of DSC implementation and identifies key leverage points for intervention. The findings provide strategic guidance for policymakers, port authorities, and supply chain stakeholders pursuing digitally enabled sustainable maritime corridors. This study also highlights areas for future empirical validation, particularly in relation to governance integration and cross-border alignment.","author":[{"family":"Alavi-Borazjani","given":"Seyedeh"},{"family":"Bengue","given":"Alberto"},{"family":"Chkoniya","given":"Valentina"},{"family":"Shafique","given":"Muhammad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17125537","URL":"https://doi.org/10.3390/su17125537","source":"openalex"},{"id":"oa:W4412991678","type":"article-journal","title":"A knowledge foundation and prospect review on thermal response of bridges","abstract":"Amidst the rapid global expansion of bridge infrastructure, insufficient consideration of thermal effects during the design, construction, and maintenance of bridges persists, resulting in high-cost incidents and escalating safety concerns. A comprehensive understanding of thermal responses in bridges is essential not only for enhancing the safety and reliability of construction processes but also for minimizing long-term operational losses. As of December 2024, using CiteSpace and VOSviewer, a bibliometric analysis was conducted on 2190 publications from the Web of Science, generating the first comprehensive knowledge map of bridge thermal behavior. The field has evolved through four stages from the 2000 to 2024, progressing from theoretical and empirical modeling to finite element methods and, more recently, multi-physics coupling and digital twin technologies. Major research hotspots include spatiotemporal temperature gradients, AI-driven thermal monitoring, and macro-micro thermal effects on concrete structures. A novel fluid-solid-thermal interaction (FSTI) framework combining computational fluid dynamics (CFD) wind fields with ABAQUS heat transfer modeling reveals internal thermal differentials during cantilever construction and large-volume concrete casting. Future research is expected to focus on AI-enhanced digital twins, the distribution of temperature fields under extreme climates, and probabilistic models linking thermal environments to structural damage.","author":[{"family":"Zhu","given":"Jinsong"},{"family":"Wang","given":"Ziyi"},{"family":"Zhang","given":"Yuanhao"},{"family":"Wang","given":"Yanlei"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1177/13694332251365970","URL":"https://doi.org/10.1177/13694332251365970","source":"openalex"},{"id":"oa:W4406786184","type":"manuscript","title":"Leveraging Digital Twin and Machine Learning Techniques for Anomaly Detection in Power Electronics Dominated Grid","abstract":"Modern power grids are transitioning towards power electronics-dominated grids (PEDG) due to the increasing integration of renewable energy sources and energy storage systems. This shift introduces complexities in grid operation and increases vulnerability to cyberattacks. This research explores the application of digital twin (DT) technology and machine learning (ML) techniques for anomaly detection in PEDGs. A DT can accurately track and simulate the behavior of the physical grid in real-time, providing a platform for monitoring and analyzing grid operations, with extended amount of data about dynamic power flow along the whole power system. By integrating ML algorithms, the DT can learn normal grid behavior and effectively identify anomalies that deviate from established patterns, enabling early detection of potential cyberattacks or system faults. This approach offers a comprehensive and proactive strategy for enhancing cybersecurity and ensuring the stability and reliability of PEDGs.","author":[{"family":"Idrisov","given":"Ildar"},{"family":"Okeke","given":"Divine"},{"family":"Albaseer","given":"Abdullatif"},{"family":"Abdallah","given":"Mohamed"},{"family":"Ibáñez","given":"Federico"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2501.13474","URL":"https://doi.org/10.48550/arxiv.2501.13474","source":"openalex"},{"id":"oa:W4414516182","type":"article-journal","title":"Ophthalmic drug discovery and development using artificial intelligence and digital health technologies","abstract":"Globally, drug discovery and development programs are complex, multi-decade long and prohibitively expensive. Artificial intelligence (AI) and other digital health technologies have the potential to enhance and accelerate each stage of drug discovery and development, from pre-clinical target identification to post-market repurposing, and even revolutionize the entire process. Using ophthalmology as an example, this review highlights recent AI and digital health innovations in different phases of drug discovery and development. By leveraging machine learning algorithms and vast clinical and multiomics datasets, AI can rapidly identify and validate new drug targets, optimize lead compounds, and predict pharmacokinetics, pharmacodynamics and toxicity. AI-assisted multi-modal ocular biomarkers may improve treatment monitoring and support personalized medicine. Integrating AI shortens development timelines, enhances efficiency, reduces costs, and increases the success rate of new drugs. Currently, standardized regulations for AI in ocular drug development are still lacking and urgently needed to ensure safe and equitable implementation.","author":[{"family":"Cheng","given":"Haoran"},{"family":"Wong","given":"Joy"},{"family":"Quek","given":"Chrystie"},{"family":"Goldberg","given":"Jeffrey"},{"family":"Mahajan","given":"Vinit"},{"family":"Wong","given":"Tien"},{"family":"Mehta","given":"Jodhbir"},{"family":"Ting","given":"Daniel"},{"family":"Ting","given":"Darren"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41746-025-01954-y","URL":"https://doi.org/10.1038/s41746-025-01954-y","source":"openalex"},{"id":"oa:W7124142707","type":"article-journal","title":"Integrating thermal point clouds into BIM-GIS environments: workflow proposal for multi-layer digital twins","abstract":"Introduction The integration of Thermal Point Clouds (TPCs) into professional Building Information Models (BIM) and Geographic Information System (GIS) workflows is currently hampered by a lack of established methodologies and significant format interoperability challenges. This study addresses this methodological gap by developing and testing integration processes for both BIM and GIS platforms. Methods Two proofs of concept were developed using data from a commercial scanner at the New York University Abu Dhabi (NYUAD) campus. For BIM integration, a process was designed to generate open Industry Foundation Classes (IFC) files where average surface temperatures are embedded as native properties of architectural elements. For GIS integration, thermal data was assigned as custom attributes to a manually generated 3D geometric reference model, establishing the preliminary steps for a dedicated thermal-GIS workflow. Results The methodologies were successfully validated through visualization in ArcGIS Pro and ACCA Software GeoTwin. The results demonstrate a tangible path to overcoming current format limitations, enabling the creation of multi-layer thermal digital twins. Discussion This approach makes complex thermal data more accessible to Architecture, Engineering, Construction, and Operation (AECO) professionals. By providing a structured workflow for interoperability, the study facilitates improved building management and more accurate energy analysis through the use of integrated thermal digital models.","author":[{"family":"Ramón-Constantí","given":"Amanda"},{"family":"Pascual","given":"FC"},{"family":"Soto","given":"Borja"},{"family":"Adán-Oliver","given":"Antonio"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fbuil.2025.1715347","URL":"https://doi.org/10.3389/fbuil.2025.1715347","source":"openalex"},{"id":"oa:W4412177800","type":"article-journal","title":"Impact of surface roughness and preheat temperature on fecrbmnsi coating properties prepared by the twin wire Arc spray method","abstract":"The purpose of this study is to evaluate the effects of substrate surface roughness (35 μm and 40 μm) and preheat temperature (50 °C, 100 °C, 150 °C) on the properties of the FeCrBMnSi coating layer applied to 304 stainless steels using the TWAS (Twin Wire Arc Spray) method. Surface preparation involved sandblasting and preheat treatment, followed by coating application with TWAS, and subsequent characterization using pull-off bonding, hardness, corrosion rate, Light Optical Microscope (LOM), and scanning electron microscopy (SEM) test. The current study's findings indicate that increasing preheat temperature and surface roughness consistently reduces the percentage of porosity, unmelted material, and coating layer thickness. This enhances the hardness and adhesive strength of the coating layers. The hardness of the coating layer obtained in the present study was improved by 360-439% compared to the uncoated material. The best specimen in this study was found on a substrate with a surface roughness of 40 μm and performed a preheating treatment at a temperature of 150 °C. The thickness of the coating layer for this specimen was 150.58 × 10⁻³ mm, with a porosity and unmelted materials of 7.233%, a hardness of 1114.6 HV, an adhesive strength of 20.29 MPa, and a corrosion rate of 1.0640 × 10⁻² mmpy. However, the corrosion resistance of the coated specimens remains lower than that of the uncoated 304 stainless steel.","author":[{"family":"Fitriyana","given":"Deni"},{"family":"Puspitasari","given":"Windy"},{"family":"Palanisamy","given":"Sivasubramanian"},{"family":"Muhadzdzib","given":"Mufti"},{"family":"Anis","given":"Samsudin"},{"family":"Siregar","given":"Januar"},{"family":"Cionita","given":"Tezara"},{"family":"Alagarsamy","given":"Aravindhan"},{"family":"Sarath","given":"KS"},{"family":"Alfarraj","given":"Saleh"},{"family":"Almansour","given":"Mansour"},{"family":"Ma","given":"Quanjin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-10713-8","URL":"https://doi.org/10.1038/s41598-025-10713-8","source":"openalex"},{"id":"oa:W4411812738","type":"article-journal","title":"Physical digital twins for ancient stone masonry informed of original construction techniques: the case of Sardinian nuraghi","abstract":"A short review is provided regarding modern technical tools allowing to build digital twins for modelling ancient stone masonry structures and their physical behaviour. The objective of such tools is to assess the structural safety of cultural heritage masonry structures. The present work focuses on the particular case of Sardinian nuraghi, which are ancient corbelled stone masonry structures whose typical form is a truncated cone. As a starting point we consider a careful historical analysis of the construction techniques of those nuraghi. From this analysis, we address the choice of theoretical and numerical tools apt to construct a digital twin of complex nuraghi, in addition to delineating future challenges in building digital twins capable of simulating any physical process which may be relevant to ancient buildings.","author":[{"family":"Tran","given":"Chuong"},{"family":"Barchiesi","given":"Emilio"},{"family":"Busonera","given":"Roberto"},{"family":"Yildizdag","given":"ME"},{"family":"Trivelloni","given":"Ilaria"},{"family":"Turco","given":"Emilio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5802/crmeca.308","URL":"https://doi.org/10.5802/crmeca.308","source":"openalex"},{"id":"oa:W7118181140","type":"article-journal","title":"Framework for the Development of a Process Digital Twin in Shipbuilding: A Case Study in a Robotized Minor Pre-Assembly Workstation","abstract":"This article proposes a framework for the development of process digital twins (DTs) in the shipbuilding sector, based on the ISO 23247 standard and structured around the achievement of three levels of digital maturity. The framework is demonstrated through a real pilot cell developed at the Innovation and Robotics Center of NAVANTIA—Ferrol shipyard, incorporating various cutting-edge technologies such as robotics, artificial intelligence, automated welding, computer vision, visual inspection, and autonomous vehicles for the manufacturing of minor pre-assembly components. Additionally, the study highlights the crucial role of discrete event simulation (DES) in adapting traditional methodologies to meet the requirements of Process digital twins. By addressing these challenges, the research contributes to bridging the gap in the current state of the art regarding the development and implementation of Process digital twins in the naval sector.","author":[{"family":"Sánchez-Fernández","given":"Ángel"},{"family":"Vlad-Voinea","given":"Elena"},{"family":"Pernas-Álvarez","given":"Javier"},{"family":"Crespo-Pereira","given":"Diego"},{"family":"Sañudo-Costoya","given":"Belén"},{"family":"Rodríguez","given":"Adolfo"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/jmse14010106","URL":"https://doi.org/10.3390/jmse14010106","source":"openalex"},{"id":"oa:W4411661902","type":"article-journal","title":"Digital transformation of construction enterprises and carbon emission reduction: evidence from listed companies","abstract":"As a key sector for energy consumption and carbon emissions, the construction industry’s carbon reduction measures have important strategic significance for achieving the “dual carbon” goals. Based on data from Chinese listed construction companies from 2000 to 2021, this study empirically explores the effects and pathways of digital transformation on carbon reduction. The results indicate that digital transformation can significantly reduce the carbon emission intensity of enterprises, mainly through promoting green technology innovation, improving total factor productivity, and optimizing production processes and business structures. Heterogeneity analysis shows that digital technology has a more significant emission reduction effect on highly competitive enterprises in the industry, and there are significant differences in carbon emission reduction between regions. This study provides a reference for carbon neutrality pathways in the field of architecture.","author":[{"family":"Zhao","given":"Sanglin"},{"family":"Deng","given":"Hao"},{"family":"Cao","given":"Jikang"},{"family":"Gustaf","given":"Måns"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fenvs.2025.1570182","URL":"https://doi.org/10.3389/fenvs.2025.1570182","source":"openalex"},{"id":"oa:W4409405994","type":"article-journal","title":"AI-DRIVEN OPTIMIZATION IN RENEWABLE HYDROGEN PRODUCTION: A REVIEW","abstract":"This paper presents a comprehensive systematic review of artificial intelligence (AI)-driven optimization in renewable hydrogen production, emphasizing its pivotal role over the past decade in enabling the transition toward a sustainable, low-carbon energy future. As green hydrogen gains prominence as a clean energy carrier—particularly in hard-to-decarbonize sectors such as transportation, heavy industry, and grid balancing—the demand for efficient, scalable, and economically viable production methods has intensified. AI has emerged as a transformative enabler, offering innovative solutions to technical and economic barriers across various production pathways, including electrolysis (proton exchange membrane, alkaline, and solid oxide), biomass gasification, solar-to-hydrogen, and wind-to-hydrogen systems. This study employs a structured methodology based on a systematic literature review (SLR), drawing from over 150 peer-reviewed journal articles, patents, industry reports, and conference proceedings published between 2014 and 2024. Data were sourced from academic databases, leading energy organizations, and international technology forums. The review categorizes AI techniques—machine learning, deep learning, reinforcement learning, and optimization algorithms—and examines their applications in process control, predictive maintenance, energy forecasting, material discovery, cost reduction, and hybrid renewable system integration. Emerging trends include AI-powered digital twins, AI-quantum hybrid frameworks, and intelligent supply chain management. However, the widespread deployment of AI in hydrogen systems faces challenges, such as limited access to high-quality real-time datasets, lack of standardization, regulatory hurdles, and high computational demands. The paper concludes by identifying key research gaps and outlining future directions, including the development of lightweight, explainable AI models, cross-sectoral collaborations, and supportive policy frameworks. Ultimately, this review underscores the transformative potential of AI in accelerating the commercialization, optimization, and global adoption of renewable hydrogen technologies, laying the groundwork for a robust, intelligent, and decarbonized energy infrastructure.","author":[{"family":"Bhuiyan","given":"Sharif"},{"family":"Chowdhury","given":"AKMA"},{"family":"Hossain","given":"Md"},{"family":"Mobin","given":"Saleh"},{"family":"Parvez","given":"Imtiaz"}],"issued":{"date-parts":[[2025]]},"DOI":"10.63125/06z40b13","URL":"https://doi.org/10.63125/06z40b13","source":"openalex"},{"id":"oa:W4410008516","type":"article-journal","title":"Assessing Agri-Food Digitalization: Insights from Bibliometric and Survey Analysis in Andalusia","abstract":"The agri-food sector is going through a massive digital transformation thanks to new technologies such as the Internet of Things (IoT), big data, and Artificial Intelligence (AI). Regional disparities and implementation barriers prevent widespread uptake despite significant research advances. Drawing on bibliometric and survey data collected up to the end of 2023, this study examines global research trends and stakeholder perceptions in Andalusia (Spain) to identify challenges and opportunities in agricultural digitalization. Bibliographic analysis revealed that research has moved from early remote sensing to precision agriculture, IoT, robotics and big data, and that AI has recently taken over in predictive analytics, automation, and decision-support systems. However, our survey of Andalusian stakeholders highlighted a limited adoption of cutting-edge tools such as AI, blockchain, and predictive models due to economic constraints, technical challenges, and skepticism. Participants emphasized the importance of trust-building, as well as the use of simple tools that require minimal input and provide immediate benefits. Priorities for the responders were also improving market transparency, optimizing resource use, and system interoperability. The findings show that closing the gap between research and practice requires developing digital solutions that are user-centered, simplified, and context-adapted, especially when dealing with complex technologies like AI and predictive systems. This must be supported by targeted public policies and collaborative innovation ecosystems, all essential elements to accelerate the integration of smart agricultural technologies and align scientific innovation with real-world needs.","author":[{"family":"Luque-Reyes","given":"José"},{"family":"Zidi","given":"A"},{"family":"Peña","given":"Adolfo"},{"family":"Gallardocobos","given":"Rosa"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/world6020057","URL":"https://doi.org/10.3390/world6020057","source":"openalex"},{"id":"oa:W4410457013","type":"article-journal","title":"Soil salinization in drylands: Measure, monitor, and manage","abstract":"Soil salinization poses a critical threat to global agricultural productivity, ecosystem resilience , and regional resource sustainability . Primary and secondary salinization processes—driven by natural and anthropogenic factors—are intensifying under climate change and unsustainable land-use practices, jeopardizing food security and soil health in drylands. This viewpoint article synthesizes global research on the mechanisms governing soil salinization in drylands, evaluates spatial–temporal drivers of salt accumulation, and critically assesses advances in measuring, monitoring, and managing strategies. Emerging technologies are highlighted, including accurate monitoring using multi-source data fusion , advanced modeling techniques and multiscale full-cycle soil salinity simulation through digital twin technology, and integrated approaches combining hydraulic engineering , chemistry, biology, ecology, and nature-based solutions (NBS) to address soil salinization. Salinization management is a global priority for achieving SDG2. Integrating Earth’s Critical Zone framework reveals salinization’s cascading impacts on agroecosystems, urging synergistic adoption of nature-based solutions and precision agriculture. We emphasize sensor-driven soil health monitoring, salt-tolerant crop breeding, and policy frameworks that incentivize circular resource systems. Shifting from soil amelioration to salt-tolerant germplasm innovation, supported by multidisciplinary synergies, represents a strategically crucial pathway for transforming saline-alkali soils into climate-resilient agricultural assets, thereby securing national food security.","author":[{"family":"Wang","given":"Jingzhe"},{"family":"Ding","given":"Jianli"},{"family":"Wang","given":"Yankun"},{"family":"Ge","given":"Xiangyu"},{"family":"Lizaga","given":"Iván"},{"family":"Chen","given":"Xiangyue"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.ecolind.2025.113608","URL":"https://doi.org/10.1016/j.ecolind.2025.113608","source":"openalex"},{"id":"oa:W4417500782","type":"article-journal","title":"Green digital accounting and sustainable entrepreneurship in emerging economies: impacts on financial sustainability and performance","abstract":"As entrepreneurial ventures in emerging economies face growing pressures to remain competitive while adopting environmentally responsible practices, the integration of digital technologies into sustainability-oriented accounting has become increasingly essential. In this context, Green Digital Accounting (GDA) offers a promising pathway for improving both environmental accountability and financial outcomes. This study investigates the influence of GDA on financial sustainability and business performance among entrepreneurial ventures. Employing quantitative research design and survey data, structural equation modelling (SEM) was used to assess the relationships among GDA, financial sustainability, business performance, and Digital Financial Literacy (DFL). The findings demonstrate that GDA significantly enhances financial sustainability and business performance, with financial sustainability playing a mediating role in transforming environmentally conscious accounting practices into improved organisational outcomes. Furthermore, DFL positively moderates the relationship between GDA and business performance, indicating that entrepreneurs with stronger digital financial skills are better able to leverage GDA for strategic and financial gains. The study provides valuable insights for policymakers, entrepreneurs, and firms by emphasising the need for DFL training and the adoption of environmentally integrated accounting practices to support sustainable entrepreneurial development. This research is among the first to empirically establish the strategic role of GDA in promoting sustainable entrepreneurship within emerging economies.","author":[{"family":"Alhattami","given":"Hamood"},{"family":"Mady","given":"Khalid"},{"family":"Albukhrani","given":"Mohammed"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/23311975.2025.2601944","URL":"https://doi.org/10.1080/23311975.2025.2601944","source":"openalex"},{"id":"oa:W4416454684","type":"article-journal","title":"The digital organization transformation (DOT) model: bridging digital transformation and organizational structures in construction firms","abstract":"Digital transformation is a pathway to improve productivity in the construction sector, but organizational structures still need more adaptation. There are no fully developed models at the level of factors and evidence between organizational structures and digital transformation. This paper analyzes the impact of digital transformation on organizational structures within the construction sector, utilizing a semi-structured interview and field inspection methodology to validate key organizational factors and evidence influencing this process. The research focuses on Colombia’s medium and large construction companies and aims to validate an integrated conceptual model of digital transformation and organizational structures. Results indicate that while technological tools have been adopted, the full potential of digital transformation still needs to be explored. The study highlights the factors and evidence that affect the variables of digital transformation and organizational structures. While technological tools are essential, they are unlikely to create a long-term competitive advantage. This research advances the understanding that the integrated implementation of digital transformation and organizational structures, grounded in validated factors and evidence, can drive enhanced decision-making, reduce inefficiencies, and improve productivity within the construction industry.","author":[{"family":"Gómez","given":"Cristian"},{"family":"Herrera","given":"Rodrigo"},{"family":"Tūpėnaitė","given":"Laura"},{"family":"Pellicer","given":"Eugenio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3846/jcem.2025.24318","URL":"https://doi.org/10.3846/jcem.2025.24318","source":"openalex"},{"id":"oa:W7140668043","type":"article-journal","title":"AI-Driven Digital Twin Framework for Adaptive and Real-Time Structural Health Monitoring of Offshore Marine Structures","abstract":"Reliable structural health monitoring of offshore jack-up platforms is challenging due to harsh environments, measurement uncertainty, and gradual damage over time. This study proposes an integrated framework combining digital twin technology with a machine learning–based damage identification pipeline for adaptive assessment of jack-up legs. A simplified model using a ten-element Euler–Bernoulli beam represents a 124 m leg with a fixed base. Synthetic datasets were generated by introducing random stiffness reductions in elements 3–8, covering single and multiple damage scenarios with severities of 5–20%. To improve realism, environmental variability and measurement uncertainty were incorporated through temperature variations between −10°C and +30°C together with multiple levels of simulated sensor noise. The signal processing workflow involved detrending, band-pass filtering, Fast Fourier Transform analysis, and adaptive peak detection to extract modal features, including natural frequencies and spectral entropy indicators. These features were used to train a four-layer multilayer perceptron implemented in . Model performance was evaluated using five-fold stratified cross-validation. The classifier achieved an accuracy of 41.0%, a macro-F1 score of 40.1%, and a ROC AUC of 0.8155 on the test dataset, indicating reliable discrimination between healthy and damaged structural states despite environmental variability and measurement noise. In parallel, an adaptive digital twin updating procedure was implemented to refine the numerical model using modal frequency discrepancies. This updating process reduced the root mean square error of frequency prediction from 0.0596 Hz to 0.0554 Hz, corresponding to a 6.98% improvement in predictive consistency between the numerical model and the simulated structural response. The results demonstrate that coupling machine learning based damage classification with digital twin model updating provides a practical pathway toward adaptive monitoring of offshore structures.","author":[{"family":"Riffat","given":"James"},{"family":"Nazari","given":"Kourosh"},{"family":"Samaei","given":"Seyed"}],"issued":{"date-parts":[[2026]]},"DOI":"10.65582/aifsc.2026.006","URL":"https://doi.org/10.65582/aifsc.2026.006","source":"openalex"},{"id":"oa:W4410069105","type":"article-journal","title":"Digital Transformation in the Shipping Industry: A Network-Based Bibliometric Analysis","abstract":"This paper presents a network-based bibliometric analysis of digital transformation in the shipping industry, a sector undergoing rapid change due to advancements in automation, artificial intelligence, blockchain, and Internet of Things. The study synthesizes existing knowledge to identify trends, challenges, and opportunities for industry stakeholders and researchers. Unlike previous literature reviews, this work adopts a graph theory approach applied to a large dataset of scientific publications, without predefined technological or industrial sub-domains. Data were collected from EBSCO, ProQuest, and IEEE eXplore, then refined using OpenAlex to comprise 2293 scientific publications. The analysis includes descriptive statistics, co-authorship network analysis, co-citation network analysis, and thematic analysis. The findings reveal a significant increase in publications since 2005, with exponential growth after 2015. They also suggest a potential inflection point after 2024. A small percentage of authors and institutions account for a disproportionate share of publications, suggesting a skewed distribution of research efforts and encouraging funding agencies to broaden maritime research worldwide. The co-authorship network exhibits a heavy-tail distribution and interconnected communities, indicating extensive national and international collaborations. The co-citation analysis identifies key research areas such as fuel consumption optimization, safety and risk management, and smart port development. Thematic analysis highlights the growing importance of artificial intelligence and cybersecurity.","author":[{"family":"Ferrarini","given":"Luca"},{"family":"Filippopoulos","given":"Ioannis"},{"family":"Lajic","given":"Zoran"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/jmse13050894","URL":"https://doi.org/10.3390/jmse13050894","source":"openalex"},{"id":"oa:W4413941245","type":"article-journal","title":"The Impact of Digital Marketing Capability on Firm Performance: Empirical Evidence from Chinese Listed Manufacturing Firms","abstract":"The rapid expansion of e-commerce has pushed firms to adopt more sophisticated digital marketing strategies to reach, engage, and retain consumers. Research has shown that digital marketing significantly enhances firm performance by enhancing marketing-related capabilities, yet overlooks its role in driving transformation across other business functions. Grounded in resource orchestration theory, this study examines how digital marketing resources and capabilities support broader business transformation and comprehensively improve firm performance. Drawing on empirical data from Chinese A-share listed manufacturing firms from 2010 to 2023, this study demonstrates that there is a significant positive relationship between digital marketing capability and firm performance. Notably, this relationship is mediated by production capability and R&D capability. Moreover, the effect is more pronounced in firms operating in highly marketized regions, within competitive industries, and among digitally advanced firms. This study contributes to the digital marketing literature by developing a novel framework for measuring digital marketing capability, and uncovering the mechanisms through which it influences firm performance. In addition, this study contributes to the digitalization literature in the manufacturing sector by demonstrating the strategic role of digital marketing in driving value creation. Implications for digital marketing in manufacturing industry are discussed.","author":[{"family":"Liang","given":"Zhihao"},{"family":"Du","given":"Jinming"},{"family":"Hua","given":"Ying"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/jtaer20030236","URL":"https://doi.org/10.3390/jtaer20030236","source":"openalex"},{"id":"oa:W4415493591","type":"article-journal","title":"Human Neuromuscular System Identification Using Functional Electrical Stimulation for the Development of a Digital Twin of the Locomotor System","abstract":"Introduction Our research group has been developing and applying a human digital twin of the locomotor system and has proposed a simple method for estimating the dynamics of the neuromusculoskeletal system using functional electrical stimulation based on the equilibrium point hypothesis, which focuses on coordination between extensor and flexor muscles. This method defines two parameters: the electrical agonist-antagonist ratio (rE) and sum (sE), representing the ratio and sum of the stimulation intensities applied to the extensor and flexor muscles, respectively. Our previous study showed that the relationship between rE and the evoked force, i.e., the neuromuscular system (NMS), can be approximated by a second-order system with dead time under isometric conditions, and that the NMS parameters vary with sE. However, this variation has not yet been modeled. This study investigates how sE influences the parameters of isometric elbow joint motion with one degree of freedom. Methods Under isometric contraction, we conducted experiments to estimate the parameters of a second-order system, such as proportional gain (Kp), natural frequency (ωn), and damping ratio (ζ), at 15 different sE levels. Data were collected from 10 participants (nine males and one female; mean age: 22.7 ± 0.8 years; all right-handed). For group-averaged and individual data, we fitted models describing the relationship between sE and each parameter. Model performance was evaluated using the corrected Akaike information criterion (AICc) across linear, quadratic, and exponential models. Results For Kp, the quadratic model with a concave shape best fit the group mean data as indicated by the AICc values (linear: -2.78, quadratic: -15.8, and exponential: -14.9). For ωn and ζ, the convex quadratic models best described the group mean (for ωn, linear: 3.30, quadratic: -2.74, and exponential: 3.46; for ζ, linear: -49.8, quadratic: -53.5, and exponential: -49.8). However, at the individual level, some participants exhibited monotonic trends. Discussion For Kp, although the quadratic model provided the best fit for the group mean, the exponential model showed comparable AICc values. Moreover, when summing AICc values across individuals, the exponential model yielded the lowest AICc sum, suggesting that the relationship between Kp and sE can be reasonably approximated by an exponential function. For ωn and ζ, the overall trend with sE was best described by a convex quadratic function. However, due to interindividual differences in muscle properties, some participants did not exhibit a turning point within the tested sE range, resulting in monotonic trends. These convex patterns may be explained by the influence of the refractory period of skeletal muscle fibers. Conclusions The clinical significance of the model obtained in this study lies in its potential to contribute to the development of the human digital twin of the locomotor system. By incorporating dynamics in which each parameter changes in real time with sE​, it may become possible to estimate human movement from electromyographic (EMG) signals. However, because the stimulation frequency used in this study was higher than the EMG frequency, the influence of the refractory period may have been amplified. Future studies should investigate whether similar parameter trends are observed at stimulation frequencies closer to those of EMG signals.","author":[{"family":"Hori","given":"Soichiro"},{"family":"Matsui","given":"Kazuhiro"},{"family":"Atsuumi","given":"Keita"},{"family":"Mori","given":"Yoshiki"},{"family":"Hirai","given":"Hiroaki"},{"family":"Nishikawa","given":"Atsushi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.7759/cureus.95270","URL":"https://doi.org/10.7759/cureus.95270","source":"openalex"},{"id":"oa:W7169556595","type":"article-journal","title":"Agentic AI-enhanced digital twins for Smart City civil infrastructure: A secure, autonomous and auditable management framework","abstract":"Smart city implementation increasingly relies on sensing and analytics; however, a persistent operational gap remains between anomaly detection and safe, timely, and accountable intervention in civil infrastructure systems. This paper proposes an Agentic AI-supported Digital Twin framework for smart city civil infrastructure management, where monitoring and action are linked and auditability is maintained. The Digital Twin continuously updates asset and network models of bridges, roads, and water infrastructure using multi-stream telemetry, incorporating state estimation, predictive maintenance, and what-if simulation services. At the orchestration layer, an agent-based Perception-Conceptualization-Action workflow implemented with LangChain and LangGraph enables cross-domain reasoning and coordinated mitigation planning through controlled API calls to municipal data. A permissioned blockchain cryptographically binds observations, approvals, and executed interventions, ensuring provenance, governance, and tamper evidence. To evaluate the framework, 18,000 incident simulations were conducted across five architectural configurations and three scenario complexity levels over 30 independent runs. This simulation study characterises framework behaviour under controlled stochastic conditions and does not constitute real-world operational validation. Ablation analysis isolates each component's contribution, demonstrating that latency and mitigation gains are primarily attributable to multi-agent orchestration, while the blockchain layer drives decision auditability. Across all configurations, the fully agentic system substantially outperforms the rule-based baseline: mean detection latency of 3,197 s vs. 39,374 s, mitigation success rate of 66.2% vs. 45.5%, blockchain-anchored decision justification of 71.8% vs. 0%, and operator workload reduction of 91.7% vs. 0%. These results demonstrate that combining simulation-enabled digital twins with governance-aware agentic orchestration measurably improves response efficiency, recommendation quality, and action accountability within the bounds of a synthetic evaluation environment.","author":[{"family":"Syed","given":"Toqeer"},{"family":"Akarma","given":"Ali"},{"family":"Alatify","given":"Ali"},{"family":"Naqash","given":"Muhammad"},{"family":"Alqurashi","given":"Abdulaziz"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1371/journal.pone.0353610","URL":"https://doi.org/10.1371/journal.pone.0353610","source":"europepmc"},{"id":"oa:W7164368199","type":"article-journal","title":"Computational tools for personalizing treatment of acute respiratory failure, from machine learning to digital twins: a narrative review","abstract":"Patient-specific computational tools hold great promise for the development of more personalized treatment strategies for acute respiratory failure. Such tools span a continuum from data-driven predictors, to patient-specific mechanistic models, and ultimately to fully realized digital twins with continuous bidirectional model-patient interactions. Data-driven prediction models apply machine learning to large-scale patient datasets to develop tools that can help clinicians identify patients who are likely, or unlikely, to benefit from a particular course of treatment. By incorporating detailed computational representations of disease pathophysiology, patient-specific mechanistic models can provide insights into the effects of existing or novel treatment strategies, support patient stratification and treatment personalization, and enable the design of in silico clinical trials of new interventions. Finally, fully realized dynamic digital twins of patients could provide real-time decision support and 'simulate-before-treat' capabilities at the bedside, helping clinicians optimize treatment as the patient's disease state evolves. This narrative review provides an overview of recent research applying these approaches in the context of acute respiratory failure, encompassing both respiratory and ventilatory support across neonatal, paediatric and adult populations, and pre-hospital, ward and intensive care environments.","author":[{"family":"Saffaran","given":"Sina"},{"family":"Yu","given":"Hang"},{"family":"Shamohammadi","given":"Hossein"},{"family":"Weaver","given":"Liam"},{"family":"Joy","given":"William"},{"family":"Ketteridge","given":"Lauren"},{"family":"Albanese","given":"Beatrice"},{"family":"Regulski","given":"Lukasz"},{"family":"Becker","given":"Simon"},{"family":"Sharkey","given":"Don"},{"family":"Kwok","given":"T’ng"},{"family":"Hardman","given":"Jonathan"},{"family":"Yehya","given":"N"},{"family":"Mauri","given":"T"},{"family":"Scott","given":"Timothy"},{"family":"Tonelli","given":"Roberto"},{"family":"Clini","given":"Enrico"},{"family":"Laffey","given":"JG"},{"family":"Camporota","given":"Luigi"},{"family":"Bates","given":"Declan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1186/s13054-026-06079-6","URL":"https://doi.org/10.1186/s13054-026-06079-6","source":"openalex"},{"id":"oa:W4417490646","type":"article-journal","title":"Smart Digital Twin for Energy Efficiency in Buildings Using BIM, IoT and AI: Case Study of Villa in Morocco","abstract":"This work outlines the creation of an intelligent digital twin for residential Villa that integrates Building Information Modeling (BIM), the Internet of Things (IoT), and Artificial Intelligence (AI) to improve building energy efficiency. A comprehensive 3D model was developed using Revit 2024.3, allowing for solar and energy simulations through Insight and DesignBuilder. Real-time environmental data,such as temperature, humidity, lighting, and occupancy, were gathered via IoT sensors and analyzed using machine learning algorithms to forecast energy consumption patterns and identify anomalies. Based on these insights, automated control strategies for HVAC and lighting systems were implemented to enhance comfort and reduce energy waste. The proposed framework offers a dynamic, scalable, and regulation-compliant solution for smart energy management in Moroccan buildings. Overall, the developed digital twin showcases the practical potential of integrating BIM, IoT, and AI to achieve sustainable and autonomous building operations.","author":[{"family":"Saaidi","given":"Fatima"},{"family":"Boulanouar","given":"Abderrahim"},{"family":"Géraud","given":"Yves"},{"family":"Rahmouni","given":"Abdelaali"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1051/e3sconf/202568000144","URL":"https://doi.org/10.1051/e3sconf/202568000144","source":"openalex"},{"id":"oa:W7170154985","type":"article-journal","title":"High-definition shoreline digital twin from UAV-LiDAR-MBES fusion and XR-optimised 3D modelling","abstract":"Understanding and monitoring the land-water interface is critical for navigation safety, shoreline management, and environmental protection in inland waters, yet its consistent digital representation remains challenging because terrestrial and submerged domains are commonly surveyed and analysed separately. This study presents an integrated workflow for constructing a high-definition shoreline geospatial twin from multi-sensor data within a unified RTK-referenced geodetic framework. Centimetre-scale topographic information from UAV photogrammetry and airborne LiDAR is fused with multibeam bathymetry to generate a spatially coherent 3D model of the land-water continuum. The workflow combines field calibration, harmonised horizontal and vertical referencing, topology-preserving surface reconstruction, mesh optimisation, and export to interoperable 3D formats for real-time GIS and XR use. A case study from the Masurian Lake District (Poland) demonstrates sub-decimetre geometric coherence across terrestrial and submerged zones. The study moves beyond static 3D shoreline representation toward an immersive and updateable geospatial twin for analytical exploration and navigation-oriented decision support. A virtual reality module supports exploration, planning, and training, while an augmented reality module enables in situ visualisation of shoreline and bathymetric features for hazard awareness. The framework provides a reproducible basis for inland-water navigation, environmental monitoring, and digital-earth applications.","author":[{"family":"Templin","given":"Tomasz"},{"family":"Popielarczyk","given":"Dariusz"},{"family":"Leszczyńska","given":"Julia"},{"family":"Kozakiewicz","given":"Tomasz"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/17538947.2026.2696646","URL":"https://doi.org/10.1080/17538947.2026.2696646","source":"openalex"},{"id":"oa:W4413224587","type":"article-journal","title":"AI for Humanity: Battling Pandemics with Digital Intelligence","abstract":"AI for Humanity: Battling Pandemics with Digital Intelligence embarks on a journey across the timeline of some of history's most devastating outbreaks, reformulated by the transformational power of artificial intelligence. Each calamitous event, from the Black Death to a near digital awakening during SARS, from insights via social media frameworks like H1N1 to the stress test of COVID-19, inculcates historical lessons with the technology's current opportunity. Coming across zoonotic threats and antimicrobial resistance, the book shows how having AI has practically become humankind's greatest partner in attempting to predict, check, and most importantly, stop future pandemics even before they begin.","author":[{"family":"Gehlot","given":"Anita"},{"family":"Singh","given":"Rajesh"},{"family":"Sinha","given":"Aashna"},{"family":"Parveen","given":"Fraiz"}],"issued":{"date-parts":[[2025]]},"DOI":"10.55938/wlp.v2i1.197","URL":"https://doi.org/10.55938/wlp.v2i1.197","source":"openalex"},{"id":"oa:W4409598066","type":"article-journal","title":"Integration of Pavement Finite Element simulation with Digital Twin: Current Practices, Emerging Trends, and Future Enablers","abstract":"In the transition towards Construction 5.0, intelligent systems, such as predictive Digital Twins (DTs), have emerged as a critical solution in infrastructure assets management. This is by leveraging advanced simulations and analytical methods for accurate asset condition prediction. However, while simulations are essential for enabling predictive DTs, existing literature often overlooks the role of pavement simulation within developed DTs. This paper systematically leverages the literature on Finite Element (FE) modelling for pavement performance prediction to assess the current state and practice of simulations, identifies trends in simulation integration, proposes advancements to enhance the incorporation of FE models within DTs, and proposes an architecture for the integration. Finally, the study concludes with a call for future research directions to address existing gaps, aiming to advance DTs for intelligent and sustainable pavement management.","author":[{"family":"Oditallah","given":"Mohammad"},{"family":"Alam","given":"Morshed"},{"family":"Ekambaram","given":"Palaneeswara"},{"family":"Ranjha","given":"Sagheer"}],"issued":{"date-parts":[[2025]]},"DOI":"10.36680/j.itcon.2025.023","URL":"https://doi.org/10.36680/j.itcon.2025.023","source":"openalex"},{"id":"oa:W7168123239","type":"article-journal","title":"Modeling Drone-Assisted Subway Fire Evacuation Based on Digital Twin and Human–Fire-Station Interaction","abstract":"Subway fire evacuations face severe challenges due to high passenger density, spatial unfamiliarity, and toxic smoke, which often render traditional static signage ineffective and cause chaotic congestion. To address this, we propose a drone-assisted evacuation strategy evaluated via a high-fidelity digital twin platform coupling PyroSim and AnyLogic. The developed human–fire-station interaction model integrates CO-induced physiological degradation and a binary logit model to capture bounded-rational decision-making and herding behaviors. Using the Suzhou Olympic Sports Centre Station as a case study, simulations reveal that spatial familiarity’s impact on spontaneous evacuation exhibits strict diminishing marginal returns. Under a realistic low-familiarity scenario (25%), unguided evacuation requires 312 s with severe bottlenecking. Drone guidance actively intercepts this chaos, slashing clearance time to 237 s—a 24.0% improvement in efficiency. Furthermore, aerial directives successfully transform panicked clusters into structured platoons, mitigating stampede risks and ensuring the safe egress of vulnerable demographics. This study provides robust quantitative evidence for integrating unmanned aerial systems into smart transit emergency management, serving as a high-fidelity virtual testbed for future evacuation drills.","author":[{"family":"Qiang","given":"Rui"},{"family":"Yuan","given":"Yinnan"},{"family":"Lu","given":"Weike"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/electronics15143070","URL":"https://doi.org/10.3390/electronics15143070","source":"openalex"},{"id":"oa:W7143488417","type":"article-journal","title":"Research on wind deflection risk early warning method of transmission line driven by digital twin and data fusion","abstract":"To improve the complex dynamic transmission lines monsoon weather environment risk early warning and refinement management capability, this paper proposes a digital twin and multi-source data fusion-driven transmission lines monsoon risk early warning method. First, a multi-source heterogeneous data system is constructed, which integrates meteorological, geographic, line ontology, and real-time monitoring data. Based on high-precision three-dimensional modelling and physical attribute binding technology, the digital twin of transmission lines is established and the bidirectional dynamic mapping between physical entity and virtual model at the geometry, attribute and state levels is realized. Beyond the one-way mapping from physical entity to virtual model, a bidirectional dynamic feedback mechanism is designed: real-time monitoring data continuously update the twin state, while the twin's simulation results (e.g., predicted wind-induced responses) are fed back to guide online sensor calibration and inspection strategies, thereby closing the loop between physical and digital spaces at geometry, attribute, and state levels. Next, the temporal and spatial heterogeneity of multi-source data, which are designed based on the deep learning framework of multimodal data fusion model, realize the weather forecast, the geographical environment, and collaborative analysis and dynamic structural response line deduction. Further, by integrating the dynamic mechanical response of the line with its electrical insulation characteristics, the critical state under monsoon conditions and the corresponding dynamic safety thresholds are defined. A real-time probabilistic risk assessment model is then established, enabling a paradigm shift from static threshold-based early warning to dynamic, evolution-based risk early warning. Finally, selecting typical typhoon influence area on the southeastern coast of China's 220 kv transmission line, the presented method is introduced in detail, from the front-end data integration, twin model driven, fusion algorithm operation to the early warning information to generate the whole process of application, and through comparing analysis of early warning effectiveness, more groups of data form. The results show that the warning accuracy of the proposed method is 92.3% and the average effective warning advance time is 98 minutes. Compared with the traditional warning method based on wind speed at meteorological stations, the spatial accuracy and time resolution of the proposed method are significantly improved, which provides more accurate and reliable decision support for the disaster prevention and mitigation and intelligent operation and maintenance of the power grid under extreme weather.","author":[{"family":"Zheng","given":"Wulue"},{"family":"Chen","given":"Qingpeng"},{"family":"Zhang","given":"Xin"},{"family":"Yuan","given":"Wenjun"},{"family":"Chen","given":"Hao"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3934/environsci.2026012","URL":"https://doi.org/10.3934/environsci.2026012","source":"openalex"},{"id":"oa:W4413993478","type":"article-journal","title":"Sustainability of AI-Assisted Mental Health Intervention: A Review of the Literature from 2020–2025","abstract":"This systematic review examines the role of artificial intelligence (AI) in the development of sustainable mental health interventions through a comprehensive analysis of literature published between 2020 and 2025. In accordance with the PRISMA guidelines, 62 studies were selected from 1652 initially identified records across four major databases. The results revealed four dimensions critical for sustainability: ethical considerations (privacy, informed consent, bias, and human oversight), personalization approaches (federated learning and AI-enhanced therapeutic interventions), risk mitigation strategies (data security, algorithmic bias, and clinical efficacy), and implementation challenges (technical infrastructure, cultural adaptation, and resource allocation). The findings demonstrate that long-term sustainability depends on ethics-driven approaches, resource-efficient techniques such as federated learning, culturally adaptive systems, and appropriate human-AI integration. The study concludes that sustainable mental health AI requires addressing both technical efficacy and ethical integrity while ensuring equitable access across diverse contexts. Future research should focus on longitudinal studies examining the long-term effectiveness and cultural adaptability of AI interventions in resource-limited settings.","author":[{"family":"Carrasco","given":"Danicsa"},{"family":"Alcántara","given":"María"},{"family":"Várgas","given":"Carmen"},{"family":"Espino","given":"Briseidy"},{"family":"Valdera","given":"Luis"},{"family":"Cabrera","given":"Cindy"},{"family":"Carrasco","given":"Madeleine"},{"family":"Valdera","given":"Anny"},{"family":"Córdova","given":"Luz"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/ijerph22091382","URL":"https://doi.org/10.3390/ijerph22091382","source":"openalex"},{"id":"oa:W4413035000","type":"article-journal","title":"Digital traceability in horticulture: a systematic review of edge-cloud-blockchain-terminal (ECBT) integration with IoT and AI technologies","abstract":"Global horticultural supply chains face escalating vulnerabilities from pathogenic outbreaks, climate disruptions, and regulatory demands. This systematic mini-review examines the Edge-Cloud-Blockchain-Terminal (ECBT) framework—an integrated architecture positioning blockchain as the trust backbone connecting distributed computing, edge intelligence, and user terminals—for comprehensive traceability. Following PRISMA guidelines, we analyzed 40 high-quality studies selected from 156 peer-reviewed articles retrieved from Web of Science, Scopus, and IEEE Xplore databases (2022–2025) using combined technology (“IoT” OR “blockchain” OR “AI” OR “edge computing”) and application (“traceability” OR “supply chain”) search terms. Technology coverage analysis revealed fragmented adoption: IoT dominates (45%, n = 18), followed by blockchain (32%, n = 13) and AI/ML (23%, n = 9), with only 3% achieving full ECBT integration despite demonstrated benefits. Blockchain implementations achieve 94.2% storage optimization through selective anchoring while maintaining cryptographic verification, with latency reduced by 73% through the CRPBFT consensus mechanism. While edge computing achieves a 65% reduction in latency, its integration with blockchain’s global state management presents persistent architectural challenges. Critical barriers persist: technical interoperability (23% metadata loss in cross-chain transitions), economic exclusion (42% of smallholder annual income for deployment), and scalability constraints (processing 47 million daily data points). The review identifies blockchain’s triple role as trust orchestrator, semantic preservator, and incentive aligner as key to overcoming the integration paradox. Future research should focus on agricultural-specific consensus, semantic interoperability, and inclusive deployment models to resolve the integration paradox.","author":[{"family":"Huang","given":"Yan"},{"family":"Li","given":"Xin"},{"family":"Xu","given":"Lei"},{"family":"Ma","given":"Yongqiang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fbloc.2025.1636627","URL":"https://doi.org/10.3389/fbloc.2025.1636627","source":"openalex"},{"id":"oa:W4415684350","type":"article-journal","title":"The Impact of Focal Firm Digitalization on Supply Chain Resilience: A Supply Chain Collaboration Perspective","abstract":"In the context of a complex and volatile domestic and global environment, Chinese enterprises face frequent risks of supply chain disruption that seriously hinder their operations. The rise of the digital economy offers new opportunities to strengthen supply chain resilience. Building on supply chain collaboration and value co-creation theories, this study conceptualizes supply chain collaboration through three dimensions, namely information collaboration, governance collaboration, and innovation collaboration, and explores their role in enhancing resilience. Using panel data of Chinese A-share listed firms from 2011 to 2023, this study investigates the impact of focal firm digitalization on supply chain resilience and its underlying mechanisms. The results indicate that focal firm digitalization generates significant backward spillover effects, enhancing the resilience of its upstream suppliers. Although its positive influence on supply chain stability (measured by supply chain demand and supply fluctuations) is not statistically significant, it substantially enhances recovery (measured by supply chain efficiency) and adaptability (measured by supplier innovation). Mechanism analysis further reveals that digitalization strengthens supply chain collaboration through information, governance, and innovation channels, thereby reinforcing resilience. Moreover, the positive effects are heterogeneous, varying with industry competition intensity, the closeness of upstream–downstream relationships, and suppliers’ regional resource endowments. These findings highlight the need to design digitalization strategies centered on focal firm leadership and upstream–downstream collaboration, thereby advancing both resilience improvement and collaborative mechanism development through differentiated and targeted approaches.","author":[{"family":"Duan","given":"Jia"},{"family":"Hu","given":"Wen"},{"family":"Zhang","given":"Zhigang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17219505","URL":"https://doi.org/10.3390/su17219505","source":"openalex"},{"id":"oa:W4413796002","type":"article-journal","title":"Digital Heritage from a Socio-Technical Systems Perspective: Integrated Case Analysis and Framework Development","abstract":"Digital heritage (DH) research serves as a bridge between technological applications and broader cultural, social, and policy issues. A comprehensive understanding of DH requires the integration of multiple fields. To address this, this work applies a socio-technical systems (STS) perspective to DH as a strategy to bridge the technological and social aspects. It first examines how DH functions as STSs, analyses the dynamic interactions between technological and social subsystems, and explains the need to achieve joint optimisation to tackle the complexity of DH research. Second, a comparative analysis of six STS models is conducted, using the Venice Time Machine project as a representative case, to explore both the potential and limitations of STSs as a theoretical framework for DH. Third, STS theory is applied to emphasise that the approach needs to incorporate cultural expression, technological feasibility, diverse stakeholder interests, and long-term adaptability in order to address the complexity of current DH challenges. Finally, an STS-DH framework is proposed to guide the design, implementation and evaluation of DH projects using the elements identified through the present analysis. This work extends STS theory applications to cultural heritage digitisation; provides stakeholders with new practical tools; recognises the lack of empirical research in this field and highlights the need for further research.","author":[{"family":"Lu","given":"Junwen"},{"family":"García-Badell","given":"Guillermo"},{"family":"Rodriguez","given":"Joan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/heritage8090348","URL":"https://doi.org/10.3390/heritage8090348","source":"openalex"},{"id":"oa:W4412880429","type":"article-journal","title":"Digital Twin-Driven Virtual Cinematography: Statistical Analysis of Camera Techniques for Enhanced Narrative Engagement in Drama Production","abstract":"Camera techniques and angles are essential for shaping the visual narrative of digital media productions, especially in dramatic films. The traditional methods for selecting the best camera angles often depend on subjective decisions, leading to expensive and time-consuming trial-and-error processes. This study presents a novel approach using the Digital Twin (DT) technology to simulate and evaluate the effects of various camera techniques and angles in a virtual production environment. A two-way Analysis of Variance (ANOVA) was employed to investigate the impact of nine imaging techniques and three camera angles (X, Y, Z) on the cinematic quality. The results indicate that the Y-axis angle has a significant influence on the visual and emotional impact of dramatic scenes, with an F-value of 36,305.71 and a p-value of 0.000, indicating a strong relationship. Additionally, the interaction between the camera distance and angle demonstrated a significant effect, with an F-value: 198.07 and p-value: 0.000. By leveraging the DT simulations, filmmakers can reduce the production costs by up to 30% and improve the decision-making efficiency during pre-production. This research establishes a groundbreaking framework for integrating data-driven virtual production into filmmaking, providing a systematic and scalable method to enhance cinematic storytelling.","author":[{"family":"Ramadhani","given":"Nugrahardi"},{"family":"Prasetyo","given":"Didit"},{"family":"Hariadi","given":"Mochamad"},{"family":"Wardhani","given":"Anindya"},{"family":"Mutiaz","given":"Intan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48084/etasr.11745","URL":"https://doi.org/10.48084/etasr.11745","source":"openalex"},{"id":"oa:W7116891329","type":"article-journal","title":"Mapping digital transformation and social impact in Italian healthcare: a holistic evaluation of organizational digital maturity","abstract":"CONTEXT: Digital transformation (DT) is a key driver of innovation in the healthcare sector, as it improves efficiency, quality, and patient outcomes. In the Italian public healthcare system, assessing digital organizational maturity is essential to evaluate the readiness and ability to effectively implement DT, particularly in chronic care management. METHODS: This study used a multi-case approach to assess the digital organizational maturity of four Italian healthcare cases: \"Silver Age - Multiple Screening\", \"Telemedicine for Chronic Disease Care\", \"Diabetes Network\" and \"Digital Healthcare Ecosystem\". The assessment applied a holistic maturity model comprising four sequential stages: awareness, readiness, planning, and execution. Data collection included direct observations, semi-structured interviews with organizational stakeholders, and analysis of institutional documents. RESULTS: The analysis revealed different levels of digital maturity across the cases. Notable strengths were observed in strategic alignment and innovation, particularly in the \"Digital Healthcare Ecosystem\". However, challenges remain in terms of scalability, interoperability, and comprehensive data management. Cases such as \"Silver Age - Multiple Screening\" identified critical gaps in stakeholder alignment and process integration, while \"Telemedicine for Chronic Disease Care\" demonstrated significant results in reducing hospital admissions but encountered barriers to adoption by end users. CONCLUSIONS: The findings highlight the critical role of structured digital maturity assessments in guiding healthcare organizations on their transformation journey. Addressing integration, workforce training, and strategic alignment is essential to achieving scalable and sustainable DT, especially in contexts involving chronic care management. This study underscores the value of a comprehensive maturity model for identifying gaps and providing targeted improvement strategies.","author":[{"family":"Galdiero","given":"Caterina"},{"family":"Marrapodi","given":"Rosario"},{"family":"Mele","given":"Stefania"},{"family":"Scaletti","given":"Alessandro"},{"family":"Martinez","given":"Marcello"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1186/s12913-025-13473-3","URL":"https://doi.org/10.1186/s12913-025-13473-3","source":"openalex"},{"id":"oa:W7122746695","type":"article-journal","title":"From Automation to Autonomy: A Digital Twin Framework for Transparent Agent and Human Collaboration in Industrial Multi-Agent Systems","abstract":"With the advancement of digitization in the era of Industry 4.0 (I4.0), highly automated, semi-autonomous, and fully autonomous systems are emerging. Within this context, multi-agent systems (MAS) offer a promising approach for automating tasks and processes based on autonomous agents that work together in an overall system to increase the degree of system autonomy stepwise in a modular and flexible way. A critical research challenge is determining how these agents can collaboratively engage with both other agents and human operators to facilitate the gradual transition from automated to fully autonomous industrial systems. To close transparency and connectivity gaps, this study contributes with a framework for the collaboration of agents and humans in increasingly autonomous MAS based on a Digital Twin (DT). The framework specifies a standards-based data model for MAS representation and proposes to introduce a DT infrastructure as a service layer for system coordination, supervision, and interaction. To demonstrate the feasibility and assess the quality of the framework, it is implemented and evaluated in a case study in a real-world industrial scenario. Although additional long-term evaluations across different contexts are needed, the assessment of functional completeness and selected quality attributes show that the proposed framework provides a solid technical foundation that facilitates a transparent and seamless collaboration between agents and humans within increasingly autonomous industrial MAS.","author":[{"family":"Miadowicz","given":"Inga"},{"family":"Kuhl","given":"Mathias"},{"family":"Quinto","given":"Daniel"},{"family":"Pitz-Paal","given":"Robert"},{"family":"Felderer","given":"Michael"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/systems14010076","URL":"https://doi.org/10.3390/systems14010076","source":"openalex"},{"id":"oa:W4413331093","type":"article-journal","title":"A Credibility-Based Self-Evolution Algorithm for Equipment Digital Twins Based on Multi-Layer Deep Koopman Operator","abstract":"In the context of Industry 4.0 and intelligent manufacturing, the scale and complexity of complex equipment systems are continuously increasing, making effective high-precision modeling, simulation, and prediction in the engineering field significant challenges. Digital twin technology, by establishing real-time connections between virtual models and physical systems, provides strong support for the real-time monitoring, optimization, and prediction of complex systems. However, traditional digital twin models face significant limitations when synchronizing with high-dimensional nonlinear and non-stationary dynamical systems due to the latter’s dynamic characteristics. To address this issue, we propose a multi-layer deep Koopman operator-based (MDK) credibility-based self-evolution algorithm for equipment digital twins. By constructing multiple time-scale embedding layers and combining deep neural networks for observability function learning, the algorithm effectively captures the dynamic features of complex nonlinear systems at different time scales, enabling their global dynamic modeling and precise analysis. Furthermore, to enhance the model’s adaptability, a trustworthiness-based evolution-triggering mechanism and an adaptive model fine-tuning algorithm are designed. When the digital twin model’s trustworthiness assessment indicates a decline in prediction accuracy, the evolution mechanism is automatically triggered to optimize and update the model with the fine-tuning algorithm to maintain its stability and robustness during dynamic evolution. The experimental results demonstrate that the proposed method achieves significant improvements in prediction accuracy within unmanned aerial vehicle (UAV) systems, showcasing its broad application potential in intelligent manufacturing and complex equipment systems.","author":[{"family":"Cheng","given":"Hongbo"},{"family":"Li","given":"Zhang"},{"family":"Wang","given":"Kunyu"},{"family":"Lu","given":"Han"},{"family":"Guo","given":"Yihan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15169082","URL":"https://doi.org/10.3390/app15169082","source":"openalex"},{"id":"oa:W4414091483","type":"article-journal","title":"Digital Transformation Drives Regional Innovation Ecosystem Resilience: A Study Based on the Dynamic QCA Method","abstract":"In an era marked by volatility, uncertainty, complexity, and ambiguity, constructing resilient regional innovation ecosystems is identified as a critical strategic imperative for achieving high-quality development and advancing sustainable development goals. Drawing on the Technology–Organization–Environment (TOE) integrative framework, this study examines six antecedent conditions of ecosystem resilience from the perspective of digital transformation: digital infrastructure, digital innovation capacity, digital human capital, digital government governance, digital attention, and digital finance. A sample of 48 prefecture-level cities from the Beijing–Tianjin–Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations in China between 2018 and 2022 is selected. Through the application of dynamic Qualitative Comparative Analysis (QCA), the study explores the multiple configurations across temporal and spatial dimensions through which technological, organizational, and environmental factors contribute to enhancing regional innovation ecosystem resilience. The results indicate that ecosystem resilience is jointly driven by multiple interacting factors, and no single condition is found to be necessary. Four distinct causal pathways are identified as sufficient to enhance resilience: (1) a triadic synergy of technology, organization, and environment; (2) a technology-driven, talent-supported configuration; (3) a technology-driven, government-supported configuration; and (4) a dual technology–environment-driven model. While none of the configurations exhibit consistent temporal effects, some are influenced by unobserved factors in specific years. Moreover, cities do not converge on a single dominant configuration when achieving high levels of ecosystem resilience.","author":[{"family":"Wang","given":"Yunan"},{"family":"Xiao","given":"Jing"},{"family":"Xu","given":"Zhihong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17188148","URL":"https://doi.org/10.3390/su17188148","source":"openalex"},{"id":"oa:W7203628919","type":"article-journal","title":"Digital Twin-Based Imitation Learning for Human-Like and Efficient Driving of Mobile Robots in Virtual Factory Environments","abstract":"Abstract In smart manufacturing and flexible production systems, autonomous mobile robots must complete logistics tasks efficiently while exhibiting driving behaviors that human operators can interpret and accept. This study proposes a simulation-based digital-twin imitation learning framework for learning human-like driving patterns in virtual factory environments. The proposed system is built on the proximal policy optimization algorithm and integrates generative adversarial imitation learning to establish a dual-reward structure that combines extrinsic rewards with demonstration-derived intrinsic rewards. Evaluation was conducted on seven virtual factory routes, including loop, test, serpentine aisle, junction, narrow U-turn, loop-short cut, and asymmetric layouts. The study also compares the method with behavior cloning and DAgger and analyzes intrinsic reward strength at five different levels (0, 0.001, 0.1, 0.5, and 1.0). To rigorously evaluate performance, operational metrics, such as completion rate, cycle time, collision count, shortcut use, path length, and an energy proxy, were measured, while the dynamic time warping algorithm was used to quantify the similarity between human trajectories and the AI agent’s paths. Experimental results demonstrate that stronger imitation rewards can improve trajectory similarity on several maps, but they also introduce efficiency and robustness trade-offs across route topologies. This research provides a methodology for pre-training Physical AI in a simulation-based environment, offering a tunable approach to balance task efficiency and human-like behavior before actual field deployment.","author":[{"family":"Song","given":"Seunghwa"},{"family":"Kwon","given":"Woojin"},{"family":"Oh","given":"Juyoung"},{"family":"Kim","given":"Hyungjung"},{"family":"Lee","given":"Jun"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s12541-026-01611-8","URL":"https://doi.org/10.1007/s12541-026-01611-8","source":"openalex"},{"id":"oa:W7168270499","type":"article-journal","title":"From wearables to digital twins: the digital transformation of cardiovascular prevention: ESC Digital & AI Summit 2025","abstract":"We thank our colleagues for their thoughtful and constructive comments on our review [1]. We address the four points raised in turn. Stratification of clinical evidence. Our article was written as a narrative review under the SANRA framework, not as a formal evidence grading exercise. Its purpose was to introduce clinicians to AI (artificial intelligence) concepts and applications in an accessible way, while highlighting that the field is still evolving. The methodological breadth of the cited studies reflects the current state of the field, in which proof-of-concept work and emerging validation studies legitimately coexist. We agree that readers benefit when distinctions between exploratory findings and more mature validation work are made as explicit as possible, and we believe the Key Messages and Risks and Pitfalls sections already emphasize the need for human oversight and careful interpretation. Large language model failure modes. We agree that LLM (large language models) limitations deserve prominent attention in clinical contexts. In the review, we explicitly note that ChatGPT is not fully reliable for nutritional advice, describe the hemodialy-sis menu example reported by Chatelan and colleagues, and state that such tools cannot be used without expert oversight. We also recommend cross-checking outputs against established guidelines such as ESPEN. Operationalizing HITL (Human-in-the-Loop) oversight. We agree that effective oversight requires more than a general principle. At the same time, specific review criteria, override thresholds, and documentation standards are typically determined by institutional governance, local workflows, and regulatory context. Our intent was to introduce HITL as a foundational safeguard and to illustrate its clinical relevance, rather than to prescribe implementation protocols that necessarily vary across healthcare systems and clinical fields. Bias and population-specific validation. We agree that this is an important point. AI models in clinical nutrition must be validated in populations that reflect the intended clinical use. Population-specific reference standards for anthropometric parameters make underrepresentation in training data a concrete clinical safety issue rather than an abstract ethical concern, as the GLIM acknowledgment of Asian-specific cutoffs already illustrates. The review highlights possible biases and cites these population-specific considerations, and we appreciate the opportunity to sharpen this message further as a prerequisite for deployment rather than a future aspiration. In conclusion, we are grateful for the thoughtful critique. We believe it strengthens the discussion around evidence hierarchy, LLM safety, workflow governance, and population validation, all of which are central to responsible AI integration in clinical nutrition.","author":[{"family":"Bruining","given":"Nico"},{"family":"Kizilkilic","given":"Sevda"},{"family":"Dendale","given":"Paul"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1093/eurjpc/zwag009","URL":"https://doi.org/10.1093/eurjpc/zwag009","source":"openalex"},{"id":"oa:W4410279384","type":"manuscript","title":"Simulating Pulp Vitality Measurements via Digital Optical Twins: Influence of Dental Components on Spectral Transmission","abstract":"Optical diagnostic techniques represent an attractive complement to conventional pulp vitality tests, as they can provide direct information about the vascular status of the pulp. However, the complex, multi-layered structure of a tooth significantly influences the detected signal and, ultimately, the diagnostic decision. Despite this, the impact of the various dental components on light propagation within the tooth, particularly in the context of diagnostic applications, remains insufficiently studied. To help bridge this gap and potentially enhance diagnostic accuracy, this study employs digital optical twins based on the Monte Carlo method. Using incisor and molar models as examples, the influence of tooth and pulp geometry, blood concentration, and pulp composition, such as the possible presence of pus, on spectrally resolved transmission signals is demonstrated. Furthermore, it is shown that gingival blood absorption can significantly overlay the pulpal measurement signal, posing a substantial risk of misdiagnosis. Strategies such as shifting the illumination and detection axes, as well as time-gated detection, are explored as potential approaches to suppress interfering signals, particularly those originating from the gingiva.","author":[{"family":"Hevisov","given":"David"},{"family":"Ertl","given":"Thomas"},{"family":"Kienle","given":"Alwin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202505.0596.v1","URL":"https://doi.org/10.20944/preprints202505.0596.v1","source":"openalex"},{"id":"oa:W4406247928","type":"article-journal","title":"Applications of Digital Technologies in Promoting Sustainable Construction Practices: A Literature Review","abstract":"In recent years, the applications of digital technologies in sustainable construction have gained increasing interest. However, no comprehensive literature review has been conducted. Thus, this paper analyzes 990 relevant articles in this regard published from 2014 to 2023 by using CiteSpace (version 6.3.R1) and HistCite (version Pro 2.1) and identifies the most influential journals, institutions, and regions. The knowledge base was detected through a cluster analysis, which concentrates more on seven core themes: barriers, energy efficiency and building energy performance, life cycle assessment, computer vision, renovation, building sustainability assessment, and management. A citation analysis revealed that the applications of digital technologies were based in four dimensions of sustainable construction: environmental, social, and economic performance and green building assessment are the current hotspots. Finally, the potential future research trends in this field were proposed: (1) strengthening research on the application of more digital technologies; (2) expanding the use of digital technologies in the Operation and Maintenance (O & M) and demolition phases; (3) deepening the research on multi-objective optimization; and (4) exploring how to overcome obstacles. The findings provide highly valuable information for researchers with current research ideas and future directions in this field. This paper also has the potential to deepen practitioners’ comprehension of optimal digital technologies for bolstering construction sustainability.","author":[{"family":"Li","given":"Yuanyuan"},{"family":"Zhao","given":"Xiujuan"},{"family":"Liu","given":"Chunlu"},{"family":"Zhang","given":"Zhigang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17020487","URL":"https://doi.org/10.3390/su17020487","source":"openalex"},{"id":"oa:W4406604592","type":"manuscript","title":"Uncertainty-Aware Digital Twins: Robust Model Predictive Control using Time-Series Deep Quantile Learning","abstract":"Digital Twins, virtual replicas of physical systems that enable real-time monitoring, model updates, predictions, and decision-making, present novel avenues for proactive control strategies for autonomous systems. However, achieving real-time decision-making in Digital Twins considering uncertainty necessitates an efficient uncertainty quantification (UQ) approach and optimization driven by accurate predictions of system behaviors, which remains a challenge for learning-based methods. This paper presents a simultaneous multi-step robust model predictive control (MPC) framework that incorporates real-time decision-making with uncertainty awareness for Digital Twin systems. Leveraging a multistep ahead predictor named Time-Series Dense Encoder (TiDE) as the surrogate model, this framework differs from conventional MPC models that provide only one-step ahead predictions. In contrast, TiDE can predict future states within the prediction horizon in a one-shot, significantly accelerating MPC. Furthermore, quantile regression is employed with the training of TiDE to perform flexible while computationally efficient UQ on data uncertainty. Consequently, with the deep learning quantiles, the robust MPC problem is formulated into a deterministic optimization problem and provides a safety buffer that accommodates disturbances to enhance constraint satisfaction rate. As a result, the proposed method outperforms existing robust MPC methods by providing less-conservative UQ and has demonstrated efficacy in an engineering case study involving Directed Energy Deposition (DED) additive manufacturing. This proactive while uncertainty-aware control capability positions the proposed method as a potent tool for future Digital Twin applications and real-time process control in engineering systems.","author":[{"family":"Chen","given":"Yi"},{"family":"Tsai","given":"Ying"},{"family":"Karkaria","given":"Vispi"},{"family":"Chen","given":"Wei"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2501.10337","URL":"https://doi.org/10.48550/arxiv.2501.10337","source":"openalex"},{"id":"oa:W7140481365","type":"article-journal","title":"Integrating Digital Twins into Smart Warehousing: A Practice-Based View Framework for Identifying and Prioritizing Critical Success Factors","abstract":"Background. Smart warehousing increasingly relies on digital twin technologies to enhance operational efficiency, real-time visibility, and decision-making in logistics systems. However, existing research primarily focuses on technological capabilities while paying limited attention to the organizational practices that shape successful implementation. Methods. This study aims to identify and prioritize the critical success factors (CSFs) for integrating digital twins into smart warehousing using the Practice-Based View (PBV) as the theoretical lens. Based on insights from prior research and expert validation, nine CSFs were identified and evaluated using the Best–Worst Method (BWM). Empirical input was obtained from six industry experts with experience in digital transformation, warehousing, and supply chain management. Results. The results indicate that collaborative learning, contextual training, and gamification elements emerge as the most influential critical success factors, highlighting the importance of organizational practices in supporting digital twin adoption in smart warehousing. Conclusions. By linking technological capabilities with organizational routines, the proposed framework provides both theoretical insights and practical guidance for implementing digital twins in smart warehouse environments.","author":[{"family":"Ali","given":"Sadia"},{"family":"Marmolejo-Saucedo","given":"José"},{"family":"Piedra","given":"Rosario"},{"family":"Weber","given":"Gerhard"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/logistics10040073","URL":"https://doi.org/10.3390/logistics10040073","source":"openalex"},{"id":"oa:W4416876150","type":"article-journal","title":"Exploring research trends in use of finite element analysis for optimization of stress concentration factor in bars with fillets","abstract":"This study delivers a critical bibliometric and technical synthesis of finite element analysis (FEA)-based optimization of stress concentration factors (SCFs) in stepped flat tension bars (2005–2025). Analysis of 747 publications reveals a clear evolution from early validation studies to optimization-driven, application-ready frameworks. Comparisons of the most-cited works show methodological advances from mesh-converged parametric FEA and experimental benchmarking to evolutionary algorithms, surrogate modeling, and recent AI/ML-enhanced pipelines, though reproducibility and experimental validation remain limited. Keyword clusters align strongly with aerospace, automotive, and energy applications, while biomedical and microscale domains remain underexplored. Emerging research (2023–2025) highlights transformative directions: AI-driven surrogates for rapid SCF prediction, HPC-enabled digital twins for real-time monitoring, and additive manufacturing-specific SCF behaviors. These advances shift the field toward dynamic, data-informed frameworks that integrate computation, optimization, and sensing. By coupling bibliometric mapping with technical interpretation, this study identifies not only the past trajectories but also future opportunities, AI-informed predictive design, multiscale SCF modeling, and optimization for advanced materials, positioning bibliometrics as a strategic tool to guide next-generation structural design. References to ‘biomedical’ and ‘microscale’ indicate emergent mentions in the bibliometric maps (keywords and small clusters) rather than large, focused subfields within the Dimensions.ai export. These areas appeared only in a minority of records and are identified here as promising, under-explored directions requiring targeted systematic reviews and experimental benchmarking.","author":[{"family":"Bhosle","given":"Sachin"},{"family":"Bhosale","given":"Sangram"},{"family":"Mahadik","given":"Shrikant"},{"family":"Pondkule","given":"Sunil"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s44245-025-00163-x","URL":"https://doi.org/10.1007/s44245-025-00163-x","source":"openalex"},{"id":"oa:W4417369343","type":"article-journal","title":"Towards Smart and Sustainable Last Mile Delivery Systems: A Scoping Review and Conceptual Framework","abstract":"The accelerated growth of e-commerce and ongoing urban expansion have intensified the challenges associated with last-mile delivery, making it a critical issue in sustainable urban logistics. Therefore, our paper presents a scoping review to systematically delineate the current state of research on smart and sustainable last-mile delivery systems. We explore both innovative technologies—such as artificial intelligence, autonomous vehicles, the Internet of Things, and digital twins—and human-centered dimensions, including urban design, policy development, and collaborative stakeholder engagement. Using the PRISMA-ScR-based methodology, 140 peer-reviewed articles (2015–2025) have been analyzed to highlight key trends, gaps, and prospective directions. The study underlines how the technologies of Industry 4.0 have improved visibility and operational efficiency, but holistic thinking that incorporates environmental, human, and policy factors remains undeveloped. Based on these findings, this article provides a conceptual framework for smart and sustainable last-mile delivery, focusing on the intersection of digital and simulation tools and human-centric governance to achieve optimized efficiency, environmental performance, and equity. This framework helps both academics and decision-makers to advance data-driven, resilient, and integrative city logistic ecosystems.","author":[{"family":"Moufad","given":"Imane"},{"family":"Frichi","given":"Youness"},{"family":"Jawab","given":"Fouad"},{"family":"Mkhalfi","given":"Jihad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su172411270","URL":"https://doi.org/10.3390/su172411270","source":"openalex"},{"id":"oa:W7141489730","type":"article-journal","title":"Semantic Agent-Based Intelligent Digital Twins Integrating Demand, Production and Product Through Asset Administration Shells","abstract":"Complex products and production processes are intertwined and demand expressive, lifecycle-wide digital representations. The Asset Administration Shell emerged as a standard for Digital Twins (DTs), structuring heterogeneous data across cloud-based Industrial Internet of Things (IIoT) infrastructures. However, today’s deployments predominantly realize passive or reactive DTs, while intelligent behavior remains underexploited. This paper addresses this gap, proposing an end-to-end architecture operationalizing the DT Reference Model through the integration of machine-interpretable granulated industrial skills, which are semantically accumulated into a knowledge graph enabling discovery and reasoning, while a multi-agent system provides autonomous, utility-based negotiation via machine-to-machine interactions within a federated marketplace. The approach is applied in a real smart manufacturing demonstrator, combining order processes, production orchestration, and lifecycle documentation into a unified execution pipeline spanning IIoT-connected shopfloor assets and cloud-based services. Quantitative experiments evaluating negotiation latency, renegotiation robustness, and utility variation demonstrate stable, predictable behavior even under concurrent demand and failure scenarios. The architecture lays a foundation for interoperable, sovereign collaboration across value chains to realize shared production. The results underline the effectiveness of the tightly coupled enabler technologies realizing proactive, reconfigurable, and semantically enriched intelligent DTs.","author":[{"family":"Lehmann","given":"Joel"},{"family":"Häußermann","given":"TM"},{"family":"Reichwald","given":"Julian"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/bdcc10040103","URL":"https://doi.org/10.3390/bdcc10040103","source":"openalex"},{"id":"oa:W4414542523","type":"article-journal","title":"Evaluating mobile robot navigation behavior in flexible assembly systems through digital twin and real-world experiments","abstract":"Although digital twins are increasingly used for pre-deployment testing, their reliability as predictive tools remains understudied due to the lack of established validation frameworks. This paper presents a systematic methodology for validating the predictive fidelity of physics-based digital twins in robotic navigation tasks, addressing a critical gap in sim-to-real transferability for industrial mobile manipulators. We propose a novel evaluation approach combining (1) multi-metric comparison (localization accuracy, path consistency, goal accuracy, and navigation performance) between real-world and simulated navigation experiments, and (2) an uncertainty quantification method to establish confidence intervals for digital twin predictions. Using an NVIDIA Isaac Sim model of an omnidirectional mobile manipulator and digitally reconstructed production environments, we conduct 50 real-world and 50 digital twin experiments across five industrial scenarios. The results show a mean Hausdorff distance of 0.195 m between real and simulated paths, localization RMSE differences of 0.005 m, and a path prediction accuracy of ±0.229 m (95% CI). The findings contribute to robotic navigation by addressing key challenges in using digital twins for real-world applications, reducing the sim-to-real gap, and enhancing the reliable deployment of mobile manipulators in flexible assembly systems.","author":[{"family":"Bergs","given":"Lukas"},{"family":"Huber","given":"Meike"},{"family":"Moriz","given":"Alexander"},{"family":"Göppert","given":"Amon"},{"family":"Schmitt","given":"Robert"},{"family":"Chan","given":"Frodo"},{"family":"Law","given":"Yan"},{"family":"Pan","given":"Xiaoyu"},{"family":"Drescher","given":"Benny"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s44430-025-00010-4","URL":"https://doi.org/10.1007/s44430-025-00010-4","source":"openalex"},{"id":"oa:W7125792526","type":"article-journal","title":"Transformer Models, Graph Networks, and Generative AI in Gut Microbiome Research: A Narrative Review","abstract":"BACKGROUND: The rapid advancement in artificial intelligence (AI) has fundamentally reshaped gut microbiome research by enabling high-resolution analysis of complex, high-dimensional microbial communities and their functional interactions with the human host. OBJECTIVE: This narrative review aims to synthesize recent methodological advances in AI-driven gut microbiome research and to evaluate their translational relevance for therapeutic optimization, personalized nutrition, and precision medicine. METHODS: A narrative literature review was conducted using PubMed, Google Scholar, Web of Science, and IEEE Xplore, focusing on peer-reviewed studies published between approximately 2015 and early 2025. Representative articles were selected based on relevance to AI methodologies applied to gut microbiome analysis, including machine learning, deep learning, transformer-based models, graph neural networks, generative AI, and multi-omics integration frameworks. Additional seminal studies were identified through manual screening of reference lists. RESULTS: The reviewed literature demonstrates that AI enables robust identification of diagnostic microbial signatures, prediction of individual responses to microbiome-targeted therapies, and design of personalized nutritional and pharmacological interventions using in silico simulations and digital twin models. AI-driven multi-omics integration-encompassing metagenomics, metatranscriptomics, metabolomics, proteomics, and clinical data-has improved functional interpretation of host-microbiome interactions and enhanced predictive performance across diverse disease contexts. For example, AI-guided personalized nutrition models have achieved AUC exceeding 0.8 for predicting postprandial glycemic responses, while community-scale metabolic modeling frameworks have accurately forecast individualized short-chain fatty acid production. CONCLUSIONS: Despite substantial progress, key challenges remain, including data heterogeneity, limited model interpretability, population bias, and barriers to clinical deployment. Future research should prioritize standardized data pipelines, explainable and privacy-preserving AI frameworks, and broader population representation. Collectively, these advances position AI as a cornerstone technology for translating gut microbiome data into actionable insights for diagnostics, therapeutics, and precision nutrition.","author":[{"family":"Zhu","given":"Yan"},{"family":"Tang","given":"Yiteng"},{"family":"Qi","given":"Xin"},{"family":"Zhu","given":"Xiong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/bioengineering13020144","URL":"https://doi.org/10.3390/bioengineering13020144","source":"openalex"},{"id":"oa:W4413422829","type":"article-journal","title":"SMART PETROLEUM SYSTEMS: LEVERAGING MACHINE LEARNING AND DIGITAL TWINS FOR ENHANCED OIL RECOVERY AND GAS EMISSION CONTROL","abstract":"The evolution to smart and sustainable oilfield operations requires the implementation of advanced technologies with the ability to maximize production while minimizing the environmental imprint. The current study hypothesizes a hybrid method that bridges machine learning (ML) and digital twin (DT) technologies for visualizing an intelligent petroleum system towards the maximization of oil recovery (EOR) and reduction of greenhouse gas emissions. A mixed-method methodology was followed, with an initial qualitative systematic review of the literature to identify main themes of predictive maintenance, flare monitoring, and real-time optimization. These results fed into developing a quantitative simulation model based on synthetic and public data. ML models such as Artificial Neural Networks (ANN), XGBoost, and Long Short-Term Memory (LSTM) networks were trained to predict reservoir performance and issue warnings for abnormal CO₂ and CH₄ emissions. The best models were incorporated into a DT prototype developed in MATLAB Simulink and Python that would emulate and control the most influential production parameters in real time. It was optimized with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) and provided a 13.7% improvement in oil recovery and a 28.1% decrease in CO₂ emission at optimized conditions. The findings verify that ML-DT integration enhances proactive data-driven decision-making, enhancing operational efficiency and environmental responsibility. The study provides a scalable framework for smart petroleum system deployment and enriches the literature in digital transformation for the energy industry.","author":[{"family":"Adekomi","given":"Abdulmuiz"},{"family":"Emmanuel","given":"Apeh"},{"family":"Omenanya","given":"Emmanuel"},{"family":"Chinonyerem","given":"Confidence"}],"issued":{"date-parts":[[2025]]},"DOI":"10.70382/nijpas.v9i9.009","URL":"https://doi.org/10.70382/nijpas.v9i9.009","source":"openalex"},{"id":"oa:W7133656260","type":"article-journal","title":"Situational Deduction and Active Defense for Distribution Networks Under Complex Conditions: A Service-Oriented Digital Twin Approach","abstract":"In modern distribution networks (DNs), extreme weather events and cascading faults pose severe challenges to operational safety. However, existing defense mechanisms struggle with a core question: How to maintain high-fidelity situational awareness and make precise active decisions when physical parameters drift and historical fault data is scarce? To address this, this paper proposes a situational deduction and active defense framework based on a service-oriented digital twin. First, regarding the modeling fidelity gap, a data–physics fusion mechanism is constructed. By integrating Kirchhoff’s laws with data-driven error correction, it dynamically calibrates time-varying parameters to resolve mapping distortion. Second, regarding the data scarcity bottleneck, a predictive perception method is introduced. Utilizing the digital twin as a generative engine, it augments rare fault samples to enable super-real-time deduction of future trends. Third, regarding the decision-making passivity, a service-driven simulation model is established. It transforms abstract indicators (safety, economy, resilience) into executable constraints, shifting the paradigm from ‘passive response’ to ‘active defense.’ Case studies on a modified IEEE 123-node system demonstrate that the proposed method significantly enhances resilience and decision accuracy under complex conditions.","author":[{"family":"Xia","given":"Yuanyi"},{"family":"Du","given":"Xianbo"},{"family":"Chen","given":"Xing"},{"family":"Zhang","given":"Rui"},{"family":"Zhu","given":"Ying"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19051323","URL":"https://doi.org/10.3390/en19051323","source":"openalex"},{"id":"oa:W4415928438","type":"article-journal","title":"Low-cost data integration framework for integration with simulation-as-a-service digital twins for make-to-order manufacturing SME","abstract":"Small and medium enterprises (SMEs) face major challenges when implementing Digital Twin (DT) technology due to high infrastructure costs and complex integration requirements. While the development of comprehensive DT models remains an expensive, resource-intensive activity, most issues often lie in the complex integration processes required to connect existing manufacturing systems with simulation environments. This paper presents a novel low-cost data architecture for integrating data from enterprise manufacturing systems (such as MES and WMS) into external simulation-as-a-service platforms, facilitating DT integration while cutting the related costs. The proposed methodology addresses the challenge of connecting different IT systems with simulation services through a data-driven integration approach. Rather than relying on expensive enterprise integration architectures, the solution leverages a simplified framework focusing on intelligent data transformation with minimal pressure on existing infrastructure. The integration strategy centers on comprehensive data modeling that standardizes how products, resources, and materials information are represented across heterogeneous systems for DT consumption, particularly addressing the complexities of make-to-order environments where product-centric information requires flexible approaches. The work has been validated through the implementation in a medium-sized manufacturing company, and it demonstrated simplicity and cost-effectiveness compared to traditional integration approaches. The data architecture successfully transformed production plans, workforce allocation data, and warehouse materials records from native formats into standardized simulation-ready models. By isolating and addressing the integration complexity while utilizing existing simulation-as-a-service providers for the computationally intensive modeling aspects, the proposed methodology significantly reduces the overall burden of DT implementation for SME, supporting the adoption of this technology through a cost-effective integration strategy.","author":[{"family":"Ragazzini","given":"Lorenzo"},{"family":"Negri","given":"Elisa"},{"family":"Macchi","given":"Marco"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/icp.2025.3684","URL":"https://doi.org/10.1049/icp.2025.3684","source":"openalex"},{"id":"oa:W4411501561","type":"article-journal","title":"Long-term prediction of the Gulf Stream meander using OceanNet: a principled neural-operator-based digital twin","abstract":"Abstract. Many meteorological and oceanographic processes throughout the eastern US and western Atlantic Ocean, such as storm tracks and shelf water transport, are influenced by the position and warm sea surface temperature of the Gulf Stream (GS) – the region's western boundary current. Due to highly nonlinear processes associated with the GS, predicting its meanders and frontal position has been a long-standing challenge within the numerical modeling community. Although the weather and climate modeling communities have begun to turn to data-driven machine learning frameworks to overcome analogous challenges, there has been less exploration of such models in oceanography. Using a new dataset from a high-resolution data-assimilative ocean reanalysis (1993–2022) for the northwestern Atlantic Ocean, OceanNet (a neural-operator-based digital twin for regional oceans) was trained to predict the GS's frontal position over subseasonal to seasonal timescales. Here, we present the architecture of OceanNet and the advantages it holds over other machine learning frameworks explored during development. We also demonstrate that predictions of the GS meander are physically reasonable over at least a 60 d period and remain stable for longer. OceanNet can generate a 120 d forecast of the GS meander within seconds, offering significant computational efficiency.","author":[{"family":"Gray","given":"Michael"},{"family":"Chattopadhyay","given":"Ashesh"},{"family":"Wu","given":"Tianning"},{"family":"Lowe","given":"Anna"},{"family":"He","given":"Ruoying"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/os-21-1065-2025","URL":"https://doi.org/10.5194/os-21-1065-2025","source":"openalex"},{"id":"oa:W7117668117","type":"article-journal","title":"Development of a simulation model of a WEB-oriented servo drive frequency control system based on “Digital Twins” technology","abstract":"The object of this research is the information processes of interaction between virtual components of a WEB-oriented simulation model of a frequency control system for a synchronous servo drive. The research problem lies in the need for a comprehensive solution to the tasks of developing simulation models of control systems for technological objects based on advanced algorithms, procedures, and unified hardware and software tools. A project of a frequency control system for a SIMOTICS S-1FK2 synchronous servo drive was developed using a PLC S7-1500 and a FC SINAMICS S210 within the TIA Portal environment. Application software for the frequency control system was developed in FBD language with an integrated specialized technological object “SpeedAxis”. During the development of the simulation model, a “Digital Twins” were generated for the frequency converter with an integrated synchronous servo drive. To ensure interaction between the virtual components of the simulation model, procedures for basic parameterization and loading of the TIA Portal project components into the “Digital Twins” were implemented. Testing and investigation of the information exchange processes between the virtual components of the simulation model were carried out in “on-line” mode using the capabilities of the integrated WEB-server. The tests were conducted at speeds of 2000 rpm and 4000 rpm, switched periodically every 12 sec. Parameters of the reference and actual speed, as well as the instantaneous voltage, current, torque, and output power of the virtual frequency converter, were measured and analyzed. Based on the test results, the feasibility and correctness of the joint operation of the simulation model components in an isochronous real-time mode with a 1 ms synchronization cycle were confirmed, demonstrating the effectiveness of the approach based on “Digital Twins” technology.","author":[{"family":"Zamikhovskyі","given":"Leonid"},{"family":"Nykolaychuk","given":"Mykola"},{"family":"Levytskyi","given":"Ivan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.15587/2706-5448.2025.345825","URL":"https://doi.org/10.15587/2706-5448.2025.345825","source":"openalex"},{"id":"oa:W7152584410","type":"article-journal","title":"BIM-Based Digital Twin and Extended Reality for Electrical Maintenance in Smart Buildings: A Structured Review with Implementation Evidence","abstract":"The current literature on electrical system maintenance highlights three technology domains—Building Information Modeling (BIM), Digital Twin (DT), and extended reality (XR)—that have independently demonstrated strong potential for improving lifecycle information management, predictive analytics, and operational support. However, their convergence remains largely underexplored, particularly in electrical system maintenance. This paper provides a structured review of BIM–DT–XR convergence in electrical system lifecycle management, examining their roles across lifecycle phases and their integration through literature synthesis and cross-domain implementation evidence. BIM is analyzed as a basis for modeling and integrating facility management with electrical asset lifecycles; DT as a framework for dynamic system representation and applications in electrical and power systems; and XR as a means of visualizing and interacting with BIM-DT environments. Cross-domain implementation evidence from an industrial electrical facility and a tertiary smart-building pilot shows that BIM–DT–XR integration is technically feasible at pilot scale. However, the analysis identifies five structural integration gaps: semantic misalignment between building-oriented IFC and grid-oriented CIM ontologies; fragmented standard adoption; inconsistent data governance and naming practices; validation approaches focused on syntactic rather than dynamic model fidelity; and the separation of XR visualization from predictive DT capabilities. The implementation evidence further indicates that real-world deployment remains constrained by data quality limitations, integration complexity, cost factors, and interoperability with legacy systems. The review concludes that, despite the maturity of individual technologies, their effective application depends on advances in semantic alignment, lifecycle data governance, validation of dynamic models, and scalable integration frameworks, enabling the transition toward integrated, interoperable, and lifecycle-aware infrastructures for electrical system maintenance.","author":[{"family":"Leo","given":"Paolo"},{"family":"Zucco","given":"Michele"},{"family":"Giudice","given":"MD"},{"family":"Giudice","given":"Matteo"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/app16083685","URL":"https://doi.org/10.3390/app16083685","source":"openalex"},{"id":"oa:W7127338090","type":"article-journal","title":"Modeling metacognition and executive functions in the metacognitive wisconsin card sorting test using the neuropsychological digital-twin method","abstract":"Executive functions rely on goal-directed manipulation of representations, while metacognition reflects the evaluation and control of one’s own representations. Several studies have examined these processes separately, but none formalise the neuro-representational computations underlying their interaction during goal-directed behaviour. This gap prevents comprehensive frameworks and extended model-based neuropsychological investigations. Here we address these issues by introducing a neuropsychological digital-twin method - a translational modelling framework that integrates clinical and experimental data, theoretical formalisation, and computational modelling for neuropsychological profiling and prediction. We formalised the three-component theory of metacognitive and flexible goal-directed cognition - grounded in theoretical and neuroscientific literature - and developed a neuro-inspired computational model tested with a standard neuropsychological task (Metacognitive Wisconsin Card Sorting Test, Meta-WCST). We further corroborated the proposal by reproducing experimental data from healthy controls and psychiatric populations (Anorexia Nervosa and Schizophrenia). Finally, we generated three digital-twins - computational models fitted to human data and reproducing behavioural and neuro-cognitive features - for neuropsychological profiling and intervention prediction. Our results support an integrated framework of executive functions and metacognition in healthy and pathological goal-directed behaviour and provide the first theory-based computational model of the Meta-WCST. They also reveal that Anorexia Nervosa and Schizophrenia share hidden cognitive and metacognitive similarities (motivational impairment and over-confidence) alongside differences (perseveration and poor self-improvement in the former; distraction and poor self-evaluation in the latter). Consistently, simulations predict differential benefits from metacognitive-based psychotherapy, highlighting the importance of personalised interventions. Finally, our contributions have implications for cognitive science (e.g., consciousness studies) and emerging technologies (digital-twin healthcare and autonomous robotics).","author":[{"family":"Granato","given":"Giovanni"},{"family":"Mattera","given":"Andrea"},{"family":"Cartoni","given":"Emilio"},{"family":"Baldassarre","given":"Gianluca"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41598-026-37612-w","URL":"https://doi.org/10.1038/s41598-026-37612-w","source":"openalex"},{"id":"oa:W7128786244","type":"article-journal","title":"Rule-Based Digital Twin: An Integrated Parametric-BIM Workflow for Life-Cycle Delivery of Free-Form, Special-Shaped Envelopes in Large-Scale Public Buildings","abstract":"Despite the aesthetic potential of free-form envelopes in large-scale public buildings, geometric interlacing complexity, ambiguous façade boundaries, and constructability translation gaps persist as systemic barriers. This study addresses these challenges through a Design Science Research (DSR) approach, developing a rule-based digital twin methodology that maintains parametric intelligence across the building life cycle. Implemented via a five-layer integrated framework, i.e., geometric, parametric, BIM, coordination, and fabrication, the methodology was validated through a revelatory case study of the Shenzhen Bay Culture Plaza. Results demonstrate 91.2% clash resolution prior to construction, 20.3 million RMB in cost savings (10.8% reduction), and 35.4% schedule compression, while preserving rule-based relationships into operational facility management. The study advances BIM theory by operationalizing life-cycle digital twins for non-standard geometries, offering a replicable framework for future special-shaped construction projects.","author":[{"family":"Li","given":"Xiang"},{"family":"Gan","given":"Wei"},{"family":"Liu","given":"Xiaopei"},{"family":"Yang","given":"Jun"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/buildings16040778","URL":"https://doi.org/10.3390/buildings16040778","source":"openalex"},{"id":"oa:W7129091575","type":"article-journal","title":"A Fully Self‐Powered Digital Wearable System for the Auxiliary Treatment of Plantar Fasciitis","abstract":"ABSTRACT Plantar fasciitis severely impairs daily life through persistent pain and limited mobility, whereas conventional treatments often lack real‐time monitoring and personalized feedback. This study introduces a fully self‐powered digital wearable system (FS‐DWS), integrating an arch support auxiliary (ASA) device, a wearable sensing system (WSS), and a machine learning‐driven closed‐loop visualized feedback system (VFS) to enable real‐time plantar pressure monitoring and abnormal gait recognition for the auxiliary treatment of plantar fasciitis. As a system‐level engineering achievement, the ASA module integrates elastic support with energy harvesting, alleviating plantar pressure and powering the wearable sensing system without any batteries, with a maximum power density of 41.6 mW/cm 3 , one order of magnitude higher than those of previously reported biomechanical energy harvesting devices. The VFS utilizes a flexible sensor array to collect dynamic pressure data, which is processed via a machine learning algorithm to achieve real‐time classification of 7 gait cycle phases with an accuracy of 99.3%, enabling identification of abnormal pressure distribution, causal tracing of gait deviations, and generation of personalized correction instructions. As a proof‐of‐concept study, the proposed dual‐function strategy of “physical support + intelligent regulation” provides an efficient and sustainable approach to the long‐term management of plantar fasciitis and supports a shift in therapeutic approach from passive relief to active correction.","author":[{"family":"Hou","given":"Jiacheng"},{"family":"Hong","given":"Ying"},{"family":"Liu","given":"Shiyuan"},{"family":"Pan","given":"Qiqi"},{"family":"Zhang","given":"Jingyu"},{"family":"Xu","given":"QMXD"},{"family":"Nie","given":"Qiyi"},{"family":"Wang","given":"Zhonghe"},{"family":"Xin","given":"Liming"},{"family":"Wang","given":"Yilong"},{"family":"Wang","given":"Biao"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1002/advs.202521682","URL":"https://doi.org/10.1002/advs.202521682","source":"openalex"},{"id":"oa:W7130837187","type":"article-journal","title":"Challenges and potential of using digital biomarkers in healthcare and clinical trials","abstract":"Digital biomarkers use sensors and analytics, to offer continuous monitoring and personalized medicine. In this Perspective, we describe real-world use cases, such as glucose tracking to optimise insulin dosing and wearables to measure heart rhythms to de-risk cardiovascular trials. We also discuss the issues preventing most candidate biomarkers from reaching clinical practice. Evidence generation is costly, regulatory reviews can be redundant, commercial incentives fall short, and data silos can be biased and/or nonrepresentative. By combining harmonized qualification pathways, value-based reimbursement, modular extensions for single-trial biomarkers, and adaptive post-market evidence loops, we propose a path from experimental signal to standard of care.","author":[{"family":"Lieberwirth","given":"Johann"},{"family":"Mittermaier","given":"Mirja"},{"family":"Stern","given":"Ariel"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s43856-026-01450-8","URL":"https://doi.org/10.1038/s43856-026-01450-8","source":"openalex"},{"id":"oa:W4414011103","type":"article-journal","title":"Review on data-informed planning for underground space","abstract":"Urban underground space (UUS) development, guided by prudent planning, has emerged as a vital solution to the increasingly complex issues of urban built environments globally. Driven by the growing needs for human-centric urban design, low-carbon development, enhanced urban resilience, and alignment with sustainable development goals, UUS planning is rapidly shifting from experience-based approaches to evidence-based and data-driven methodologies. Yet, the broader landscape of this research field remains ambiguous, with the characteristics and future trajectories of such emerging planning technologies still to be clearly delineated. To this end, this systematic review delves into the burgeoning field of data-informed planning technologies for underground space (DIPTUS), examining how data-driven methods are revolutionizing the planning, design, and management of underground environments. Through a comprehensive bibliometric analysis of 134 articles published from 2014 to 2024, we identified key trends and mapped research themes within DIPTUS. Our narrative synthesis evaluated DIPTUS advancements across three dimensions: sensing and measurement, pattern and model, and planning and governance. The results indicate that DIPTUS exploits diverse data streams to quantitatively analyze UUS development. Utilizing advanced analytical tools such as spatial statistics, machine learning, and causal inference, these technologies uncover utilization patterns and planning optimization strategies. The review also underscores the increasing integration of planning and governance within DIPTUS, merging resource evaluation and demand forecasting, layout planning optimization, development benefits and spatial performance evaluation into a cohesive framework. Enhancements in 3D cadastral systems, innovative management models, and digital twin technologies further bolster this integrated approach. Despite significant strides, challenges in data integration, model complexity, and practical application persist. Lastly, we proposed a visionary framework to address these issues through interdisciplinary research and robust model development, aiming to fully harness DIPTUS's transformative potential for sustainable, resilient, and human-centered urban environments. © 2025 Tongji University.","author":[{"family":"Peng","given":"Fang"},{"family":"Wang","given":"Wei"},{"family":"Qiao","given":"Yong"},{"family":"Ma","given":"Chen"},{"family":"Dong","given":"Yun"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.undsp.2025.06.001","URL":"https://doi.org/10.1016/j.undsp.2025.06.001","source":"openalex"},{"id":"oa:W7131846320","type":"article-journal","title":"Robust Backstepping Control of a Twin Rotor MIMO System via an RBF-Tuned High-Gain Observer","abstract":"The design of robust controllers for complex nonlinear systems remains a formidable challenge, particularly concerning the disparity between simulation performance and real-world implementation constraints. This research investigates the practical implementation of a backstepping controller integrated with a High-Gain Observer (HGO) on a Twin Rotor MIMO System (TRMS). While the control architecture exhibited stability and precise tracking in simulation, physical deployment initially failed due to sensitivity to measurement noise and the peaking phenomenon, resulting in a divergent response with a Yaw RMSE of 2.56 rad. Unlike conventional approaches that attempt to bridge the simulation-to-reality gap by optimizing the controller, we hypothesized that the critical bottleneck lay within the observer dynamics. To address this, a Radial Basis Function (RBF) Neural Network was employed to adaptively tune the observer gains in real time. Experimental results demonstrate that this adaptive mechanism successfully mitigated the effects of unmodeled dynamics and noise, reducing the Root Mean Square Error (RMSE) by over 85% in the pitch axis and 95% in the yaw axis. These findings substantiate that online adaptive observer tuning is a decisive strategy for ensuring the reliability of advanced nonlinear controllers on physical hardware.","author":[{"family":"Beloufa","given":"Azeddine"},{"family":"Tahraoui","given":"Souad"},{"family":"Kacimi","given":"Abderrahmane"},{"family":"Allouache","given":"H"},{"family":"Tiang","given":"Jun"},{"family":"Azzouz","given":"Abdelbasset"},{"family":"Zaid","given":"Mehdi"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/automation7020040","URL":"https://doi.org/10.3390/automation7020040","source":"openalex"},{"id":"oa:W4411695247","type":"article-journal","title":"Redefining Digital Dentistry: Multidisciplinary Applications of 3D Printing for Personalized Dental Care","abstract":"The integration of 3D printing into dentistry has led to a revolution in the precision and personalization of dental care. This review examines the extensive applications of 3D printing technology in various branches of dentistry. With the capability to create highly detailed, patient-specific models, devices, and appliances, 3D printing is transforming clinical workflows, enhancing the accuracy of treatments, and reducing procedural time. Moreover, it supports a digital workflow that aligns with the growing trend of personalized healthcare. Innovations in printer resolution, biocompatible materials, and printing speed continue to push the boundaries of what is possible in dental care. However, limitations related to material properties, regulatory considerations, and the need for specialized training persist. The review also highlights ongoing advancements in 3D printing technology and materials, which promise to further revolutionize dental practice. In conclusion, 3D printing holds immense potential for enhancing dental care, although overcoming existing challenges will require ongoing research and innovation.","author":[{"family":"Almarshadi","given":"Ruqayyah"},{"family":"Hamdi","given":"Sabreen"},{"family":"Hadi","given":"Fatimah"},{"family":"Alshehri","given":"Aisha"},{"family":"Alsahafi","given":"Reem"},{"family":"Aljohani","given":"Nouf"},{"family":"Alyamani","given":"Rafan"},{"family":"Alhbchi","given":"Mariam"},{"family":"Alqahtani","given":"Nisrin"},{"family":"Almutiri","given":"Reem"},{"family":"Alqadi","given":"Thageba"},{"family":"Alhabardi","given":"Afnan"},{"family":"Aziz","given":"Khairul"},{"family":"Alshammeri","given":"Talal"}],"issued":{"date-parts":[[2025]]},"DOI":"10.7759/cureus.86791","URL":"https://doi.org/10.7759/cureus.86791","source":"openalex"},{"id":"oa:W4411061779","type":"article-journal","title":"Decentralized Proof-of-Location systems for trust, scalability, and privacy in digital societies","abstract":"Verifying physical presence in digital systems is essential for secure authentication, authorization, and accountability. Proof-of-Location (PoL) systems address this need by enabling verifiable, tamper-resistant claims of location and time, particularly in adversarial environments where traditional localization methods such as GPS fall short. While recent efforts have explored decentralized PoL architectures, existing systems often lack a unified model that integrates spatio-temporal synchronization, distributed consensus, and cryptographic attestation. In this paper, we formalize the architectural foundations of decentralized PoL systems by introducing a composable model based on fault-tolerant witnessing zones. We define core components for synchronization and collective attestation, integrating primitives such as distributed digital signatures, distance bounding protocols, and consensus mechanisms. We contextualize the model across diverse application domains that necessitate digital trust-such as civic processes, content authentication, infrastructure auditing, and supply chain tracking-and argue for a shared, interoperable decentralized PoL infrastructure. To validate our design, we implement and emulate a reference protocol instance, analysing scalability, synchronization behaviour, and timing misalignment under varied conditions. We also outline its security model and discuss limitations and future directions in privacy, interoperability, and real-world deployment. Our contributions lay a formal and practical foundation for scalable, secure, and general-purpose decentralized PoL systems.","author":[{"family":"Brito","given":"Eduardo"},{"family":"Hadachi","given":"Amnir"},{"family":"Kamm","given":"Liina"},{"family":"Norbisrath","given":"Ulrich"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-04566-4","URL":"https://doi.org/10.1038/s41598-025-04566-4","source":"openalex"},{"id":"oa:W4416311384","type":"article-journal","title":"Artificial Intelligence Empowering the Transformation of Building Maintenance: Current State of Research and Knowledge","abstract":"With the acceleration of urbanization and the continuous expansion of building stock, building maintenance plays a critical role in ensuring structural safety, extending service life, and promoting sustainable development. In recent years, the application of artificial intelligence (AI) in building maintenance has expanded significantly, markedly improving detection accuracy and decision-making efficiency through predictive maintenance, automated defect recognition, and multi-source data integration. Although existing studies have made progress in predictive maintenance, defect identification, and data fusion, systematic quantitative analyses of the overall knowledge structure, research hotspots, and technological evolution in this field remain limited. To address this gap, this study retrieved 423 relevant publications from the Web of Science Core Collection covering the period 2000–2025 and conducted a systematic bibliometric and scientometric analysis using tools such as bibliometrix and VOSviewer. The results indicate that the field has entered a phase of rapid growth since 2017, forming four major thematic clusters: (1) intelligent construction and digital twin integration; (2) predictive maintenance and health management; (3) algorithmic innovation and performance evaluation; and (4) deep learning-driven structural inspection and automated operation and maintenance. Research hotspots are evolving from passive monitoring to proactive prediction, and further toward system-level intelligent decision-making and multi-technology integration. Emerging directions include digital twins, energy efficiency management, green buildings, cultural heritage preservation, and climate-adaptive architecture. This study constructs, for the first time, a systematic knowledge framework for AI-enabled building maintenance, revealing the research frontiers and future trends, thereby providing both data-driven support and theoretical reference for interdisciplinary collaboration and the practical implementation of intelligent maintenance.","author":[{"family":"Zheng","given":"YH"},{"family":"Sun","given":"Boyuan"},{"family":"Guan","given":"Yiming"},{"family":"Yang","given":"Yufeng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/buildings15224118","URL":"https://doi.org/10.3390/buildings15224118","source":"openalex"},{"id":"oa:W7125934423","type":"article-journal","title":"Multi-Phase Demand Modeling and Simulation of Mission-Oriented Supply Chains Using Digital Twin and Adaptive PSO","abstract":"Mission-oriented supply chains involve multi-phase tasks, strong resource interdependencies, and stringent reliability requirements, which make demand planning complex and uncertain. This study develops a structured demand modeling framework to support multi-phase mission-oriented supply chains under budget and reliability constraints by integrating digital twin technology with an adaptive inertia weight particle swarm optimization (AIW-PSO) algorithm. The supply support process is decomposed into four sequential phases—storage, transportation, preparation, and execution—and phase-specific demand models are constructed based on system reliability theory, explicitly incorporating redundancy, maintainability, and repairability. In this work, digital twin technology functions as a data acquisition and virtual experimentation layer that supports parameter calibration, state-aware scenario simulation, and event-triggered re-optimization rather than continuous real-time control. Physical-state updates are mapped to model parameters such as phase durations, failure rates, repair rates, and instantaneous availability, after which the integrated optimization model is re-solved using a warm-start strategy to generate updated demand plans. The resulting multi-phase demand optimization problem is solved using AIW-PSO to enhance global search performance and mitigate premature convergence. The proposed method is validated using a representative mission-oriented supply support scenario with operational and simulated data. Simulation results demonstrate that, under identical budget constraints, the proposed approach achieves higher mission completion capability than conventional PSO-based methods, providing effective and practical decision support for multi-phase mission-oriented supply chain planning.","author":[{"family":"Zhao","given":"Jianbo"},{"family":"Wang","given":"Ruikang"},{"family":"Jing","given":"Yijia"},{"family":"Wang","given":"Yalin"},{"family":"Pan","given":"Chenghao"},{"family":"Tong","given":"Yifei"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/pr14030468","URL":"https://doi.org/10.3390/pr14030468","source":"openalex"},{"id":"oa:W4416337235","type":"article-journal","title":"Advancing Conceptual Understanding: A Meta-Analysis on the Impact of Digital Technologies in Higher Education Mathematics","abstract":"The integration of digital technologies in mathematics is becoming increasingly significant, particularly in promoting conceptual understanding and student engagement. This study systematically reviews the literature on applications of Computer Algebra Systems, Artificial Intelligence, Visualisation Tools, augmented-reality technologies, Statistical Software, game-based learning and cloud-based learning in higher education mathematics. This meta-analysis synthesises findings from 88 empirical studies conducted between 1990 and 2025 to evaluate the impact of these technologies. The included studies encompass diverse geographical regions, providing a comprehensive global perspective on the integration of digital technologies in higher mathematics education. Using the PRISMA framework and quantitative effect size calculations, the results indicate that all interventions had a statistically significant impact on student performance. Among them, Visualisation Tools demonstrated the highest average percentage improvement in academic performance (39%), whereas cloud-based learning and game-based approaches, while beneficial, showed comparatively modest gains. The findings highlight the effectiveness of an interactive environment in fostering a deeper understanding of mathematical concepts. This study provides insights for educators and policymakers seeking to improve the quality and equity of mathematics education in the digital era.","author":[{"family":"Sofroniou","given":"Anastasia"},{"family":"Patel","given":"Mansi"},{"family":"Premnath","given":"Bhairavi"},{"family":"Wall","given":"Julie"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/educsci15111544","URL":"https://doi.org/10.3390/educsci15111544","source":"openalex"},{"id":"oa:W4417114518","type":"article-journal","title":"Multiple Normalization Rating Analysis (MUNRA) and its application to digital supplier selection in the textile industry","abstract":"The rapid development of digital technologies – such as IoT, AI, blockchain, and digital twins – has transformed supply chains into interconnected ecosystems, making digital supplier selection both critical and complex. For the first time, this study proposes a novel multi-criteria decision-making (MCDM) method, Multiple Normalization Rating Analysis (MUNRA), for ranking alternatives. It integrates linear, vector, and non-linear normalization to improve robustness, reduce rank reversal, and enhance decision accuracy. A case study of digital supplier selection in the textile industry is considered for a real-life application of the method. Results highlight technology integration, flexibility, and technological capability as the most influential criteria for selecting digital suppliers. Moreover, the final ranking of the six digital suppliers is as follows: DS5, DS4, DS2, DS6, DS1, and DS3. Validation through comparative MCDM methods, Spearman correlation, and sensitivity analyses confirms the credibility of the method. It is also shown that it is free from the rank reversal phenomenon. The research presents a computationally efficient and rigorous method for evaluating digital suppliers, offering strategic insights for digital supply chain management. The application of MUNRA to a larger decision-making problem further illustrates its scalability and cross-domain applicability.","author":[{"family":"Ulutaş","given":"Alptekin"},{"family":"Ecer","given":"Fatih"},{"family":"Turskis","given":"Zenonas"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3846/tede.2025.25346","URL":"https://doi.org/10.3846/tede.2025.25346","source":"openalex"},{"id":"oa:W4415835475","type":"article-journal","title":"An AI-Driven Adaptive Training Platform with Digital Twin-Based Skill Gap Analysis and Future Readiness Insights","abstract":"The rapid digital transformation of industries has intensified the demand for adaptive, data-driven learning ecosystems capable of continuously aligning workforce skills with evolving technological trends. Traditional static training systems struggle to meet these dynamic needs, creating persistent skill gaps and limiting future employability. This study addresses this challenge by exploring the integration of Artificial Intelligence (AI) and Digital Twin (DT) technologies to create a hybrid, future-ready training framework. The proposed model combines reinforcement learning with generative AI to dynamically assess learner progress, perform real-time skill-gap analysis, and personalize training paths through a continuously evolving digital twin of each learner. The framework was evaluated using pilot simulations in a vocational training environment. Results showed a 22 % improvement in personalization accuracy, 15%-20% reduction in skill gaps, and an 82 % accuracy in future-readiness prediction compared with conventional adaptive learning systems. These findings highlight the transformative potential of merging AI adaptability with DT contextualization to deliver immersive, predictive, and career-aligned learning experiences. The impact of this research lies in redefining the paradigm of personalized education and workforce development-moving beyond reactive learning to proactive, anticipatory training models that prepare individuals for the demands of the digital economy.","author":[{"family":"Nayak","given":"MM"},{"family":"Rishi","given":"Pratik"},{"family":"Neupane","given":"Ram"},{"family":"Pahurkar","given":"Pranali"},{"family":"Shrimal","given":"Drashti"}],"issued":{"date-parts":[[2025]]},"DOI":"10.64189/css.25410","URL":"https://doi.org/10.64189/css.25410","source":"openalex"},{"id":"oa:W4409181517","type":"article-journal","title":"Revolutionizing supply chains: The role of emerging technologies in digital transformation","abstract":"The main objectives of the study are to provide a comprehensive overview of emerging technological solutions, their applications, and their impacts on supply chain digital transformation. It is qualitative research, and secondary data were collected. The study identified five effective applications of the individual solutions. AI provides effective insights, demand forecasting, warehouse automation, transportation and route optimization, supplier selection and management, and predictive maintenance. Blockchain enables tracking and transparency, enhancing traceability, cutting down on counterfeiting, encouraging sustainable and ethical sourcing, and facilitating smart payments. Business intelligence ensures improved communication, monitoring expenses, inventory management, tracking key performance indicators, and optimized visualization. Data science facilitates demand prediction, route enhancement, inventory management, hazard assessment, and supplier administration. IoT enables shipment and delivery tracking, warehouse capacity monitoring, inventory management, storage condition monitoring, and routine optimization and automation. RFID is effective for warehouse management, inventory management, freight transportation, supply chain visibility, and retail management. These emerging technologies collectively promote a more integrated, adaptable, and resilient supply chain landscape, address significant challenges, and open doors to future innovations. The results suggest that by adopting all emerging technologies within the supply chain context, business executives would increase their efficiency and enhance firm value as well.","author":[{"family":"Islam","given":"Naimul"},{"family":"Tanchangya","given":"Tipon"},{"family":"Naher","given":"Kamrun"},{"family":"Tafsirun","given":"Ummah"},{"family":"Mia","given":"Md"},{"family":"Sarker","given":"Shoaibur"},{"family":"Rashid","given":"Fahad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.18488/89.v11i1.4143","URL":"https://doi.org/10.18488/89.v11i1.4143","source":"openalex"},{"id":"oa:W7143480620","type":"article-journal","title":"Research on a Smart Fire Monitoring System for University Dormitories Based on Edge-Cloud Collaboration and Digital Twin Technology","abstract":"In response to significant fire hazards arising from high population density and complex electricity consumption in university dormitories, as well as industry pain points such as the \"information silos\" of traditional standalone smoke alarms and the spatial localization difficulties of 2D planar monitoring systems, this paper comprehensively utilizes embedded development, Internet of Things (IoT) communication, and digital twin technologies to design and implement an edge-cloud collaborative visual monitoring system for smart fire protection. Addressing the limitations of existing fire monitoring systems, the primary innovations and research outcomes of this paper include: the design of a network self-healing mechanism against process blocking based on a kernel-level soft reset; the construction of an early fire prediction model based on multi-dimensional environmental feature fusion; and the development of a 3D digital twin interactive architecture featuring an intelligent viewpoint scheduling algorithm. For environmental data extraction at the underlying hardware level, the system employs an STM32F103 microcontroller as the core computing engine, integrating an MQ-9 combustible gas sensor, a DHT11 temperature and humidity sensor, and a far-infrared flame detector. This enables the multi-dimensional, high-frequency capture of environmental fire factors in dormitories alongside local sound and light coordinated alarms. Regarding the network communication link design, the system utilizes an ESP8266 wireless module in coordination with an Alibaba Cloud EMQX message broker server. It adopts the lightweight MQTT protocol instead of the traditional HTTP protocol and achieves the efficient packaging of heterogeneous data via JSON serialization. To solve the engineering problem of frequent device freezing (\"pseudo-death\") in the complex and weak network environments typical of university dormitories, this paper innovatively introduces a network error counter and a kernel-level soft reset self-healing mechanism to prevent process blocking. Testing indicates that this mechanism can complete a full-link self-recovery within an average of 7.79 seconds following a network disconnection, ensuring stable, 24/7 unattended terminal operation. In terms of algorithmic models and upper-level visualization applications, this project breaks through traditional rigid alarm thresholds by introducing a multi-dimensional environmental feature spatial fusion prediction model based on logistic regression. By calculating the joint posterior probability of fire occurrence through weighted bias, this algorithm significantly advances the time window for fire early warning, transitioning the system from passive response to active prevention. Furthermore, a high-fidelity digital twin monitoring platform was developed using the Unity3D engine, constructing a 3D virtual mirror of the physical dormitory. Leveraging a self-developed asynchronous MQTT client middleware and cross-platform feature tag mapping technology, the platform achieves high-frame-rate, lossless parsing of massive data. Combined with a quaternion spherical linear interpolation camera movement algorithm, the system not only triggers global audio-visual effects upon detecting a fire but also automatically and smoothly navigates the monitoring perspective to lock onto the affected room. This creates an immersive interactive experience where \"alarm equals localization, and localization equals visual confirmation.\" Comprehensive testing demonstrates that this system successfully integrates the full-stack technical pipeline, spanning underlying hardware data acquisition and cloud-based data transmission to upper-computer 3D simulation. All functional metrics meet the anticipated design requirements, validating the high feasibility and advanced nature of integrating digital twin technology with the IoT in the smart fire protection sector.","author":[{"family":"Wang","given":"Xin"},{"family":"Ma","given":"Lei"},{"family":"Xiong","given":"Junjie"}],"issued":{"date-parts":[[2026]]},"DOI":"10.54097/7kjjak38","URL":"https://doi.org/10.54097/7kjjak38","source":"openalex"},{"id":"oa:W4411675053","type":"article-journal","title":"Can digital transformation enhance labor productivity in enterprises: An analysis from the perspective of business process reengineering","abstract":"From the perspective of business process reengineering, this paper analyzes the impact of digital transformation on labor productivity in enterprises and its underlying mechanisms. The study finds that digital transformation significantly enhances labor productivity in enterprises, with both the application of digital technologies and innovation in digital technology scenarios having a notable positive effect. Furthermore, digital transformation improves labor productivity mainly by optimizing production management processes, reducing human resource redundancy, enhancing the efficiency of human resource utilization, and improving internal control mechanisms to enhance decision-making efficiency. The effects of digital transformation on labor productivity are more pronounced in non-state-owned enterprises and enterprises that are highly dependent on their industrial chains. Further analysis shows that the level of industry monopoly and the overall digitalization level of the industry play a moderating role in the process by which digital transformation affects labor productivity.","author":[{"family":"Zhou","given":"Yi"},{"family":"Lyu","given":"Ji"},{"family":"Li","given":"Li"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1371/journal.pone.0325484","URL":"https://doi.org/10.1371/journal.pone.0325484","source":"openalex"},{"id":"oa:W4417493825","type":"article-journal","title":"Unmanned Aerial Vehicles (UAVs) in the Energy and Heating Sectors: Current Practices and Future Directions","abstract":"Dynamic social and legal transformations drive technological innovation and the transition of energy and heating sectors toward renewable sources and higher efficiency. Ensuring the reliable operation of these systems requires regular inspections, fault detection, and infrastructure maintenance. Unmanned Aerial Vehicles (UAVs) are increasingly being used for monitoring and diagnostics of photovoltaic and wind farms, power transmission lines, and urban heating networks. Based on literature from 2015 to 2025 (Scopus database), this review compares UAV platforms, sensors, and inspection methods, including thermal, RGB/multispectral, LiDAR, and acoustic, highlighting current challenges. The analysis of legal regulations and resulting operational limitations for UAVs, based on the frameworks of the EU, the US, and China, is also presented. UAVs offer high-resolution data, rapid coverage, and cost reduction compared to conventional approaches. However, they face limitations related to flight endurance, weather sensitivity, regulatory restrictions, and data processing. Key trends include multi-sensor integration, coordinated multi-UAV missions, on-board edge-AI analytics, digital twin integration, and predictive maintenance. The study highlights the need to develop standardised data models, interoperable sensor systems, and legal frameworks that enable autonomous operations to advance UAV implementation in energy and heating infrastructure management.","author":[{"family":"Jakubiak","given":"Mateusz"},{"family":"Sroka","given":"Katarzyna"},{"family":"Maciuk","given":"Kamil"},{"family":"Abazeed","given":"Amgad"},{"family":"Kovalova","given":"Anastasiia"},{"family":"Santos","given":"Luís"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/en19010005","URL":"https://doi.org/10.3390/en19010005","source":"openalex"},{"id":"oa:W4407341241","type":"article-journal","title":"Evaluation and Analysis of Industrial Internet Maturity for Power Enterprises in the Digital Transformation","abstract":"The industrial Internet plays a vital role in promoting the digital transformation of enterprises, especially in the core application field of the power industry. Evaluating the maturity of the industrial Internet of power enterprises and finding the weak points in the construction of the industrial Internet are of great significance for the digital transformation of power enterprises. Firstly, this paper reviews the existing literature and analyzes the evaluation situation of industrial Internet maturity. Research has found that there is relatively little research on the maturity evaluation of the industrial Internet for the power industry, and existing maturity models have difficulty meeting industry-specific needs. Therefore, it is very important and necessary to build a maturity evaluation model of the industrial Internet suitable for the power industry. Subsequently, based on the specific characteristics of the power industry, while referring to the authoritative literature and industry standards, this paper constructs a three-level index system covering key elements such as equipment networking, information network infrastructure construction, supply chain management, and intelligent production and simultaneously expounds the quantitative collection methods and scoring principles of indices. Then, introducing the Analytic Hierarchy Process (AHP) to determine subjective weights and the Entropy Weight Method (EWM) to quantify the objective weights of indices, a maturity evaluation method that combines subjective judgment and objective data support is formed. Later, the calculation method for the comprehensive score of indices and the criteria for classifying maturity levels are explained. Finally, a specific power enterprise is selected as a case study, and the evaluation results are analyzed to verify the feasibility of the evaluation method.","author":[{"family":"Yan","given":"Jia"},{"family":"Wang","given":"Zengqiang"},{"family":"Li","given":"Qianying"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/systems13020104","URL":"https://doi.org/10.3390/systems13020104","source":"openalex"},{"id":"oa:W7116650528","type":"article-journal","title":"Hazard- and Fairness-Aware Evacuation with Grid-Interactive Energy Management: A Digital-Twin Controller for Life Safety and Sustainability","abstract":"The paper introduces a real-time digital-twin controller that manages evacuation routes while operating GEEM for emergency energy management during building fires. The system consists of three interconnected parts which include (i) a physics-based hazard surrogate for short-term smoke and temperature field prediction from sensor data (ii), a router system that manages path updates for individual users and controls exposure and network congestion (iii), and an energy management system that regulates the exchange between PV power and battery storage and diesel fuel and grid electricity to preserve vital life-safety operations while reducing both power usage and environmental carbon output. The system operates through independent modules that function autonomously to preserve operational stability when sensors face delays or communication failures, and it meets Industry 5.0 requirements through its implementation of auditable policy controls for hazard penalties, fairness weight, and battery reserve floor settings. We evaluate the controller in co-simulation across multiple building layouts and feeder constraints. The proposed method achieves superior performance to existing AI/RL baselines because it reduces near-worst-case egress time (T95 and worst-case exposure) and decreases both event energy Eevent and CO2-equivalent CO2event while upholding all capacity, exposure cap, and grid import limit constraints. A high-VRE, tight-feeder stress test shows how reserve management, flexible-load shedding, and PV curtailment can achieve trade-offs between unserved critical load Uenergy and emissions. The team delivers implementation details together with reporting templates to assist researchers in reaching reproducibility goals. The research shows that emergency energy systems, which integrate evacuation systems, achieve better safety results and environmental advantages that enable smart-city integration through digital thread operations throughout design, commissioning, and operational stages.","author":[{"family":"Alghamdi","given":"Mansoor"},{"family":"Abadleh","given":"Ahmad"},{"family":"Mnasri","given":"Sami"},{"family":"Alrashidi","given":"Malek"},{"family":"Alkhazi","given":"Ibrahim"},{"family":"Alghamdi","given":"Abdullah"},{"family":"Albelwi","given":"Saleh"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su18010133","URL":"https://doi.org/10.3390/su18010133","source":"openalex"},{"id":"oa:W4416322172","type":"article-journal","title":"Virtual Museums as Meaning-Modeling Systems in Digital Heritage","abstract":"This article frames the virtual museum as a meaning-modeling system within digital heritage and proposes an operational semiotic method for analysis. Grounded in Modeling Systems Theory and informed by Adorno’s non-identity, we construct a twelve-category coding matrix that combines three modeling levels with four organizational forms. Applying this matrix to five heterogeneous cases (web, VR, and 3D environments), we derive three quantitative ratios that summarize each system’s profile: the Abstraction Ratio (degree of conceptual mediation), the Connectivity Ratio (degree of interlinking and systematic organization), and the Object Primacy Score (degree of object-centered representation). Exploratory clustering on these ratios reveals three recurrent patterns of virtual-heritage mediation: Network-Symbolic, Concept-Dominant, and Object-Preserving. The results articulate how different curatorial and technical choices redistribute attention between objects, contexts, and concepts, and how these redistributions affect the subject–object balance in digital settings. The contribution is twofold: a transparent, reproducible coding protocol that enables cross-case comparison, and an interpretive lens that relates quantitative patterns to critical concerns in heritage, including authenticity, legibility, and over-standardization. We conclude with implications for curators and designers seeking to align immersive interfaces with heritage values while preserving the irreducible remainder of the object.","author":[{"family":"Guan","given":"Huining"},{"family":"Chen","given":"Pengbo"},{"family":"Kwon","given":"Cheeyun"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/heritage8110484","URL":"https://doi.org/10.3390/heritage8110484","source":"openalex"},{"id":"oa:W4416188208","type":"article-journal","title":"Crystal Plasticity Simulations of Dislocation Slip and Twinning in α-Ti Single and Polycrystals","abstract":"A crystal plasticity finite element model is developed and implemented to numerically study the deformation behavior of hexagonal close-packed metals using α-titanium as an example. The model takes into account micromechanical deformation mechanisms through dislocation slip along prismatic, basal, and first-order pyramidal systems, as well as tensile twinning. Twin initiation follows a two-conditional criterion requiring that both the resolved shear stress in a twin system and the accumulated pyramidal slip simultaneously reach their critical values. Three-dimensional polycrystalline models are generated using the step-by-step packing method. The crystal plasticity constitutive model describing the deformation behavior of grains is integrated into the boundary-value problem of continuum mechanics, including dynamic governing equations. The three-dimensional problem is solved numerically using the finite element method. The micromechanical model is tested for an α-titanium single crystal along the [0001] direction and a polycrystal consisting of 50 grains. The numerical results reveal that twin propagation is controlled by the critical value of accumulated pyramidal slip, emphasizing the need for experimental calibration. The agreement between numerical and experimental results provides the model validation at the meso- and macroscales.","author":[{"family":"Emelianova","given":"Е"},{"family":"Pisarev","given":"M"},{"family":"Балохонов","given":"РР"},{"family":"Романова","given":"ВА"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/met15111243","URL":"https://doi.org/10.3390/met15111243","source":"openalex"},{"id":"oa:W4411472917","type":"article-journal","title":"Fostering Sustainable Urban Energy Transitions: Backcasting for Positive Energy Districts and Digital Twin strategies in a European context","abstract":"Positive Energy Districts (PEDs) have emerged as a key urban innovation to accelerate the transition toward climate neutrality and sustainability in cities. This study explores the integration of backcasting methodologies and Digital Twin (DT) strategies to advance the development of PEDs. A two-step approach was employed: participatory backcasting workshops to co-create long-term visions and actionable strategies, and DT technology applications tailored to three Urban Living Labs (ULLs) in Vienna (Austria), Gothenburg (Sweden), and Sakarya (Türkiye). The backcasting process facilitated the identification of pathways to energy efficiency, renewable energy integration, and decarbonization, creating a structured yet adaptable roadmap for PED development. DT functionalities—including Digitize, Visualize, Simulate, Predict, and Orchestrate—transformed these plans into operational tools, enabling real-time monitoring, predictive modeling, and adaptive energy management. The study underscores the critical role of stakeholder collaboration in aligning local priorities with sustainability goals and demonstrates the capacity of DT frameworks and PEDs to enhance energy efficiency in diverse urban contexts. However, challenges such as scalability, resource intensity, and sustaining long-term engagement persist. This dual approach highlights the potential of integrating participatory planning with advanced digital tools to bridge the gap between visionary energy goals and practical implementation, offering a replicable framework for urban energy transitions and decarbonization.","author":[{"family":"Malakhatka","given":"Elena"},{"family":"Wallbaum","given":"Holger"},{"family":"Abouebeid","given":"Sara"},{"family":"Hofer","given":"Gerhard"},{"family":"Pooyanfar","given":"Parham"},{"family":"Dursun","given":"İlker"},{"family":"Weber","given":"Gundula"},{"family":"Geçer","given":"Hüseyin"},{"family":"Thuvander","given":"Liane"}],"issued":{"date-parts":[[2025]]},"DOI":"10.7771/3067-4883.1959","URL":"https://doi.org/10.7771/3067-4883.1959","source":"openalex"},{"id":"oa:W4417428933","type":"article-journal","title":"Bridging digital innovation and energy justice: The role of artificial intelligence in advancing energy equity","abstract":"Type of the article: Research ArticleAbstract Global progress toward universal access to affordable, reliable, and clean energy has stalled, with over two billion people still lacking access to clean cooking, and affordability pressures are rising. AI is emerging as an energy-intensive technology and a potential enabler of more equitable energy systems. This paper assesses whether AI vibrancy contributes to advancing energy equity across countries while accounting for differences in economic capacity. The study employs a balanced panel of 36 countries from 2017 to 2023 (252 observations), drawing on the Global AI Vibrancy Tool, World Bank Open Data, and the World Energy Council’s Energy Trilemma Index. Box–Cox transformations were applied to address skewness, and panel econometric models (fixed and random effects) with robust standard errors were estimated. The FE model shows no significant within-country effect of AI vibrancy on energy equity (R² = 0.012). The RE model indicates a positive association: a one-unit increase in the AI vibrancy score results in an improvement of 0.00165 in the energy equity index (p < 0.01). At the same time, GDP per capita exerts a strong and highly significant effect (p < 0.001). The RE model explains 12.4% of the overall variation in energy equity. After correcting for heteroscedasticity and cross-sectional dependence, GDP per capita remains significant, whereas the effect of AI vibrancy weakens to marginal significance (p ≈ 0.09). Country-specific effects further reveal systematic over- and under-performance beyond what AI vibrancy and income predict, underscoring the critical role of governance and institutional quality in shaping energy equity outcomes.AcknowledgmentThe article was prepared as a part of the MSCA4Ukraine project 06030419, European Union’s Horizon 2020 Research and Innovation Programme. Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union, the European Research Executive Agency, or the MSCA4Ukraine Consortium. Neither the European Union nor the European Research Executive Agency, nor the MSCA4Ukraine Consortium as a whole, nor any individual member institutions of the MSCA4Ukraine Consortium can be held responsible for them.","author":[{"family":"Kirichok","given":"Oxana"},{"family":"Orlovska","given":"Yuliia"},{"family":"Zhanseitova","given":"GS"},{"family":"Oriekhova","given":"Alvina"},{"family":"Babaiev","given":"Denys"},{"family":"Havrylenko","given":"Oleksii"},{"family":"Vasylieva","given":"Tetiana"}],"issued":{"date-parts":[[2025]]},"DOI":"10.21511/ee.16(4).2025.11","URL":"https://doi.org/10.21511/ee.16(4).2025.11","source":"openalex"},{"id":"oa:W4414480456","type":"article-journal","title":"Cyber threat in drone systems: bridging real-time security, legal admissibility, and digital forensic solution readiness","abstract":"The rapid expansion of drones otherwise known as Unmanned Aerial Vehicles (UAVs), in critical sectors has increased their exposure to cyber threats such as GPS spoofing, command hijacking, and firmware tampering. Existing forensic tools often fail to address UAV-specific challenges like volatile memory and limited storage, hindering effective investigations. Hence, to address this gap, this study proposes the Enhanced UAV Forensic Framework (EUAVFF) a modular, forensic-by-design model integrating blockchain audit trails, secure logging, telemetry offloading, and UAV-friendly encryption. Validated through a literature review and a stakeholder survey (n = 100), results showed that over 70% of respondents lacked awareness of UAV cyber risks, and current drones were rated poorly in key forensic areas, including tamper-proof logging and legal evidence handling. Only 28% were familiar with drone-specific threats, reflecting critical gaps in preparedness.These findings emphasize the urgent need for proactive forensic integration. EUAVFF offers a structured path to secure, accountable, and resilient UAV operations in increasingly hostile cyber environments.","author":[{"family":"Mohammed","given":"Usman"},{"family":"Omolara","given":"Abiodun"},{"family":"Abiodun","given":"Oludare"},{"family":"Rasheed","given":"Jawad"},{"family":"Osman","given":"Onur"},{"family":"Lar","given":"Patricia"},{"family":"Adeyinka","given":"Philip"},{"family":"Olugbenga","given":"Adeola"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/frcmn.2025.1661928","URL":"https://doi.org/10.3389/frcmn.2025.1661928","source":"openalex"},{"id":"oa:W4416177507","type":"article-journal","title":"A Comprehensive Review of Real-Time Feeder Monitoring and Auditing Systems: Architectures, Technologies, and Analytics for the Smart Grid","abstract":"Abstract: The modernization of power distribution networks into intelligent Smart Grids necessitates a paradigm shift from periodic, manual inspections to continuous, real-time feeder monitoring and auditing. Traditional systems, reliant on legacy SCADA and manual meter reading, are plagued by high Aggregate Technical and Commercial (AT&C) losses, prolonged outage durations, and a lack of granular visibility into feeder health. This review paper comprehensively synthesizes the architecture, technologies, and methodologies underpinning modern Real-Time Feeder Power Line Monitoring and Auditing Systems. We explore the integrated ecosystem of advanced sensing devices, including Smart Meters, Feeder Remote Terminal Units (FRTUs), and Phasor Measurement Units (PMUs), coupled with robust communication protocols like cellular networks and LPWAN. The core of the paper delves into the data analytics pipeline, detailing applications in state estimation, fault detection and location, power quality assessment, and, crucially, real-time energy auditing. A significant focus is placed on techniques for segregating technical losses from non-technical losses (NTLs), such as energy theft, using data-driven algorithms and machine learning. Furthermore, the paper addresses key implementation challenges, including cybersecurity, data management, and economic viability, and highlights future research directions involving Artificial Intelligence (AI), digital twins, and edge computing. The synthesis concludes that the deployment of such integrated systems is indispensable for enhancing grid resilience, optimizing operational efficiency, and achieving significant financial savings for utilities.","author":[{"family":"Jamadade","given":"Vidya"},{"family":"Ghodake","given":"Madhubala"},{"family":"Katakdhond","given":"Samridhi"},{"family":"Godase","given":"Vaibhav"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48175/ijarsct-29476","URL":"https://doi.org/10.48175/ijarsct-29476","source":"openalex"},{"id":"oa:W4416903279","type":"article-journal","title":"Sim2Real Transfer of Imitation Learning of Motion Control for Car-like Mobile Robots Using Digital Twin Testbed","abstract":"Reliable transfer of control policies from simulation to real-world robotic systems remains a central challenge in robotics, particularly for car-like mobile robots. Digital Twin (DT) technology provides a robust framework for high-fidelity replication of physical platforms and bi-directional synchronization between virtual and real environments. In this study, a DT-based testbed is developed to train and evaluate an imitation learning (IL) control framework in which a neural network policy learns to replicate the behavior of a hybrid Model Predictive Control (MPC)–Backstepping expert controller. The DT framework ensures consistent benchmarking between simulated and physical execution, supporting a structured and safe process for policy validation and deployment. Experimental analysis demonstrates that the learned policy effectively reproduces expert behavior, achieving bounded trajectory-tracking errors and stable performance across simulation and real-world tests. The results confirm that DT-enabled IL provides a viable pathway for Sim2Real transfer, accelerating controller development and deployment in autonomous mobile robotics.","author":[{"family":"Mohaghegh","given":"Narges"},{"family":"Wang","given":"Hai"},{"family":"Yazdani","given":"Amirmehdi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/robotics14120180","URL":"https://doi.org/10.3390/robotics14120180","source":"openalex"},{"id":"oa:W4412012642","type":"article-journal","title":"Editorial: Leveraging phenotyping and crop modeling in smart agriculture","abstract":"In recent years, the agricultural sector has witnessed a significant transformation driven by the integration of sensing technologies, big data analytics, and artificial intelligence (Ahmed and Shakoor, 2025). Cutting-edge innovations, notably high-throughput phenotyping and crop modeling, have fundamentally altered our understanding and management of crop systems (Keating and Thorburn, 2018;Yang et al., 2020). In many cases, phenotyping and modeling are closely intertwined: phenotyping provides accurate characterization of plant traits, forming the basis for reliable crop models, while modeling elucidates interactions among phenotypes, genotypes, and the environment, and enables prediction of phenotypic outcomes (Yu et al., 2023;Zhang et al., 2023b). Despite their natural synergy, phenotyping and modeling are still frequently treated as separate domains, limiting their full potential. This research topic aims to close that gap by promoting the development of integrated phenotyping-modeling frameworks to advance smart agriculture. The following sections provide a categorized overview of the contributions to this research topic, highlighting key findings and identifying future directions for this rapidly advancing field.Crop phenotyping, which plays a vital role in gene function analysis, plant breeding, and smart agriculture, can be broadly categorized based on the traits measured.Morphological and structural traits include leaf length, leaf width, leaf area, and leaf angle, while physiological and biological traits encompass chlorophyll content, nitrogen levels, transpiration, and photosynthetic parameters.2D imaging combined with machine vision remains the most widely adopted technique for acquiring plant morphological and structural phenotypes. In this topic, a range of studies have explored deep learning-based approaches tailored for specific plant phenotyping applications, with a particular focus on refining model architectures and technical strategies to enhance detection accuracy, computational efficiency, and adaptability to complex field conditions. Among them, semantic segmentation A region-growing algorithm was used for stem and leaf segmentation, though substantial leaf overlap during the tillering, jointing, and booting stages made the process particularly challenging. Plant height, convex hull volume, plant surface area, and crown area were extracted, enabling a detailed analysis of dynamic changes in wheat throughout its growth cycle. In recent years, ultra-low-altitude UAV-based crosscircling oblique imaging has become a more efficient and cost-effective approach for in-field 3D reconstruction (Fei et al., 2025;Sun et al., 2024). Unlike indoor multi-view imaging systems, 3D phenotyping conducted directly in the field more accurately reflects real-world agricultural conditions and population-level dynamics. and the Nitrogen Balance Index (NBI), measured by a Dualex sensor, alongside machine learning models for nitrogen status assessment. Data from 15 rice varieties under varying nitrogen rates showed chlorophyll saturation at high nitrogen levels, while Flav and NBI remained reliable. Random Forest and Extreme Gradient Boosting achieved high prediction accuracy, with SHAP analysis identifying NBI and Flav from the top two leaves as critical predictors. In recent years, these technologies have been widely applied to precision farmland management. For example, on farms in Brazil, Castilho Silva et al. (2025) used UAV-based multispectral remote sensing to monitor leaf nitrogen content in maize and applied variable-rate fertilization accordingly. Compared to conventional methods, this approach reduced nitrogen input by 6.6% to 35% without compromising yield.Phenotyping equipment is essential for the precise monitoring of plant traits and environmental growth conditions. Liu et al. developed a portable vegetation canopy reflectance (VCR) sensor for continuous operation throughout the day, featuring optical bands at 7","author":[{"family":"Sun","given":"T"},{"family":"Xiao","given":"Liujun"},{"family":"Ata-Ul-Karim","given":"Syed"},{"family":"Ma","given":"Yuntao"},{"family":"Zhang","given":"W"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fpls.2025.1626622","URL":"https://doi.org/10.3389/fpls.2025.1626622","source":"openalex"},{"id":"oa:W4411299301","type":"article-journal","title":"Availability and Use of Digital Technology Among Women With Polycystic Ovary Syndrome: Scoping Review","abstract":"Background: Polycystic ovary syndrome (PCOS) is a common endocrinopathy among women that requires self-management to improve mental and physical health outcomes and reduce risk of comorbidity. Digital technology has rapidly emerged as a valuable self-management tool for people with chronic health conditions. However, little is known about the digital technology available for and used by women with PCOS. . Objective: The purpose of this scoping review was to identify what is known about digital technology currently available and used by women with PCOS for PCOS-specific knowledge, self-management, or social support. Methods: The databases PubMed, Embase, CINAHL, and Compendex were searched using Medical Subject Headings terms for PCOS, digital technology, health knowledge, self-management, and social support. Inclusion criteria were full-text, peer-reviewed publications of primary research from 2010 to 2025 in English about digital technology used for PCOS-specific knowledge, self-management, or social support by women aged 18 years and older with PCOS. Exclusion criteria were articles about pediatric populations and digital technology used for intervention recruitment or by health care providers to diagnose or treat patients. Results: In total, 34 full-text articles met the inclusion criteria. Given the scope of digital technology, eligible studies were grouped into 7 domains: mobile apps (n=14), internet-based programs (eg, Google; n=6), social media (n=6), SMS text message (n=2), machine learning (n=2), artificial intelligence (eg, ChatGPT [OpenAI]; n=3), and web-based intervention platforms (n=1). Findings highlighted participants' varied perceptions of technology usefulness based on reliability of health care information, application features, accuracy of PCOS or fertility prediction, social group engagement, user-friendly interfaces, cultural sensitivity, and accessibility. Conclusions: There is potential for digital technology to transform PCOS self-management, but further design and development are needed to optimize the technologies for women with PCOS. Future research should focus on including end users during the design phase of digital technology, refining predictive models, improving app inclusivity, conducting frequent reliability testing, and enhancing user engagement and support via additional features to promote more comprehensive self-management of PCOS. .","author":[{"family":"Wright","given":"Pamela"},{"family":"Burts","given":"Charlotte"},{"family":"Harmon","given":"Carolyn"},{"family":"Corbett","given":"Cynthia"}],"issued":{"date-parts":[[2025]]},"DOI":"10.2196/68469","URL":"https://doi.org/10.2196/68469","source":"openalex"},{"id":"oa:W4409289543","type":"article-journal","title":"STEP-NC in additive manufacturing: a comprehensive review, architecture, and data model proposal","abstract":"Abstract In modern manufacturing, Digital Thread and Digital Twin technologies integrate and orchestrate data throughout the production lifecycle. To fully realize their potential, it is crucial to address challenges in data integration, management, and interoperability while enhancing system intelligence and contextual awareness. STEP-NC (STandard for the Exchange of Product model data - Numerical Control) emerges as a potential solution, enriching these digital systems with contextual information about products, processes, and machines. While STEP-NC has been extensively studied in machining, its application in Additive Manufacturing (AM) is still emerging. The current reliance on legacy formats like STL and G-code fails to meet the industry’s advancing needs. This work offers a comprehensive review of the current state of STEP-NC development for AM, highlighting a growing interest in its application, despite limited publications and advancements. To bridge these gaps, we propose STEP-NC entity definitions for managing data related to process parameters and operations in Fused Deposition Modeling (FDM) and Laser Metal Deposition (LMD) technologies. STEP-NC facilitates refined data management at the individual layer level, encompassing geometry, process parameters, material properties, and other key aspects. Additionally, we introduce a cyber-physical architecture for STEP-NC in manufacturing, aligned with the ISO 23247 framework. This architecture envisions a robust digital ecosystem driven by standards-based Digital Thread and Digital Twin technologies, with STEP and STEP-NC at its core, supported by essential open standards such as QIF, MTConnect, OPC-UA, and MQTT. By integrating contextual information, it enhances Digital Twin development for virtual monitoring, optimization, knowledge generation, and informed decision-making in manufacturing environments.","author":[{"family":"Rodriguez","given":"Efrain"},{"family":"Álvares","given":"Alberto"},{"family":"Riaño","given":"Cristhian"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s00170-025-15290-8","URL":"https://doi.org/10.1007/s00170-025-15290-8","source":"openalex"},{"id":"oa:W4407028937","type":"article-journal","title":"Digital transformation in the construction industry: Analysing the impact of technological changes on construction processes","abstract":"The relevance of the problem under study lies in the rapid development of digital technologies, which provide unique opportunities for optimising and improving the efficiency of construction production. The purpose of the study is to analyse the impact of digital changes on the technology and organisation of construction activities in Ukraine. The methods of literature review, experimentation, and abduction were used. The study determined which digital technologies, such as BIM, IoT, and AI, are most important to construction organisations. A framework of efficiency-boosting tactics, including personnel training, process optimisation, and technology integration, was created. To visualise data on digital priorities and initiatives, an application was developed. The study emphasised the significance of all-encompassing digital transformation plans and the demand for ongoing innovation in the building sector.","author":[{"family":"Emelianova","given":"Olena"},{"family":"Tytok","given":"Viktoriya"},{"family":"Lavrukhina","given":"Kateryna"},{"family":"Shatrova","given":"Inna"},{"family":"Demydova","given":"Olena"}],"issued":{"date-parts":[[2025]]},"DOI":"10.18537/est.v014.n027.a16","URL":"https://doi.org/10.18537/est.v014.n027.a16","source":"openalex"},{"id":"oa:W4409802747","type":"article-journal","title":"Digital Innovations in Orthognathic Surgery: A Systematic Review of Virtual Surgical Planning, Digital Transfer, and Conventional Model Surgery","abstract":"OBJECTIVES: Orthognathic surgery has evolved due to the use of virtual surgical planning (VSP) and digital model surgery, which are technological advancements replacing conventional approaches with accurate personalised digital models made from computed tomography (CT) or magnetic resonance imaging (MRI) scans. Their integration has enhanced surgical efficiency, patient satisfaction and communication among surgeons and patients, while some challenges such as cybersecurity issues and the requirement for information technology backup have also been noted in hospitals. MATERIALS AND METHODS: From January 2013 to October 2024, this systematic review aimed at orthognathic surgery virtual planning; it was carried out on the basis of a digital library with 437 works from PubMed, Embase, Cochrane, Web of Science and Scopus searched through an initial selection of specific keywords. The final step is filtering out irrelevant studies through scrutiny, resulting in 25 original interventional studies that met inclusion criteria for quality control purposes via bias analysis. RESULTS: In relation to the future of orthognathic surgery, it can be advanced by improving VSP, digital transfer techniques and conventional model surgery with technical innovations that need to meet the challenges. The integration of Artificial Intelligence (AI) into VSP can be an opportunity for its development in the sphere of accuracy and visualisation during surgery with augmented reality (AR) utilisation. Among them are the real-time data integration offered by digital transfer techniques, but they are hindered in cost and standardisation. On the other hand, conventional model surgery may revolutionise with three-dimensional (3D) printing; however, there is a long way to go for conventional model surgery to address time constraints as well as ecological concerns. Compatibility issues, training needs and ethical considerations represent three major obstacles that must be tackled successfully so that surgery will have a bright future. CONCLUSION: Case complexity and patient preferences are important factors that should be considered before making a decision about orthognathic surgery. VSP offers precision for complicated cases. Real-time guidance can be achieved using digital transfer techniques, whereas traditional model surgery provides a tactile, hands-on experience. Analysing digital innovations jointly will enhance orthognathic patient care and education while improving patient safety.","author":[{"family":"Kobravi","given":"Sepehr"},{"family":"Jafari","given":"Aida"},{"family":"Lotfalizadeh","given":"Mohammadhassan"},{"family":"Azimi","given":"Abolfazl"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1111/ocr.12934","URL":"https://doi.org/10.1111/ocr.12934","source":"openalex"},{"id":"oa:W4414080072","type":"article-journal","title":"Digital Development: Reimagining Research Beyond ICT4D","abstract":"This editorial introduces a conceptual framework that reimagines research on Information and Communication Technologies for Development (ICT4D) as “digital development,” recognizing the inseparable intertwining of digital and development trajectories. This framing is aimed at the broader information systems (IS) research community, which includes ICT4D researchers, based both in the Global South and the Global North. Digital development encompasses three dimensions: digital in development (institutional use), digital for development (conscious design for outcomes), and development in a digital world (digital entanglement in development practice.). We argue that this reimagination is necessary for three reasons. First, digital technologies are becoming increasingly entangled with many development initiatives, implying the need to be studied as a duality, not a dualism. Second, we are witnessing the rising complexity of contemporary and emergent development challenges, which are not just limited to the Global South, but to the world at large. Third, the IS and ICT4D research fields have long worked in relative isolation from each other, but they need to synergistically create new theories and methods to address the rising complexities inherent in the “digital” and “development.” We provide a brief overview of the existing ICT4D field to identify critical areas for reconceptualization and expansion. This is then illustrated by examples from four empirical domains, namely humanitarian governance, global health, financial inclusion, and digital nomadism, which are representative of contemporary and emerging digital development challenges. This leads to the development of theoretical, policy and practice, and methodological implications, which provide a basis to formulate a research agenda for digital development.","author":[{"family":"Sahay","given":"Sundeep"},{"family":"Srivastava","given":"Shirish"},{"family":"Barrett","given":"Michael"},{"family":"Davison","given":"Robert"},{"family":"Madon","given":"Shirin"},{"family":"Schlagwein","given":"Daniel"},{"family":"Brown","given":"Irwin"},{"family":"Sarker","given":"Suprateek"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1287/isre.2025.editorial.v36.n3","URL":"https://doi.org/10.1287/isre.2025.editorial.v36.n3","source":"openalex"},{"id":"oa:W4415792992","type":"article-journal","title":"Advancing Cardio-Obstetric Care Through Digital Health Technologies: A Narrative Review","abstract":"Cardiovascular disease is a leading cause of maternal morbidity and mortality. As cardio-obstetric care evolves, digital health technologies including telehealth, wearable devices and remote monitoring are playing an increasingly critical role. These innovations have the potential to enhance cardiovascular screening, risk assessment and disease management across the perinatal continuum. This article explores the role of digital health technologies in advancing cardio-obstetrics care. It focuses on the impact of telehealth, wearable sensors and emerging digital tools on improving maternal cardiovascular outcomes and reducing disparities in care delivery. A narrative review approach was used to synthesize existing literature and clinical insights related to telecardiology, wearable monitoring and digital innovations. Emphasis was placed on applications in pregnancy and post-partum care, as well as on evaluating implementation challenges and equity concerns. Digital health tools improve access to care and facilitate early diagnosis of cardiovascular conditions. Telehealth increases care continuity and patient satisfaction, especially in underserved populations. Wearable devices equipped with photoplethysmography and electrocardiogram sensors enable intermittent, non-invasive monitoring, aiding early detection of arrhythmias and hypertensive disorders. Furthermore, novel technologies such as digital twins, natural language processing and virtual reality show potential to personalize care and support medical education. Despite these advancements, key barriers persist, including data privacy concerns, unequal access to technology and algorithmic bias. Digital health technologies are transforming cardio-obstetrics care by enabling proactive management and expanding access. However, for these tools to deliver equitable benefits, targeted efforts are needed to address privacy, infrastructure and literacy challenges. Future efforts should focus on integrating digital health into routine maternal care, promoting digital literacy, ensuring equitable technology access and improving interoperability with electronic health records. Additionally, ongoing evaluation through clinical trials in high-risk pregnancies and ethical safeguards to mitigate algorithmic bias will be essential to ensure safe, scalable and inclusive implementation of these innovations in maternal cardiovascular care.","author":[{"family":"Awoyemi","given":"Toluwalase"},{"family":"Tolu-Akinnawo","given":"Oluwaremilekun"},{"family":"Mahtani","given":"Arun"},{"family":"Padda","given":"Inderbir"},{"family":"Ogunniyi","given":"Kayode"},{"family":"Bolakalerufai","given":"Ikeoluwapo"},{"family":"Olusanya","given":"Abiola"},{"family":"Adeleke","given":"Oluwaseun"},{"family":"Amarachi","given":"Chituru"},{"family":"Akinmoju","given":"Olumide"},{"family":"Uche-Orji","given":"Christabel"},{"family":"Fattah","given":"Mina"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/ehf2.15426","URL":"https://doi.org/10.1002/ehf2.15426","source":"openalex"},{"id":"oa:W4412602460","type":"article-journal","title":"The Impact of Rural Digital Economy Development on Agricultural Carbon Emission Efficiency: A Study of the N-Shaped Relationship","abstract":"This study investigates the impact of rural digital economy development on agricultural carbon emission efficiency, aiming to elucidate the intrinsic mechanisms and pathways through which digital technology enables low-carbon transformation in agriculture, thereby contributing to the achievement of agricultural carbon neutrality goals. Based on provincial-level panel data from China spanning 2011 to 2022, this study examines the relationship between the rural digital economy and agricultural carbon emission efficiency, along with its underlying mechanisms, using bidirectional fixed effects models, mediation effect analysis, and Spatial Durbin Models. The results indicate the following: (1) A significant N-shaped-curve relationship exists between rural digital economy development and agricultural carbon emission efficiency. Specifically, agricultural carbon emission efficiency exhibits a three-phase trajectory of “increase, decrease, and renewed increase” as the rural digital economy advances, ultimately driving a sustained improvement in efficiency. (2) Industrial integration acts as a critical mediating mechanism. Rural digital economy development accelerates the formation of the N-shaped curve by promoting the integration between agriculture and other sectors. (3) Spatial spillover effects significantly influence agricultural carbon emission efficiency. Due to geographical proximity, regional diffusion, learning, and demonstration effects, local agricultural carbon emission efficiency fluctuates with changes in neighboring regions’ digital economy development levels. (4) The relationship between rural digital economy development and agricultural carbon emission efficiency exhibits a significant inverted N-shaped pattern in regions with higher marketization levels, planting-dominated areas of southeast China, and digital economy demonstration zones. Further analysis reveals that within rural digital economy development, production digitalization and circulation digitalization demonstrate a more pronounced inverted N-shaped relationship with agricultural carbon emission efficiency. This study proposes strategic recommendations to maximize the positive impact of the rural digital economy on agricultural carbon emission efficiency, unlock its spatially differentiated contribution potential, identify and leverage inflection points of the N-shaped relationship between digital economy development and emission efficiency, and implement tailored policy portfolios—ultimately facilitating agriculture’s green and low-carbon transition.","author":[{"family":"Feng","given":"Yong"},{"family":"Wang","given":"Shuokai"},{"family":"Cao","given":"Fangping"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/agriculture15151583","URL":"https://doi.org/10.3390/agriculture15151583","source":"openalex"},{"id":"oa:W4415030178","type":"manuscript","title":"From Mind to Machine: The Rise of Manus AI as a Fully Autonomous Digital Agent","abstract":"Manus AI is a general-purpose AI agent introduced in early 2025, marking a significant advancement in autonomous artificial intelligence. Developed by the Chinese startup Monica.im, Manus is designed to bridge the gap between \"mind\" and \"hand\" - combining the reasoning and planning capabilities of large language models with the ability to execute complex, end-to-end tasks that produce tangible outcomes. This paper presents a comprehensive overview of Manus AI, exploring its core technical architecture, diverse applications across sectors such as healthcare, finance, manufacturing, robotics, and gaming, as well as its key strengths, current limitations, and future potential. Positioned as a preview of what lies ahead, Manus AI represents a shift toward intelligent agents that can translate high-level intentions into real-world actions, heralding a new era of human-AI collaboration.","author":[{"family":"Shen","given":"Minjie"},{"family":"Li","given":"Yanshu"},{"family":"Chen","given":"Lulu"},{"family":"Fan","given":"Zhichao"},{"family":"Li","given":"Yanhang"},{"family":"Yang","given":"Qikai"},{"family":"Yang","given":"Haochen"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2505.02024","URL":"https://doi.org/10.48550/arxiv.2505.02024","source":"openalex"},{"id":"oa:W7123706991","type":"article-journal","title":"Innovative Cyber-Physical/Electronic AI-Assisted Digital Twin Model of Small Energy Harvesting Cantilever Power Generators","abstract":"The paper deals with the design of a Digital Twin model of an energy harvesting cantilever beam for low frequency energy harvesting applications and specifically with a digital model matching simulations corresponding with Finite Element Method solutions in order to validate the model. The physical behavior is based on the main parameters to be investigated. The finite elements analysis is geometrically and parametrically carried out for a small PZT5A device of the orders of millimeters and is optimized to take into consideration the relationships between tip displacement, generated voltages and vibration gravitational forces for standard industrial applications in the acceleration range between 0.5 and 2 g. Then a procedure to integrate the Digital Twin into a design framework has been developed, including an artificial intelligence algorithm that supports the modelling of the real behavior of the device. The paper is devoted to help researchers involved in a Digital Twin adoption in the field of electronic design and of the physical characterization of low frequency energy harvesting devices exclusively using open-source tools.","author":[{"family":"Massaro","given":"Alessandro"},{"family":"Fanizza","given":"Giuseppe"},{"family":"Starace","given":"Giuseppe"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19020390","URL":"https://doi.org/10.3390/en19020390","source":"openalex"},{"id":"oa:W4410951482","type":"article-journal","title":"Guided Reinforcement Learning with Twin Delayed Deep Deterministic Policy Gradient for a Rotary Flexible-Link System","abstract":"This study proposes a robust methodology for vibration suppression and trajectory tracking in rotary flexible-link systems by leveraging guided reinforcement learning (GRL). The approach integrates the twin delayed deep deterministic policy gradient (TD3) algorithm with a linear quadratic regulator (LQR) acting as a guiding controller during training. Flexible-link mechanisms common in advanced robotics and aerospace systems exhibit oscillatory behavior that complicates precise control. To address this, the system is first identified using experimental input-output data from a Quanser® virtual plant, generating an accurate state-space representation suitable for simulation-based policy learning. The hybrid control strategy enhances sample efficiency and accelerates convergence by incorporating LQR-generated trajectories during TD3 training. Internally, the TD3 agent benefits from architectural features such as twin critics, delayed policy updates, and target action smoothing, which collectively improve learning stability and reduce overestimation bias. Comparative results show that the guided TD3 controller achieves superior performance in terms of vibration damping, transient response, and robustness, when compared to conventional LQR, fuzzy logic, neural networks, and GA-LQR approaches. Although the controller was validated using a high-fidelity digital twin, it has not yet been deployed on the physical plant. Future work will focus on real-time implementation and structural robustness testing under parameter uncertainty. Overall, this research demonstrates that guided reinforcement learning can yield stable and interpretable policies that comply with classical control criteria, offering a scalable and generalizable framework for intelligent control of flexible mechanical systems.","author":[{"family":"Enderica","given":"Carlos"},{"family":"Llata","given":"JR"},{"family":"Torreferrero","given":"Carlos"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/robotics14060076","URL":"https://doi.org/10.3390/robotics14060076","source":"openalex"},{"id":"oa:W4414139457","type":"article-journal","title":"Digital Transformation of Cultural Heritage: Prospects and Threats","abstract":"The research investigates the impact of digital transformation on culture, particularly cultural heritage, by examining how preservation, representation, and access are evolving in the context of global and Ukrainian-European digitalization. It aims to analyze how digital technologies reshape heritage practices, highlight the challenges they pose, and propose possible solutions. An assessment of prominent initiatives — such as Europeana, Euromuseum, Twin it! World Digital Library, Doctoral Program in Cultural Heritage, Ark, Museum of Stolen Art, and ResearchUA — illustrates that digital tools not only broaden access to cultural resources but also foster new forms of public participation, multicultural exchange, and collaborative digital creation. In this regard, the Internet emerges as a multifunctional space that serves as a technology, a platform for unity, a channel of communication, and a means of cooperation. Of particular significance is the Museum of Stolen Art project launched in Ukraine in 2023, which stands as a unique model of digital innovation in heritage preservation. Nevertheless, the study identifies pressing challenges accompanying digitalization, including fragmented platforms, unstable formats, unequal access, legal and ethical uncertainties, and funding constraints. Addressing these issues requires understanding digitalization not merely as a technological process but as a socio-cultural phenomenon that fundamentally reshapes cultural memory, identity, and institutional responsibility. The findings of this research thus provide practical value for designing effective strategies, educational initiatives, and institutional practices to advance the preservation, accessibility, and sustainability of cultural heritage in the digital era.","author":[{"family":"Melnyk","given":"Roman"},{"family":"Volkova","given":"Galyna"},{"family":"Hvozdetska","given":"Mariia"},{"family":"Bashmanivskyi","given":"Oleksii"},{"family":"Perederii","given":"Iryna"}],"issued":{"date-parts":[[2025]]},"DOI":"10.63931/ijchr.v7isi1.381","URL":"https://doi.org/10.63931/ijchr.v7isi1.381","source":"openalex"},{"id":"oa:W4413961395","type":"article-journal","title":"Exploring electric vehicle consumer behavior: impact of digital innovation, environmental concern, perceived value, and social influence on purchase intentions","abstract":"Background Understanding the drivers and boundary conditions of electric vehicle (EV) adoption is critical to fostering sustainable transportation. Building on perceived value and planned behavior theories, this study proposes a moderated mediation model in which perceived value influences both sustainability perception and purchase intentions, with household income, technology trust, and environmental knowledge serving as moderators. Methods A cross-sectional survey of 496 licensed drivers familiar with EVs was conducted using validated multi-item scales. Data were analyzed in R using confirmatory factor analysis and structural equation modeling (lavaan), incorporating product-indicator interactions and 5,000-sample bootstrapping to test the direct, moderating, and mediating effects. Results Consumers’ perceived value has a positive effect on sustainability perception (0.122, p < 0.001) and purchase intentions (0.002, p < 0.001). Household income also strengthens the relationship between perceived value and purchase intention (0.043, p < 0.001). Digital innovation (0.285, p < 0.001) and environmental concerns (0.411, p < 0.001) dynamically influenced the perception of sustainability at a significant level, although social influence was not significant. Compared with other variables, sustainability perception had the greatest effect on consumers’ intention to buy an electric car (0.624, p < 0.001) and served as a mediator in three out of four indirect connections between perceived value and purchase intention. The moderating effects of technology trust and environmental knowledge were not supported. Conclusion These findings highlight the central roles of value and sustainability perceptions in EV adoption and identify income as a key boundary condition. Practical implications include tailoring incentives by income segment, investing in user-centric digital platforms, and emphasizing both economic and environmental benefits. Theoretically, this study extends technology acceptance models by integrating sustainability constructs and underscores the nuanced impact of socioeconomic factors on green consumer behavior.","author":[{"family":"Kottala","given":"Sri"},{"family":"Chanagala","given":"Shankar"},{"family":"Balaji","given":"C"},{"family":"Reddy","given":"Vijeth"},{"family":"Babu","given":"GNPV"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/frsc.2025.1655074","URL":"https://doi.org/10.3389/frsc.2025.1655074","source":"openalex"},{"id":"oa:W4414452310","type":"article-journal","title":"Impact of Point Density Variation in Aerial Photogrammetric Point Clouds on Feature Extraction for the development of Cultural Heritage Digital Twin","abstract":"Abstract. The development of Digital Twins for cultural heritage applications depends highly on accurate and detailed 3D representations of historical structures. Aerial photogrammetry has emerged as a popular remote sensing technique for capturing such Cultural Heritage (CH) structures, primarily due to its high-resolution, detailed outputs and cost-effectiveness. However, the quality of the derived photogrammetric point clouds, particularly point density, significantly influences the efficiency and accuracy of downstream procedures such as feature extraction to be used for different applications. This research work investigates how variations in point density affect the detection and segmentation of windows and rooftops, which are two key architectural features for the development of Energy Digital Twins (EDT) for the analysis of energy consumption patterns of the CH buildings. Using aerial photogrammetric datasets, we generated point clouds using the photogrammetric images and their accurate image orientations with a bundle adjustment processing. After that, we tested the point cloud at different densities (ranging from original resolution to 1/16th of the original point density) by controlled uniform down-sampling of an original high-density cloud. We evaluated an automated deep learning-based method segmentation of the windows and rooftop features from the point cloud datasets. The investigation indicates a strong correlation between point density and feature extraction accuracy, with a clear decline in detection performance if the subsampling goes below 1/8th of the original point density, which is around 20 points/m². Rooftop features exhibited greater resilience to reduced density compared to window features and were still detected even with down-sampled point clouds. The research work proposes a density-aware workflow for CH Digital Twin development and emphasises the need for strategic planning in aerial data acquisition for heritage documentation for the optimisation of aerial photogrammetric data practices and to enhance the reliability of Digital Twins in cultural heritage conservation.","author":[{"family":"Yadav","given":"Yogender"},{"family":"Zlatanova","given":"Sisi"},{"family":"Boccardo","given":"Piero"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5194/isprs-annals-x-m-2-2025-373-2025","URL":"https://doi.org/10.5194/isprs-annals-x-m-2-2025-373-2025","source":"openalex"},{"id":"oa:W4411835477","type":"article-journal","title":"Threat Analysis of Power System Case Study via STRIDE Threat Model in Digital Twin Real-time Platform","abstract":"Threat modeling is a pivotal analytical procedure employed to specify the potential threats and select the appropriate security measures. It helps reduce the risk of cyber-attacks that may target several components of the cyber-physical power systems. Accordingly, identifying potential cyber threats and assessing their consequences is an imperative aspect of the supervision and monitoring of power systems. This paper presents a threat analysis scheme of a power system case study utilizing the STRIDE threat model methodology. The developed model addresses several attack and threat scenarios combined into an attack graph model. In terms of security measures, this paper introduces a Secure, Encrypted, Authenticated Communication Channel (SEAC2), which is a two-level encryption method to secure the communication layer. Further, this study introduces an open-source Digital Twin (DT) platform that enables a real-time comprehensive assessment of the system's energy dynamics. It also prioritizes threat detection as another crucial aspect. A real case study from the Jordanian electrical network has been utilized in this study to validate the proposed platform.","author":[{"family":"Muhsen","given":"Hani"},{"family":"Allahham","given":"Adib"},{"family":"Qandil","given":"Moath"},{"family":"Alkhraibat","given":"Asma"},{"family":"Almomani","given":"Ahmad"},{"family":"Al-Halhouli","given":"Ala‘aldeen"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1051/epjconf/202533003010","URL":"https://doi.org/10.1051/epjconf/202533003010","source":"openalex"},{"id":"oa:W4415917392","type":"article-journal","title":"Connected, digitalized wire arc additive manufacturing: utilizing data in the internet of production to enable industrie 4.0","abstract":"This work explores the potential of connected, digitalized Wire Arc Additive Manufacturing (WAAM) within the framework of Industrie 4.0, analyzing it through distinct process layers: workpiece, assembly, and product. Each layer presents unique timeframes and stakeholder interactions, necessitating varied data infrastructure demands, including a consideration of data security and privacy challenges. The workpiece layer mostly covers the local production setup and is thus directly coupled with the product and process quality as well as maintaining a safe operation. In the assembly layer, ensuring interoperability among diverse stakeholders is crucial, requiring clear definitions of responsibilities and access rights to enhance data exchange. The product layer prioritizes the reliability and trustworthiness of information for informed decision-making, advocating for solutions that guarantee authenticity and verifiability while addressing privacy concerns through techniques like privacy-preserving computing. The paper identifies a critical gap in real-world applications of these concepts in additive manufacturing. It proposes a data-driven quality control approach to enhance process and product quality in arc welding, leveraging digital shadows to create effective interfaces within production networks. This approach has demonstrated potential reductions in welding fume emissions by 12-40%, alongside connected applications that minimize exposure and energy consumption.","author":[{"family":"Mann","given":"Samuel"},{"family":"Pennekamp","given":"Jan"},{"family":"Ay","given":"Muzaffer"},{"family":"Behery","given":"Mohamed"},{"family":"Oster","given":"Lukas"},{"family":"Ebert","given":"Benjamin"},{"family":"Sharma","given":"Rahul"},{"family":"Abel","given":"Dirk"},{"family":"Lakemeyer","given":"Gerhard"},{"family":"Reisgen","given":"Uwe"},{"family":"Wehrle","given":"Klaus"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-15250-y","URL":"https://doi.org/10.1038/s41598-025-15250-y","source":"europepmc"},{"id":"oa:W4407045420","type":"article-journal","title":"Multi-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitals","abstract":"This paper focuses on the elective surgical scheduling problem with multi-resource constraints, including material resources, such as operating rooms (ORs) and non-operating room (NOR) beds, and human resources (i.e., surgeons, anesthesiologists, and nurses). The objective of multi-resource constrained elective surgical scheduling (MESS) is to simultaneously minimize the average recovery completion time for all patients, the average overtime for medical staffs, and the total medical cost. This problem can be formulated as a mixed integer linear multi-objective optimization model, and the honey badger algorithm based on the Nash equilibrium (HBA-NE) is developed for the MESS. Experimental studies were carried out to test the performance of the proposed approach, and the performance of the proposed surgical scheduling scheme was validated. Finally, to narrow the gap between the optimal surgical scheduling solution and actual hospital operations, digital twin (DT) technology is adopted to build a physical-virtual hospital surgery simulation model. The experimental results show that by introducing a digital twin, the physical and virtual spaces of the smart hospital can be integrated to visually simulate and verify surgical processes.","author":[{"family":"Xue","given":"Jun"},{"family":"Li","given":"Zhi"},{"family":"Zhang","given":"Shuangli"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-87867-y","URL":"https://doi.org/10.1038/s41598-025-87867-y","source":"pubmed"},{"id":"oa:W4411351242","type":"article-journal","title":"A Generic Modeling Method of Multi-Modal/Multi-Layer Digital Twins for the Remote Monitoring and Intelligent Maintenance of Industrial Equipment","abstract":"Digital twin (DT) is a useful tool for the remote monitoring, analyzing, controlling, etc. of industrial equipment in a harsh working environment unfriendly to human workers. Although much research has been devoted to DT modeling methods, there are still limitations. For example, (1) existing DT modeling methods are usually focused on specific types of equipment rather than being generally applicable to different types of equipment and requirements. (2) Existing DT models usually emphasize working condition monitoring and have relatively limited capability for modeling the operation and maintenance mechanism of the equipment for further decision making. (3) How to integrate artificial intelligence algorithms into DT models still requires further exploration. In this regard, a systematic and general DT modeling method is proposed for the remote monitoring and intelligent maintenance of industrial equipment. The DT model contains a multi-modal digital model, a multi-layer status model, and an intelligent interaction model driven by a kind of human-readable/computer-deployable event-state knowledge graph. Using the model, the dynamic workflows, working mechanisms, working status, workpiece logistics, monitoring data, and intelligent functions, etc., during the remote monitoring and maintenance of industrial equipment can be realized. The model was verified through three different DT modeling scenarios of a robot-based carbon block polishing processing line.","author":[{"family":"Yang","given":"Maolin"},{"family":"Cao","given":"Yifan"},{"family":"Shangguan","given":"Siwei"},{"family":"Chen","given":"Xin"},{"family":"Jiang","given":"Pingyu"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/machines13060522","URL":"https://doi.org/10.3390/machines13060522","source":"openalex"},{"id":"oa:W4415135420","type":"article-journal","title":"Optimising energy usage of a semi-continuous fluidised bed dryer using digital twin technology and energy management strategies","abstract":"Pharmaceutical manufacturers are under increasing pressure to reduce energy consumption and enhance sustainability to meet net-zero emission targets. Achieving these goals requires advanced methodologies capable of capturing complex process dynamics and driving realtime optimisation. Industry 4.0 technologies – particularly Digital Twins (DTs) – offer significant potential, yet their effectiveness can be limited by undetected process anomalies and subtle energy-performance deviations. This study presents a novel DT integrated framework that combines energy management techniques, statistical monitoring, and a newly defined Energy Performance Indicator (EnPI) to optimise a semicontinuous fluidised bed dryer (FBD) within the GEA Consigma25 line at the Diamond Pilot Plant, University of Sheffield. Realtime experimental data and DT outputs were analysed using CUSUM (Cumulative Sum) deviation analysis, enabling sensitive detection of energy-moisture performance shifts that the DT alone could not identify. Results highlight 60°C as the optimal drying air temperature, delivering superior energy efficiency across liquid-to-solid ratios of 0.18 and 0.30, with opportunities for further refinement within the 50–60°C range. By bridging gaps in realtime multi‑objective monitoring, this integrated approach provides actionable insights for energy-efficient, quality-driven process control and establishes a scalable pathway towards sustainable pharmaceutical manufacturing.","author":[{"family":"Ntamo","given":"Donald"},{"family":"Kuliss","given":"Vladislavs"},{"family":"Soulatiantork","given":"Payam"},{"family":"Omar","given":"Chalak"},{"family":"Zandi","given":"Mohammad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/19397038.2025.2573275","URL":"https://doi.org/10.1080/19397038.2025.2573275","source":"openalex"},{"id":"oa:W4413407758","type":"article-journal","title":"Modeling the effects of slip, twinning, and notch on the deformation of single-crystal austenitic manganese steel","abstract":"The objective of this work is to deconvolute the interaction of slip, twinning, and notch on the deformation response of an austenitic manganese (Hadfield) steel using detailed finite element simulations. The simulations employ a rate-dependent crystal plasticity constitutive model that incorporates both slip and twinning deformation mechanisms. The model accounts for the spatially non-uniform appearance of new twin-related orientations, hardening due to slip–twin interactions, and modified properties of the twinned crystal. Limited experiments on single-crystal dog-bone and single-edge notch specimens, with two crystal orientations, are also conducted to aid the simulation. Several features of the experimental observations are accurately captured in the simulations. For example, simulations accurately capture distinct stress–strain responses associated with different crystallographic orientations, including variations in initial hardening behavior followed by either decreasing or increasing hardening depending on the dominant deformation mechanisms. The simulation also captures the observed orientation-dependent asymmetric deformation of the notch in single-edge notch specimens. Additionally, by selectively activating deformation mechanisms, the role of twinning is isolated and its influence on both global and local response is clearly demonstrated. These results provide a mechanistic understanding of how deformation mode interactions and local geometry (i.e., notch) influence the response of these materials.","author":[{"family":"Virupakshi","given":"Saketh"},{"family":"Zheng","given":"Xinzhu"},{"family":"Frydrych","given":"Karol"},{"family":"Karaman","given":"İbrahim"},{"family":"Srivastava","given":"Abhinav"},{"family":"Kowalczyk-Gajewska","given":"K"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.ijplas.2025.104453","URL":"https://doi.org/10.1016/j.ijplas.2025.104453","source":"openalex"},{"id":"oa:W4412490433","type":"article-journal","title":"Impact of regional digital transformation on public health: an empirical analysis based on 31 provinces in China","abstract":"BACKGROUND: With the rapid development of digital transformation driven by big data and artificial intelligence in China, the field of public health is undergoing profound transformations. This study introduces technological innovation as a mediating variable into an analytical framework to systematically explore the impact of digital transformation on public health and the underlying mechanism. METHODS: Using panel data from 31 provinces in mainland China from 2010 to 2019, this study empirically investigated the impact of digital transformation on public health via two-way fixed-effect analysis. Moreover, the internal mechanism was determined by testing the mediation effect of technological innovation. RESULTS: The research findings showed a significant positive relationship between digital transformation and improvements in public health. Mediation effect analysis indicated that digital transformation enhances public health by fostering technological innovation. Additional analysis revealed that the promoting effect in the central and western regions of China is more pronounced than that in the eastern regions. CONCLUSION: This study unveils that digital transformation significantly improves public health, especially through enhanced technological innovations that achieve health improvement, and proposes specific recommendations for future health development strategies. It not only offers a scientific foundation for government digital health policies but also provides a forward-looking perspective for academics engaged in the field of digital transformation and public health. Additionally, it empirically verifies the differential impacts of digital technology on public health across regions, provides scientific references for optimizing health resource allocation and narrowing regional health gaps, and contributes empirical findings toward achieving a Healthy China.","author":[{"family":"Xu","given":"Xiping"},{"family":"Zhang","given":"Yuanyuan"},{"family":"Wang","given":"Yadong"},{"family":"Zhao","given":"Chenjian"},{"family":"Zhang","given":"Yuhang"},{"family":"Xie","given":"Xuefeng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1186/s12889-025-23670-8","URL":"https://doi.org/10.1186/s12889-025-23670-8","source":"openalex"},{"id":"oa:W4417124812","type":"article-journal","title":"Artificial Intelligence Physician Avatars for Patient Education: A Pilot Study","abstract":"Background: Generative AI and synthetic media have enabled realistic human Embodied Conversational Agents (ECAs) or avatars. A subset of this technology replicates faces and voices to create realistic likenesses. When combined with avatars, these methods enable the creation of “digital twins” of physicians, offering patients scalable, 24/7 clinical communication outside the immediate clinical environment. This study evaluated surgical patient perceptions of an AI-generated surgeon avatar for postoperative education. Methods: We conducted a pilot feasibility study with 30 plastic surgery patients at Mayo Clinic, USA (July–August 2025). A bespoke interactive surgeon avatar was developed in Python using the HeyGen IV model to reproduce the surgeon’s likeness. Patients interacted with the avatar through natural voice queries, which were mapped to predetermined, pre-recorded video responses covering ten common postoperative topics. Patient perceptions were assessed using validated scales of usability, engagement, trust, eeriness, and realism, supplemented by qualitative feedback. Results: The avatar system reliably answered 297 of 300 patient queries (99%). Usability was excellent (mean System Usability Scale score = 87.7 ± 11.5) and engagement high (mean 4.27 ± 0.23). Trust was the highest-rated domain, with all participants (100%) finding the avatar trustworthy and its information believable. Eeriness was minimal (mean = 1.57 ± 0.48), and 96.7% found the avatar visually pleasing. Most participants (86.6%) recognized the avatar as their surgeon, although many still identified it as artificial; voice resemblance was less convincing (70%). Interestingly, participants with prior exposure to deepfakes demonstrated consistently higher acceptance, rating usability, trust, and engagement 5–10% higher than those without prior exposure. Qualitative feedback highlighted clarity, efficiency, and convenience, while noting limitations in realism and conversational scope. Conclusions: The AI-generated physician avatar achieved high patient acceptance without triggering uncanny valley effects. Transparency about the synthetic nature of the technology enhanced, rather than diminished, trust. Familiarity with the physician and institutional credibility likely played a key role in the high trust scores observed. When implemented transparently and with appropriate safeguards, synthetic physician avatars may offer a scalable solution for postoperative education while preserving trust in clinical relationships.","author":[{"family":"Haider","given":"Syed"},{"family":"Prabha","given":"Srinivasagam"},{"family":"Gomez-Cabello","given":"Cesar"},{"family":"Genovese","given":"Ariana"},{"family":"Collaço","given":"Bernardo"},{"family":"Wood","given":"Nadia"},{"family":"Lifson","given":"Mark"},{"family":"Bagaria","given":"Sanjay"},{"family":"Tao","given":"Cui"},{"family":"Forte","given":"Antonio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/jcm14238595","URL":"https://doi.org/10.3390/jcm14238595","source":"openalex"},{"id":"oa:W4414702782","type":"article-journal","title":"Large language models forecast patient health trajectories enabling digital twins","abstract":"Generative artificial intelligence is revolutionizing digital twin development, enabling virtual patient representations that predict health trajectories, with large language models (LLMs) showcasing untapped clinical forecasting potential. We developed the Digital Twin-Generative Pretrained Transformer (DT-GPT), extending LLM-based forecasting solutions to clinical trajectory prediction. DT-GPT leverages electronic health records without requiring data imputation or normalization and overcomes real-world data challenges such as missingness, noise, and limited sample sizes. Benchmarking on non-small cell lung cancer, intensive care unit, and Alzheimer's disease datasets, DT-GPT outperformed state-of-the-art machine learning models, reducing the scaled mean absolute error by 3.4%, 1.3% and 1.8%, respectively. It maintained distributions and cross-correlations of clinical variables, and demonstrated explainability through a human-interpretable interface. Additionally, DT-GPT's ability to perform zero-shot forecasting highlights potential advantages of LLMs as clinical forecasting platforms, proposing a path towards digital twin applications in clinical trials, treatment selection, and adverse event mitigation.","author":[{"family":"Makarov","given":"Nikita"},{"family":"Bordukova","given":"Maria"},{"family":"Quengdaeng","given":"Papichaya"},{"family":"Garger","given":"Dániel"},{"family":"Rodriguezesteban","given":"Raul"},{"family":"Schmich","given":"Fabian"},{"family":"Menden","given":"Michael"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41746-025-02004-3","URL":"https://doi.org/10.1038/s41746-025-02004-3","source":"openalex"},{"id":"oa:W4409222030","type":"article-journal","title":"Integrating Digital Twins and Machine Learning for Advanced Control in Green Hydrogen Production","abstract":"The successful reduction of carbon emissions in major sectors such as heavy industry and long-distance transport depends crucially on the ability to produce green hydrogen on a large scale. This involves generating hydrogen via water electrolysis, utilizing power sourced from renewable energies. However, persistent challenges, such as dynamic inefficiencies, material degradation, and renewable intermittency, demand a paradigm shift from static control strategies to adaptive, self-optimizing systems. This perspective argues that the synergistic integration of digital twins (DTs) and machine learning (ML) offers a transformative framework for real-time optimization, predictive maintenance, and resilient grid integration. By synthesizing physics-based modeling with data-driven intelligence, DT-ML systems enable closed-loop control architectures that dynamically adapt to operational uncertainties. We analyze the technical foundations of this integration, address critical barriers, and propose actionable pathways for stakeholders to accelerate the hydrogen economy's transition from promise to practice.","author":[{"family":"Feng","given":"Zhiming"},{"family":"Luo","given":"Yue"},{"family":"Li","given":"Da"},{"family":"Pan","given":"Jianxin"},{"family":"Tan","given":"Rui"},{"family":"Chen","given":"Yi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.23919/chain.2025.000003","URL":"https://doi.org/10.23919/chain.2025.000003","source":"openalex"},{"id":"oa:W4409634005","type":"article-journal","title":"Research and Prospects of Digital Twin-Based Fault Diagnosis of Electric Machines","abstract":"This paper focuses on the application of digital twins in the field of electric motor fault diagnosis. Firstly, it explains the origin, concept, key technology and application areas of digital twins, compares and analyzes the advantages and disadvantages of digital twin technology and traditional methods in the application of electric motor fault diagnosis, discusses in depth the key technology of digital twins in electric motor fault diagnosis, including data acquisition and processing, digital modeling, data analysis and mining, visualization technology, etc., and enumerates digital twin application examples in the fields of induction motors, permanent magnet synchronous motors, wind turbines and other motor fields. A concept of multi-phase synchronous generator fault diagnosis based on digital twins is given, and challenges and future development directions are discussed.","author":[{"family":"Hu","given":"Jia"},{"family":"Han","given":"Xiao"},{"family":"Ye","given":"Zhihao"},{"family":"Luo","given":"Ningzhao"},{"family":"Zhou","given":"Minhao"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/s25082625","URL":"https://doi.org/10.3390/s25082625","source":"europepmc"},{"id":"oa:W4413439620","type":"article-journal","title":"Current progress of digital twin construction using medical imaging","abstract":"Medical imaging is fundamental to digital twin technology, enabling patient-specific virtual models of anatomy and physiology. By integrating high-resolution modalities (Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), ultrasound) with computational frameworks, recent imaging advances now support real-time simulation, predictive modeling, and earlier disease detection. Such capabilities directly inform individualized treatment planning and contribute to more precise, personalized care. Despite remaining challenges-complex anatomical modeling, multimodal integration, and high computational demands-recent advances in imaging and machine learning have significantly enhanced the accuracy and clinical utility of digital twins. The main contributions of our review are: (1) a system-by-system classification of methodologies; (2) evidence that advanced imaging modalities have improved diagnostic accuracy, treatment effectiveness, and patient outcomes beyond conventional approaches; and (3) identification of remaining technical bottlenecks. We further analyze key technical barriers-such as data scarcity and computational complexity-and outline future directions (e.g., AI-driven data augmentation, real-time model optimization) to unlock digital twins' full potential in precision medicine.","author":[{"family":"Zhao","given":"Feng"},{"family":"Wu","given":"Yizhou"},{"family":"Hu","given":"Mingzhe"},{"family":"Chang","given":"Chih‐wei"},{"family":"Liu","given":"Ruirui"},{"family":"Qiu","given":"Richard"},{"family":"Yang","given":"Xiaofeng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/acm2.70226","URL":"https://doi.org/10.1002/acm2.70226","source":"openalex"},{"id":"oa:W4406331418","type":"article-journal","title":"Comparative Study of Digital Twin Developed in Unity and Gazebo","abstract":"Digital twin (DT) technology has become a cornerstone in the simulation and analysis of real-world systems, offering unparalleled insights into the lifecycle management of physical assets. By providing a real-time synchronized replica of the physical entity, DTs enable predictive maintenance, performance optimization, and lifecycle extension, which are pivotal for industries aiming for digital transformation. This paper presents a comprehensive comparative study of DT development of a robotic arm using two prominent simulation platforms: Unity and Gazebo. Unity, with its roots in the gaming industry, offers robust real-time rendering and a user-friendly interface, making it a versatile choice for various industries. Gazebo, traditionally used in robotics, provides detailed physics simulations and sensor data emulation, which is ideal for precise engineering applications. We explored the performance of both platforms in creating accurate and dynamic digital replicas. Through qualitative and quantitative analyses, this study evaluates each platform’s strengths and limitations. The study assesses these platforms across key performance metrics such as accuracy, latency, graphic quality, and integration with the Robot Operating System (ROS). The DTs were developed using a consistent physical setup and communication layer to ensure fair comparisons. The results indicate that Unity performed better in terms of accurately mimicking the robotic arm with lower latency, making it ideal for applications requiring high-fidelity visualizations and real-time responsiveness. However, Gazebo excels in its ease of ROS integration and cost-effectiveness, making it a suitable choice for smaller robotics and automation projects. This study conducts an empirical comparison of these platforms in terms of their performance in creating DTs of robotic arms which is not readily available. This paper aims to guide developers and organizations in selecting the appropriate platform for their DT initiatives, ensuring efficient resource utilization and optimal outcomes.","author":[{"family":"Singh","given":"Maulshree"},{"family":"Kapukotuwa","given":"Jayasekara"},{"family":"Gouveia","given":"Eber"},{"family":"Fuenmayor","given":"Evert"},{"family":"Qiao","given":"Yuansong"},{"family":"Murray","given":"Niall"},{"family":"Devine","given":"Declan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/electronics14020276","URL":"https://doi.org/10.3390/electronics14020276","source":"openalex"},{"id":"oa:W4406650129","type":"article-journal","title":"AIoT-powered building digital twin for smart firefighting and super real-time fire forecast","abstract":"• Propose a framework of AIoT-integrated Digital Twin for the full-scale three-story building. • Apply ADLSTM-Fire model to transform point-sensor arrays into spatiotemporal temperature field. • Super real-time fire forecast of hazardous floor regions to support smart firefighting and rescue operation. • Full-scale building fire experiments demonstrate smart system validity and generalization capability. Complex dynamics inherent of building fire poses big challenges to firefighting and rescue, especially with limited access to critical fire-hazard information. This work proposes the novel AIoT-integrated Digital Twin for the full-scale multi-floor building to manage the dynamics fire information. This system allows for super real-time mapping of actual building fires into accurate and concise digital fire scene at the cloud platform. By developing the ADLSTM-Fire model, we effectively transform discrete sensor-array data into high-dimensional spatiotemporal temperature fields in real-time, and furthermore, forecast future fire development and hazardous regions 60 s in advance. By comparing with benchmark numerical simulations, the Digital Twin system demonstrates the high reliability of super real-time fire-scene reconstruction and the capacity of fire-risk forecasting in supporting firefighting. The full-scale building fire experiment is employed to validate the generalisation capability of the proposed smart firefighting method. This work demonstrates the great potential and robustness of AIoT and digital twin in support smart firefighting and reducing fire casualties by information fusion.","author":[{"family":"Xie","given":"Weikang"},{"family":"Zeng","given":"Yanfu"},{"family":"Zhang","given":"Xiaoning"},{"family":"Wong","given":"Ho"},{"family":"Zhang","given":"Tianhang"},{"family":"Wang","given":"Zilong"},{"family":"Wu","given":"Xiqiang"},{"family":"Shi","given":"Jihao"},{"family":"Huang","given":"Xinyan"},{"family":"Xiao","given":"Fu"},{"family":"Usmani","given":"Asif"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.aei.2025.103117","URL":"https://doi.org/10.1016/j.aei.2025.103117","source":"openalex"},{"id":"doi:10.5281/zenodo.22091947","type":"article-journal","title":"D2A-HWY-60: A Reproducible Benchmark for Design-to-As-Built Highway Construction Verification","abstract":"D2A-HWY-60 is a reproducibility package and controlled benchmark for design-to-as-built verification in highway construction quality management. It accompanies the manuscript “An AI-Enabled Digital-Twin Information Framework for Design-to-As-Built Verification in Highway Construction Quality Management.” The package contains 60 research-constructed highway scenarios spanning horizontal alignment, vertical profile/elevation, lane and shoulder width, cross-slope, surface deviation, and compound nonconformities. It includes LandXML design corridors, structured as-built evidence, machine-readable QA/QC information, deterministic verification outputs, specification-sensitivity results, and station-addressable evidence packets. The experimental archive contains 300 information-ablation evaluations and 1,080 controlled information-quality scenario-condition runs (60 scenarios × 6 information-quality conditions × 3 replicates). These experiments provide internal verification and stress testing of the proposed framework; they are not field validation and should not be interpreted as observations from 1,080 independent highway projects. The repository also contains the complete Python implementation, pinned software environment, numerical verification script, figures, metadata, licenses, checksums, and a frozen Grok 4.6 experiment comprising 60 ungrounded and 60 evidence-grounded archived completions. The deposited code loads and re-scores the archived LLM completions; it does not regenerate hosted-model responses or query Grok. The benchmark supports reproducible investigation of highway design-to-as-built correspondence, encoded construction acceptance rules, PASS/NONCONFORMING/REVIEW REQUIRED decision logic, uncertainty-aware human review, grounded generative-AI reporting, and verified-as-built digital-twin information states. D2A-HWY-60 uses research-constructed corridors and synthetic as-built information. It does not contain live DOT project files or field-survey measurements. The primary S1 rule profile is based on publicly available UK Specification for Highway Works Series 700 provisions, with an S2 sensitivity profile based on TxDOT Item 340 and research operationalisations documented in the accompanying files. Researchers may reuse the benchmark to test alternative construction tolerance profiles, verification algorithms, uncertainty policies, or language models. Data are released under CC BY 4.0.","author":[{"family":"Haider","given":"Usman"},{"family":"Iqbal","given":"Hina"},{"family":"Humayon","given":"Muhammad"},{"family":"Johnston","given":"Wesley"},{"family":"Ali","given":"Asif"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.22091947","URL":"https://doi.org/10.5281/zenodo.22091947","source":"datacite"},{"id":"doi:10.5281/zenodo.22091949","type":"article-journal","title":"D2A-HWY-60: A Reproducible Benchmark for Design-to-As-Built Highway Construction Verification","abstract":"D2A-HWY-60 is a reproducibility package and controlled benchmark for design-to-as-built verification in highway construction quality management. It accompanies the manuscript “An AI-Enabled Digital-Twin Information Framework for Design-to-As-Built Verification in Highway Construction Quality Management.” The package contains 60 research-constructed highway scenarios spanning horizontal alignment, vertical profile/elevation, lane and shoulder width, cross-slope, surface deviation, and compound nonconformities. It includes LandXML design corridors, structured as-built evidence, machine-readable QA/QC information, deterministic verification outputs, specification-sensitivity results, and station-addressable evidence packets. The experimental archive contains 300 information-ablation evaluations and 1,080 controlled information-quality scenario-condition runs (60 scenarios × 6 information-quality conditions × 3 replicates). These experiments provide internal verification and stress testing of the proposed framework; they are not field validation and should not be interpreted as observations from 1,080 independent highway projects. The repository also contains the complete Python implementation, pinned software environment, numerical verification script, figures, metadata, licenses, checksums, and a frozen Grok 4.6 experiment comprising 60 ungrounded and 60 evidence-grounded archived completions. The deposited code loads and re-scores the archived LLM completions; it does not regenerate hosted-model responses or query Grok. The benchmark supports reproducible investigation of highway design-to-as-built correspondence, encoded construction acceptance rules, PASS/NONCONFORMING/REVIEW REQUIRED decision logic, uncertainty-aware human review, grounded generative-AI reporting, and verified-as-built digital-twin information states. D2A-HWY-60 uses research-constructed corridors and synthetic as-built information. It does not contain live DOT project files or field-survey measurements. The primary S1 rule profile is based on publicly available UK Specification for Highway Works Series 700 provisions, with an S2 sensitivity profile based on TxDOT Item 340 and research operationalisations documented in the accompanying files. Researchers may reuse the benchmark to test alternative construction tolerance profiles, verification algorithms, uncertainty policies, or language models. Data are released under CC BY 4.0.","author":[{"family":"Haider","given":"Usman"},{"family":"Iqbal","given":"Hina"},{"family":"Humayon","given":"Muhammad"},{"family":"Johnston","given":"Wesley"},{"family":"Ali","given":"Asif"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.22091949","URL":"https://doi.org/10.5281/zenodo.22091949","source":"datacite"},{"id":"doi:10.5281/zenodo.20584234","type":"article-journal","title":"Case Study: Servitisation as the Driver for Supply Chain Resilience – Enabled by Multi-Level Interoperability in the Lasers4MaaS Platform","abstract":"Peer-reviewed conference paper presented at I-ESA'26 (Interoperability for Enterprise Systems and Applications, Funchal, Madeira, 13–16 April 2026). European manufacturing is trapped in a rigid \"ownership model\" in which high-value assets are locked to specific locations, creating brittleness under energy volatility and supply shocks. This paper presents the Lasers4MaaS project (EU Horizon Europe, Grant No. 101178719) through the lens of servitisation — shifting from selling laser hardware to selling validated, defect-free manufacturing capacity, billed per ROM-validated component rather than per machine-hour. The core contribution is a Multi-Level Interoperability Framework — a \"Laser Operating System\" structured across three decoupled-yet-synchronised layers: Micro (hardware-agnostic execution via Dynamic Beam Shaping, on a sovereign edge), Meso (automated trust via a Reduced-Order-Model \"Digital Handshake\" and a cryptographic \"Liability Shield\" for SMEs), and Macro (automated ESPR/Digital Product Passport compliance and renewable-aware Industrial Grid Balancing). Two development-phase case studies — agile capacity shifting in automotive and remote weld monitoring for nuclear fusion — demonstrate a resilient, Gaia-X-aligned, sovereign manufacturing ecosystem. Funded by the European Union's Horizon Europe research and innovation programme under grant agreement No. 101178719. Views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the granting authority.","author":[{"family":"Nützel","given":"Christoph"},{"family":"Otto","given":"Andreas"},{"family":"Onuseit","given":"Volkher"},{"family":"Cinelli","given":"Marco"},{"family":"Eller-Shein","given":"Linda"},{"family":"Skilton","given":"Robert"},{"family":"Moretti","given":"Ivan"},{"family":"Gianotti","given":"Piergiuseppe"},{"family":"Hohmann","given":"Tobias"},{"family":"Castelo","given":"Antonio"},{"family":"Franciosa","given":"Pasquale"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20584234","URL":"https://doi.org/10.5281/zenodo.20584234","source":"datacite"},{"id":"doi:10.5281/zenodo.20584235","type":"article-journal","title":"Case Study: Servitisation as the Driver for Supply Chain Resilience – Enabled by Multi-Level Interoperability in the Lasers4MaaS Platform","abstract":"Peer-reviewed conference paper presented at I-ESA'26 (Interoperability for Enterprise Systems and Applications, Funchal, Madeira, 13–16 April 2026). European manufacturing is trapped in a rigid \"ownership model\" in which high-value assets are locked to specific locations, creating brittleness under energy volatility and supply shocks. This paper presents the Lasers4MaaS project (EU Horizon Europe, Grant No. 101178719) through the lens of servitisation — shifting from selling laser hardware to selling validated, defect-free manufacturing capacity, billed per ROM-validated component rather than per machine-hour. The core contribution is a Multi-Level Interoperability Framework — a \"Laser Operating System\" structured across three decoupled-yet-synchronised layers: Micro (hardware-agnostic execution via Dynamic Beam Shaping, on a sovereign edge), Meso (automated trust via a Reduced-Order-Model \"Digital Handshake\" and a cryptographic \"Liability Shield\" for SMEs), and Macro (automated ESPR/Digital Product Passport compliance and renewable-aware Industrial Grid Balancing). Two development-phase case studies — agile capacity shifting in automotive and remote weld monitoring for nuclear fusion — demonstrate a resilient, Gaia-X-aligned, sovereign manufacturing ecosystem. Funded by the European Union's Horizon Europe research and innovation programme under grant agreement No. 101178719. Views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the granting authority.","author":[{"family":"Nützel","given":"Christoph"},{"family":"Otto","given":"Andreas"},{"family":"Onuseit","given":"Volkher"},{"family":"Cinelli","given":"Marco"},{"family":"Eller-Shein","given":"Linda"},{"family":"Skilton","given":"Robert"},{"family":"Moretti","given":"Ivan"},{"family":"Gianotti","given":"Piergiuseppe"},{"family":"Hohmann","given":"Tobias"},{"family":"Castelo","given":"Antonio"},{"family":"Franciosa","given":"Pasquale"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20584235","URL":"https://doi.org/10.5281/zenodo.20584235","source":"datacite"},{"id":"doi:10.5281/zenodo.21603171","type":"article-journal","title":"AI-Driven Design, Simulation, and Optimization in Engineering Systems","abstract":"Artificial Intelligence is revolutionizing engineering by enabling intelligent design, rapid simulation, and efficient optimization of complex systems. Traditional engineering methods often involve extensive computational effort, iterative design cycles, and significant time and resource consumption. AI-driven approaches, including Machine Learning, Deep Learning, Genetic Algorithms, Particle Swarm Optimization, and Reinforcement Learning, provide data-driven solutions that enhance decision-making, prediction accuracy, and system performance. This chapter explores the integration of AI techniques in engineering design automation, simulation acceleration, and multi-objective optimization across various engineering domains such as mechanical, civil, electrical, aerospace, and biomedical engineering. It discusses emerging concepts such as generative design, digital twins, surrogate modeling, and physics-informed neural networks, which enable engineers to develop innovative, adaptive, and sustainable solutions. The chapter further examines the advantages of AI, including reduced design time, lower development costs, improved resource utilization, and enhanced reliability, while also addressing challenges related to data quality, computational requirements, model interpretability, and ethical concerns. By combining traditional engineering principles with advanced AI methodologies, engineering systems can become more autonomous, resilient, and efficient. The chapter concludes that AI-driven technologies will play a pivotal role in shaping next-generation engineering systems and fostering innovation in smart manufacturing, infrastructure development, and intelligent industrial applications.","author":[],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.21603171","URL":"https://doi.org/10.5281/zenodo.21603171","source":"datacite"},{"id":"doi:10.5281/zenodo.21603172","type":"article-journal","title":"AI-Driven Design, Simulation, and Optimization in Engineering Systems","abstract":"Artificial Intelligence is revolutionizing engineering by enabling intelligent design, rapid simulation, and efficient optimization of complex systems. Traditional engineering methods often involve extensive computational effort, iterative design cycles, and significant time and resource consumption. AI-driven approaches, including Machine Learning, Deep Learning, Genetic Algorithms, Particle Swarm Optimization, and Reinforcement Learning, provide data-driven solutions that enhance decision-making, prediction accuracy, and system performance. This chapter explores the integration of AI techniques in engineering design automation, simulation acceleration, and multi-objective optimization across various engineering domains such as mechanical, civil, electrical, aerospace, and biomedical engineering. It discusses emerging concepts such as generative design, digital twins, surrogate modeling, and physics-informed neural networks, which enable engineers to develop innovative, adaptive, and sustainable solutions. The chapter further examines the advantages of AI, including reduced design time, lower development costs, improved resource utilization, and enhanced reliability, while also addressing challenges related to data quality, computational requirements, model interpretability, and ethical concerns. By combining traditional engineering principles with advanced AI methodologies, engineering systems can become more autonomous, resilient, and efficient. The chapter concludes that AI-driven technologies will play a pivotal role in shaping next-generation engineering systems and fostering innovation in smart manufacturing, infrastructure development, and intelligent industrial applications.","author":[],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.21603172","URL":"https://doi.org/10.5281/zenodo.21603172","source":"datacite"},{"id":"doi:10.5281/zenodo.21865004","type":"article-journal","title":"Differential Passive Optical Sentinels for Lunar Surface Environmental Monitoring: A Reduced Digital-Twin Framework","abstract":"This record contains the simulation code, generated datasets, figures and supplementary computational outputs associated with the manuscript “Degradation-as-Signal for Lunar Surface Environmental Monitoring: A Digital-Twin Framework for Passive Optical Sentinels”, prepared for submission to Advances in Space Research.The repository implements a reduced-order digital-twin framework for evaluating passive optical environmental sentinels on the lunar surface. The model simulates a differential array of selectively protected thin-film patches exposed to coupled lunar environmental stressors, including ultraviolet exposure, ionising-radiation proxies, thermal cycling and dust deposition.The package includes forward simulation, inverse reconstruction, sensitivity analysis, surrogate modelling and figure-generation scripts. It also includes the CSV outputs used to generate the scenario summaries, inverse-reconstruction metrics, sensitivity rankings, surrogate-model metrics and representative sensor parameters reported in the manuscript.The simulations use representative exploratory parameters rather than experimentally calibrated material constants. The results should therefore be interpreted as architecture-level and identifiability analyses within the simulated design space, not as validated performance estimates for a flight-ready lunar sensor.Included materials:- Python source code for the reduced digital-twin framework.- Generated CSV datasets.- Main and supplementary figures.- Supplementary material files.- README, license, requirements and citation metadata.","author":[{"family":"Vega Fleitas","given":"Erika"},{"family":"Moll Lopez","given":"Santiago"},{"family":"Moraño","given":"José"},{"family":"Sánchez Ruiz","given":"Luis"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.21865004","URL":"https://doi.org/10.5281/zenodo.21865004","source":"datacite"},{"id":"doi:10.5281/zenodo.20031244","type":"article-journal","title":"Differential Passive Optical Sentinels for Lunar Surface Environmental Monitoring: A Reduced Digital-Twin Framework","abstract":"This record contains the simulation code, generated datasets, figures and supplementary computational outputs associated with the manuscript “Degradation-as-Signal for Lunar Surface Environmental Monitoring: A Digital-Twin Framework for Passive Optical Sentinels”, prepared for submission to Advances in Space Research.The repository implements a reduced-order digital-twin framework for evaluating passive optical environmental sentinels on the lunar surface. The model simulates a differential array of selectively protected thin-film patches exposed to coupled lunar environmental stressors, including ultraviolet exposure, ionising-radiation proxies, thermal cycling and dust deposition.The package includes forward simulation, inverse reconstruction, sensitivity analysis, surrogate modelling and figure-generation scripts. It also includes the CSV outputs used to generate the scenario summaries, inverse-reconstruction metrics, sensitivity rankings, surrogate-model metrics and representative sensor parameters reported in the manuscript.The simulations use representative exploratory parameters rather than experimentally calibrated material constants. The results should therefore be interpreted as architecture-level and identifiability analyses within the simulated design space, not as validated performance estimates for a flight-ready lunar sensor.Included materials:- Python source code for the reduced digital-twin framework.- Generated CSV datasets.- Main and supplementary figures.- Supplementary material files.- README, license, requirements and citation metadata.","author":[{"family":"Vega Fleitas","given":"Erika"},{"family":"Moll Lopez","given":"Santiago"},{"family":"Moraño","given":"José"},{"family":"Sánchez Ruiz","given":"Luis"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20031244","URL":"https://doi.org/10.5281/zenodo.20031244","source":"datacite"},{"id":"doi:10.5281/zenodo.20012975","type":"article-journal","title":"Differential Passive Optical Sentinels for Lunar Surface Environmental Monitoring: A Reduced Digital-Twin Framework","abstract":"This record contains the simulation code, generated datasets, figures and supplementary computational outputs associated with the manuscript “Degradation-as-Signal for Lunar Surface Environmental Monitoring: A Digital-Twin Framework for Passive Optical Sentinels”, prepared for submission to Advances in Space Research.The repository implements a reduced-order digital-twin framework for evaluating passive optical environmental sentinels on the lunar surface. The model simulates a differential array of selectively protected thin-film patches exposed to coupled lunar environmental stressors, including ultraviolet exposure, ionising-radiation proxies, thermal cycling and dust deposition.The package includes forward simulation, inverse reconstruction, sensitivity analysis, surrogate modelling and figure-generation scripts. It also includes the CSV outputs used to generate the scenario summaries, inverse-reconstruction metrics, sensitivity rankings, surrogate-model metrics and representative sensor parameters reported in the manuscript.The simulations use representative exploratory parameters rather than experimentally calibrated material constants. The results should therefore be interpreted as architecture-level and identifiability analyses within the simulated design space, not as validated performance estimates for a flight-ready lunar sensor.Included materials:- Python source code for the reduced digital-twin framework.- Generated CSV datasets.- Main and supplementary figures.- Supplementary material files.- README, license, requirements and citation metadata.","author":[{"family":"Vega Fleitas","given":"Erika"},{"family":"Moll Lopez","given":"Santiago"},{"family":"Moraño","given":"José"},{"family":"Sánchez Ruiz","given":"Luis"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20012975","URL":"https://doi.org/10.5281/zenodo.20012975","source":"datacite"},{"id":"doi:10.5281/zenodo.20012976","type":"article-journal","title":"Differential Passive Optical Sentinels for Lunar Surface Environmental Monitoring: A Reduced Digital-Twin Framework","abstract":"This record contains the simulation code, generated datasets, figures and supplementary computational outputs associated with the manuscript “Degradation-as-Signal for Lunar Surface Environmental Monitoring: A Digital-Twin Framework for Passive Optical Sentinels”, prepared for submission to Advances in Space Research.The repository implements a reduced-order digital-twin framework for evaluating passive optical environmental sentinels on the lunar surface. The model simulates a differential array of selectively protected thin-film patches exposed to coupled lunar environmental stressors, including ultraviolet exposure, ionising-radiation proxies, thermal cycling and dust deposition.The package includes forward simulation, inverse reconstruction, sensitivity analysis, surrogate modelling and figure-generation scripts. It also includes the CSV outputs used to generate the scenario summaries, inverse-reconstruction metrics, sensitivity rankings, surrogate-model metrics and representative sensor parameters reported in the manuscript.The simulations use representative exploratory parameters rather than experimentally calibrated material constants. The results should therefore be interpreted as architecture-level and identifiability analyses within the simulated design space, not as validated performance estimates for a flight-ready lunar sensor.Included materials:- Python source code for the reduced digital-twin framework.- Generated CSV datasets.- Main and supplementary figures.- Supplementary material files.- README, license, requirements and citation metadata.","author":[{"family":"Vega Fleitas","given":"Erika"},{"family":"Moll Lopez","given":"Santiago"},{"family":"Moraño","given":"José"},{"family":"Sánchez Ruiz","given":"Luis"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20012976","URL":"https://doi.org/10.5281/zenodo.20012976","source":"datacite"},{"id":"oa:W4413294494","type":"article-journal","title":"Robot digital twin systems in manufacturing: Technologies, applications, trends and challenges","abstract":"The manufacturing industry is undergoing a profound transformation toward smart, digital, and flexible production systems under the Industry 4.0 framework. Within this paradigm, Digital Twin (DT) serves as a key enabler, bridging physical and digital domains to simulate, analyse, and optimise manufacturing operations. Concurrently, robotic systems, enhanced by smart sensor perception, Industrial Internet of Things connectivity, and adaptive control mechanisms, are increasingly deployed to handle complex and dynamic tasks. However, the evolving demands of the modern manufacturing industry require a high degree of flexibility and responsiveness, necessitating more intelligent solutions. The Robot Digital Twin (RDT) has emerged as a transformative approach, facilitating dynamic adaptation and continuous operational improvement. This review offers a comprehensive examination of the literature on RDT in manufacturing from both technology and application perspectives, aiming to provide insight for researchers and practitioners in Industry 4.0. The paper introduces a four-layer RDT system architecture and summarises how Industry 4.0 technologies, e.g., the Industrial Internet of Things, Cloud/Edge Computing, 5 G, Virtual Reality, Modelling and Simulation, and Artificial Intelligence, converge and influence the RDT system based on this architecture. Furthermore, the review covers domain-specific and system-level applications, such as assembly, machining, grasping, material handling, human-robot interaction, predictive maintenance, and additive manufacturing systems, with an analysis of their development status. Finally, the trends, practical challenges, and future research directions for RDT systems in manufacturing are summarised at different levels.","author":[{"family":"Qin","given":"Qiang"},{"family":"Liu","given":"Zhihao"},{"family":"Zhong","given":"Ruirui"},{"family":"Wang","given":"Xi"},{"family":"Wang","given":"Lihui"},{"family":"Wiktorsson","given":"Magnus"},{"family":"Wang","given":"Wei"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.rcim.2025.103103","URL":"https://doi.org/10.1016/j.rcim.2025.103103","source":"openalex"},{"id":"oa:W4409164428","type":"article-journal","title":"Model‐Driven Engineering for Digital Twins: Opportunities and Challenges","abstract":"ABSTRACT Digital twins are increasingly used across a wide range of industries. Modeling is a key to digital twin development—both when considering the models which a digital twin maintains of its real‐world complement (“models in digital twin”) and when considering models of the digital twin as a complex (software) system itself. Thus, systematic development and maintenance of these models is a key factor in effective and efficient digital twin development, maintenance, and use. We argue that model‐driven engineering (MDE), a field with almost three decades of research, will be essential for improving the efficiency and reliability of future digital twin development. To do so, we present an overview of the digital twin life cycle, identifying the different types of models that should be used and re‐used at different life cycle stages (including systems engineering models of the actual system, domain‐specific simulation models, models of data processing pipelines, etc.). We highlight some approaches in MDE that can help create and manage these models and present a roadmap for research towards MDE of digital twins.","author":[{"family":"Michael","given":"Judith"},{"family":"Cleophas","given":"Loek"},{"family":"Zschaler","given":"Steffen"},{"family":"Clark","given":"Tony"},{"family":"Combemale","given":"Benoît"},{"family":"Godfrey","given":"Thomas"},{"family":"Khelladi","given":"Djamel"},{"family":"Kulkarni","given":"Vinay"},{"family":"Lehner","given":"Daniel"},{"family":"Rumpe","given":"Bernhard"},{"family":"Wimmer","given":"Manuel"},{"family":"Wortmann","given":"Andreas"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/sys.21815","URL":"https://doi.org/10.1002/sys.21815","source":"openalex"},{"id":"oa:W4408175675","type":"article-journal","title":"Transforming the maintenance of underground infrastructure through Digital Twins: State of the art and outlook","abstract":"• Four-level DT framework spans descriptive to prescriptive functionality. • Sensing and machine learning into reflective twins for dynamic updates. • Deterioration modelling and multi-physics simulations underpin predictive twin. • Progress and insights of multi-criteria decision makings for intervention. • Industry 5.0 shifts DTs from technology-focused to value-focused infrastructure. Underground infrastructure, designed to last for decades, play a vital role in urban life. Its maintenance and upkeep have significant societal values and contribute to sustainability. Simulation and modelling along with digitisation and virtualisation as key technologies in the context of Industry 4.0 have fundamentally transformed delivery of engineering projects. With climate change pose pressing challenges on the physical environment of human dwelling, infrastructure resilience has been strategised as a sustainable development goal. Inception of Industry 5.0 has been formulated surrounding this need incentivising to build and maintain with sustainability, resilience and human-centric as core values. Digital twin (DT) paradigm facilitated by a series of cross-disciplinary technologies has emerged to play a role toward these targets. Along with data management and artificial intelligence (AI), DTs present transforming potentials from a technology-focus approach to a value-focus approach. This paper conducts a systematic review on generation and applications of DTs for underground infrastructure maintenance, highlighting the multi-physics, multi-scale, and interdisciplinary characteristics of underground infrastructure. After examining challenges and opportunities for underground infrastructure, and thoroughly reviewing the existing definitions and maturity levels of DT in Section 1 , a DT framework for maintenance is established under the “Descriptive-Reflective-Predictive-Prescriptive” maturity model featuring progressive function requirements, forming 2 Descriptive twin , 2.1 BIM multi-system modelling , 2.1.1 BIM for underground infrastructure , 2.1.2 Geo- and structural model , 2.2 Functions and interoperability of digitalisation , 2.3 BIM for maintenance , 3 Reflective twin , 3.1 Sensing technologies , 3.2 Data-driven interpretation , 3.3 Data fusion and augmentation , 3.4 Interoperability and semantics , 4 Predictive twin , 4.1 Deterioration modelling , 4.1.1 Physics-based methods , 4.1.2 Machine learning methods , 4.2 Multi-physics simulation , 4.2.1 Interoperability and computational scalability , 4.2.2 Case studies , 4.3 Towards interpretable and reliable predictive twin , 5 Prescriptive twin of the paper. Section 2 focuses on reviewing information modelling techniques for creating a descriptive twin, essentially answering the question of “what is it”. Section 3 explores sensing technologies and data-driven analytics to develop a reflective twin, addressing applications requiring the knowledge of “what is happening”. Section 4 examines methods of deterioration modelling and multi-physics simulations to establish a predictive twin, providing insights into “what will happen”. Section 5 investigates approaches to intervention decision-making through service-oriented and multi-criteria frameworks, providing outlook into a prescriptive twin that addresses “what should be done”. Finally, a brief summary and some prospects requiring further investigations are presented.","author":[{"family":"Zhu","given":"Huamei"},{"family":"Huang","given":"Mengqi"},{"family":"Ji","given":"Pei"},{"family":"Xiao","given":"Feng"},{"family":"Zhang","given":"Qianbing"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.tust.2025.106508","URL":"https://doi.org/10.1016/j.tust.2025.106508","source":"openalex"},{"id":"oa:W4409413452","type":"article-journal","title":"Digital twin system for manufacturing processes based on a multi-layer knowledge graph model","abstract":"Abstract Digital twin technology in the manufacturing process faces challenges like integrating diverse data sources and managing real-time data flow. To address this, we propose a novel three-layer knowledge graph architecture to enhance digital twin modeling for manufacturing processes. This architecture consists of a concept layer that structures key information into a knowledge network, a model layer that aligns digital and physical parameters, and a decision layer that leverages model and real-time data for decision support. Validated in aero-engine blade production, this system integrates multi-source data, enhances predictive analysis and anomaly detection, and supports process control and quality management. Over a 5-month validation period, the maximum contour error precision of the blades improved from 0.073 mm to 0.062 mm, and the product qualification rate increased from 81.3% to 85.2%. This demonstrates the system’s robust capability for advancing digital twin utilization in manufacturing, highlighting its potential for future improvements.","author":[{"family":"Su","given":"Chang"},{"family":"Tang","given":"Xin"},{"family":"Jiang","given":"Qi"},{"family":"Han","given":"Yong"},{"family":"Wang","given":"Tao"},{"family":"Jiang","given":"Dongsheng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-024-85053-0","URL":"https://doi.org/10.1038/s41598-024-85053-0","source":"europepmc"},{"id":"doi:10.1038/s44333-026-00112-5","type":"article-journal","title":"REVI-twin: an integrated AI-driven methodology for creating digital twin of residential electric vehicle infrastructure","abstract":"Integrating electric vehicles (EVs) into homes and the electrical grid creates complex dynamics that traditional planning tools struggle to address. Accurately estimating residential EV charging demand typically requires resource-intensive agent-based simulations reliant on substantial input data, limiting scalability. We present REVI-Twin, an AI-driven digital twin of residential EV infrastructure that scales without computationally-intensive simulations. It encompasses: ( i ) household-level EV ownership; ( i i ) user behavior and charging preferences; ( i i i ) hourly power consumption; and ( i v ) planned trips. Our framework performs two tasks: ( i ) predicts EV adoption using transfer learning, semi-supervised learning, and Bayesian optimization; ( i i ) synthesizes hourly consumption with active-learning multi-output Gaussian processes from < 1% of data. We also release a comprehensive hourly integrated residential energy dataset. Our case study indicates that each 1% of battery adoption reduces Virginia’s net imports by ~ 0.06% daily and ~ 0.08% during peak hours. REVI-Twin assists policymakers and planners in analyzing adoption and infrastructure needs for resilient electrification.","author":[{"family":"Kishore","given":"Aparna"},{"family":"Islam","given":"Kazi"},{"family":"Marathe","given":"Madhav"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s44333-026-00112-5","URL":"https://doi.org/10.1038/s44333-026-00112-5","source":"openalex"},{"id":"doi:10.17632/jc2rszd2vj.2","type":"article-journal","title":"Dataset of Full-Scale Structural Strain, Vibration, and Acoustic Measurements from a Passenger Rail Vehicle Operating Under Service Conditions","abstract":"This repository contains a full-scale experimental dataset of structural strain, vibration, and acoustic responses collected from an executive-class passenger rail vehicle operating on a 1067 mm narrow-gauge railway network in Indonesia. The measurements were acquired under representative operating conditions including maximum speed (100 km/h), acceleration, deceleration, inclined curve, declined curve, and sharp curve manoeuvres. The dataset was obtained using synchronized multi-sensor instrumentation comprising: Ten three-element rosette strain gauges installed on the carbody, coupler assembly, and bogie structure. One triaxial accelerometer and two uniaxial accelerometers mounted at representative vehicle locations. Five Class-1 free-field microphones positioned inside the passenger cabin. The repository includes raw and processed measurement data covering three physical domains: Structural strain measurements recorded from rosette strain gauges. Vibration measurements in longitudinal, lateral, and vertical directions, including frequency-domain representations. Acoustic measurements including sound pressure level (SPL) data and one-third octave band spectra. Supporting materials are also provided, including sensor layouts, instrumentation schematics, metadata files, channel descriptions, acquisition parameters, and illustrative figures describing the experimental configuration. This dataset is intended to support numerical model development, calibration, verification, and validation activities in railway engineering. Potential applications include finite element modelling, structural dynamics, vibration analysis, fatigue assessment, noise and vibration (NVH) studies, vibro-acoustic simulations, digital twin development, machine learning applications, and comparative benchmarking investigations. The dataset provides a synchronized multi-domain experimental reference acquired under real operating conditions and may be reused for research and educational purposes.","author":[{"family":"Syaifudin","given":"Achmad"},{"family":"Rusli","given":"Meifal"},{"family":"Huda","given":"Feblil"},{"family":"Kurniawan","given":"Yani"},{"family":"Hendrowati","given":"Wiwiek"},{"family":"Nurhadi","given":"Hendro"},{"family":"Mario Valentino","given":"Jean"},{"family":"Wibawa Purabaya","given":"Raden"},{"family":"Sabrina","given":"Malinda"}],"issued":{"date-parts":[[2026]]},"DOI":"10.17632/jc2rszd2vj.2","URL":"https://doi.org/10.17632/jc2rszd2vj.2","source":"datacite"},{"id":"doi:10.17632/jc2rszd2vj","type":"article-journal","title":"Dataset of Full-Scale Structural Strain, Vibration, and Acoustic Measurements from a Passenger Rail Vehicle Operating Under Service Conditions","abstract":"This repository contains a full-scale experimental dataset of structural strain, vibration, and acoustic responses collected from an executive-class passenger rail vehicle operating on a 1067 mm narrow-gauge railway network in Indonesia. The measurements were acquired under representative operating conditions including maximum speed (100 km/h), acceleration, deceleration, inclined curve, declined curve, and sharp curve manoeuvres. The dataset was obtained using synchronized multi-sensor instrumentation comprising: Ten three-element rosette strain gauges installed on the carbody, coupler assembly, and bogie structure. One triaxial accelerometer and two uniaxial accelerometers mounted at representative vehicle locations. Five Class-1 free-field microphones positioned inside the passenger cabin. The repository includes raw and processed measurement data covering three physical domains: Structural strain measurements recorded from rosette strain gauges. Vibration measurements in longitudinal, lateral, and vertical directions, including frequency-domain representations. Acoustic measurements including sound pressure level (SPL) data and one-third octave band spectra. Supporting materials are also provided, including sensor layouts, instrumentation schematics, metadata files, channel descriptions, acquisition parameters, and illustrative figures describing the experimental configuration. This dataset is intended to support numerical model development, calibration, verification, and validation activities in railway engineering. Potential applications include finite element modelling, structural dynamics, vibration analysis, fatigue assessment, noise and vibration (NVH) studies, vibro-acoustic simulations, digital twin development, machine learning applications, and comparative benchmarking investigations. The dataset provides a synchronized multi-domain experimental reference acquired under real operating conditions and may be reused for research and educational purposes.","author":[{"family":"Syaifudin","given":"Achmad"},{"family":"Rusli","given":"Meifal"},{"family":"Huda","given":"Feblil"},{"family":"Kurniawan","given":"Yani"},{"family":"Hendrowati","given":"Wiwiek"},{"family":"Nurhadi","given":"Hendro"},{"family":"Mario Valentino","given":"Jean"},{"family":"Wibawa Purabaya","given":"Raden"},{"family":"Sabrina","given":"Malinda"}],"issued":{"date-parts":[[2026]]},"DOI":"10.17632/jc2rszd2vj","URL":"https://doi.org/10.17632/jc2rszd2vj","source":"datacite"},{"id":"doi:10.17605/osf.io/rq2kc","type":"article-journal","title":"Digital twins in health system management: a scoping review protocol","abstract":"Digital twins are virtual representations of physical entities that are updated continuously in real time based on data from their physical counterparts. They represent an innovative technological solution that can be employed in health system management to promote the delivery of efficient and high-quality care. While digital twins have been a subject of increasing study in healthcare, existing evidence on their application in health system management is fragmented. This hinders healthcare organizations’ ability to understand the conditions under which digital twins can effectively support system level decision making. Consequently, this scoping review aims to map the current state of digital twins in health system management, describing their potential benefits to healthcare services, system performance, and efficiency. It will also identify the main challenges to implementing digital twins in health system management and the key enablers that facilitate their adoption.","author":[{"family":"Falcão","given":"Maria"},{"family":"Santana","given":"Rui"},{"family":"Seringa","given":"Joana"}],"issued":{"date-parts":[[2026]]},"DOI":"10.17605/osf.io/rq2kc","URL":"https://doi.org/10.17605/osf.io/rq2kc","source":"datacite"},{"id":"doi:10.5281/zenodo.18755457","type":"article-journal","title":"Verso il Gemello Civico di Bologna:  Per una Intelligenza Ambientale e Democratica","abstract":"Settembre 2025 ha segnato l’avvio di PianetaLab, un’iniziativa pensata per affrontare le sfide ambientali, sociali e digitali a partire dal contesto locale, con il patrocinio dell’Universita’ Tecnica di Monaco e del Patto per il Clima Europeo. L’obiettivo è creare spazi di confronto e co-progettazione tra cittadini, istituzioni e realtà del territorio, favorendo dialogo e partecipazione. A Bologna ci siamo confrontati con il Gemello Digitale, gestito dal Comune di Bologna, con l’obbiettivo di migliorare il coinvolgimento dei cittadini nella realizzazione di questo strumento così importante per il futuro della vita di tutti in città. Le attività di PianetaLab a Bologna si inseriscono all’interno di un percorso più ampio promosso dall’associazione Pianeta, attiva a livello nazionale sui temi delle disuguaglianze sociali e dei cambiamenti climatici. L’obiettivo centrale dell’iniziativa a Bologna è riflettere in modo partecipato sul concetto di gemello civico digitale della città, inteso non come uno strumento puramente tecnico, ma come un dispositivo democratico e inclusivo, capace di supportare e monitorare le politiche pubbliche migliorare concretamente la vita delle persone. In questo documento, abbiamo raccolto i risultati di conversazioni tenute con cittadini di Bologna, online e di persona, con diversi soggetti del mondo scientifico, con le istituzioni locali e soprattutto tramite tre eventi pubblici tenuti il 13 settembre 2025, il 13 dicembre 2025 e il 13 febbraio 2026. Nel costruire il documento abbiamo usufruito di studi accademici sull’uso dei gemelli digitali, la partecipazione e la gestione etica dei dati, fatti dal TUM Public Science Lab, l’Ethical Data Initiative e la Cattedra di Filosofia e Storia della Scienza e della Tecnologia.","author":[{"family":"Leonelli","given":"Sabina"},{"family":"Cavazzoni","given":"Emma"},{"family":"Stefano","given":"Rimini"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.18755457","URL":"https://doi.org/10.5281/zenodo.18755457","source":"datacite"},{"id":"doi:10.5281/zenodo.18755458","type":"article-journal","title":"Verso il Gemello Civico di Bologna:  Per una Intelligenza Ambientale e Democratica","abstract":"Settembre 2025 ha segnato l’avvio di PianetaLab, un’iniziativa pensata per affrontare le sfide ambientali, sociali e digitali a partire dal contesto locale, con il patrocinio dell’Universita’ Tecnica di Monaco e del Patto per il Clima Europeo. L’obiettivo è creare spazi di confronto e co-progettazione tra cittadini, istituzioni e realtà del territorio, favorendo dialogo e partecipazione. A Bologna ci siamo confrontati con il Gemello Digitale, gestito dal Comune di Bologna, con l’obbiettivo di migliorare il coinvolgimento dei cittadini nella realizzazione di questo strumento così importante per il futuro della vita di tutti in città. Le attività di PianetaLab a Bologna si inseriscono all’interno di un percorso più ampio promosso dall’associazione Pianeta, attiva a livello nazionale sui temi delle disuguaglianze sociali e dei cambiamenti climatici. L’obiettivo centrale dell’iniziativa a Bologna è riflettere in modo partecipato sul concetto di gemello civico digitale della città, inteso non come uno strumento puramente tecnico, ma come un dispositivo democratico e inclusivo, capace di supportare e monitorare le politiche pubbliche migliorare concretamente la vita delle persone. In questo documento, abbiamo raccolto i risultati di conversazioni tenute con cittadini di Bologna, online e di persona, con diversi soggetti del mondo scientifico, con le istituzioni locali e soprattutto tramite tre eventi pubblici tenuti il 13 settembre 2025, il 13 dicembre 2025 e il 13 febbraio 2026. Nel costruire il documento abbiamo usufruito di studi accademici sull’uso dei gemelli digitali, la partecipazione e la gestione etica dei dati, fatti dal TUM Public Science Lab, l’Ethical Data Initiative e la Cattedra di Filosofia e Storia della Scienza e della Tecnologia.","author":[{"family":"Leonelli","given":"Sabina"},{"family":"Cavazzoni","given":"Emma"},{"family":"Stefano","given":"Rimini"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.18755458","URL":"https://doi.org/10.5281/zenodo.18755458","source":"datacite"},{"id":"doi:10.5281/zenodo.21807104","type":"article-journal","title":"A Secure and Intelligent Drug Supply Chain System using IoT, Blockchain and Digital Twin-Based Quality Assessment","abstract":"The pharmaceutical supply chain faces major challenges in ensuring the safety, authenticity, and proper storage of medicines during transportation and distribution. Traditional drug monitoring systems mainly rely on manual records and basic tracking methods, which lack real-time monitoring, transparency, and secure data management. Improper environmental conditions such as temperature and humidity variations can damage medicines and vaccines, leading to serious risks to patient safety. In addition, the absence of secure tracking mechanisms increases the possibility of counterfeit drugs and data manipulation in the supply chain. To address these challenges, this project proposes a secure and intelligent drug supply chain monitoring system using IoT, Blockchain, and Digital Twin technologies. The system uses IoT sensors such as DHT11, and GPS to continuously monitor temperature, humidity, and location of pharmaceutical products during transportation and storage. The collected sensor data is processed using NodeMCU and transmitted through Wi-Fi to Firebase cloud storage for real-time monitoring and visualization through a web dashboard. Blockchain technology based on Ethereum and smart contracts is integrated to provide secure, transparent, and tamper-proof storage of drug transaction and monitoring data. In addition, a Digital Twin model is implemented to create a virtual representation of the real-time condition of medicines, enabling better visualization and monitoring of the pharmaceutical environment. The system also generates instant alerts whenever environmental conditions exceed safe limits, helping maintain drug quality and safety. Overall, the proposed system improves transparency, enhances patient safety, reduces the risk of counterfeit medicines, and provides a scalable and efficient solution for modern pharmaceutical supply chain management.","author":[{"family":"Shelmeya","given":"MF"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.21807104","URL":"https://doi.org/10.5281/zenodo.21807104","source":"datacite"},{"id":"doi:10.5281/zenodo.21807105","type":"article-journal","title":"A Secure and Intelligent Drug Supply Chain System using IoT, Blockchain and Digital Twin-Based Quality Assessment","abstract":"The pharmaceutical supply chain faces major challenges in ensuring the safety, authenticity, and proper storage of medicines during transportation and distribution. Traditional drug monitoring systems mainly rely on manual records and basic tracking methods, which lack real-time monitoring, transparency, and secure data management. Improper environmental conditions such as temperature and humidity variations can damage medicines and vaccines, leading to serious risks to patient safety. In addition, the absence of secure tracking mechanisms increases the possibility of counterfeit drugs and data manipulation in the supply chain. To address these challenges, this project proposes a secure and intelligent drug supply chain monitoring system using IoT, Blockchain, and Digital Twin technologies. The system uses IoT sensors such as DHT11, and GPS to continuously monitor temperature, humidity, and location of pharmaceutical products during transportation and storage. The collected sensor data is processed using NodeMCU and transmitted through Wi-Fi to Firebase cloud storage for real-time monitoring and visualization through a web dashboard. Blockchain technology based on Ethereum and smart contracts is integrated to provide secure, transparent, and tamper-proof storage of drug transaction and monitoring data. In addition, a Digital Twin model is implemented to create a virtual representation of the real-time condition of medicines, enabling better visualization and monitoring of the pharmaceutical environment. The system also generates instant alerts whenever environmental conditions exceed safe limits, helping maintain drug quality and safety. Overall, the proposed system improves transparency, enhances patient safety, reduces the risk of counterfeit medicines, and provides a scalable and efficient solution for modern pharmaceutical supply chain management.","author":[{"family":"Shelmeya","given":"MF"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.21807105","URL":"https://doi.org/10.5281/zenodo.21807105","source":"datacite"},{"id":"doi:10.5281/zenodo.20451915","type":"article-journal","title":"Aldrovandi Digital Twin","abstract":"The Aldrovandi Digital Twin presents a virtual and interactive reconstruction of the temporary exhibition The Other Renaissance: Ulisse Aldrovandi and the Wonders of the World, held at the Museum of Palazzo Poggi in Bologna between December 2022 and May 2023. One of its primary objectives is to enable visitors to relive a cultural event that has already concluded through the meticulous 3D modelling of the exhibition’s six galleries, which contain more than 300 cultural objects digitised using photogrammetry and structured-light scanning techniques. This spatial reconstruction not only preserves the physical relationships among the objects but also maintains and enriches the original curatorial narrative, supported by integrated audio guides. At the heart of the experience lies the diversity of the digitised artefacts—including natural history specimens, fossils, manuscripts, paintings, casts, and many other items—each enriched with structured, machine-readable metadata. This integration enables semantic querying and supports layered exploration, offering both the public and researchers deeper contextual insights into the legacy of wonder and scientific curiosity left by Aldrovandi. Developed by a multidisciplinary team within the framework of Spoke 4 of Project CHANGES, the Digital Twin is the outcome of a collaborative methodological research effort to define a rigorous workflow compliant with the FAIR principles (Findable, Accessible, Interoperable, Reusable). This approach establishes a replicable case study for cultural heritage digitisation and valorisation practices, demonstrating how virtual and immersive experiences can effectively connect academic research with public engagement. This dataset contains two zip files of the Dockerised version of the Aldrovandi Digital Twin, provided for two different architectures: ARM and Intel x64. Instructions for running the Digital Twin on a machine are included in the zip files. Docker must be installed to run the application. The digital twin is built on ATON, an open-source Node.js and Three.js framework for creating Web3D/WebXR apps that interact with CH objects and 3D scenes on the Web, licensed under GPLv3. The metadata panel for each 3D object exposed in the Digital Twin has been designed using Melody, a dashboarding system that enables users familiar with Linked Open Data to create web-ready data stories, licensed under ISC. All metadata for the objects has been expressed in RDF, following the CHAD-AP ontology, while the provenance of the metadata records is tracked using the OpenCitations Data Model and the related OpenCitations Ontology. They are exposed using an Apache Jena Fuseki SPARQL server, licensed under Apache 2.0. All the 3D objects exposed in the Aldrovandi Digital Twin and their related metadata are licensed under CC0. Main projectCHANGES project, Spoke 4 (Virtual technologies for Museums and Art Collections) TeamAmmirati Luisa – Dipartimento di Filologia Classica e Italianistica, Alma Mater Studiorum – Università di BolognaBarzaghi Sebastian – Dipartimento di Beni Culturali, Alma Mater Studiorum – Università di BolognaBonifazi Federica – Istituto di Scienze del Patrimonio Culturale, Consiglio Nazionale delle RicercheBordignon Alice – Dipartimento di Filologia Classica e Italianistica, Alma Mater Studiorum – Università di BolognaCasadei Veronica – Dipartimento di Beni Culturali, Alma Mater Studiorum – Università di BolognaCipriani Luca – Dipartimento di Architettura, Alma Mater Studiorum – Università di BolognaColitti Simona – Dipartimento di Architettura, Alma Mater Studiorum – Università di BolognaCollina Federica – Dipartimento di Beni Culturali, Alma Mater Studiorum – Università di BolognaDaquino Marilena - Dipartimento di Filologia Classica e Italianistica, Alma Mater Studiorum – Università di BolognaFabbri Francesca – Dipartimento di Filologia Classica e Italianistica, Alma Mater Studiorum – Università di BolognaFanini Bruno – Istituto di Scienze del Patr","author":[{"family":"Ammirati","given":"Luisa"},{"family":"Barzaghi","given":"Sebastian"},{"family":"Bonifazi","given":"Federica"},{"family":"Bordignon","given":"Alice"},{"family":"Casadei","given":"Veronica"},{"family":"Cipriani","given":"Luca"},{"family":"Colitti","given":"Simona"},{"family":"Collina","given":"Federica"},{"family":"Daquino","given":"Marilena"},{"family":"Fabbri","given":"Francesca"},{"family":"Fanini","given":"Bruno"},{"family":"Fantini","given":"Filippo"},{"family":"Ferdani","given":"Daniele"},{"family":"Fiorini","given":"Giulia"},{"family":"Forte","given":"Anna"},{"family":"Giacomini","given":"Federica"},{"family":"Girelli","given":"Valentina"},{"family":"Gualandi","given":"Bianca"},{"family":"Heibi","given":"Ivan"},{"family":"Manganelli Del Fá","given":"Rachele"},{"family":"Massari","given":"Arcangelo"},{"family":"Massidda","given":"Marcello"},{"family":"Moretti","given":"Arianna"},{"family":"Peroni","given":"Silvio"},{"family":"Pescarin","given":"Sofia"},{"family":"Rega","given":"Maria"},{"family":"Renda","given":"Giulia"},{"family":"Ronchi","given":"Diego"},{"family":"Petrella","given":"Mario"},{"family":"Sullini","given":"Mattia"},{"family":"Tini","given":"Maria"},{"family":"Travaglini","given":"Laura"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20451915","URL":"https://doi.org/10.5281/zenodo.20451915","source":"datacite"},{"id":"doi:10.5281/zenodo.20451916","type":"article-journal","title":"Aldrovandi Digital Twin","abstract":"The Aldrovandi Digital Twin presents a virtual and interactive reconstruction of the temporary exhibition The Other Renaissance: Ulisse Aldrovandi and the Wonders of the World, held at the Museum of Palazzo Poggi in Bologna between December 2022 and May 2023. One of its primary objectives is to enable visitors to relive a cultural event that has already concluded through the meticulous 3D modelling of the exhibition’s six galleries, which contain more than 300 cultural objects digitised using photogrammetry and structured-light scanning techniques. This spatial reconstruction not only preserves the physical relationships among the objects but also maintains and enriches the original curatorial narrative, supported by integrated audio guides. At the heart of the experience lies the diversity of the digitised artefacts—including natural history specimens, fossils, manuscripts, paintings, casts, and many other items—each enriched with structured, machine-readable metadata. This integration enables semantic querying and supports layered exploration, offering both the public and researchers deeper contextual insights into the legacy of wonder and scientific curiosity left by Aldrovandi. Developed by a multidisciplinary team within the framework of Spoke 4 of Project CHANGES, the Digital Twin is the outcome of a collaborative methodological research effort to define a rigorous workflow compliant with the FAIR principles (Findable, Accessible, Interoperable, Reusable). This approach establishes a replicable case study for cultural heritage digitisation and valorisation practices, demonstrating how virtual and immersive experiences can effectively connect academic research with public engagement. This dataset contains two zip files of the Dockerised version of the Aldrovandi Digital Twin, provided for two different architectures: ARM and Intel x64. Instructions for running the Digital Twin on a machine are included in the zip files. Docker must be installed to run the application. The digital twin is built on ATON, an open-source Node.js and Three.js framework for creating Web3D/WebXR apps that interact with CH objects and 3D scenes on the Web, licensed under GPLv3. The metadata panel for each 3D object exposed in the Digital Twin has been designed using Melody, a dashboarding system that enables users familiar with Linked Open Data to create web-ready data stories, licensed under ISC. All metadata for the objects has been expressed in RDF, following the CHAD-AP ontology, while the provenance of the metadata records is tracked using the OpenCitations Data Model and the related OpenCitations Ontology. They are exposed using an Apache Jena Fuseki SPARQL server, licensed under Apache 2.0. All the 3D objects exposed in the Aldrovandi Digital Twin and their related metadata are licensed under CC0. Main projectCHANGES project, Spoke 4 (Virtual technologies for Museums and Art Collections) TeamAmmirati Luisa – Dipartimento di Filologia Classica e Italianistica, Alma Mater Studiorum – Università di BolognaBarzaghi Sebastian – Dipartimento di Beni Culturali, Alma Mater Studiorum – Università di BolognaBonifazi Federica – Istituto di Scienze del Patrimonio Culturale, Consiglio Nazionale delle RicercheBordignon Alice – Dipartimento di Filologia Classica e Italianistica, Alma Mater Studiorum – Università di BolognaCasadei Veronica – Dipartimento di Beni Culturali, Alma Mater Studiorum – Università di BolognaCipriani Luca – Dipartimento di Architettura, Alma Mater Studiorum – Università di BolognaColitti Simona – Dipartimento di Architettura, Alma Mater Studiorum – Università di BolognaCollina Federica – Dipartimento di Beni Culturali, Alma Mater Studiorum – Università di BolognaDaquino Marilena - Dipartimento di Filologia Classica e Italianistica, Alma Mater Studiorum – Università di BolognaFabbri Francesca – Dipartimento di Filologia Classica e Italianistica, Alma Mater Studiorum – Università di BolognaFanini Bruno – Istituto di Scienze del Patr","author":[{"family":"Ammirati","given":"Luisa"},{"family":"Barzaghi","given":"Sebastian"},{"family":"Bonifazi","given":"Federica"},{"family":"Bordignon","given":"Alice"},{"family":"Casadei","given":"Veronica"},{"family":"Cipriani","given":"Luca"},{"family":"Colitti","given":"Simona"},{"family":"Collina","given":"Federica"},{"family":"Daquino","given":"Marilena"},{"family":"Fabbri","given":"Francesca"},{"family":"Fanini","given":"Bruno"},{"family":"Fantini","given":"Filippo"},{"family":"Ferdani","given":"Daniele"},{"family":"Fiorini","given":"Giulia"},{"family":"Forte","given":"Anna"},{"family":"Giacomini","given":"Federica"},{"family":"Girelli","given":"Valentina"},{"family":"Gualandi","given":"Bianca"},{"family":"Heibi","given":"Ivan"},{"family":"Manganelli Del Fá","given":"Rachele"},{"family":"Massari","given":"Arcangelo"},{"family":"Massidda","given":"Marcello"},{"family":"Moretti","given":"Arianna"},{"family":"Peroni","given":"Silvio"},{"family":"Pescarin","given":"Sofia"},{"family":"Rega","given":"Maria"},{"family":"Renda","given":"Giulia"},{"family":"Ronchi","given":"Diego"},{"family":"Petrella","given":"Mario"},{"family":"Sullini","given":"Mattia"},{"family":"Tini","given":"Maria"},{"family":"Travaglini","given":"Laura"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20451916","URL":"https://doi.org/10.5281/zenodo.20451916","source":"datacite"},{"id":"oa:W7162408310","type":"article-journal","title":"Chaos Engineering for Resilient Manufacturing: A Digital Twin Perspective","abstract":"Chaos engineering is currently being used by some of the largest software companies in the world to develop IT systems that can withstand turbulent production conditions. This study presents an approach for applying chaos engineering across manufacturing systems to improve system resilience. For this purpose, the proposed chaos twin framework includes a four-step process for the manufacturing and interlinked digital twin system. A case study is discussed based on a material flow simulation. The case study shows the example implementation of the chaos twin framework for improving the resilience of a manufacturing system. The research intends to enhance the field of designing and operating manufacturing systems by demonstrating novel perspectives on applying chaos engineering within the cyberspace. Additionally, the research intends to provide a more industry-oriented guide to facilitate the practical application of chaos engineering within the manufacturing industry.","author":[{"family":"Erp","given":"Tim"},{"family":"Hohberg","given":"Vickie"},{"family":"Huus","given":"Christoffer"},{"family":"Tiedemann","given":"Laura"},{"family":"Tiedemann","given":"Joakim"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/systems14060608","URL":"https://doi.org/10.3390/systems14060608","source":"openalex"},{"id":"oa:W4411623435","type":"article-journal","title":"The Integration of the Internet of Things (IoT) Applications into 5G Networks: A Review and Analysis","abstract":"The incorporation of Internet of Things (IoT) applications into 5G networks marks a significant step towards realizing the full potential of connected systems. 5G networks, with their ultra-low latency, high data speeds, and huge interconnection, provide a perfect foundation for IoT ecosystems to thrive. This connectivity offers a diverse set of applications, including smart cities, self-driving cars, industrial automation, healthcare monitoring, and agricultural solutions. IoT devices can improve their reliability, real-time communication, and scalability by exploiting 5G’s advanced capabilities such as network slicing, edge computing, and enhanced mobile broadband. Furthermore, the convergence of IoT with 5G fosters interoperability, allowing for smooth communication across diverse devices and networks. This study examines the fundamental technical applications, obstacles, and future perspectives for integrating IoT applications with 5G networks, emphasizing the potential benefits while also addressing essential concerns such as security, energy efficiency, and network management. The results of this review and analysis will act as a valuable resource for researchers, industry experts, and policymakers involved in the progression of 5G technologies and their incorporation with IT solutions.","author":[{"family":"Zreikat","given":"Aymen"},{"family":"Al-Arnaout","given":"Zakwan"},{"family":"Abadleh","given":"Ahmad"},{"family":"Elbaşı","given":"Ersin"},{"family":"Mostafa","given":"Nour"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/computers14070250","URL":"https://doi.org/10.3390/computers14070250","source":"openalex"},{"id":"oa:W7165112680","type":"article-journal","title":"Beyond snapshot dosing: a dynamic living digital twin framework for model-informed precision dosing in critical illness","abstract":"INTRODUCTION: Model-Informed Precision Dosing (MIPD) has improved individualized therapy, but in critical illness its reliance on intermittently updated data creates a temporal mismatch between pharmacokinetic (PK) models and rapidly evolving physiology. AREAS COVERED: Synthesizing population pharmacokinetic (popPK) and data science literature, we examine the limitations of snapshot-based dosing, using vancomycin as example. We propose the Dynamic Living Digital Twin (DLDT) framework, which integrates high-frequency electronic health record data into adaptive state-space models such as Kalman filtering. Rather than adding more covariates, the DLDT reframes patient physiology as a continuously evolving latent state that can be updated using temporally dense clinical data. Methodological, infrastructural, and regulatory Software as Medical Device (SaMD) barriers are also evaluated. A non-systematic PubMed search identified relevant publications available up to March 2026. EXPERT OPINION: The next advance in precision dosing will come from temporally adaptive PK reasoning. In this paradigm, patient physiology is treated as an evolving latent state, and clinical pharmacists may increasingly interpret exposure trajectories rather than isolated dose recommendations. Although technically feasible, implementation remains constrained by data interoperability and workflow integration challenges. Clinical pharmacists may therefore increasingly act as stewards of dynamic model outputs, using anticipated exposure trajectories to preempt PK shifts.","author":[{"family":"Yalçın","given":"Hülya"},{"family":"Yalçın","given":"Nadir"},{"family":"Yalcin","given":"Hulya"},{"family":"Yalcin","given":"Nadir"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/17512433.2026.2693120","URL":"https://doi.org/10.1080/17512433.2026.2693120","source":"europepmc"},{"id":"oa:W7124418651","type":"article-journal","title":"Additional Material for the paper A Self-Adaptive Digital Twin Architecture for Dynamic Resource Management","abstract":"Additional Material for the paper A Self-Adaptive Digital Twin Architecture for Dynamic Resource Management The repository contains additional material for the SEAMS 2026 conference paper.The material includes: The source code of the prototype implementation of the approach presented in the paper in the src folder. The evaluation data and results in the data folder. To process the data and reproduce the graphs presented in the paper, the following Python packages are required: matplotlib numpy the requirements.txt file can be used to install the required packages using pip: pip install -r requirements.txt Data evaluation The `data` folder contains the evaluation data and results for the experiments presented in the paper, alongside the scripts used to generate the plots.To execute the commands below, navigate to the `data` folder in your terminal cd data To reproduce the graph in Figure 9 in the paper, run the following command in the data folder: python3 plot_single.py sim_output_no_peaks/normal_40_15_1_20_True To reproduce the graph in Figure 10 in the paper, run the following command in the `data` folder: python3 plot_multi.py --mean 40 --std 15 --mode normal --iterations 5 --time_steps 20 --adaptive --base sim_output_peaks The results will be saved in the two folders, sim_output_no_peaks and sim_output_peaks, respectively. To generate the time statistics (with the different times captured) from the results, run the following commands in the data folder: python3 plot_time_multi.py --iterations 10 --mean 40 --std 15 --time_steps 20 --adaptive --base sim_output_no_peaks for the results without peak adaptation, and python3 plot_time_multi.py --iterations 10 --mean 40 --std 15 --time_steps 20 --adaptive --base sim_output_peaks for the results with peak adaptation.The parameters passed to the scripts are as follows: --mean: the lambda of the distribution used to generate the sensor data. --std: the standard deviation. While not used in the Poisson distribution, it still serves to identify the correct folder names. --mode: the distribution mode used to generate the distribution with different characteristics. We used `normal` in the experiments, and the parameter is used to identify the correct folder names. --iterations: the number of iterations used in the experiments. --time_steps: the number of time steps used in the experiments. --adaptive: flag to indicate that the adaptive strategy was used. --base: the base folder where the results are stored. Source code The src folder contains the source code of the prototype implementation of the approach presented in the paper. The README in the folder further shows how to install the system and run tests.","author":[{"family":"Sieve","given":"Riccardo"},{"family":"Kobialka","given":"Paul"},{"family":"Pferscher","given":"Andrea"},{"family":"Bencomo","given":"Nelly"},{"family":"Tarifa","given":"Silvia"},{"family":"Rasmussen","given":"B"},{"family":"Johnsen","given":"Einar"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.18269300","URL":"https://doi.org/10.5281/zenodo.18269300","source":"openalex"},{"id":"oa:W7204649719","type":"article-journal","title":"From knowledge exchange to action plan: The Kronoby-Helsingborg NZC Twinning experience","abstract":"This paper explores the collaborative framework of the NetZeroCities Twinning Learning Programme (TLP) through the case of Kronoby, Finland, and its partnership with the frontrunner city of Helsingborg, Sweden. Serving as the TLP Facilitator, the researcher provided the methodological structure for knowledge exchange, enabling the two cities to effectively navigate their different municipal scales. The process (September 2024 to May 2026) transitioned from online alignment to high-impact physical site visits, which proved essential for building the trust and tacit knowledge required to transfer practices. The primary output is the Twin City Action Plan, a roadmap integrating transferability assessments and implementation steps. Key initiatives of Kronoby’s Action Plan include a digital Furniture Bank for municipal assets, sustainability-focused participatory budgeting, and youth-led \"Social Hubs.\" This case illustrates that significant differences in municipal size are no barrier to inspiration; instead, the \"human element\" (facilitated dialogue and physical observation) remains the critical catalyst for translating experiences into local action.","author":[{"family":"Azambuja","given":"Luiza"},{"family":"Björklund","given":"Matilda"},{"family":"Svarvar","given":"Patricia"}],"issued":{"date-parts":[[2026]]},"DOI":"10.59490/6a91ad6f0fd2bd55cd254711","URL":"https://doi.org/10.59490/6a91ad6f0fd2bd55cd254711","source":"openalex"},{"id":"oa:W4415007248","type":"article-journal","title":"Beyond years of schooling: Shifting genetic influences across educational milestones in two Norwegian cohorts","abstract":"Abstract Although educational attainment is heritable, its conventional measurement in genetic research as years of education (EduYears) is not designed to reveal potential stage-specific genetic influences across discrete milestones. In two Norwegian cohorts (Norwegian Mother, Father and Child Cohort Study, N = 120,527; Norwegian Twin Registry, N = 8,910), we quantified the genetic contributions to completing high school, bachelor’s, master’s and PhD using genome-wide association studies (GWAS), polygenic indices (PGIs) and twin models. Transition-specific analyses, conditioning on prior success, revealed that observed-scale common-variant heritability (h 2 SNP ) and PGI predictability followed an inverse-U pattern, peaking at the transition into higher education (h 2 SNP ≈ 0.14; R 2 Tjur ≈ 0.05) before declining for postgraduate degrees. Genetic correlations (r g ) with large-scale GWAS of EduYears (EA4) and intelligence (IQ3) were high for early transitions but declined markedly for later ones (e.g., r g with EA4 from ≈ 0.92 to ≈ 0.38). In cumulative analyses, aggregating liability across prior milestones, the gap between twin- and SNP-based heritability narrowed at higher levels of attainment (h 2 twin ≈ 0.6→0.3; h 2 SNP ≈ 0.22→0.19), while the genetic overlap between distant milestones diminished (r g ≈ 0.92→0.71). These patterns, obscured by EduYears metrics, highlight a dynamic genetic architecture across educational milestones, refining polygenic prediction and addressing misconceptions about uniform genetic influences on educational progression.","author":[{"family":"Kvalvik","given":"Eirik"},{"family":"Wang","given":"Yunpeng"},{"family":"Walhovd","given":"Kristine"},{"family":"Lyngstad","given":"Torkild"},{"family":"Røgeberg","given":"Ole"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1101/2025.10.08.680992","URL":"https://doi.org/10.1101/2025.10.08.680992","source":"openalex"},{"id":"oa:W7164928928","type":"article-journal","title":"Digital twins for lifespan prediction of used storage racks","abstract":"Digital twins (DTs) are vital tools to (1) model products or systems at their design stages and (2) monitor systems' conditions and predict their lifespans in their deployment stages. However, not many real-world case studies of DTs have been reported in literature to show significant benefits to Small and Medium sized Enterprises (SMEs). In this paper, DTs are proposed to predict the lifespans of used resources to pursue the sustainability of Reconfigurable Manufacturing Systems (RMSs). To illustrate the potential applications of DTs in enhancing the sustainability of real-world SMEs, a Technical Assistive Project (TAP) for the assessment of lifespans of materials storage racks is presented. The background and data collection methods are introduced, and digital models for 4 selective racks are developed to evaluate their Factor of Safety (FoS) subject to the worst loading scenarios. Parametric design studies are defined and conducted to investigate the dependence of FoS on varying loads. The results support managers' scientific decision-makings on reusing and recycling manufacturing resources in Sustainable Manufacturing.","author":[{"family":"Zhuming","given":"Bi"},{"family":"Mueller","given":"Donald"},{"family":"Chen","given":"Bin"},{"family":"Luo","given":"Chaomin"},{"family":"Li","given":"Muzi"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41598-026-56844-4","URL":"https://doi.org/10.1038/s41598-026-56844-4","source":"openalex"},{"id":"oa:W7161163973","type":"article-journal","title":"Using digital twins for co-designing cities: a review of digital participatory approaches","abstract":"Urban design is crucial in fostering sustainable, resilient and inclusive cities. As digital technology advances, digital twins have emerged as a powerful tool for enhancing citizen participation in urban design. This scoping review systematically explores and maps existing digital twin-based frameworks, methods and tools that engage citizens in urban design processes. By synthesizing findings from 26 studies, this review identifies key trends, challenges and research gaps in implementing digital twins for participatory urban planning. The results suggest that digital twins facilitate enhanced decision-making, bridge the gap between experts and citizens and improve the accessibility of urban planning through interactive platforms. However, data governance, inclusivity and technical integration complexity persist. This study proposes a Digital Twin Framework that categorizes digital twins into four types: analytical, visualization-driven, interactive participatory and operational, each serving distinct functions in citizen engagement. The findings underscore the need for further research on the socio-technical implications of digital twin adoption in urban design, ensuring equitable and effective citizen participation. Future work should address technical barriers, ethical considerations and policy frameworks to maximize the potential of digital twins in shaping urban environments.","author":[{"family":"Thuresson","given":"Frida"},{"family":"Lau","given":"Kevin"},{"family":"Rizzo","given":"Agatino"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/09654313.2026.2668560","URL":"https://doi.org/10.1080/09654313.2026.2668560","source":"openalex"},{"id":"oa:W7132840894","type":"article-journal","title":"Digital twins in oncology: Revolutionising precision cancer care","abstract":"The emergence of digital twin technology represents a paradigm shift in precision oncology, offering unprecedented opportunities to transform how we diagnose, treat, and monitor cancer patients. Originally conceived in aerospace and manufacturing industries, digital twins – dynamic virtual replicas that evolve with real-time data inputs – are now poised to revolutionize cancer care by enabling truly personalized therapeutic strategies. THE DIGITAL TWIN PARADIGM IN CANCERA cancer patient digital twin integrates multiscale, multimodal patient data – including genomics, proteomics, imaging, clinical records, and real-time monitoring – to create a computational model that mirrors an individual patient’s disease trajectory. Unlike static predictive models, digital twins continuously assimilate new data, enabling dynamic adaptation as a patient’s condition evolves. This real-time learning capability addresses a fundamental limitation of traditional clinical approaches, where treatment decisions are often based on population averages rather than individual characteristics. The global digital twin market in healthcare is experiencing explosive growth, projected to reach USD 21.1 billion by 2028 with a compound annual growth rate exceeding 25%. In oncology specifically, research output has surged dramatically since 2020, with major initiatives from institutions including the National Cancer Institute, MD Anderson Cancer Center, and European Union-funded consortia driving innovation. TRANSFORMATIVE APPLICATIONSDigital twins offer transformative potential across multiple domains of cancer care. In personalized treatment planning, they enable simulation of tumor responses across treatment modalities – immunotherapy, chemotherapy, radiation – allowing clinicians to develop bespoke treatment plans that optimize outcomes while minimizing adverse effects. Early clinical applications have demonstrated success, including evolution-based mathematical models that significantly prolonged time-to-progression in metastatic castrate-resistant prostate cancer through adaptive therapy strategies. In clinical trial design, digital twins enable in silico simulation of trial outcomes, optimizing study designs and accelerating drug development. Virtual patient populations can be generated to test hypotheses, identify potential biomarkers for patient stratification, and predict treatment responses before human exposure – potentially reducing the time and cost associated with traditional clinical trials.9 Recent validation studies comparing virtual trials with conventional outcomes have demonstrated remarkable concordance, supporting the reliability of this approach. For real-time monitoring and adaptation, digital twins continuously integrate data from clinical encounters, imaging, and even wearable devices to track disease progression and treatment response. This enables clinicians to adjust protocols dynamically – critical in oncology where tumor biology and treatment responsiveness vary significantly over time and between individuals. Despite their promise, significant challenges remain. Data integration across heterogeneous sources presents substantial technical hurdles, requiring robust frameworks for harmonizing genomic, imaging, and clinical data under findability, accessibility, interoperability, reusability principles. The complexity of cancer biology – including mechanisms of drug resistance, immune responses, and inter-patient heterogeneity – poses challenges for mechanistic modeling, particularly in immuno-oncology, where treatment mechanisms are not fully understood. Regulatory frameworks remain underdeveloped. Bodies, including the Food and Drug Administration and European Medicines Agency will need to establish clear guidelines for validating and deploying digital twins in clinical settings, similar to existing frameworks for medical devices. Furthermore, ethical considerations regarding data privacy, algorithmic bias, and equitable access ne","author":[{"family":"Dhar","given":"Ruby"},{"family":"Kumar","given":"Arun"},{"family":"Karmakar","given":"Subhradip"}],"issued":{"date-parts":[[2026]]},"DOI":"10.71152/ajms.v17i3.5141","URL":"https://doi.org/10.71152/ajms.v17i3.5141","source":"openalex"},{"id":"oa:W7117233730","type":"article-journal","title":"Research on output power modeling of all-electric marine diesel generator set based on data-driven","abstract":"• Proposed a data-driven modeling method for diesel generator sets based on information entropy and Elastic Net regression. • Validated the algorithm using actual operational data collected during vessel operation. • The developed model reveals the underlying correlation mechanisms among the operational parameters of the diesel generator set. Multi-energy integrated all-electric vessels, centred on generator sets and lithium-ion battery packs, represent a pivotal direction for the development of green intelligent vessels. Their intelligent operation and maintenance heavily rely on digital twin technology. As the core power source, shipboard diesel generator sets exhibit strong multi-physics coupling characteristics, making the construction of mechanism-based models challenging and difficult to simultaneously meet the accuracy and real-time requirements of digital twin systems. Considering that most operational conditions during vessel navigation are steady-state or quasi-steady-state, high-precision steady-state models provide a reliable foundation for conducting energy efficiency analysis, load distribution optimisation, and performance degradation assessment. To this end, this paper proposes a data-driven steady-state modelling method for diesel generators. This approach uses prime mover operational data as input and generator power as output, employing information entropy for feature selection and an elastic net regression algorithm for model construction. A dataset derived from actual vessel operational data was used for model training and validation. After normalisation, the model achieved a Mean Absolute Error (MAE) of 0.0110, a Root Mean Square Error (RMSE) of 0.0162, and a Coefficient of Determination (R²) of 0.9974. This model reveals underlying correlation mechanisms among unit characteristics, providing a critical steady-state simulation module for the digital twin system of all-electric vessels. It also lays a robust foundation for subsequent energy efficiency optimisation and condition monitoring efforts.","author":[{"family":"Xiao","given":"Longhai"},{"family":"Yu","given":"Wanneng"},{"family":"Wang","given":"Haibin"},{"family":"Chen","given":"Yao"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.oceaneng.2025.123955","URL":"https://doi.org/10.1016/j.oceaneng.2025.123955","source":"openalex"},{"id":"oa:W4416300580","type":"article-journal","title":"Transitioning to smart circular construction: A conceptual framework for circular economy implementation through Construction 4.0 technologies","abstract":"The integration of Construction 4.0 technologies, such as digital technologies, with circular economy (CE) concepts, offers significant potential to advance smart circular construction (SCC). Yet, the literature lacks a cohesive understanding of the measurable, value-driven outcomes, termed smart circular values, that can guide SCC's systemic adoption. This study addresses this gap by developing a conceptual framework for strategically deploying Construction 4.0 technologies to enhance material circularity in the construction sector, grounded in the human-centric, resilient, and sustainable principles of Industry 5.0. A systematic literature review of 96 peer-reviewed articles was conducted to map interdependencies between Construction 4.0 technologies and CE concepts. Using a novel operationalisation technique, the direct clustering algorithm, technologies were grouped according to their support for CE concepts, revealing five distinct smart circular values: smart energy management, smart construction methods, smart resource optimisation, smart tracking and tracing, and smart waste management. These values form the foundation for defining SCC and reveal distinct, technology-enabled pathways for its realisation. Potential adverse impacts of adopting Construction 4.0 technologies were also identified to guide implementation strategies and inform assessments of the net benefits of SCC adoption. Overall, the framework outlines key adoption priorities, highlights pressing challenges, and emphasises the importance of organisation-level assessments to accelerate progress toward a more circular built environment.","author":[{"family":"Abiodun","given":"Oluwapelumi"},{"family":"Abadi","given":"Mohamed"},{"family":"Ejohwomu","given":"Obuks"},{"family":"Manu","given":"Patrick"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.eiar.2025.108260","URL":"https://doi.org/10.1016/j.eiar.2025.108260","source":"openalex"},{"id":"oa:W7133118302","type":"article-journal","title":"Precision Agriculture Through a Real-Time Systems Perspective: A Narrative Review","abstract":"Precision agriculture employs state-of-the-art technologies to improve the economic viability, sustainability, and efficiency of agricultural practices. This paper offers a thorough review of precision agriculture, with an emphasis on real-time systems as a foundation for understanding the integration and impact of major technologies. We examine technologies such as digital twins, mobile applications, autonomous systems, location-aware technologies, edge computing, and Wireless Sensor Networks (WSN) that are revolutionizing agricultural processes. We also discuss the potential of other sensing techniques to enhance precision farming, including image analysis, sensory and chemical analysis, and physical state detection. Additionally, the roles that data transmission protocols, artificial intelligence (AI), and machine learning play in maximizing real-time data processing and decision-making are examined. We emphasize the main challenges and limitations in precision agriculture, such as data interoperability, scalability, and system integration. With a focus on market trends and local issues, we examine how AI, real-time systems, sensor technologies, and financial constraints impact the growth of precision agriculture. These advancements have an impact on precise monitoring, post-harvest management, and human health. Lastly, we provide suggestions for successful integration and future developments in precision agriculture, emphasizing design, engineering, and creative approaches to assist the field’s ongoing development.","author":[{"family":"Bhat","given":"Mansub"},{"family":"Silva","given":"Rickiel"},{"family":"Bhat","given":"Sameer"},{"family":"Sinha","given":"Aeshna"},{"family":"Moore","given":"Kenneth"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/agronomy16050552","URL":"https://doi.org/10.3390/agronomy16050552","source":"openalex"},{"id":"oa:W7131863007","type":"article-journal","title":"Artificial intelligence for personalized multiple micronutrient supplementation in maternal health","abstract":"Maternal undernutrition and micronutrient deficiencies remain pervasive, contributing to adverse pregnancy outcomes and long-term health risks for mothers and offspring. Multiple micronutrient supplementation (MMS) during pregnancy has demonstrated benefits, including reduced risks of low birth weight, small-for-gestational-age births, and neonatal mortality, when compared with standard iron-folic acid supplementation. Current MMS strategies, however, often follow a standard MMS, overlooking variations in nutritional status, health profiles, and context. Advances in artificial intelligence (AI), particularly deep learning and natural language processing, provide opportunities to strengthen maternal nutrition programs by integrating diverse data sources. Rather than promising fully individualized recommendations, AI could help stratify women by risk of insufficiencies or deficiencies, highlight groups most likely to benefit from additional support, and inform the design of more responsive supplementation strategies during preconception and pregnancy. We outline a conceptual model in which multimodal health data-including electronic health records (EHRs), wearable sensor outputs, nutrition and fertility app logs, genomic markers, and sociodemographic information-are aggregated and analyzed by AI systems to inform personalized MMS plans. The framework introduces the concept of a \"nutritional digital twin,\" a virtual profile of the patient's nutritional and metabolic state. This digital twin can simulate micronutrient needs and predict maternal-fetal outcomes under different supplementation scenarios, enabling clinicians to test scenario-based options (e.g. standard MMS ± targeted add-ons) for individuals. We describe how deep learning models can identify complex patterns (e.g. diet-genome interactions or behavioral trends) while natural language processing (NLP) algorithms extract clinically relevant insights from unstructured data (such as medical notes or patient queries). In addition, we discuss the role of digital maternal health tools, such as mobile apps and wearable trackers, in supplying real-time data to the AI models and in engaging women to improve adherence to supplementation regimens. Harnessing AI for MMS could transform maternal nutrition care in both high- and low-resource settings. In high-income contexts, rich data (comprehensive EHRs, genetic tests, continuous monitoring devices) could feed advanced predictive models to support risk-stratified care with protocolized supplementation options, under clinical oversight. In low- and middle-income countries, where maternal undernutrition and micronutrient gaps are most prevalent, AI-driven approaches can help stratify risk groups and optimize limited resources. Ubiquitous mobile phone access and digital health tools in many such settings provide avenues for data collection and intervention delivery. We highlight examples where machine learning on population data revealed \"hidden hunger\" patterns and key predictors of low supplement uptake (e.g. low education, minimal antenatal visits)-insights that policymakers can use to target nutrition programs. A nutritional digital twin could further allow scenario-testing (e.g. predicting the impact of adding a vitamin D supplement for a specific patient) before clinical decisions are made. To realize this vision, the key concerns are ethics, credibility, and fairness. Ethical frameworks must guide development so that sensitive reproductive health data are protected and clinician oversight remains central. The credibility of AI-generated recommendations depends on transparency about the assumptions used to translate nutritional and health data into supplement type and dose, and on prospective validation against maternal and neonatal outcomes. This requires a continuous feedback loop in which recommendations are tested in real-world settings and recalibrated using outcomes data, ensuring that the system learns from observed bene","author":[{"family":"Jones","given":"Gabriel"},{"family":"Papageorghiou","given":"Aris"},{"family":"Shehata","given":"Hassan"},{"family":"Divakar","given":"Hema"},{"family":"Beek","given":"Eline"},{"family":"Senikas","given":"Vyta"},{"family":"Konje","given":"JC"},{"family":"Kihara","given":"AN"},{"family":"Hod","given":"Moshe"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1002/ijgo.70911","URL":"https://doi.org/10.1002/ijgo.70911","source":"openalex"},{"id":"oa:W7165517885","type":"article-journal","title":"Using Digital Twins of Bearing Units for Their Automatic Diagnostics","abstract":"Diagnostics of bearing assemblies during operation are essential for maintaining operational reliability. The study focused on the bearing assemblies of the rear axle gearbox of a KAMAZ 6×4 vehicle. Finite element modeling of temperature distribution was performed using APM FEM. An INSTRUMAX PIRO-330 pyrometer and a UTi260B thermal imager were used to measure temperatures. Digital twins of the bearing assemblies were developed to obtain friction zone temperatures and proportionality coefficients for the finite element models, based on the nominal load criterion and lubricant properties. Thermal imaging demonstrated the practical applicability of digital thermal diagnostics technology and the developed digital twins. Practical recommendations are proposed for technical diagnostics of bearings using infrared pyrometers, thermal imagers, temperature indicator stickers, and a transmission fault recorder.","author":[{"family":"Erokhin","given":"Mikhail"},{"family":"Pastukhov","given":"Alexander"},{"family":"Timashov","given":"EP"}],"issued":{"date-parts":[[2026]]},"DOI":"10.46793/adeletters.2026.5.2.5","URL":"https://doi.org/10.46793/adeletters.2026.5.2.5","source":"openalex"},{"id":"oa:W7128373410","type":"manuscript","title":"A Review of Markerless Pose Estimation Methods for Digital Twins","abstract":"As robots and other forms of intelligent automation are improved, solutions to safely and accurately control their operation have also evolved. Many recent solutions to this control problem rely heavily upon Digital Twins (DT), or a digital copy of the environment, which tracks the presence and location of all agents and objects. However, implementing a digital twin is a non-neglible challenge as a high fidelity link between the real and digital worlds must be maintained. To this end, we have compiled a brief background on the problem of 3-Dimensional (3D) Pose Recovery from markerless visual data, listing some of the most recent works in the field and comparing their suitability for DT. In 3D Pose Recovery (3DPR), a subject’s position and orientation, or pose, is recovered from visual data in which objects and actors are not physically tagged or identified. This pose can then be used to help identify the location of a target object or actor to track in the digital twin. Additionally, we identify some emerging or remaining challenges in visual 3DPR in the context of DT and highlight a few methods that attempt to address them.","author":[{"family":"Panoff","given":"Maximillian"},{"family":"Hendricks","given":"Antonio"},{"family":"Forcha","given":"Peter"},{"family":"Minchul","given":"Jung"},{"family":"Wang","given":"Shuo"},{"family":"Bobda","given":"Christophe"}],"issued":{"date-parts":[[2026]]},"DOI":"10.20944/preprints202602.0443.v1","URL":"https://doi.org/10.20944/preprints202602.0443.v1","source":"preprints"},{"id":"oa:W7160320950","type":"article-journal","title":"A Composable Architectural Model for Digital Twin Computing Applications","abstract":"Digital Twins (DTs) are increasingly deployed in Industry 4.0 to enable real-time monitoring, analysis, and control, yet the transition from isolated DT instances to plant-wide ecosystems across cloud and edge infrastructures introduces fragmentation and coordination challenges among heterogeneous assets, data sources, and services. This paper addresses this gap by proposing a cloud-native Digital Twin Computing Layer (DTCL) that provides a unified control and orchestration plane for composing and operating DT applications in Smart Manufacturing. The DTCL is designed as a three-tier architecture comprising a developer-facing user interface, a Deploy Engine for automated deployment and lifecycle management, and a Service Catalog of reusable, independently deployable microservices. Standardized interaction is supported through semantic DT models and API- and message-based communication mechanisms. A governance workflow, based on service discovery and validation, is introduced to support non-redundant integration and controlled evolution of services. The approach is demonstrated through a Smart Manufacturing predictive maintenance case study and further extended with a Smart Mobility scenario for urban public transport planning, highlighting the flexibility of the DTCL across different application domains. Overall, the DTCL supports modular composition, interoperability, and lifecycle governance across heterogeneous Digital Twin applications, providing a scalable foundation for both industrial and urban data-driven scenarios.","author":[{"family":"Ieva","given":"Saverio"},{"family":"Loconte","given":"Davide"},{"family":"Pazienza","given":"Andrea"},{"family":"Colombo","given":"Matteo"},{"family":"Marzo","given":"Federico"},{"family":"Loseto","given":"Giuseppe"},{"family":"Scioscia","given":"Floriano"},{"family":"Ruta","given":"Michele"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/app16094541","URL":"https://doi.org/10.3390/app16094541","source":"openalex"},{"id":"oa:W7155616511","type":"article-journal","title":"From equations to agents: The artificial intelligence virtual cell reshaping precision oncology","abstract":"The Artificial Intelligence Virtual Cell (AIVC) is an advanced computational tool that combines detailed cellular data from single-cell and spatial technologies, including gene expression, epigenetic changes, and cell characteristics, while incorporating fundamental physical and biological rules. This approach creates accurate digital twins of cells that can simulate how tumors develop, evolve, and change over time across multiple scales, from molecules to tissues. Unlike traditional models based on fixed equations that struggle with cancer's extreme complexity and diversity, AIVC learns patterns directly from large biological datasets using modern AI methods. It models cells as intelligent agents operating in a mathematical space and refines predictions through ongoing feedback. This enables patient-specific computer simulations of drug effects, genetic alterations, and tumor environment interactions, moving precision oncology toward truly personalized and dynamic treatment strategies. Despite challenges like incomplete datasets, validation needs, and high computing demands, AIVC is maturing into a valuable research partner and advancing toward clinical use, positioned to transform cancer care.","author":[{"family":"Wei","given":"Ruochen"},{"family":"Wang","given":"Boquan"},{"family":"Yan","given":"Bin"},{"family":"Yang","given":"Yuxi"},{"family":"Liu","given":"Wanyi"},{"family":"Ding","given":"Jia"},{"family":"Hu","given":"Dehua"},{"family":"Zhang","given":"Wei"},{"family":"Sun","given":"Shengjie"},{"family":"Peng","given":"Yun"},{"family":"Luo","given":"Peng"},{"family":"Cui","given":"Yanru"},{"family":"Liu","given":"Xue"},{"family":"Zhou","given":"Jian"},{"family":"Wang","given":"Shixiang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.59717/j.xinn-oncol.2026.100002","URL":"https://doi.org/10.59717/j.xinn-oncol.2026.100002","source":"openalex"},{"id":"oa:W7124464271","type":"article-journal","title":"Additional Material for the paper A Self-Adaptive Digital Twin Architecture for Dynamic Resource Management","abstract":"Additional Material for the paper A Self-Adaptive Digital Twin Architecture for Dynamic Resource Management The repository contains additional material for the SEAMS 2026 conference paper.The material includes: The source code of the prototype implementation of the approach presented in the paper in the src folder. The evaluation data and results in the data folder. To process the data and reproduce the graphs presented in the paper, the following Python packages are required: matplotlib numpy the requirements.txt file can be used to install the required packages using pip: pip install -r requirements.txt Data evaluation The `data` folder contains the evaluation data and results for the experiments presented in the paper, alongside the scripts used to generate the plots.To execute the commands below, navigate to the `data` folder in your terminal cd data To reproduce the graph in Figure 9 in the paper, run the following command in the data folder: python3 plot_single.py sim_output_no_peaks/normal_40_15_1_20_True To reproduce the graph in Figure 10 in the paper, run the following command in the `data` folder: python3 plot_multi.py --mean 40 --std 15 --mode normal --iterations 5 --time_steps 20 --adaptive --base sim_output_peaks The results will be saved in the two folders, sim_output_no_peaks and sim_output_peaks, respectively. To generate the time statistics (with the different times captured) from the results, run the following commands in the data folder: python3 plot_time_multi.py --iterations 10 --mean 40 --std 15 --time_steps 20 --adaptive --base sim_output_no_peaks for the results without peak adaptation, and python3 plot_time_multi.py --iterations 10 --mean 40 --std 15 --time_steps 20 --adaptive --base sim_output_peaks for the results with peak adaptation.The parameters passed to the scripts are as follows: --mean: the lambda of the distribution used to generate the sensor data. --std: the standard deviation. While not used in the Poisson distribution, it still serves to identify the correct folder names. --mode: the distribution mode used to generate the distribution with different characteristics. We used `normal` in the experiments, and the parameter is used to identify the correct folder names. --iterations: the number of iterations used in the experiments. --time_steps: the number of time steps used in the experiments. --adaptive: flag to indicate that the adaptive strategy was used. --base: the base folder where the results are stored. Source code The src folder contains the source code of the prototype implementation of the approach presented in the paper. The README in the folder further shows how to install the system and run tests.","author":[{"family":"Sieve","given":"Riccardo"},{"family":"Kobialka","given":"Paul"},{"family":"Pferscher","given":"Andrea"},{"family":"Bencomo","given":"Nelly"},{"family":"Tarifa","given":"Silvia"},{"family":"Rasmussen","given":"B"},{"family":"Johnsen","given":"Einar"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.18270926","URL":"https://doi.org/10.5281/zenodo.18270926","source":"openalex"},{"id":"oa:W7157997025","type":"article-journal","title":"Biodegradable Metals and Corrosion Control: Challenges, Limits and New Opportunities for Innovating in Orthopedic Fixations","abstract":"Biodegradable metals represent a paradigm shift in orthopedic fixation by providing temporary mechanical support synchronized with bone healing while eliminating long-term complications associated with permanent implants. Conventional bioinert alloys, including stainless steels, Ti-based alloys, and Co-Cr alloys, exhibit high elastic moduli that induce stress shielding and often require secondary removal surgeries. In response, resorbable metallic systems based on Mg, Zn, and Fe have emerged as promising alternatives. Among these, Fe-Mn-C alloys stand out for load-bearing applications due to their exceptional strength-ductility balance governed by twinning-induced plasticity mechanisms, tunable degradation behavior, and intrinsic magnetic resonance imaging compatibility through austenitic phase stabilization. Focusing on Fe-Mn-C alloys, this review critically examines the metallurgical design principles underlying stacking fault energy optimization, phase stability, and Mn-controlled electrochemical behavior. Processing innovations, such as additive manufacturing, are discussed as tools to architecture porosity, refine microstructure, and accelerate degradation by graded designs while preserving mechanical structural support during healing. Hybrid metallic-bioactive systems, surface functionalization strategies, and functionally graded porous architectures were evaluated as advanced approaches to enhance osteointegration and modulate degradability. Despite these advances, significant barriers remain for clinical translation. Persistent discrepancies between in vitro and in vivo degradation rates, often attributed to biological encapsulation and degradation product accumulation, complicate lifetime prediction. Localized corrosion at microstructural heterogeneities such as twin boundaries and phase interfaces can undermine structural reliability under load-bearing conditions. Moreover, predictive multi-physics modeling frameworks capable of coupling electrochemical kinetics, mechanical loading, microstructural evolution, and bone remodeling remain underdeveloped, limiting reliable safety-margin estimation. Regulatory progress is further hindered by the absence of standardized testing protocols specifically tailored to Fe-based biodegradable alloys, including harmonized degradation rate windows, validated corrosion-mechanics coupling methodologies, and clinically defined Mn ion release thresholds. This review aims to discuss whether Fe-based alloys, especially Fe-Mn-C alloys, can transition from promising laboratory materials to clinically viable next-generation orthopedic implants capable of delivering patient-specific, mechanically compatible, and biologically synchronized temporary fixation.","author":[{"family":"Cherqaoui","given":"Abdelhakim"},{"family":"Paternoster","given":"Carlo"},{"family":"Mantovani","given":"Diego"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/ma19091789","URL":"https://doi.org/10.3390/ma19091789","source":"openalex"},{"id":"oa:W7125790833","type":"article-journal","title":"A Review of AI-Driven Engineering Modelling and Optimization: Methodologies, Applications and Future Directions","abstract":"Engineering is suffering a significant change driven by the integration of artificial intelligence (AI) into engineering optimization in design, analysis, and operational efficiency across numerous disciplines. This review synthesizes the current landscape of AI-driven optimization methodologies and their impacts on engineering applications. In the literature, several frameworks for AI-based engineering optimization have been identified: (1) machine learning models are trained as objective and constraint functions for optimization problems; (2) machine learning techniques are used to improve the efficiency of optimization algorithms; (3) neural networks approximate complex simulation models such as finite element analysis (FEA) and computational fluid dynamics (CFD) and this makes it possible to optimize complex engineering systems; and (4) machine learning predicts design parameters/initial solutions that are subsequently optimized. Fundamental AI technologies, such as artificial neural networks and deep learning, are examined in this paper, along with commonly used AI-assisted optimization strategies. Representative applications of AI-driven engineering optimization have been surveyed in this paper across multiple fields, including mechanical and aerospace engineering, civil engineering, electrical and computer engineering, chemical and materials engineering, energy and management. These studies demonstrate how AI enables significant improvements in computational modelling, predictive analytics, and generative design while effectively handling complex multi-objective constraints. Despite these advancements, challenges remain in areas such as data quality, model interpretability, and computational cost, particularly in real-time environments. Through a systematic analysis of recent case studies and emerging trends, this paper provides a critical assessment of the state of the art and identifies promising research directions, including physics-informed neural networks, digital twins, and human–AI collaborative optimization frameworks. The findings highlight AI’s potential to redefine engineering optimization paradigms, while emphasizing the need for robust, scalable, and ethically aligned implementations.","author":[{"family":"Li","given":"Jian"},{"family":"Polovina","given":"Nereida"},{"family":"Konur","given":"Savas"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/a19020093","URL":"https://doi.org/10.3390/a19020093","source":"openalex"},{"id":"oa:W7170158673","type":"article-journal","title":"Digital Twin Approach to Accessibility Assessment of Public Transport","abstract":"Abstract. Accessibility assessment of public transport systems is essential for ensuring that infrastructure remains inclusive for individuals with disabilities or mobility impairments. However, the sheer size of public transport networks poses a significant challenge for the physical observation and assessment of accessibility. This paper presents an efficient approach to the accessibility assessment of tram transport based on simulation within a digital twin environment. We propose a novel framework that integrates advanced data acquisition and processing steps, including mobile mapping of the tram routes, determination of the deployment zone of the mobility aid lift (MAL), and the assessment of tram accessibility by simulating the MAL deployment in the digital twin. We present a case study of three tram routes in Melbourne, Australia, which demonstrates that the digital twin provides a practical and reliable tool for assessing tram accessibility. Our results also highlight the potential of the proposed digital twin approach for assessing the accessibility of other modes of public transport, such as train networks and bus stations.","author":[{"family":"Khoshelham","given":"Kourosh"},{"family":"Zhang","given":"J"},{"family":"Radanovic","given":"Marko"},{"family":"Li","given":"Zizhao"},{"family":"Zhu","given":"Shuyu"},{"family":"Zhao","given":"Yuan"},{"family":"Tomko","given":"Martin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-archives-xlix-b2-2026-1245-2026","URL":"https://doi.org/10.5194/isprs-archives-xlix-b2-2026-1245-2026","source":"openalex"},{"id":"oa:W7138217123","type":"article-journal","title":"Operationalizing the Industrial Metaverse: Strategies, Challenges, and Opportunities for the Sustainable Factory of the Future","abstract":"The Industrial Metaverse (IM) integrates digital twins, IoT, AI, and immersive technologies to create interconnected, data-driven production environments. While its potential for enhancing efficiency and collaboration is widely acknowledged, its operationalization, particularly in alignment with sustainability goals, remains underexplored. This paper investigates how manufacturing firms transition from isolated pilots to strategic adoption of IM technologies, using a Digital Maturity Model as an analytical lens. Drawing on two industrial case studies, a university-based smart production lab, and expert roundtable discussions, we identify key barriers such as interoperability, governance, and skills gaps, alongside opportunities for circular material flows and resource optimization. Based on these insights, we propose three pathways for implementation: (1) digital maturity and Infrastructure Readiness, (2) organizational transformation for metaverse-enabled workflows, and (3) strategic value realization through sustainable business models. The study contributes a roadmap for managers and policymakers seeking to leverage the IM as a catalyst for resilience, circularity, and long-term competitiveness in smart manufacturing ecosystems.","author":[{"family":"Waehrens","given":"Brian"},{"family":"Berger","given":"Ulrich"},{"family":"Dueholm","given":"Bjoern"},{"family":"Lassen","given":"Astrid"},{"family":"Madsen","given":"Ole"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18062941","URL":"https://doi.org/10.3390/su18062941","source":"openalex"},{"id":"oa:W7203566126","type":"article-journal","title":"Explainable and Adaptive Intrusion Detection in Digital Twin Environments","abstract":"The rapid proliferation of Internet of Things (IoT) technologies has transformed the computing landscape, placing unprecedented demands on traditional cloud-centric architectures.The massive volume of distributed data, coupled with stringent latency and reliability requirements, has accelerated the adoption of edge-oriented computing paradigms.Within this context, Fog and Mist computing have become fundamental components of the edge computing system, enabling computation to be progressively shifted from centralized cloud platforms toward network edges and even directly onto end devices.This keynote examines the challenges and opportunities associated with orchestrating computational resources across the cloud-fog-mist continuum, with particular emphasis on scheduling mechanisms for real-time and mission-critical IoT applications.It reviews contemporary approaches that balance latency, resource utilization, energy efficiency, and quality of service while satisfying application deadlines in highly dynamic environments.The presentation also discusses emerging technologies, including adaptive scheduling, highlighting the key research challenges that will shape next-generation edge computing infrastructures.","author":[{"family":"Alharbi","given":"Ohood"},{"family":"Shaikh","given":"Riaz"},{"family":"Hassan","given":"Raheel"},{"family":"Asif","given":"Rameez"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/ficloud70576.2026.00016","URL":"https://doi.org/10.1109/ficloud70576.2026.00016","source":"openalex"},{"id":"oa:W7167888127","type":"article-journal","title":"An Evaluation of Synchronization and Optimization Techniques in Digital Twin Networks","abstract":"Digital Twin Network (DTN) technology has emerged as a promising approach for next-generation wireless and industrial systems by enabling real-time interaction between physical systems and their virtual counterparts. As modern communication networks continue to evolve through the rapid expansion of the Internet of Things (IoT), Industry 4.0, and the transition toward 6G, efficient network monitoring, management, and optimization have become increasingly challenging. DTNs address these challenges by providing high-fidelity digital replicas capable of supporting real-time monitoring, predictive maintenance, performance evaluation, and intelligent decision-making. This paper presents a comprehensive review and comparative analysis of Digital Twin Networks, focusing on synchronization techniques, optimization methodologies, and major application domains. Various synchronization approaches, including closed-loop feedback control, edge-cloud collaboration, and distributed learning updates, are examined and compared based on their functionality, advantages, and limitations. Furthermore, optimization techniques such as Deep Reinforcement Learning (DRL), Federated Learning (FL), blockchain-based optimization, transfer learning, and incentive mechanisms are analyzed for their effectiveness in improving network performance, resource utilization, and operational efficiency. The study also explores the adoption of DTNs across smart manufacturing, intelligent transportation systems, healthcare, smart cities, and 6G wireless networks. Through a detailed synthesis of current literature, the review identifies several persistent challenges that continue to hinder large-scale DTN deployment, including synchronization latency, security and privacy vulnerabilities, scalability constraints, interoperability issues, and high computational resource requirements. The findings provide valuable insights into current research trends and highlight key directions for future DTN development.","author":[{"family":"Joselin","given":"Dr"}],"issued":{"date-parts":[[2026]]},"DOI":"10.56975/ijvra.v4i7.708892","URL":"https://doi.org/10.56975/ijvra.v4i7.708892","source":"openalex"},{"id":"oa:W7148241806","type":"article-journal","title":"Digital Twin Based Microgrid Monitoring And Control System","abstract":"The increasing need for energy systems that provide dependable and sustainable energy has caused a surge in the growth of microgrids utilizing renewable energy sources. However, there are still many difficulties related to the implementation of distributed energy resources, such as real-time monitoring and effective control of energy resources. In response to those difficulties, the developed system is a Digital Twin Based Microgrid Monitoring and Control System that uses an ESP32 controller with Wi-Fi capability to connect all components of the microgrid to a cloud-based interface (as the digital twin) and a MATLAB environment for analysis and visualization of real-time data received from the monitored electrical parameters such as voltages, currents and power. The Digital Twin model represents (virtually) the physical microgrid system and therefore allows the user to evaluate the system performance, this can include detecting faults and developing optimized methods for controlling any of the distributed energy resources. As a result of using the Digital Twin Based Microgrid Monitoring and Control System, the microgrid will be more reliable, the operating losses will be less and it will support the implementation of smart grids for future sustainable energy management solutions.","author":[{"family":"Rganeshram"},{"family":"Govindhan","given":"VK"},{"family":"Prasath","given":"RSH"},{"family":"Mrptamilnesan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.19384084","URL":"https://doi.org/10.5281/zenodo.19384084","source":"openalex"},{"id":"oa:W7167488948","type":"article-journal","title":"Developing Digital Twins with SPADE for Autonomous Traffic Control","abstract":"In this paper, we introduce SPADE, a framework engineered for building Digital Twins through Multi-Agent Systems. The architecture is inherently scalable and distributed, aligning perfectly with the demands of modern Digital Twin environments. We implement the Agents and Artifacts meta-model via the SPADE Artifacts extension, which serves as a structured interface connecting autonomous agents with their physical system counterparts. To demonstrate the framework’s efficacy, we detail a case study involving urban traffic management in Valencia, Spain. In this implementation, we model 386 street segments as individual agents responsible for managing traffic flows and coordinating redistribution efforts. The research delineates a MAS-based communication strategy spanning the entire network and introduces a consensus algorithm specifically designed to manage traffic rerouting when a street is closed. Finally, we present results from a series of experimental trials and evaluate the system’s broader potential. By synthesizing diverse data sources and providing an interactive dashboard for visualizing network conditions, this work demonstrates how SPADE can serve as a robust foundation for Digital Twin development, illustrating its potential for real-world urban applications through a conceptual implementation grounded in open sensor data.","author":[{"family":"Raya","given":"Aarón"},{"family":"Soler","given":"Manel"},{"family":"Palanca","given":"Javier"},{"family":"Julián","given":"Vicente"},{"family":"Botti","given":"Vicente"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/systems14070779","URL":"https://doi.org/10.3390/systems14070779","source":"openalex"},{"id":"oa:W7172496538","type":"article-journal","title":"A didactic Digital Twin for engineering education: design and application","abstract":"Digital Twin (DT) has emerged as a key technology for industrial applications in the transition to Industry 4.0, enabling tighter integration between the physical and digital domains, supporting applications such as real-time monitoring and system optimisation. As Digital Twins continue to advance in research and industrial applications, there is a growing need to support education and professional training in this domain. However, the design and implementation of didactic Digital Twins tailored to educational environments remain insufficiently developed. Open and replicable DT platforms for educational contexts are particularly scarce in the literature. This paper presents the implementation of a didactic Digital Twin that comprises both its physical structure and a digital platform. The solution integrates a physical pick-and-place demonstrator with a software platform that enables real-time, bidirectional data synchronisation. The DT was implemented and experimentally tested in an undergraduate-level course. The models of the physical system and the software platform are made openly available to enable replication and further development by interested educators and researchers. The results include the didactic DT proposal, the digital platform, and an analysis of its educational application. By providing an extensible architecture, the study contributes to advancing open and replicable Digital Twin infrastructures for educational environments.","author":[{"family":"Campos","given":"Alex"},{"family":"Santos","given":"Gabriel"},{"family":"Hioki","given":"Eric"},{"family":"Zancul","given":"Eduardo"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/27525783.2026.2704996","URL":"https://doi.org/10.1080/27525783.2026.2704996","source":"openalex"},{"id":"oa:W7171567187","type":"article-journal","title":"Legal considerations for digital twins in food chain scenarios","abstract":"Abstract Digital twins offer a wide range of potential applications throughout the food supply chain, as demonstrated by the example of determining the suitability for human consumption of pre-packaged minced pork through AI-driven shelf-life assessment. As food business operators, official food control authorities and consumers are open to the use of new technology, there is currently no regulatory need for action regarding the use of AI throughout the food supply chain. However, future regulatory changes, particularly in the area of food labelling, should take into account the specific features arising from the intelligent determination of the use-by date by AI.","author":[{"family":"Brzezinski-Hofmann","given":"Katja"},{"family":"Altes","given":"Vincent"},{"family":"Brunner","given":"Matthias"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s00003-026-01625-4","URL":"https://doi.org/10.1007/s00003-026-01625-4","source":"openalex"},{"id":"oa:W4416850930","type":"article-journal","title":"Industrial Metaverse and Technical Diagnosis of Electric Drive Systems","abstract":"This article presents a part of the industrial metaverse for electric drive system diagnostics. The advantages of using a low-code/no-code platform for electric drive systems diagnostics are demonstrated. Five diagnostic scenarios were developed, programmed, and implemented. The article demonstrates the implementation and use of the platform’s main functional blocks: a visualization block (which displays the state of electric machines in any user-friendly form—graphs, Park’s vector diagrams, or diagnostic curves); a digital twin block (which simulates various engine states); a digital twin block with an engine defect (which simulates faulty engine states); and an artificial intelligence block (which trains classification model to predict various engine states). Experiments on training the artificial intelligence block using a misalignment defect dataset are presented. The dataset was divided into six classes: engine operation with/without a defect under no load, engine operation with/without a defect under a 50% load, and engine operation with/without a defect under a 100% load. The workflow for training and using the model, the basic training approaches, and the distinguishability of the presented classes are demonstrated. The model training results are shown. The article presents a methodology for extensive testing of program functionality. The obtained results demonstrate the feasibility of implementing a low-code/no-code platform and the feasibility of solving the assigned tasks with its help, as well as the simplification and reduction in engineering solution development time.","author":[{"family":"Koteleva","given":"Natalia"},{"family":"Korolev","given":"Nikolay"},{"family":"Kovalchuk","given":"Margarita"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app152312699","URL":"https://doi.org/10.3390/app152312699","source":"openalex"},{"id":"oa:W7160777680","type":"article-journal","title":"Advancing orthodontic care through digital twin technology","abstract":"Digital twin technology represents a transformative innovation in healthcare, creating virtual replicas that enable real-time monitoring, simulation, and predictive analytics. At its core, a digital twin is a comprehensive virtual representation of a physical entity that continuously synchronizes with real-world data, enabling dynamic simulation and predictive capabilities that distinguish it from static digital models or digital shadows. In orthodontics, digital twins integrate patient-specific anatomical data, treatment parameters, and biomechanical simulations to enhance clinical decision-making. Advances in three-dimensional imaging, artificial intelligence, and computational modelling have accelerated adoption, offering unprecedented opportunities for personalised planning. This narrative review aims to examine the current applications of digital twin technology in orthodontics, evaluate its clinical benefits and limitations, and explore future directions for research and implementation. A narrative review methodology was employed, synthesising peer-reviewed literature, clinical reports, and technological assessments published between 2018 and 2025. Electronic databases were searched to identify relevant studies on digital twin applications in orthodontic diagnosis, treatment planning, and biomechanical simulation. Digital twin technology demonstrates significant potential in orthodontics across multiple domains, including enhanced treatment planning accuracy, improved prediction of tooth movement, personalised biomechanical analysis, and adaptive treatment monitoring. Integration of artificial intelligence with digital twin models enables sophisticated outcome predictions and adaptive protocols. However, challenges persist, including high computational requirements, data integration complexities, the distinction between true digital twins and static digital workflows, and the need for standardised protocols. Digital twin technology represents a paradigm shift in orthodontic practice, offering transformative potential for precision diagnosis and individualised treatment. Future developments should focus on improving accessibility, establishing validation protocols, and integrating real-world evidence to support widespread adoption.","author":[{"family":"Olawade","given":"David"},{"family":"Ede","given":"Immaculata"},{"family":"Olawuyi","given":"Olabanke"},{"family":"Egbon","given":"Eghosasere"},{"family":"Makanjuola","given":"Babajide"},{"family":"Alabi","given":"John"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.tdr.2026.100088","URL":"https://doi.org/10.1016/j.tdr.2026.100088","source":"openalex"},{"id":"oa:W7167234187","type":"article-journal","title":"Interoperability of digital twin data exchange in engineering processes","abstract":"Abstract Although Digital Twins (DTs) as digital representations of products are adopted by industry, the seamless exchange of DT data across its product lifecycle, from design to engineering, manufacturing, and operation, remains challenging. In particular, the early stages of product development, where the DT and its data evolve, as well as the cross-company collaboration during those phases are affected by significant interoperability issues.The current situation forces engineers to carry out lengthy processes of manual data identification, conversion, and integration, often resulting in substandard data quality. Consequently, this review article examines how cross-company DT data interoperability can be achieved by analyzing existing challenges, in terms of relevant context factors, requirements to be met, and proposed solutions including frameworks as well as enabling processes. The results indicate the significance of the addressed research problem as a variety of conceptual solutions and frameworks have been developed. However, most of the published work lack empirically valid results which leads to a lack of practical adoption. Moreover, these studies predominantly address later lifecycle phases and mostly don´t consider interoperability dimensions. We suggest research encompassing the semantic, technical, and organizational dimensions, particularly in the early DT lifecycle stages of product development. It needs to include a deeper understanding of stakeholder roles and processes to achieve data interoperability through process alignments.","author":[{"family":"Liepert","given":"Constantin"},{"family":"Stary","given":"Christian"},{"family":"Lamprecht","given":"Axel"},{"family":"Zügn","given":"Dennis"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s00163-026-00489-x","URL":"https://doi.org/10.1007/s00163-026-00489-x","source":"openalex"},{"id":"oa:W4407369951","type":"article-journal","title":"Addressing grand ecological challenges in aquatic ecosystems: how can mesocosms be used to advance solutions?","abstract":"Rapid and drastic anthropogenic impacts are affecting global biogeochemical processes and driving biodiversity loss across Earth's ecosystems. In aquatic ecosystems, species distributions are shifting, abundances of many species have declined dramatically, and many are threatened with extinction. In addition to loss of diversity, the ecosystem functions, processes and services on which humans depend are also being heavily impacted. Addressing these challenges not only requires direct action to mitigate environmental impacts but also innovative approaches to identify, quantify and treat their effects in the environment. Mesocosms are valuable tools for achieving these goals as they provide controlled environments for evaluating effects of stressors and testing novel mitigation measures at multiple levels of biological organisation. Here, we summarise discussions from a survey of marine and freshwater researchers who use mesocosm systems to synthesise their opportunities and limitations for advancing solutions to grand ecological challenges in aquatic ecosystems. While most research utilising mesocosm systems in aquatic ecology has focused on quantifying the effects of environmental threats, there is a largely unexplored potential for using them to test solutions. To overcome spatio‐temporal constraints, there are opportunities to scale up the size and time‐scales of mesocosm studies, or alternatively, test the outcomes of habitat‐scale restoration at a smaller scale. Enhancing connectivity in future studies can help to overcome the limitation of isolation and test an important aspect of ecological recovery. Conducting ‘metacosm' studies: coordinated, distributed mesocosm experiments spanning wide climatic and environmental gradients and utilising more regression‐based experimental designs can help to tackle the challenge of context dependent results. Finally, collaboration of theoretical, experimental and applied ecologists and biogeochemists with environmental engineers and technological developers will be necessary to develop and test the tools required to advance solutions to the impacts of human activities on Earth's vulnerable aquatic ecosystems.","author":[{"family":"Macaulay","given":"Samuel"},{"family":"Jeppesen","given":"Erik"},{"family":"Riebesell","given":"Ulf"},{"family":"Nejstgaard","given":"Jens"},{"family":"Berger","given":"Stella"},{"family":"Lewandowska","given":"Aleksandra"},{"family":"Rico","given":"Andreu"},{"family":"Kefford","given":"Ben"},{"family":"Vad","given":"Csaba"},{"family":"Costello","given":"David"},{"family":"Wang","given":"Haijun"},{"family":"Pimentel","given":"Iris"},{"family":"Ramos","given":"Joana"},{"family":"González","given":"José"},{"family":"Spilling","given":"Kristian"},{"family":"Domis","given":"Lisette"},{"family":"Boersma","given":"Maarten"},{"family":"Stockenreiter","given":"Maria"},{"family":"Meerhoff","given":"Mariana"},{"family":"Vijver","given":"Martina"},{"family":"Kellyquinn","given":"Mary"},{"family":"Beklioğlu","given":"Meryem"},{"family":"Matias","given":"Miguel"},{"family":"Sswat","given":"Michael"},{"family":"Juvignykhenafou","given":"Noël"},{"family":"Fink","given":"Patrick"},{"family":"Zhang","given":"Peiyu"},{"family":"Taniwaki","given":"Ricardo"},{"family":"Ptáčník","given":"Robert"},{"family":"Langenheder","given":"Silke"},{"family":"Nederstigt","given":"Tom"},{"family":"Horváth","given":"Zsófia"},{"family":"Piggott","given":"Jeremy"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1111/oik.11020","URL":"https://doi.org/10.1111/oik.11020","source":"openalex"},{"id":"oa:W7153158558","type":"article-journal","title":"Digital Twin Based Smart Building and Energy Management","abstract":"This paper presents a smart building energy management system based on a Digital Twin.It combines real-time sensing, built-in intelligence, and cloud monitoring to improve energy awareness and operational efficiency.The Digital Twin serves as a continuously updated virtual model of the physical building, using live data from temperature, light, and energy sensors connected to an ESP32 microcontroller.A dedicated power measurement module tracks electrical energy consumption, allowing real-time checks of voltage, current, power, and energy usage for both the whole system and individual loads.The synchronized Digital Twin offers remote visualization and system insights through a cloud-based IoT platform, helping users make informed energy decisions.The system also includes safety-aware automation to enhance reliability and robustness.Experimental tests show that data synchronization is accurate and the system performs stably under different load conditions.The proposed system best describes how digital twin technology helps in effective energy management.","author":[{"family":"Vijayan","given":"PM"},{"family":"Thirisha","given":"KD"},{"family":"Kumar","given":"KK"},{"family":"Yuvaraju","given":"K"},{"family":"Revathi","given":"K"},{"family":"Rehman","given":"MA"}],"issued":{"date-parts":[[2026]]},"DOI":"10.58482/ijersem.v2i3.16","URL":"https://doi.org/10.58482/ijersem.v2i3.16","source":"openalex"},{"id":"oa:W7204212800","type":"manuscript","title":"Towards a Digital Twin for the Ground to QEYSSat Quantum Link","abstract":"Simulations of physical systems require high-fidelity models to accurately represent reality. Simple models may be analytically tractable, but may not be sufficiently representative of reality for the given application. The cost of this simplicity is accuracy, or in the case of quantum key distribution, provable security. Sources of this accuracy gap include the difficulty of modelling physical effects which do not lend themselves well to analytical descriptions, such as afterpulsing. Here, we introduce a novel Monte Carlo based photon emission, transmission, and detection simulator, designed in the context of the Quantum Encryption and Science Satellite (QEYSSat) mission. Within this simulator, every major physical effect a photon may experience during an experiment, from emission to detection, can be accounted for in a probabilistic manner. This methodology allows for the inclusion of experimental parameters which are relevant for a satellite mission, and their impacts on secure key lengths. This simulator serves as a comprehensive baseline to predict and validate experimental data for the upcoming QEYSSat mission.","author":[{"family":"Morin","given":"Henri"},{"family":"Maierean","given":"Alex"},{"family":"Higgins","given":"Brendon"},{"family":"Dsouza","given":"Ian"},{"family":"Muthu","given":"Vinodh"},{"family":"Jennewein","given":"T"}],"issued":{"date-parts":[[2026]]},"DOI":"10.48550/arxiv.2608.21968","URL":"https://doi.org/10.48550/arxiv.2608.21968","source":"openalex"},{"id":"oa:W7164886111","type":"article-journal","title":"An Agentic LLM Framework for Autonomous Surgical Continuum Monitoring: ReAct-Driven Tool-Use Agents for Presurgical, Intraoperative, and Postsurgical Cardiopulmonary Care","abstract":"BACKGROUND: Rule-based multi-agent system (MAS) architectures for healthcare coordination rely on hardcoded decision trees that cannot generalise to novel clinical scenarios or self-correct reasoning errors. These limitations are acute in surgical continuum care, where patients traverse presurgical risk stratification, intraoperative monitoring, postsurgical ICU, ward care, and remote rehabilitation over days to weeks-a complexity no fixed-policy agent architecture can address without prohibitive rule engineering. OBJECTIVE: We present the first agentic large language model (LLM) framework for autonomous end-to-end surgical continuum monitoring, superseding the prior rule-based MAS Digital Twin. Six ReAct-driven tool-use agents replace fixed-policy agents with dynamic reasoning, multi-hop evidence retrieval, and Reflexion self-correction while maintaining mandatory confidence-gated Human-in-the-Loop (HITL) gating at every care-pathway-modifying decision. METHODS: The framework is grounded in the ReAct paradigm and Reflexion self-evaluation, embedded within the DETER Digital Twin state engine S(t). Each agent is specified by a ReAct loop signature, a ten-function clinical tool registry, and confidence-gated HITL escalation logic. Inter-agent coordination replaces the rule-based Priority Queue Manager with an LLM-mediated Coordination Supervisor Agent reasoning over competing resource requests. RESULTS: The framework delivers: (i) six formally specified ReAct-loop agents with explicit tool registries and authorisation boundaries; (ii) a confidence-gated HITL architecture that reduces alert fatigue while preserving safety for ambiguous clinical scenarios; (iii) an extended conflict resolution function P(p,t,context) incorporating surgical phase and DETER deterioration trajectory gradient; (iv) Reflexion self-correction with a formal N_max = 2 termination condition and Clinical Factuality Verification Layer; and (v) a multi-phase Digital Twin state engine extending S(t) to the full surgical continuum. CONCLUSIONS: The proposed framework represents a fundamental architectural departure from rule-based clinical AI-from hardcoded policies to dynamic reasoning, from static retrieval to multi-hop tool-use chains, and from fixed escalation thresholds to confidence-gated self-evaluation-providing a formally specified, clinically deployable foundation for next-generation autonomous surgical care coordination.","author":[{"family":"Pylarinou","given":"Charalampia"},{"family":"Gortzis","given":"Lefteris"},{"family":"Leivaditis","given":"Vasileios"},{"family":"Liolis","given":"Elias"},{"family":"Antzoulas","given":"Andreas"},{"family":"Papadoulas","given":"Spyros"},{"family":"Nikolakopoulos","given":"Konstantinos"},{"family":"Panagiotopoulos","given":"Ioannis"},{"family":"Mitsos","given":"Sofoklis"},{"family":"Tomos","given":"Periklis"},{"family":"Koletsis","given":"Efstratios"},{"family":"Mulita","given":"Francesk"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/bioengineering13060686","URL":"https://doi.org/10.3390/bioengineering13060686","source":"openalex"},{"id":"oa:W7127413792","type":"article-journal","title":"Energy Communities Design and Optimisation: A Decision-Making Tool for the Italian Case","abstract":"Renewable Energy Communities are expected to play a key role in the decarbonization of power systems, but their design and operation involve multiple, often conflicting objectives and evolving regulatory frameworks. However, prospective REC promoters and members must make early-stage design choices under policy constraints while balancing economic, environmental, and reliability goals, which motivates the need for transparent and reproducible decision-support tools. This paper presents Adapters, a two-level decision-making tool that couples long-term planning with short-term operational adaptation for hybrid renewable energy systems. The core optimisation model is explicitly multi-objective, with three weighted terms (w1, w2, and w3) that represent total cost, CO2 emissions, and unserved energy, respectively, allowing users to explore trade-offs between economic performance, environmental impact, and reliability. The tool integrates detailed component models (such as photovoltaic, wind, and battery storage) with a flexible optimisation layer and architecture compatible with digital-twin approaches. Its capabilities are illustrated through prototype single-household case studies, showing how different stakeholder preferences and regulatory conditions can be reflected in the choice of objective weights and system configurations. The overall aim is to provide a transparent and reproducible environment to support the emergence and operation of RECs in line with EU energy and climate goals.","author":[{"family":"Ferrucci","given":"Tommaso"},{"family":"Winkler","given":"Sarah"},{"family":"Estevez","given":"Manuel"},{"family":"Renzi","given":"Massimiliano"},{"family":"Cardozo","given":"Sara"},{"family":"Alberizzi","given":"Jacopo"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18031553","URL":"https://doi.org/10.3390/su18031553","source":"openalex"},{"id":"oa:W7143519149","type":"manuscript","title":"Semantic Core for Sensor Telemetry Ingestion for Digital Twins","abstract":"Digital twin platforms for smart cities must continuously receive different types of data from sensors, gateways, and services, but in real situations these data is heterogeneous in terms of indicator names, measurement units, time rules, and object identification, which makes integrations expensive and fragile, while second verification becomes complicated. In this paper, a minimal semantic core for \"first-stage\" telemetry receiving of the DTwin platform, where semantics are used as operational rules during data ingestion. The core includes a machine-readable model of entities and relation-ships, dictionaries of metrics and measurement units, a unified event format with sep-aration into a stable envelope and payload, formal validation against data schemas, a mapping table for transforming raw fields into standardized measurements [name, value, unit], as well as an ingestion service with canonicalization of the event record and integrity control through the SHA-256 cryptographic hash. The implementation ensures ingestion of correct events, rejection of incorrect ones without recording, and reproducible verification through control examples, a testing protocol, and evidence snapshots. In smart city settings, such a telemetry ingestion foundation can support reliable monitoring of municipal buildings and infrastructure, including energy efficiency, indoor environmental quality, and data-driven operational decision-making. The proposed approach creates a core for stable integration of different sensor data into digital twins and further scaling of the platform.","author":[{"family":"Osolinskyi","given":"Oleksandr"},{"family":"Lipianina-Honcharenko","given":"Khrystyna"},{"family":"Komar","given":"Myroslav"}],"issued":{"date-parts":[[2026]]},"DOI":"10.20944/preprints202603.2186.v1","URL":"https://doi.org/10.20944/preprints202603.2186.v1","source":"openalex"},{"id":"oa:W7170035741","type":"article-journal","title":"Student Lifestyle Digital Twin and Impact Simulation System","abstract":"The increasing prevalence of unhealthy lifestyle habits among students, including poor nutrition, inadequate sleep, physical inactivity, and high stress levels, can significantly impact overall health and well-being. Existing health applications primarily focus on activity tracking and lack the capability to predict and simulate the long-term impact of lifestyle choices. This research proposes a Student Lifestyle Digital Twin and Impact Simulation System, which creates a virtual representation of a user to analyze and simulate lifestyle effects over time. The system integrates Machine Learning techniques for predicting nutritional deficiencies and health risks, along with Digital Twin technology to simulate future wellness outcomes based on user inputs such as diet, exercise, sleep, hydration, and symptoms. Built using Flask, PostgreSQL, HTML/CSS, and data analysis tools such as Pandas and Matplotlib, the proposed system aims to provide personalized health insights, lifestyle recommendations, and predictive analysis to improve health awareness and proactive decision-making among students.","author":[{"family":"Vaidya","given":"SDO"},{"family":"Addagatla","given":"Rohit"},{"family":"Bhanse","given":"Salvi"},{"family":"Sankpal","given":"Anoushka"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.21487016","URL":"https://doi.org/10.5281/zenodo.21487016","source":"openalex"},{"id":"oa:W4410972821","type":"article-journal","title":"A Conceptual Approach to Developing the Organizational-Technological Structure of the Management of Model-Type New Generation Enterprises","abstract":"In the conditions of digital transformation, the issues of developing the organizational-technological structure of the formation and management of model-type new-generation enterprises are of special importance.In this aspect, Artificial Intelligence, cloud, etc. the dynamic development of innovative digital technologies, the relevance of their application in the production, service, and decision-making processes of enterprises, in the improvement of management efficiency, in the development of the organizational and economic structure, is substantiated.Some problems have been revealed based on the overview analysis of the scientific research works related to the state of processing of the problem.Those problems were used in the synthesis of the new-generation enterprise model.The considered issues include: 1)Development of a structural model reflecting some advantages using enterprise architecture management approaches, 2)Development of a conceptual model of effective management of innovative enterprises based on digital twin technologies, 3)Innovation in the enterprise, market conditions, economic efficiency and analysis of indicators characterizing the positive relationship between external and internal factors that support development, 4)Development of the model of the process of designing the organizational structure of enterprises and the development of the main stages of the process of improving the organizational structure, 5)Analysis of the impact of information technologies on the organizational structure of the enterprise, 6)Parametric analysis tools ways of optimizing the organizational structure of the enterprise management, proposing innovative methods to ensure the high quality of the organizational structure of its management, 7)Using the enterprise architecture approach in conceptual modeling for enterprise management, 8)Enterprise architecture within the framework of the open innovation concept and development of investment models for IT architectural projects, offering investment and evaluation models, etc.The role and importance of model-type, new-paradigm innovative digital enterprises in the formation of the new generation digital economy has been studied.Relevant analyses were conducted on the scientific-theoretical bases of enterprise management, existing approaches, and specific features, and scientific theories that determine its effective organizational-technological structure.Functional structural models of enterprise architecture at different levels and some of their elements have been defined.The characteristics of some platforms of the main enterprise architecture are studied, the structural elements, levels, and advantages of The Open Group Architecture Framework are shown.The elements of the organizational-technological structure of the management of model-type new-generation enterprises have been determined, and the functional stages of its organizational structure improvement have been worked out.Contradictions and defective elements of the enterprise's organizational structures have been identified.Recommendations were made regarding the conceptual model of the organizational-technological structure of the management of model-type new-generation enterprises.A Conceptual Approach to Developing the Organizational-Technological Structure of the Management of Model-Type New Generation Enterprises Volume 15 (2025), Issue 3 41 Conceptual linking blocks of the organizational-technological structure of the management of model-type newgeneration enterprises have been proposed.Relevant recommendations were given for the development of the organizational-technological structure of the management of such enterprises for the transition to the digital innovationbased development stage on the Industry 4.0 platform.","author":[{"family":"Aliyev","given":"Alovsat"},{"family":"Shahverdiyeva","given":"Roza"},{"family":"Salimkhanova","given":"Sunyakhanim"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5815/ijeme.2025.03.04","URL":"https://doi.org/10.5815/ijeme.2025.03.04","source":"openalex"},{"id":"oa:W7117248575","type":"article-journal","title":"Multidimensional determinants of active and healthy aging trajectories: a position paper from the Age-It Research Program","abstract":"OBJECTIVES: This position paper presents perspectives from Spoke 4 (Trajectories for Active and Healthy Aging) of the Age-It Research Program, which adopts a One Health perspective to examine the interplay of cognitive, behavioral, nutritional, social, and environmental determinants of aging. Addressing these multidimensional factors is crucial to promoting health, independence, and well-being across the life course. METHODS: We reviewed evidence on lifelong determinants of aging, including physical activity, nutrition, mental engagement, and social participation, alongside emerging digital health solutions. The One Health framework guided our analysis, emphasizing the interconnectedness of individual, societal, and environmental influences. Spoke 4 integrates multidisciplinary expertise to translate scientific knowledge into practical tools for communities, healthcare providers, and policymakers. RESULTS: Evidence shows that sustained engagement in physical activity, cognitively stimulating activities, and strong social networks supports resilience, reduces frailty, and preserves independence. Tailored nutritional strategies further enhance functional capacity. Digital technologies-such as mobile apps, wearable devices, and online platforms-demonstrate potential to improve disease prevention and health monitoring. However, disparities in digital literacy and access remain significant barriers, particularly for older adults. DISCUSSION: Spoke 4 of Age-It highlights the need for multidimensional, One Health-based strategies that integrate traditional health determinants with digital innovations. By combining evidence-based interventions with user-centered e-health platforms, scalable and inclusive solutions can be developed to support healthy aging. These efforts provide policymakers and healthcare systems with tools to foster resilience, mitigate frailty, and enhance quality of life in aging populations.","author":[{"family":"Paoli","given":"Antonio"},{"family":"Iaccarino","given":"Guido"},{"family":"Lucidi","given":"Fabio"},{"family":"Pagnini","given":"Francesco"},{"family":"Boccuzzo","given":"Giovanna"},{"family":"Illario","given":"Maddalena"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1093/geronb/gbaf196","URL":"https://doi.org/10.1093/geronb/gbaf196","source":"openalex"},{"id":"oa:W7125923688","type":"article-journal","title":"Catalyst Loading Technology for Fixed-Bed Reactors: From Empirical Heuristics to Data-Driven Intelligent Regulation","abstract":"Fixed-bed reactors are pivotal in chemical industries, where catalyst loading critically determines reactor performance and economy. This critical review delineates and analyzes a three-stage evolution of loading technology: from empirical manual methods, through scenario-adaptive innovations, to closed-loop intelligent systems. It aims to decode the underlying scientific principles, assess the performance enhancements and inherent limitations of each stage, and critically examine the architectural framework and constraints of intelligent loading systems. Industrial validation data, such as from a 2.4 Mt/a hydrocracker, demonstrate potential improvements (e.g., 20–22% catalyst life extension, 1.8% bed pressure-drop fluctuation). However, the progression presents complex trade-offs in terms of scalability, cost, and standardization. The future direction is discussed, pointing toward addressing challenges in multi-physics modeling, digital twin integration, and fundamental research gaps. This work provides a balanced framework for evaluating loading technology evolution, acknowledging its context-dependent applicability.","author":[{"family":"Xu","given":"Zili"},{"family":"Liu","given":"Wenming"},{"family":"Yin","given":"Hongmei"},{"family":"Xq","given":"Liu"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/catal16020123","URL":"https://doi.org/10.3390/catal16020123","source":"openalex"},{"id":"oa:W7171644785","type":"article-journal","title":"Characterizing Functional Clusters of V4 Neurons in Digital Twins","abstract":"Abstract Neurons in primate visual cortical area V4 display tuning for multiple visual features, including color, shape, texture, and depth. Whether and how these neurons are organized into functional architectures remains largely unknown. Using two-photon calcium imaging in anesthetized macaques, we recorded responses of hundreds of V4 neurons to natural images and used these data to train deep convolutional neural network models (digital twins), obtaining synthetic images (SI) that maximized neuronal responses. Based on their SIs, these neurons clustered into classes that spatially matched the orientation, color, and curvature maps from intrinsic signal imaging. Furthermore, lesion study in digital twins revealed different integration rules for different neuron classes. Thus, digital twins of V4 neurons can be applied as a promising tool to characterize neurons’ fundamental features, which underlie the functional clustering in this area. Highlights Neurons in V4 are examined with two-photon calcium imaging and DCNN modeling (digital twins) Synthetic images derived from neurons’ digital twins reveal distinct neuron groups These groups match functional types defined by intrinsic signal optical imaging Lesion study in digital twins demonstrates neural mechanisms underlying feature tuning","author":[{"family":"Tang","given":"Rendong"},{"family":"Zhou","given":"Qiongyi"},{"family":"Zhao","given":"Wenhao"},{"family":"Dai","given":"Zhuoyue"},{"family":"Zhang","given":"Rui"},{"family":"Wang","given":"Jiayu"},{"family":"Wang","given":"Gongting"},{"family":"Du","given":"Changde"},{"family":"He","given":"Huiguang"},{"family":"Lu","given":"Haidong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.64898/2026.07.25.740202","URL":"https://doi.org/10.64898/2026.07.25.740202","source":"openalex"},{"id":"oa:W7165532852","type":"article-journal","title":"Statistical and context-based diagnostics for Digital Twin environments","abstract":"The Digital Twin concept is increasingly applied in engineering practice to support simulation-based design and validation processes.However, ensuring consistency between simulations and experimental data remains a critical challenge.In engineering systems identical statistical patterns can originate from different causes, so it may lead to incorrect diagnostic conclusions.This paper proposes an approach that integrates statistical validation methods with context-based reasoning to improve the interpretation of data in Digital Twin environments.The proposed framework combines data preprocessing techniques with statistical analysis and context-based reasoning.The applicability of the approach is shown through a representative case study.The results confirm that the integration of statistical methods with context-based reasoning enhances the robustness of Digital Twin systems and supports more effective use of simulation in modern engineering environments.","author":[{"family":"Król","given":"Artur"},{"family":"Timofiejczuk","given":"Anna"},{"family":"Łukasik","given":"Tomasz"}],"issued":{"date-parts":[[2026]]},"DOI":"10.29354/diag/224917","URL":"https://doi.org/10.29354/diag/224917","source":"openalex"},{"id":"oa:W7134811610","type":"article-journal","title":"Artificial Intelligence Marketing Technologies and Consumer Purchasing Decisions: The Moderating Role of Virtual Customer Experience and Implications for Sustainable Consumption in Telecommunications Service Environments","abstract":"Artificial intelligence (AI) marketing technologies are reshaping customer engagement in service sectors, yet their performance within integrated digital ecosystems remains poorly understood. Existing research often examines AI tools in isolation, overlooking how the holistic quality of the virtual customer experience (VCE) shapes their impact on consumer decisions, particularly in intangible service contexts such as telecommunications. This study addresses this gap by investigating the influence of four AI technologies—chatbots, dynamic pricing, voice search, and visual search—on purchasing decisions, with VCE tested as a critical moderating mechanism. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) and survey data from 487 telecommunications customers in Saudi Arabia, the findings confirm significant positive direct effects for all four AI tools. Moreover, the VCE significantly amplifies these individual relationships and further strengthens their combined contribution to decision quality, enabling the model to explain 71.2% of the variance in purchasing decisions. The results indicate that competitive advantage in AI-enabled service markets depends not on deploying isolated technologies, but on orchestrating a coherent, high-quality virtual experience ecosystem. By integrating the Technology Acceptance Model (TAM) and Stimulus–Organism–Response (SOR) framework, this study advances the theoretical understanding of how AI and experience design jointly enhance digital decision-making. Practically, it underscores the need for managers to prioritize integrated VCE design to drive sustainable consumption and strengthen customer loyalty in increasingly digital service environments.","author":[{"family":"Mousa","given":"Mohammad"},{"family":"Rashed","given":"Abdullah"},{"family":"Akaileh","given":"Mustafa"},{"family":"Zamil","given":"Ahmad"},{"family":"Ahmed","given":"Hebatallah"},{"family":"Abdelghani","given":"Abdelrahman"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18062674","URL":"https://doi.org/10.3390/su18062674","source":"openalex"},{"id":"oa:W7170045378","type":"article-journal","title":"Human-centered Digital Twin in a dynamic manufacturing environment","abstract":"Abstract The optimal design of products is crucial in the manufacturing industry due to its significant impact on economic performance, resource efficiency, and environmental sustainability. This study addresses a critical challenge in tire manufacturing: determining optimal extrusion initializations to improve production efficiency and product quality. To tackle this problem, the research explores the use of Digital Twins, a technology that facilitates the simulation of various scenarios without working directly with the physical system. Specifically, a data-driven Digital Twin approach is employed, which has shown promising computational efficiency in similar contexts. Despite its potential, several challenges associated with Digital Twins have been identified in the literature, including issues related to human–machine interaction, model adaptability to dynamic changes, data quality, and overall precision. This study advances Digital Twin technology by developing a framework that enables real-time identification and control of crucial physical parameters. The proposed approach emphasizes real-time computation, seamless process integration, adaptability to production demands, and user-friendly interaction for operators. This approach, according to our results, could avoid the 99% failed extrusions and could decrease 82% the time required to stabilize product quality. These outcomes demonstrate the practicality and effectiveness of the Digital Twin in improving manufacturing operations. The study also underscores the importance of incorporating human-centric design principles, ensuring that the technology not only enhances operational efficiency but also aligns with the needs of the operators. Overall, the research highlights the significant advancements and practical benefits of applying Digital Twin technology in tire manufacturing.","author":[{"family":"Perez","given":"Eider"},{"family":"Calle","given":"Kerman"},{"family":"Calvo","given":"Borja"},{"family":"Ferreiro","given":"Susana"},{"family":"Arnáiz","given":"Aitor"},{"family":"García","given":"Álvaro"},{"family":"Garate","given":"Eider"},{"family":"Arnaiz","given":"Aitor"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1017/dce.2026.10065","URL":"https://doi.org/10.1017/dce.2026.10065","source":"openalex"},{"id":"oa:W7131265723","type":"article-journal","title":"A Survey of Smart Grid Emerging Use Cases and Relevant 5G and 6G Capabilities and Features","abstract":"The growing complexity of modern energy systems has led to the adoption of Smart Grid (SG) that use advanced communication technologies to facilitate efficient, reliable, secure, and sustainable energy operation and management. Unlike existing surveys that often treat grid and communication domains separately, this work rigorously quantifies service requirements for high-complexity emerging scenarios. It provides a comprehensive overview of SG architecture that integrates digital communication infrastructure with distributed energy resources (DERs), microgrids, energy storage systems, and cybersecurity frameworks. Furthermore, emerging SG use cases such as smart distributed voltage control, real-time fault detection and self-healing, smart and autonomous monitoring, and predictive maintenance are identified, and more importantly, service performance requirements associated with these use cases have been quantified. Additionally, key capabilities and emerging SG enablers of fifth-generation (5G) and sixth-generation (6G) networks are described. These capabilities and enablers include network slicing, edge computing, spectrum management, artificial intelligence (AI) driven optimization, digital twins, and Open-Radio Access Network (O-RAN). Finally, the paper discusses open challenges and future research directions for designing scalable, intelligent, and secure next-generation SG systems.","author":[{"family":"Kumar","given":"Manoj"},{"family":"Tripathi","given":"Nishith"},{"family":"Reed","given":"Jeffrey"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/access.2026.3667671","URL":"https://doi.org/10.1109/access.2026.3667671","source":"openalex"},{"id":"oa:W4415820067","type":"article-journal","title":"Reproducing Cold-Chain Conditions in Real Time Using a Controlled Peltier-Based Climate System","abstract":"Temperature excursions during refrigerated transport strongly affect the quality and shelf life of perishable food, yet reproducing realistic, time-varying cold-chain temperature histories in the laboratory remains challenging. In this study, we present a compact, portable climate chamber driven by Peltier modules and an identification-guided control architecture designed to reproduce real refrigerated-truck temperature histories with high fidelity. Control is implemented as a cascaded regulator: an outer two-degree-of-freedom PID for air-temperature tracking and faster inner PID loops for module-face regulation, enhanced with derivative filtering, anti-windup back-calculation, a Smith predictor, and hysteresis-based bumpless switching to manage dead time and polarity reversals. The system integrates distributed temperature and humidity sensors to provide real-time feedback for precise thermal control, enabling accurate reproduction of cold-chain conditions. Validation comprised two independent 36-day reproductions of field traces and a focused 24-h comparison against traditional control baselines. Over the long trials, the chamber achieved very low long-run errors (MAE≅0.19 °C, MedAE≅0.10 °C, RMSE≅0.33 °C, R2=0.9985). The 24-h test demonstrated that our optimized controller tracked the reference, improving both transient and steady-state behaviour. The system tolerated realistic humidity transients without loss of closed-loop performance. This portable platform functions as a reproducible physical twin for cold-chain experiments and a reliable data source for training predictive shelf-life and digital-twin models to reduce food waste.","author":[{"family":"López","given":"Javier"},{"family":"Ramallo-González","given":"Alfonso"},{"family":"Buendía","given":"Manuel"},{"family":"Toledo","given":"Ana"},{"family":"Torres-Sánchez","given":"Roque"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/s25216689","URL":"https://doi.org/10.3390/s25216689","source":"openalex"},{"id":"oa:W7162039214","type":"article-journal","title":"A Systematic Review of Data Fusion Techniques for Digital Twin Applications in the AEC Sector: Perspectives for Geotechnical Engineering","abstract":"The transformative role of Digital Twins (DTs) in the Architecture, Engineering, and Construction (AEC) sector lies in their capacity to generate dynamic, data-driven representations of physical assets that support design, construction, and lifecycle management. To achieve their full potential, DTs must integrate accurate geometric models with continuously updated information reflecting real-world conditions. This information is inherently multidisciplinary and heterogeneous, encompassing structural, environmental, operational, and monitoring data characterized by different spatial and temporal scales. Integrating these diverse datasets into a unified DT environment presents significant challenges related to data heterogeneity, interoperability, varying resolutions, data quality, and uncertainty. This paper presents a PRISMA-based systematic literature review of data fusion techniques applied to DTs within the AEC sector, with particular emphasis on geotechnical and underground infrastructure. A Scopus search conducted on 31 March 2026 retrieved 10,124 records. After sequential screening, 1916 geotechnical-related records were retained for quantitative characterization, 719 records were assessed for eligibility, 454 reports were retained for manual assessment, and 82 studies were finally included in the detailed qualitative review. Existing approaches are classified according to their integration paradigms, methodological foundations, and application domains. Particular attention is given to applications in Geotechnical Engineering, where DTs must integrate sparse, indirect, and highly uncertain subsurface data. Geological conditions are characterized by strong spatial variability, limited observability, material heterogeneity, and epistemic uncertainty, which introduce additional complexities for data fusion compared to surface infrastructure systems. By synthesizing current developments and identifying methodological trends and research gaps, this review provides a structured framework to support the selection and adaptation of data fusion strategies for geotechnical DTs and other complex AEC applications operating under high uncertainty.","author":[{"family":"Sotelo","given":"Raúl"},{"family":"Lozano-Galant","given":"Fidel"},{"family":"Lozano-Galant","given":"Jose"},{"family":"Domingo","given":"Magí"},{"family":"Turmo","given":"Jose"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/app16105170","URL":"https://doi.org/10.3390/app16105170","source":"openalex"},{"id":"oa:W7127048644","type":"article-journal","title":"Digital twins: a synthesis of complexity theory and artificial intelligence","abstract":"Purpose. The objective of this study is to analyze the concept of digital twins as a technology integrating complexity theory and artificial intelligence, and to examine their applications across various fields. Particular emphasis is placed on mathematical approaches to the construction of digital twins, their distinctions from traditional mathematical models, and future development prospects. Methods. This research employs an interdisciplinary approach, incorporating an analysis of contemporary technologies such as physics-informed neural networks, reduced-order models, graph neural networks, and reservoir computing. A comparison of first-principles and data-driven modeling methods is conducted, with a focus on their integration for creating hybrid digital twins. Results. The findings demonstrate that digital twins possess unique characteristics, including dynamism, adaptability, and bidirectional interaction with physical objects. The key advantages and limitations of various mathematical approaches are identified, encompassing their applicability in industry, medicine, economics, and other domains. A general mathematical formalization of a digital twin, integrating traditional models and machine learning methods, is proposed. Conclusion. The prospects for the development of digital twins are outlined, including the creation of end-to-end ecosystems and the advancement of hybrid approaches for modeling complex nonlinear processes. The importance of further integration of complexity theory and artificial intelligence methods to enhance the accuracy and adaptability of virtual models is emphasized. Digital twins present new opportunities for the forecasting and management of complex systems under uncertainty, establishing them as a pivotal tool in science, industry, and society.","author":[{"family":"Andreev","given":"Andrey"},{"family":"Daraselya","given":"Levan"},{"family":"Dozhdev","given":"Vladimir"},{"family":"Ministry Of Industry And Trade Of The Russian Federation","given":"Moscow"},{"family":"Shenderyuk-Zhidkov","given":"Aleksandr"},{"family":"Shpak","given":"Vasily"},{"family":"Hramov","given":"Aleksandr"}],"issued":{"date-parts":[[2026]]},"DOI":"10.18500/0869-6632-003211","URL":"https://doi.org/10.18500/0869-6632-003211","source":"openalex"},{"id":"oa:W7125103566","type":"article-journal","title":"Open Public Data and the Path to Urban Sustainable Development: A Resilience Perspective","abstract":"ABSTRACT Within the framework of sustainable development in the digital era, the vast yet inactive reservoir of public data represents a hidden pathway toward building resilient cities. This point has often been overlooked in existing research. Our core objective is to investigate the impact of China's public data openness (PDO) on urban resilience. This action aims to establish public data platforms and provide more publicly accessible, machine readable, and freely usable public data in order to fully unlock the value of public data. We find that PDO significantly enhances urban resilience, with an average treatment effect of 0.003. This conclusion remains valid after a series of robustness tests. Specifically, PDO improves economic resilience, infrastructure resilience, and institutional resilience, but has no significant effect on social resilience and even exerts a negative impact on ecological resilience. Meanwhile, the impact of PDO on urban resilience is not uniform and varies across different types of cities. We also find that PDO improves urban resilience by promoting technological innovation, fostering emerging industries, and advancing digital finance. Moreover, PDO generates a significant positive spatial spillover effect on the urban resilience of neighboring areas, and the spatial spillover boundary is well defined. Our study extends the traditional framework of urban digital governance and provides practical policy insights for emerging countries experiencing rapid urbanization on how to fully unlock the potential of public data and enhance urban resilience.","author":[{"family":"Jiang","given":"Wei"},{"family":"Jiang","given":"Nana"},{"family":"Yu","given":"Donghua"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1002/sd.70695","URL":"https://doi.org/10.1002/sd.70695","source":"openalex"},{"id":"oa:W7128538667","type":"article-journal","title":"From Point Clouds to Predictive Maintenance: A Review of Intelligent Railway Infrastructure Monitoring","abstract":"Point cloud technology, characterized by its high-precision 3D geometric acquisition in complex railway environments, has become a cornerstone for the intelligent detection, monitoring, and maintenance of railway infrastructure. This paper provides a systematic review of point cloud applications across critical railway scenarios, encompassing track geometry extraction, infrastructure component identification, tunnel and bridge modeling, clearance and encroachment analysis, and structural condition monitoring. We evaluate various mobile and stationary acquisition platforms alongside their typical data processing workflows. Furthermore, this review synthesizes cutting-edge advancements in processing algorithms, with a focus on feature extraction, semantic segmentation, and the transformative impact of deep learning and artificial intelligence on data fusion. Notably, the paper explores the synergy between point clouds and computational mechanics, specifically the construction of high-fidelity digital twins through multi-physics coupling to enable real-time simulation of structural stress distribution and damage evolution. We critically analyze persistent technical bottlenecks, such as acquisition efficiency, monitoring precision, data fragmentation, environmental interference, and the complexities of multi-modal data fusion. Finally, the paper outlines future research trajectories, focusing on autonomous intelligent sensing, multi-sensor integration, and the comprehensive digital transformation of railway infrastructure management, aiming to provide a robust theoretical framework and technical roadmap for the sustainable intelligentization of global railway systems.","author":[{"family":"Zhang","given":"Yalin"},{"family":"Dai","given":"Peng"},{"family":"Sysyn","given":"Mykola"},{"family":"Hu","given":"Yuchuan"},{"family":"Kou","given":"Lei"},{"family":"Song","given":"Haoran"},{"family":"Shi","given":"Jing"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/s26041131","URL":"https://doi.org/10.3390/s26041131","source":"openalex"},{"id":"oa:W7196961589","type":"article-journal","title":"Integration of digital twin technologies in smart grid substations","abstract":"Abstract In the era of Industry 5.0, digital transformation of smart grid substations is crucial to address growing demands for efficiency and reliability. However, conventional substations lack real-time monitoring. Fault detection takes a long time, and predictive maintenance is substandard. In this research, an entirely new approach is proposed to transform substation work processes by combining Digital Twin (DT) technologies with an algorithm based on Gradient Boosting Machine (GBM) designs. Within the confines of a digital twin technology, a substation can begin to operate, and hence a virtual representation, which can be termed, an operating digital twin of a substation can be created ready for real time, predictive fault diagnosis, and active asset management. The solution proposed reduces total operational downtime by 30% and increases fault detection performance by 25%, the results supported by the following performance metrics Precision 94%, Recall 91%, and F1-score 92%. Analysis performed in the MATLAB simulations proves that the substations adaptive control systems can maintain the stability and reliability of the electricity grid system with variable loads and environmental conditions, thereby allowing the creation of advanced smart substations which are more efficient and reliable.","author":[{"family":"Lin","given":"Jiaxin"},{"family":"Wu","given":"Wenyuan"},{"family":"Hu","given":"Bo"},{"family":"Qin","given":"Qiang"},{"family":"Huang","given":"Hanye"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s12083-026-02275-x","URL":"https://doi.org/10.1007/s12083-026-02275-x","source":"openalex"},{"id":"oa:W7116942832","type":"article-journal","title":"A Critical Review of Green Hydrogen Production by Electrolysis: From Technology and Modeling to Performance and Cost","abstract":"As the world shifts toward a low-carbon future, green hydrogen has emerged as a critical pillar of the energy transition. It is produced using renewable energy to power water electrolysis, and it is a clean and flexible alternative to hydrogen made from fossil fuels. However it is still hard to roll out on a large scale because of technological limits, high costs, and the need for infrastructure. This review critically analyzes current electrolysis methods, including established systems like alkaline and PEM electrolyzers, as well as newly developed concepts such as AEMWE and SOWE. It discusses how they can be used in renewable energy systems, important techno-economic and durability problems, system modeling, and grid interaction. This work clarifies both the technological potential and the practical limitations of green-hydrogen electrolyzer systems while highlighting key directions for future research and implementation.","author":[{"family":"Louli","given":"Rafika"},{"family":"Giurgea","given":"Stéfan"},{"family":"Salhi","given":"Issam"},{"family":"Laghrouche","given":"Salah"},{"family":"Djerdir","given":"Abdesslem"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/en19010059","URL":"https://doi.org/10.3390/en19010059","source":"openalex"},{"id":"oa:W7165064935","type":"article-journal","title":"Sandbox-Enabled Digital Twin for Cyber-Physical Systems","abstract":"Firmware/software in cyber-physical system (CPS) embedded devices/controllers can have vulnerabilities stemming from multiple sources such as weak security practices, outdated libraries, or supply chain attacks that induce adversarial effects under plant state-based triggers. However, pre-deployment validation of CPS controllers typically relies on digital twins that model controller logic as a black box. On the other hand, side channel monitoring and anomaly detection of CPS controller firmware/software is complementary, but is typically exercised with synthetic inputs or under specific CPS operational profiles and does not simultaneously track software execution and CPS plant evolution. To bridge this gap, we present a closed-loop digital twin framework that hosts unmodified controller binaries in a Linux sandbox (SaMOSA) with its I/O rerouted to an external plant simulator. The framework captures four time-synchronized side channels (hardware performance counters, system calls, disk activity, network activity) alongside plant state and provides orchestration hooks for automated, repeatable, parameterized runs. We demonstrate the framework on an OpenPLC runtime controlling a Modbus-connected IEEE 14-bus power system, and also briefly discuss application to robotics systems. The synchronized traces correlate internal controller execution with plant events, providing an observability foundation for online testing, coverage analysis, and vulnerability detection.","author":[{"family":"Udeshi","given":"Meet"},{"family":"Raz","given":"Md"},{"family":"Krishnamurthy","given":"P"},{"family":"Karri","given":"Ramesh"},{"family":"Khorrami","given":"Farshad"},{"family":"Krishnamurthy","given":"Prashanth"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/iolts69666.2026.11633564","URL":"https://doi.org/10.1109/iolts69666.2026.11633564","source":"openalex"},{"id":"oa:W7163191532","type":"article-journal","title":"Digital twin for joining mechanical structures in assembly processes","abstract":"Abstract Ensuring geometric accuracy in joining mechanical structures is a key challenge in smart manufacturing, particularly during assembly. To improve assembly and joining accuracy, this paper employs digital twin technology, with a focus on high-fidelity digital modeling as a foundational step toward realizing digital twins–while treating bidirectional automated data flow as a future development direction. Digital twin models are developed for two representative joint types: threaded connections and spot-welded sheet metal structures, incorporating critical influences from manufacturing, assembly, and service phases. Compared to traditional idealized simulations, the proposed models enable more effective assembly process optimization and enhanced geometric quality control.","author":[{"family":"Saren","given":"Qimuge"},{"family":"Tabar","given":"Roham"},{"family":"Söderberg","given":"Rikard"},{"family":"Wärmefjord","given":"Kristina"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s10845-026-02884-6","URL":"https://doi.org/10.1007/s10845-026-02884-6","source":"openalex"},{"id":"oa:W7161161234","type":"article-journal","title":"A knowledge graph framework for digital twins of chemical processes","abstract":"A digital twin, which virtually replicates a real system and fuses data, models and domain knowledge, is a key technology for accelerating chemical process development and addressing sustainability challenges. Despite its potential, one critical challenge lies in the lack of a systematic approach to integrate data, domain knowledge and predictive models to contextualize and represent chemical processes effectively. Here we propose a knowledge graph framework associated with autonomous functional agents to support the development of digital twins for chemical processes, enabling the seamless incorporation of chemical databases, artificial intelligence models and large language models. Ontologies are developed for physical models of chemical processes, allowing scalable model construction and calibration. We demonstrate the framework with practical case studies focusing on bottom-up model assembly, top-down model search and model-based reaction optimization. The framework presents an approach to manage models as a depository of chemical process knowledge, providing a foundation of digital twin technology for future chemical process development and manufacturing.","author":[{"family":"Zhang","given":"Shuyuan"},{"family":"Zhang","given":"Jiyizhe"},{"family":"Lapkin","given":"Alexei"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s44286-026-00392-1","URL":"https://doi.org/10.1038/s44286-026-00392-1","source":"europepmc"},{"id":"oa:W7155032220","type":"article-journal","title":"A Digital Twin-Inspired Correction Method for Infrared Detectors","abstract":"Infrared focal plane arrays (IRFPAs) often suffer from spatiotemporal nonuniformity that persists after conventional two-point nonuniformity correction (NUC), especially under temperature drift and time-varying readout conditions. These residuals are typically structured, including column-group striping caused by shared column-end circuits and row-wise baseline/common-mode drift induced by row-scanning paths. We propose a structured, digital-twin-inspired detector-side refinement of two-point NUC that augments the bias term with interpretable low-dimensional components: a static column bias vector capturing group-correlated residuals and a row-related structured term consisting of a static row baseline and a frame-synchronous common-mode component with row-dependent sensitivity, while keeping the two-point gain/offset backbone unchanged. Rather than representing a full system-level digital twin of the infrared payload, the proposed framework serves as a detector-side virtual representation of dominant readout-induced structured residual states that can be estimated and updated from calibration data. Experiments on blackbody calibration data across multiple temperature points demonstrate that the column-related structured component significantly reduces group-wise column residuals, the row-related structured component suppresses time-varying row striping, and the combined method improves both column- and row-direction metrics consistently across temperatures.","author":[{"family":"Tian","given":"Jiangyu"},{"family":"Jin","given":"Libing"},{"family":"Chang","given":"JJI"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/photonics13040396","URL":"https://doi.org/10.3390/photonics13040396","source":"openalex"},{"id":"oa:W4414693509","type":"article-journal","title":"Deep reinforcement learning for optimal planning of production line maintenance with deterioration","abstract":"Manufacturing companies often contend with deteriorating production systems that can significantly hinder overall performance. Therefore, optimizing maintenance planning strategies plays a crucial role in enhancing production efficiency. In this study, we address a novel maintenance decision-making problem in serial production lines, where machine degradation leads to product quality deterioration and throughput loss at the final stage. We propose a new framework that jointly considers product quality trends, buffer dynamics, and machine production states to optimize a preventive maintenance policy for the last machine in the line. To achieve this, we utilize an average-reward deep reinforcement learning (DRL) approach within a discrete event simulation environment and compare their effectiveness to conventional dispatching methods. Our results, based on a digital twin enriched with real production data, show that the proposed DRL approach consistently outperforms traditional dispatching rules and practitioner-designed heuristics. This study is the first to apply DRL to maintenance decision-making in serial production systems that explicitly model product quality degradation, machine production states and buffer interactions—addressing a key gap in current literature.","author":[{"family":"Geurtsen","given":"Michael"},{"family":"Leenen","given":"Cas"},{"family":"Adan","given":"Ivo"},{"family":"Atan","given":"Zümbül"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.ress.2025.111767","URL":"https://doi.org/10.1016/j.ress.2025.111767","source":"openalex"},{"id":"oa:W7203494127","type":"article-journal","title":"Towards a Robust Adaptive Digital Twin for Fusion Applications","abstract":"The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.","author":[{"family":"Sc","given":"Nuclear"},{"family":"Sammuli","given":"Brian"},{"family":"Tjnaf","given":"Thomas"},{"family":"Rajput","given":"Kishansingh"},{"family":"Lin","given":"Sen"},{"family":"Schram","given":"Malachi"},{"family":"Hasan","given":"Mahmudul"}],"issued":{"date-parts":[[2025]]},"DOI":"10.2172/3400840","URL":"https://doi.org/10.2172/3400840","source":"openalex"},{"id":"oa:W4410001136","type":"article-journal","title":"The Impact of Data Element Marketization on Green Total Factor Energy Efficiency: Empirical Evidence from China","abstract":"Given the escalating severity of climate change and environmental degradation, the transition to green and low-carbon energy has become a strategic priority for China’s economic development. Green total factor energy efficiency (GTFEE), which captures energy utilization efficiency while accounting for environmental constraints and desirable outputs, has emerged as a key indicator for evaluating green energy transition performance. Data element marketization (DEM), as a vital institutional innovation, provides new impetus for accelerating the transition to green and low-carbon energy. This study leveraged the establishment of China’s data trading platforms as a quasi-natural experiment to systematically assess the effects, mechanisms, and spatial heterogeneity of DEM on urban GTFEE. The findings reveal that DEM has a statistically significant positive impact on urban GTFEE in the short term, while demonstrating a gradual diminishing marginal effect over the long term. Furthermore, this study uncovered heterogeneous effects based on factors such as city type, urban energy intensity, and new-energy pilot, as well as urban government governance capacity. Mechanism analysis demonstrated that DEM enhances urban GTFEE by accelerating the generation of data elements and fostering their deep integration with artificial intelligence (AI). Spatial analysis indicated that, while DEM significantly improves GTFEE in local cities, it generates negative spillover effects on neighboring cities due to the persistence of the digital divide.","author":[{"family":"Peng","given":"Ying"},{"family":"Wang","given":"Xinyue"},{"family":"Gao","given":"Weilong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17094099","URL":"https://doi.org/10.3390/su17094099","source":"openalex"},{"id":"oa:W7163991932","type":"article-journal","title":"Constructing a Cost–Benefit Analysis Framework for Digital Twin–Enabled Spatial Planning: Articulating (Hidden) Costs and (Implicit) Benefits in Governmental Organizations","abstract":"Digital Twins (DTs) are increasingly used in urban planning and public-sector spatial development to support evidence-based decision-making and scenario analysis. However, many DT initiatives struggle to progress beyond pilot stages (Hiller et al., 2026), partly due to the absence of a clear and validated cost–benefit analysis (CBA) framework. Existing evaluations often underestimate lifecycle costs while failing to adequately articulate indirect and intangible benefits such as improved decision quality, stakeholder engagement, and transparency. This research-in-progress study tries to address this gap by asking how hidden costs and implicit benefits of DTs in public-area development can be identified and structured into a first version of a CBA framework. Using a Design Science approach, we combine a scoping review further supplemented with exploratory expert interviews in a Dutch spatial planning context. Preliminary findings highlight lifecycle and governance-related costs and indicate that DT value primarily emerges through improved decision quality and reduced downstream failure costs, though further detailing and validation is required in future research.","author":[{"family":"Leewis","given":"Sam"},{"family":"Smit","given":"Koen"},{"family":"Meerten","given":"John"},{"family":"Buijsse","given":"Ronald"}],"issued":{"date-parts":[[2026]]},"DOI":"10.18690/um.fov.4.2026.66","URL":"https://doi.org/10.18690/um.fov.4.2026.66","source":"openalex"},{"id":"oa:W7130322411","type":"article-journal","title":"Mathematical Modeling of Operational Reliability of Mine Lifting Equipment Based on Censored Data","abstract":"In this study, a comprehensive mathematical method for modeling the operational reliability of mine hoisting equipment under conditions of incomplete and heavily censored data is developed. The analyzed dataset includes 259 observations collected over a five-year period for six critical components, with the overall level of censoring reaching 62% and exceeding 70% for long life mechanical subsystems. Considering right, left, and interval censoring, the paper proposes a unified statistical procedure that combines empirical estimation of failure rates with parametric identification using Weibull, exponential, normal, and lognormal distributions. Model parameters are estimated using censored data–aware fitting procedures, while model selection is performed based on likelihood-based criteria, supplemented by correlation analysis to assess agreement between empirical and fitted reliability curves. The methodology is implemented computationally in the Mathcad Prime environment and is supplemented with mathematical tools for reconstructing survival curves, analyzing parameter sensitivity, and evaluating robustness at different censoring levels. In addition, an economic optimization model is formulated to determine cost-effective maintenance intervals by minimizing an integral functional that accounts for preventive maintenance, repair, and downtime costs. The results demonstrate that the proposed approach provides stable reliability estimates and reliable forecast intervals, enabling the construction of generalized life cycle curves for individual subsystems. The study establishes a rigorous mathematical basis for the transition from fixed-interval maintenance to adaptive, reliability-oriented maintenance strategies in industrial mine hoisting systems.","author":[{"family":"Zadkov","given":"Denis"},{"family":"Martyushev","given":"Nikita"},{"family":"Malozyomov","given":"Boris"},{"family":"Demin","given":"Anton"},{"family":"Pogrebnoy","given":"Alexander"},{"family":"Kuleshova","given":"Elezaveta"},{"family":"Valuev","given":"Denis"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/math14040716","URL":"https://doi.org/10.3390/math14040716","source":"openalex"},{"id":"oa:W4408718247","type":"article-journal","title":"Lensless imaging with a programmable Fresnel zone aperture","abstract":"Optical imaging has long been dominated by traditional lens-based systems that, despite their success, are inherently limited by size, weight, and cost. Lensless imaging seeks to overcome these limitations by replacing lenses with thinner, lighter, and cheaper optical modulators and reconstructing images computationally, while facing trade-offs in image quality, artifacts, and flexibility inherent in traditional static modulation. Here, we propose a lensless imaging method with programmable Fresnel zone aperture (FZA), termed LIP. With a commercial liquid crystal display, we designed an integrated LIP module and demonstrated its capability of high-quality artifact-free reconstruction through dynamic modulation and offset-FZA parallel merging. Compared to static-modulation approaches, LIP achieves a 2.5× resolution enhancement and a 3 decibels improvement in signal-to-noise ratio in \"static mode\" while maintaining an interaction frame rate of 15 frames per second in \"dynamic mode.\" Experimental results demonstrate LIP's potential as a miniaturized platform for versatile advanced imaging tasks like virtual reality and human-computer interaction.","author":[{"family":"Zhang","given":"Xu"},{"family":"Wang","given":"Bowen"},{"family":"Li","given":"Sheng"},{"family":"Liang","given":"Kunyao"},{"family":"Guan","given":"Haitao"},{"family":"Chen","given":"Qian"},{"family":"Zuo","given":"Chao"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1126/sciadv.adt3909","URL":"https://doi.org/10.1126/sciadv.adt3909","source":"openalex"},{"id":"oa:W7124201277","type":"article-journal","title":"Skin‐Integrated Wearable Electronics: A Dual‐Interface Perspective","abstract":"ABSTRACT Skin‐integrated wearable electronics enable continuous, medical‐grade monitoring and therapy in daily life, but must balance conflicting needs related to mechanics, power, and communication. This review uses a dual‐interface approach that separates the sensor–receiver interface, which handles wireless data and energy transfer, from the sensor–skin interface, where physiological signals are converted and mechanical and biological integration occur. We first reviewed wireless connections designed for skin electronics, focusing on Bluetooth Low Energy (BLE), Radio Frequency Identification (RFID)/Near‐Field Communication (NFC) systems, and hybrid systems. Next, we examine sensor–skin interfaces ranging from mediated contact layers such as hydrogels for wearable ultrasound and soft conductive electrodes, to skin‐conformal direct‐contact methods based on structural mechanics, and ultrathin epidermal devices. Finally, we discuss cross‐interface coupling, emphasizing how antenna layouts, power budgets, and body‐induced RF effects limit mechanical design, and how skin mechanics influence link reliability. We conclude by exploring opportunities in battery‐free and energy‐autonomous systems, body‐coupled communication, and integration with artificial intelligence (AI)‐enabled digital health, positioning future electronic skins as soft, networked platforms that are comfortable and reliable.","author":[{"family":"Dong","given":"Fuying"},{"family":"Han","given":"Chi"},{"family":"Cai","given":"Sheling"},{"family":"Lee","given":"Ju‐hyuck"},{"family":"Niu","given":"Simiao"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/sys3.70013","URL":"https://doi.org/10.1002/sys3.70013","source":"openalex"},{"id":"oa:W7118186566","type":"article-journal","title":"Innovative Preservation Technologies and Supply Chain Optimization for Reducing Meat Loss and Waste: Current Advances, Challenges, and Future Perspectives","abstract":"Food loss and waste (FLW) is a chronic problem across food systems worldwide, with meat being one of the most resource-intensive and perishable categories. The perishable character of meat, combined with complex cold chain requirements and consumer behavior, makes the sector particularly sensitive to inefficiencies and loss across all stages from production to consumption. This review synthesizes the latest advancements in new preservation technologies and supply chain efficiency strategies to minimize meat wastage and also outlines current challenges and future directions. New preservation technologies, such as high-pressure processing, cold plasma, pulsed electric fields, and modified atmosphere packaging, have substantial potential to extend shelf life while preserving nutritional and sensory quality. Active and intelligent packaging, bio-preservatives, and nanomaterials act as complementary solutions to enhance safety and quality control. At the same time, blockchain, IoT sensors, AI, and predictive analytics-driven digitalization of the supply chain are opening new opportunities in traceability, demand forecasting, and cold chain management. Nevertheless, regulatory uncertainty, high capital investment requirements, heterogeneity among meat types, and consumer hesitancy towards novel technologies remain significant barriers. Furthermore, the scalability of advanced solutions is limited in emerging nations due to digital inequalities. Convergent approaches that combine technical innovation with policy harmonization, stakeholder capacity building, and consumer education are essential to address these challenges. System-level strategies based on circular economy principles can further reduce meat loss and waste, while enabling by-product valorization and improving climate resilience. By integrating preservation innovations and digital tools within the framework of UN Sustainable Development Goal 12.3, the meat sector can make meaningful progress towards sustainable food systems, improved food safety, and enhanced environmental outcomes.","author":[{"family":"Bytyqi","given":"Hysen"},{"family":"Barros","given":"Ana"},{"family":"Krauter","given":"Victoria"},{"family":"Smaoui","given":"Slim"},{"family":"Varzakas","given":"Theodoros"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18010530","URL":"https://doi.org/10.3390/su18010530","source":"openalex"},{"id":"doi:10.1108/bepam-07-2025-0206","type":"article-journal","title":"A bibliometric review of digital twin-enabled technologies for construction project monitoring and control","abstract":"Purpose Construction projects often suffer from delays, cost overruns, and fragmented control due to isolated implementation of Computer Vision (CV), Internet of Things (IoT), Building Information Modelling (BIM), and Machine Learning (ML). This study addresses this gap by proposing a comprehensive Digital Twin framework that integrates these technologies into a unified system for real-time monitoring and predictive control of labor, material, equipment, and activity (LMPA). Design/methodology/approach A four-phase bibliometric approach was followed: (1) retrieving 2,032 studies (2014–2024) from the search database; (2) screening through multi-level filtering to retain 534 relevant papers; (3) network analysis and mapping keywords in Gephi and forming thematic clusters using the Louvain algorithm; and (4) identifying the research gap of fragmented CV, IoT, BIM, and ML applications and developing a Digital Twin framework for real-time LMPA control. Findings Nineteen functional clusters were identified across the four domains: CV (Visual Understanding, Edge Hardware, Metrics, LMPA Algorithms, Analytics), IoT (Sensors, Transmission, Edge Devices, Signal Processing, Dashboards), BIM (Foundations, 4D/5D Control, Progress Tracking, As-Built Alignment), and ML (Data Preparation, Model Training, Forecasting, Optimization, Real-Time Feedback). These form a Digital Twin framework for real-time, closed-loop project monitoring and control. Originality/value Unlike prior reviews focusing on single technologies or static visualisation, this study integrates CV, IoT, BIM, and ML into a single, evidence-based Digital Twin framework tailored to closed-loop LMPA control.","author":[{"family":"Padala","given":"SPS"},{"family":"Padala","given":"Srinivas"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1108/bepam-07-2025-0206","URL":"https://doi.org/10.1108/bepam-07-2025-0206","source":"openalex"},{"id":"doi:10.1016/j.crbeha.2026.100221","type":"article-journal","title":"Multi-modal human digital twin for hydration","abstract":"Hydration plays a crucial role in maintaining physical and mental wellbeing, yet individuals differ substantially in their daily hydration needs due to variations in diet, physiology, activity, and context. This pilot study explores the feasibility of developing a multi‑modal human digital twin for hydration, integrating continuous real‑world data from urine specific gravity (USG), nutritional intake, wearable‑based physiological signals, and ecological momentary assessments. Three participants were monitored across 20 non‑consecutive days, collecting USG at every toilet visit, logging food and drink consumption, and wearing Garmin VivoSmart5 and Chill+ sensors to capture heart rate, movement, and galvanic skin response. USG proved to be a sensitive hydration marker, revealing consistent diurnal patterns and partial alignment with subjective hydration reports, though substantial variability highlighted the limitations of self‑reported hydration. Multimodal analyses indicated a complex interplay among hydration, diet, physiological signals, and contextual factors, including strong effects of specific beverages such as Aquarius and coffee. Personalized machine‑learning models trained per participant showed reasonable predictive power and outperformed pooled models, underscoring the individualized nature of hydration dynamics. Preliminary in‑silico simulations demonstrated the potential of the digital‑twin to give specific drink recommendations. On the other hand, these also revealed limitations of window‑based modeling that cannot capture cumulative or long-term physiological dynamics, suggesting that the future hybrid approach that embeds mechanistic physiology alongside machine learning is necessary for realistic and actionable hydration digital twins. These findings support the feasibility and promise of a personalized hydration digital twin and lay the groundwork for future expansion toward more comprehensive and physiologically grounded models.","author":[{"family":"Thammasan","given":"Nattapong"},{"family":"Teichmann","given":"Tobias"},{"family":"Kraaij","given":"Alex"},{"family":"Gaitan","given":"Santiago"},{"family":"Stiphout","given":"Ruud"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.crbeha.2026.100221","URL":"https://doi.org/10.1016/j.crbeha.2026.100221","source":"openalex"},{"id":"doi:10.1117/1.jbo.31.8.080601","type":"article-journal","title":"Optical digital twins for disease prevention, diagnosis, therapy, and intervention.","abstract":"Significance: Digital twins are transitioning from conceptual models to operational frameworks that link measurement, prediction, and intervention in biomedicine. However, most biomedical digital twin efforts remain fragmented, with limited integration across biological scales, sensing modalities, and clinical decision points. Biophotonics provides a uniquely suited measurement foundation for biomedical digital twins by enabling quantitative, physics-grounded, and longitudinal noninvasive measurements spanning molecular, cellular, tissue, organ, and whole-body scales. These capabilities position photonics as a foundational measurement layer for next-generation biomedical digital twins. Aim: To synthesize current advances and future opportunities in optical digital twins and to establish a unifying framework for how photonic sensing can support digital twin architectures for disease diagnosis, therapy guidance, prevention, continuous monitoring, and interventional healthcare. Approach: This white paper summarizes perspectives presented at the annual meeting of the international society for optics and photonics (SPIE Photonics West), in the session \"Digital Twins as New Approach Methodologies (NAMs) in Biophotonics.\" We review five complementary implementations of the digital twin paradigm: (i) virtual tissue staining for histopathology, which combines label-free optical imaging with machine learning-based inference to generate clinically interpretable representations with uncertainty quantification and validation; (ii) cell-level metabolic digital twins that use autofluorescence and redox imaging to predict patient-specific therapeutic responses in tumor organoids and immune cells under controlled perturbations; (iii) therapeutic digital twin frameworks for radiation therapy, in which Cherenkov imaging and radiation chemistry sensing verify treatment delivery and enable biophysical model correction and personalization; (iv) personalized optical digital twins for continuous monitoring that integrate longitudinal photonic sensing with physiological and contextual data to support early detection, prevention, and adaptive care; and (v) personalized digital twins for interventional healthcare. Results: Across these diverse applications, a common digital twin architecture emerges. Optical measurements define patient state, inference models translate measurements into predictions, therapeutic interventions perturb the system, verification measurements constrain and validate execution, and longitudinal sensing continuously updates the twin over time. The reviewed examples demonstrate that optical measurements can serve as a scalable and biologically relevant data layer linking prediction and intervention across multiple levels of biological organization. Conclusions: Optical digital twins are no longer merely a conceptual aspiration but are emerging as a practical, measurement-driven infrastructure for precision medicine. The primary challenge is no longer feasibility, but rather the integration, interoperability, validation, and uncertainty quantification of digital twin systems capable of operating safely and at scale. Advances in photonic sensing, computational modeling, and clinical translation position optical digital twins to support real-time, patient-specific clinical decision-making across diagnosis, treatment, monitoring, and prevention.","author":[{"family":"Özcan","given":"Aydogan"},{"family":"Skala","given":"Melissa"},{"family":"Pogue","given":"Brian"},{"family":"Popp","given":"Jürgen"},{"family":"Marcu","given":"Laura"},{"family":"Clancy","given":"Colleen"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1117/1.jbo.31.8.080601","URL":"https://doi.org/10.1117/1.jbo.31.8.080601","source":"europepmc"},{"id":"oa:W7156660254","type":"article-journal","title":"Digital twins in urological oncology and surgery: A review of emerging applications","abstract":"BACKGROUND: Digital twin technology represents a transformative approach in healthcare, creating virtual replicas of physical entities that enable real-time data integration, predictive modelling, and personalised treatment strategies. In urology, this emerging technology offers unprecedented opportunities to optimise patient care through simulation-based decision-making. AIM: This narrative review comprehensively examines current applications of digital twin technology in urology, evaluates its clinical utility across various urological conditions, and identifies key challenges limiting its widespread implementation. METHOD: A comprehensive search was conducted across PubMed, Web of Science, and Scopus databases for literature published between January 2020 and January 2026. Search terms included digital twin, virtual twin, urology, uro-oncology, prostate cancer, renal surgery, and bladder dysfunction. Studies focusing on the development, validation, and clinical implementation of digital twins in urological practice were included. RESULTS: Digital twin technology demonstrates significant potential in uro-oncology for treatment planning, surgical navigation, and disease progression monitoring. Key applications include patient-specific tumour growth simulation in prostate cancer, three-dimensional anatomical modelling for partial nephrectomy, and bladder function prediction in outlet obstruction. Integration with artificial intelligence enhances predictive accuracy and enables real-time surgical guidance. CONCLUSION: Digital twin technology represents a paradigm shift towards precision urology, though challenges in data integration, computational requirements, validation, and ethical considerations must be addressed before routine clinical implementation. Future developments should focus on standardisation, regulatory frameworks, and prospective clinical validation studies.","author":[{"family":"Olawade","given":"David"},{"family":"Oisakede","given":"Emmanuel"},{"family":"Fidelis","given":"Sandra"},{"family":"Ogunbona","given":"Muyiwa"},{"family":"Makanjuola","given":"Babajide"},{"family":"Daniel","given":"Raphael"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.ejso.2026.111849","URL":"https://doi.org/10.1016/j.ejso.2026.111849","source":"europepmc"},{"id":"oa:W4409505433","type":"article-journal","title":"Digitalization in the Maritime Logistics Industry: A Systematic Literature Review of Enablers and Barriers","abstract":"Digitalization is gaining its popularity in the maritime logistics sector due to its potential to enhance information sharing and automation. These advantages can significantly improve efficiency and have the potential to replace complex manual tasks. However, the diffusion of digitalization faces certain challenges, which, in turn, has drawn the attention of researchers. Implementing digitalization is a complex process, as it is affected by various enablers and barriers, while research providing a comprehensive overview of digitalization in the maritime logistics sector is limited. This study aims to fill the gap by conducting a literature review that reveals digitalization’s enablers and barriers in the maritime logistics sector and constructs a theoretical framework. It analyzes 117 articles that have made significant contributions to this field. The development of innovative technologies, such as blockchain, digital twins, and autonomous shipping, fosters digitalization in maritime logistics. Conversely, barriers like the lack of awareness about the benefits of digitalization can slow down its progress. In total, this paper identifies 19 enablers of and 10 barriers to digitalization in the maritime logistics sector. These enablers and barriers are classified into three groups–technology, organization, and environment–following the Technology–Organization–Environment (TOE) framework. We develop a theoretical framework accordingly using, as its basis, relevant innovation diffusion theories and studies. This study contributes to the development of effective digitalization strategies for maritime organizations and provides a theoretical foundation for future research.","author":[{"family":"Zeng","given":"Fangli"},{"family":"Chen","given":"Anqi"},{"family":"Xu","given":"Shuojiang"},{"family":"Chan","given":"Hing"},{"family":"Li","given":"YL"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/jmse13040797","URL":"https://doi.org/10.3390/jmse13040797","source":"openalex"},{"id":"oa:W4406518246","type":"article-journal","title":"Facilitating Fashion Digital Product Passports: A Review and Comparison of Digital Twin Creation Tools","abstract":"This article reviews and compares two digital twin creation tools, CLO3D and Style3D, focusing on their role in enabling Digital Product Passports (DPPs) in the fashion industry. CLO3D specializes in vivid fashion simulations, helping designers visualize products, while Style3D emphasizes supply chain integration and fabric digitization. User feedback from video analysis shows Style3D receives more positive sentiment due to its practicality in production. Both tools offer unique advantages but have areas to improve. The study highlights the potential of digital twin technology in advancing sustainability and transparency in fashion, though its scope is limited to these two tools and data sources.","author":[{"family":"Zhao","given":"Rui"},{"family":"Liu","given":"Chuanlan"},{"family":"Lang","given":"Chunmin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.31274/itaa.18778","URL":"https://doi.org/10.31274/itaa.18778","source":"openalex"},{"id":"oa:W4408951722","type":"article-journal","title":"Integrated Sensing and Communication for 6G Holographic Digital Twins","abstract":"With the advent of 6G networks offering ultra-high bandwidth and ultra-low latency coupled with the enhancement of terminal device resolutions, holographic communication is gradually becoming a reality. Holographic digital twin (HDT) is considered one of the key applications of holographic communication, capable of creating virtual replicas for real-time mapping and prediction of physical entity states and performing three-dimensional reproduction of spatial information. In this context, integrated sensing and communication (ISAC) is expected to be a crucial pathway for providing data sources to HDT. This article proposes a four-layer architecture assisted by ISAC for HDT, integrating emerging paradigms and key technologies to achieve low-cost, high-precision environmental data collection for constructing HDT. Specifically, to enhance sensing resolution, we explore super-resolution techniques from the perspectives of parameter estimation and point cloud construction. Additionally, we focus on multi-point collaborative sensing for constructing HDT and provide a comprehensive review of four key techniques: node selection, multiband collaboration, cooperative beamforming, and data fusion. Finally, we high-light several interesting research directions to guide and inspire future work.","author":[{"family":"Zhang","given":"Haijun"},{"family":"Zhang","given":"Ziyang"},{"family":"Liu","given":"Xiangnan"},{"family":"Li","given":"Wei"},{"family":"Li","given":"Hongmin"},{"family":"Sun","given":"Chen"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/mwc.001.2400178","URL":"https://doi.org/10.1109/mwc.001.2400178","source":"openalex"},{"id":"oa:W4413044255","type":"article-journal","title":"Convergence of Digital Twins and food drying technology: How to bring the next generation of dryers to life!?","abstract":"Digital Twins technology is rapidly growing and has the potential to revolutionize traditional food-processing methods. However, their application in food-drying processes is still in its infancy. This study aimed to explore how Digital Twins can be applied to food drying process. Traditionally, food drying is performed under constant conditions, where air temperature and velocity remain constant. However, the literature review shows that variable drying conditions (trajectories) can improve both energy efficiency and product quality. The challenge is that the trajectories are calculated based on what happened in the process, not what is currently happening. Digital Twins address this shortcoming by enabling decision making based on real-time data. In this conceptual review paper, physiochemical parameters as an element of the physical world of a Digital Twins-based smart food dryer is first presented. Next, potential sensors for building a digital counterpart of the physiochemical parameters are discussed. This is followed by mathematical models, dynamic optimization, and advanced control, which are the core elements of a decision-making and control unit. Finally, future research needs are discussed. This conceptual review paper will guide and give a solid insight to academic researchers, companies, and other potential stakeholders on merging Digital Twins and food drying technologies.","author":[{"family":"Arefi","given":"Arman"},{"family":"Vilas","given":"Carlos"},{"family":"Delele","given":"Mulugeta"},{"family":"Foerst","given":"Petra"},{"family":"Gruber","given":"Sebastian"},{"family":"Kaveh","given":"Mohammad"},{"family":"Khoshnam","given":"Farhad"},{"family":"Hashim","given":"Norhashila"},{"family":"Ali","given":"Maimunah"},{"family":"Zohrabi","given":"Saman"},{"family":"Tayyab","given":"Muhammad"},{"family":"Parmar","given":"Aditya"},{"family":"Aradwad","given":"Pramod"},{"family":"Ndisya","given":"John"},{"family":"Amjad","given":"Waseem"},{"family":"Babor","given":"Majharulislam"},{"family":"Mahn","given":"Annika"},{"family":"Sturm","given":"Barbara"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jfoodeng.2025.112770","URL":"https://doi.org/10.1016/j.jfoodeng.2025.112770","source":"openalex"},{"id":"oa:W4417002978","type":"article-journal","title":"Integrated Digital Twin Systems in Mining Operations: A Holistic Review of the Current State, Challenges, and Future Prospects","abstract":"This review provides a systematic synthesis of the current state, challenges, and future prospects of integrated digital twin systems in the mining industry. Utilizing a comprehensive search of major electronic databases, we analysed peerreviewed literature published from January 2009 to August 2025. The study highlights that while digital twins are increasingly adopted for siloed applications—such as optimizing individual machines or specific processes—their full potential as holistic, integrated, mine-wide systems remain untapped. Key challenges identified include the high cost of implementation, complex data integration, and a lack of skilled personnel and robust cybersecurity protocols. Looking ahead, the paper suggests that future development will involve merging digital twins with artificial intelligence and machine learning to enable advanced applications like predictive maintenance and real-time optimization of the entire mining value chain, ultimately leading to smarter, safer, and more sustainable operations.","author":[{"family":"Madahana","given":"Milka"},{"family":"Marakalala","given":"Mmatlou"},{"family":"Ekoru","given":"John"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/uemcon67449.2025.11267726","URL":"https://doi.org/10.1109/uemcon67449.2025.11267726","source":"openalex"},{"id":"oa:W4414009665","type":"article-journal","title":"Digital Twin Framework for Smart City Development: Systematic Review","abstract":"Cities represent complex ecosystems that grow at a rapid pace each day. Urban management and city services face multiple issues and functional problems. Integrating technology and smart infrastructure has become the chosen solution for modern challenges. The Smart City (SC) concept is a transformative approach being adopted by many cities around the world. This concept relies on the use of smart technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and high-performance computing for urban management and future project implementation. The goal is to enhance efficiency, improve quality of life, and ensure better harmony between technological progress and environmental sustainability. Moving towards a virtual living city model, the use of Digital Twin (DT) technology for urban growth management and city development is gaining attention among researchers and stakeholders. In this paper, the importance of DT technology for SC management is highlighted through a systematic review methodology. Then, differences between Urban Digital Twin (UDT) and Digital Twin City (DTC) approaches are debated, to synthetize shared properties and outline current limitations and challenges of implementing this technology in real-world settings. Finally, the paper concludes by offering some future research directions and potential paths for further work.","author":[{"family":"Miraoui","given":"Zayneb"},{"family":"Nasser","given":"Abdelkader"},{"family":"Kodad","given":"Mohcine"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/iccsc66714.2025.11135106","URL":"https://doi.org/10.1109/iccsc66714.2025.11135106","source":"openalex"},{"id":"oa:W4417114008","type":"article-journal","title":"Digital twin technology in smart cities: A step toward intelligent urban management","abstract":"Digital twins are emerging as a core enabler of smart cities, where growing populations and increasingly complex infrastructures demand responsive, efficient, and sustainable services. This review examines the principles, design choices, and enabling technologies of urban digital twins, and surveys applications across energy, transportation, public safety, and environmental management. Beyond synthesizing prior work, the paper adopts an implementation-oriented view: it organizes twin capabilities into a practical pipeline ingest, synchronize, simulate, predict, decide, actuate and it linked to measurable targets such as latency, synchronicity error, update rate, availability, recovery time, and cost. A capability use case matrix and a Digital-Twin Implementation Readiness Level (DT-IRL) scale are introduced to align technical requirements with real city needs and to stage deployments from concept to closed-loop operation. The review clarifies the role of IoT, AI, big-data analytics, and edge–cloud architectures in achieving real-time performance, and it specifies engineering expectations for immersive services (for example, latency and throughput budgets for holographic communication and 3D streaming). It also details deployable security and privacy measures, including zero-trust controls, confidential computing, federated learning with differential privacy, and ledger backed provenance. Remaining challenges interoperability, standards, cybersecurity, scalability, and organizational readiness are translated into actionable research directions and a roadmap for validation through city-scale pilots, open datasets, and conformance testing.","author":[{"family":"Yessef","given":"Mourad"},{"family":"Hakam","given":"Youness"},{"family":"Tabaa","given":"Mohamed"},{"family":"Alammar","given":"Mohammed"},{"family":"Elbarbary","given":"ZMS"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.egyr.2025.11.097","URL":"https://doi.org/10.1016/j.egyr.2025.11.097","source":"openalex"},{"id":"oa:W4414026637","type":"article-journal","title":"Digital twin for sustainable decision-making in building net zero carbon retrofitting: a systematic review","abstract":"Purpose Digital twin (DT) is an innovative concept within the construction sector that utilizes real-world performance data to create a virtual model, enabling optimized decision-making. Building net zero carbon (NZC) retrofitting offers an opportunity to reduce global carbon emissions. However, decision-makers face challenges in making smart and sustainable decisions in NZC retrofitting. DT can improve the smartness and sustainability of the decision-making practice in NZC retrofitting, providing promising solutions. Hence, this study assesses the potential of DT for smart and sustainable decision-making in NZC retrofitting. Design/methodology/approach This study used a three-stage methodology, which included initial work, systematic review and analysis and discussion. Accordingly, the study investigated 29 relevant academic publications on DT and building retrofitting to NZC, using content analysis as the major analytical approach. Findings The findings demonstrated the effective application of DT in assessing carbon emissions, energy usage, comfort levels and financial savings within the context of building NZC retrofitting. However, it highlighted a lack of integrated focus on the environmental, social and economic pillars of sustainability in NZC retrofitting. Furthermore, the review identified the technologies utilized in implementing DT for building NZC retrofitting as data-related, modeling-related and model simulation-related technologies. Centered on the identified gaps, the study provides recommendations for building NZC retrofitting. Originality/value The identified gaps and proposed directions would guide future researchers interested in implementing DT to make sustainable decisions in building NZC retrofitting.","author":[{"family":"Weerasinghe","given":"Lichini"},{"family":"Darko","given":"Amos"},{"family":"Chan","given":"Albert"},{"family":"Xiao","given":"Bo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1108/bepam-03-2025-0090","URL":"https://doi.org/10.1108/bepam-03-2025-0090","source":"openalex"},{"id":"oa:W4408224055","type":"article-journal","title":"Digital twin technology in electric and self-navigating vehicles: Readiness, convergence, and future directions","abstract":"Digital Twin (DT) technology, which creates digital replicas of physical systems, significantly enhances the lifecycle of complex items, systems, and processes. It is especially important in the automotive industry for improving the design, construction, and operation of Electric Vehicles (EVs). Digital Twins make EVs safer, more comfortable, and more enjoyable to drive, thereby enhancing user experience. As mobility systems evolve to become more intelligent and eco-friendlier, electric and self-navigating vehicles are increasingly replacing internal combustion engine vehicles by leveraging technologies such as IoT, Big Data, AI, ML, and 5G. Significant contribution of transportation to global CO2 emissions underscores the need for sustainable practices. Smart EVs, capable of significantly reducing emissions, require innovative architectures like DTs for optimal performance. The advancement of data analytics and IoT has accelerated the adoption of DTs to increase the efficiency of system design, construction, and operation. EV batteries, being the most expensive components, necessitate thorough analysis for State of Charge (SoC) and State of Health (SoH). This review examines the application of DT technology in Intelligent Transportation Systems (ITS), addressing challenges with particular attention on issues regarding monitoring, tracking, battery and charge administration, communication, assurance, and safety. It also explores current trends in EV energy storage technologies and the crucial role of Digital Twins in optimizing battery systems. This technology enables comprehensive digital lifecycle analysis, enhancing battery management efficiency through optimal models for SoC and SoH assessments. Additionally, this review provides insights into various models, future challenges, and discusses DTs for EV battery systems, highlighting case studies, characteristics, and technological opportunities. • Digital Twin (DT) Technology: Creates digital replicas of physical systems to improve lifecycle management. • Importance in Automotive Industry: Enhances EV design, safety, comfort, and user experience. • Smart, Ecofriendly Mobility Systems: EVs and autonomous vehicles are replacing internal combustion engine vehicles, using IoT, Big Data, AI, ML, and 5G. • Environmental Impact: Transportation’s significant CO2 emissions make sustainable practice s essential. • Role of DTs in Smart EVs: Optimize performance and efficiency through data analytics and IoT. • EV Battery Analysis: DTs aid in State of Charge (SoC) and State of Health (SoH) analysis. • Challenges in ITS: Address monitoring, battery management, communication, and safety in Intelligent Transportation Systems. • Trends and Opportunities: Current trends in EV energy storage and DTs’ role in battery optimization, highlighting models, challenges, and opportunities.","author":[{"family":"Yalavarthy","given":"Uma"},{"family":"Kumar","given":"NB"},{"family":"Babu","given":"A"},{"family":"Narasipuram","given":"Rajanand"},{"family":"Padmanaban","given":"Sanjeevikumar"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.ecmx.2025.100949","URL":"https://doi.org/10.1016/j.ecmx.2025.100949","source":"openalex"},{"id":"oa:W4415657812","type":"article-journal","title":"Advancements in Digital Twin Applications for Intelligent Construction Quality Management","abstract":"The construction industry is shifting toward a human-centered approach for quality management, with digital twins (DT) facilitating this transition. However, DT applications in construction quality management are still in their early stages, and systematic reviews on this topic are lacking. This paper provides a comprehensive review of the existing research on DT-based quality management, analyzing the frameworks, methodologies, and applications. The study proposes an overarching framework comprising four layers: data acquisition layer; DT layer; data inference layer; and feedback layer, which collectively address quality issues across the construction lifecycle. Further, the paper categorizes four primary methods for DT-based quality inference: machine vision; numerical simulation; rule-based approaches; and predictive parameter derivations. Key challenges, including real-time feedback integration, cost efficiency, and scalability, are identified, along with potential research directions to address these issues. This review aims to provide a foundation for advancing DT applications in construction quality management and fostering future innovation in the field. By establishing a structured framework and synthesizing key DT-enabled methods across construction phases, this study offers theoretical insights for academic research and practical guidance for industry stakeholders seeking to enhance inspection accuracy, reduce rework, and enable proactive, real-time quality control.","author":[{"family":"Yue","given":"Hongzhe"},{"family":"Wang","given":"Qian"},{"family":"Zhao","given":"Minru"},{"family":"Yang","given":"Zhouzhou"},{"family":"Liang","given":"Lü"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1061/jcemd4.coeng-17126","URL":"https://doi.org/10.1061/jcemd4.coeng-17126","source":"openalex"},{"id":"doi:10.20944/preprints202501.0774.v1","type":"manuscript","title":"How Can Digital Technologies Enable Circular Economy in the Construction Industry? A Review of Lifecycle Applications, Integrations, Potential, and Limitations","abstract":"The circular economy (CE) implementation in the built environment is hindered by the complexity of CE strategies and unique nature of construction industry. Digital technologies (DTs) have been explored as promising solutions to aid decision-making and enable CE in the architecture, engineering, and construction (AEC) sector. Despite the rapid growing literature on both CE and DTs, very few studies have reviewed practical applications of DTs in the AEC sector and their intersection with CE. There is a need for a comprehensive review of the state-of-the-art applications, integrations, potential, and limitations of DT in the CE context. Through a systematic literature review, this study identified ten key DTs to enable circularity in the building sector: Building information modeling (BIM), spatial data acquisition (SDA), Artificial intelligence and machine learning (AI/ML), Internet of things (IoT), blockchain, digital twin, augmented and virtual realities (AR/VR), digital platform/marketplace, material passports (MPs), and additive manufacturing and digital fabrication (AM/DF). We provided a comprehensive review of current applications for each DT, discussed their integrations, and mapped the DT applications along a building’s life cycle. Additionally, we identified the potential of DTs in overcoming the most reoccurring barriers to CE in the built environment: design, policies and standards, assessment methods, digitalization, and business models. Finally, we discussed the main DT limitations and future research needs.","author":[{"family":"Keles","given":"Cagla"},{"family":"Rios","given":"Fernanda"},{"family":"Hoque","given":"Simi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202501.0774.v1","URL":"https://doi.org/10.20944/preprints202501.0774.v1","source":"preprints"},{"id":"oa:W4416677406","type":"article-journal","title":"A Method for Model-Driven Engineering of Digital Twins in Manufacturing","abstract":"Several software architectures for digital twins have been proposed, specifying their structure and key components, such as the ISO 23247 standard for manufacturing. However, systematic methodologies for developing digital twins in the manufacturing domain remain lacking. Existing research does not adequately address methodological aspects, such as composing essential digital twin components, defining their interfaces, and systematically analyzing relevant data. This gap presents a challenge for the structured development of digital twins. In this work, we introduce a systematic approach to identify key requirements for manufacturing digital twins and propose a model-driven method for their creation. Our approach enables the generation of executable digital twins based on a formalized specification. We demonstrate its applicability through multiple industrial manufacturing demonstrators, highlighting its suitability in practice. The proposed method is adaptable regarding the purpose of the digital twins to be developed and supports a largely automated process.","author":[{"family":"Heithoff","given":"Malte"},{"family":"Michael","given":"Judith"},{"family":"Rumpe","given":"Bernhard"},{"family":"Pfeiffer","given":"Jérôme"},{"family":"Wortmann","given":"Andreas"},{"family":"Zhang","given":"Jingxi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/models67397.2025.00019","URL":"https://doi.org/10.1109/models67397.2025.00019","source":"openalex"},{"id":"oa:W4406699637","type":"article-journal","title":"Virtual reality integration and credible traceability management method of transformer coil manufacturing process based on industrial internet and digital twin","abstract":"The traceability and management of the transformer coil manufacturing process lack credibility and transparency, which limits its efficiency and convenience. To address this issue, this paper proposes a novel approach for trusted traceability and management of coils in the manufacturing process. This method leverages the virtual-real fusion through the integration of industrial internet identification and resolution, blockchain technology, and digital twins. To ensure trusted storage and precise traceability of information in the coil manufacturing process, the structure of a reliable identification block for all the elements of the coil manufacturing information is studied. A trusted interaction mechanism based on distributed Oracle is also proposed for uploading data to the blockchain. An efficient traceability process for coil manufacturing information is then designed. To ensure the transparency and timeliness in the traceability of the coil manufacturing process, a digital twin modeling method based on industrial internet NFTs is studied, and a virtual-real fusion traceability process based on digital twins is expanded. A coil production workshop is considered as an example to conduct experiments and verifications. The virtual-real fusion trusted traceability of the coil manufacturing process is finally performed based on the identification of all the resources in the workshop and the integration of full-process information.","author":[{"family":"Zhang","given":"Xuedong"},{"family":"Wenlei","given":"Sun"},{"family":"Lixin","given":"Wang"},{"family":"Hua","given":"Yifei"},{"family":"Chen","given":"Ke"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/0951192x.2025.2452615","URL":"https://doi.org/10.1080/0951192x.2025.2452615","source":"openalex"},{"id":"oa:W4408767222","type":"article-journal","title":"Review of Digital Twin in the Automotive Industry on Products, Processes and Systems","abstract":"Review Review of Digital Twin in the Automotive Industry on Products, Processes and Systems Heli Liu 1,2, Benjamin Zhang 1, Vincent Wu 1,2, Xiao Yang 1,2, and Liliang Wang 1,2,* 1 Department of Mechanical Engineering, Imperial College London, London SW7 2AZ, UK 2 Smart Forming Research Base, Imperial College London, London SW7 2AZ, UK * Correspondence: liliang.wang@imperial.ac.uk Received: 17 February 2025; Revised: 10 March 2025; Accepted: 20 March 2025; Published: 24 March 2025 Abstract: In the era of digital manufacturing, digital technologies are rapidly revolutionising the automotive industry. Among these, the digital twin, an enabling industry 4.0 digital technology first introduced two decades ago, is characterised by the seamless integration of physical and cyber realms. The digital twin is undergoing extensive investigations within the automotive sector, covering various perspectives including design, manufacturing, and application. By leveraging the big manufacturing data captured by spatially distributed sensing networks, the digital twin shows the capacity to create high-fidelity models of actual manufacturing practices, thereby significantly improving the precision and efficiency of production processes. Integrated with other digital technologies such as big data analytics (BDA) and the Internet of Things (IoT), the digital twin mirrors components in the physical world into the virtual environment and facilitates the exchange of real-time information to achieve fully converged cyber-physical spaces. This in turn minimises costs and improves the overall product quality, flexibility of manufacturing processes, and system integration. This work reviewed recent advancements in digital twin applications in the automotive industry focusing on automotive products, manufacturing processes, and manufacturing systems. Insights were provided into the future of digitally enhanced technologies in automotive manufacturing towards digital manufacturing and developing digital product passports (DPPs) for circular economy (CE).","author":[{"family":"Liu","given":"Heli"},{"family":"Zhang","given":"Binyuan"},{"family":"Wu","given":"Vincent"},{"family":"Yang","given":"Xiao"},{"family":"Wang","given":"Liliang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.53941/ijamm.2025.100006","URL":"https://doi.org/10.53941/ijamm.2025.100006","source":"openalex"},{"id":"oa:W4416233937","type":"article-journal","title":"SDN-Integrated Cloud-Edge Digital Twin Framework for Real-Time Monitoring in Additive Manufacturing","abstract":"Emerging paradigms such as cloud-edge continuum, Software-Defined Networking (SDN), and Digital Twin (DT) technologies are transforming smart manufacturing systems by enabling intelligent automation, real-time monitoring, and scalable orchestration. These capabilities are particularly critical in additive manufacturing (AM), where latency-sensitive control and predictive maintenance are essential. However, current architectures often require dynamic network programmability, synchronized twin management, and secure telemetry pipelines. This paper presents an SDN-Integrated Cloud-Edge DT Framework tailored for real-time AM monitoring. The framework integrates KubeEdge’s DeviceTwin module for edge-local twin representation, a telemetry agent for structured data streaming, and SDN-controlled Open vSwitch (OVS) for adaptive traffic control. IoT-enabled AM devices, including 3D printers, CNC machines, and robotic arms, interface with the edge node for local state caching, while KubeEdge’s CloudCore aggregates device states for analytics, visualization, and policy enforcement. Experimental validation on a Kubernetes cluster demonstrates sub-100-ms twin synchronization, SDN enforcement under 312 ms, and streaming latency breakdowns across MQTT-Kafka stages. This work establishes a scalable, resilient, and programmable foundation for next-generation, Industry 5.0 manufacturing ecosystems.","author":[{"family":"Tsegaye","given":"Henok"},{"family":"Tshakwanda","given":"Petro"},{"family":"Karukutla","given":"Ashok"},{"family":"Almaayn","given":"Raddad"},{"family":"Worku","given":"Yonatan"},{"family":"Kumar","given":"Harsh"},{"family":"Devetsikiotis","given":"Michael"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/camad67323.2025.11229916","URL":"https://doi.org/10.1109/camad67323.2025.11229916","source":"openalex"},{"id":"oa:W4407226327","type":"article-journal","title":"Integrating Social Dimensions into Urban Digital Twins: A Review and Proposed Framework for Social Digital Twins","abstract":"The rapid evolution of smart city technologies has expanded digital twin (DT) applications from industrial to urban contexts. However, current urban digital twins (UDTs) remain predominantly focused on the physical aspects of urban environments (“spaces”), often overlooking the interwoven social dimensions that shape the concept of “place”. This limitation restricts their ability to fully represent the complex interplay between physical and social systems in urban settings. To address this gap, this paper introduces the concept of the social digital twin (SDT), which integrates social dimensions into UDTs to bridge the divide between technological systems and the lived urban experience. Drawing on an extensive literature review, the study defines key components for transitioning from UDTs to SDTs, including conceptualization and modeling of human interactions (geo-individuals and geo-socials), social applications, participatory governance, and community engagement. Additionally, it identifies essential technologies and analytical tools for implementing SDTs, outlines research gaps and practical challenges, and proposes a framework for integrating social dynamics within UDTs. This framework emphasizes the importance of active community participation through a governance model and offers a comprehensive methodology to support researchers, technology developers, and policymakers in advancing SDT research and practical applications.","author":[{"family":"Qanazi","given":"Saleh"},{"family":"Leclerc","given":"Éric"},{"family":"Bosredon","given":"Pauline"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/smartcities8010023","URL":"https://doi.org/10.3390/smartcities8010023","source":"openalex"},{"id":"doi:10.1109/icosec67334.2025.11459737","type":"article-journal","title":"Hybrid Deep Learning Model for Fault Diagnosis in Smart Manufacturing using Edge AI and Digital Twin Integration","abstract":"The rapid advancement of Industry 4.0 has accelerated the need for intelligent and autonomous fault diagnosis in smart manufacturing systems. This paper presents a hybrid deep learning approach that combines Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to effectively capture both spatial and temporal features from industrial sensor data. To support real-time fault detection and diagnosis, the model is deployed via Edge AI, thereby reducing latency, conserving bandwidth, and improving operational responsiveness. In addition, a Digital Twin of the manufacturing process is developed, offering a synchronized virtual representation of the physical system. This enables continuous monitoring, simulation, and predictive analytics, improving contextual awareness and fault explainability. Experimental evaluation on publicly available benchmark datasets demonstrates that the proposed model outperforms traditional approaches in terms of accuracy, noise robustness, and response time. The integration of deep learning, edge computing, and digital twin technologies provides a scalable and intelligent framework for predictive maintenance and real-time monitoring in next-generation smart factories.","author":[{"family":"Venkateswarlu","given":"Lendale"},{"family":"Mohan","given":"Ch"},{"family":"Reddy","given":"PK"},{"family":"Bande","given":"Vasavi"},{"family":"Archana","given":"M"},{"family":"Manellore","given":"Pavan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/icosec67334.2025.11459737","URL":"https://doi.org/10.1109/icosec67334.2025.11459737","source":"openalex"},{"id":"doi:10.1016/j.drudis.2026.104617","type":"article-journal","title":"Digital twins for accelerating drug discovery and development: opportunities and challenges.","abstract":"Digital twins can revolutionize drug development and personalized care by accelerating timelines, reducing costs and failure rates, and potentially improving the safety and efficacy of new therapies. In this review, we explore different applications of digital twins across the pharmaceutical value chain, from target discovery and preclinical research to clinical trials, regulatory review, manufacturing and post-market clinical practice. Key challenges, however, remain in data integration, model reliability, regulatory acceptance and data privacy. Overcoming these barriers will require innovation, transparency and collaborative efforts across the healthcare ecosystem to fully realize digital twin potential for patients, healthcare providers and the pharmaceutical industry.","author":[{"family":"Venkatapurapu","given":"Sai"},{"family":"Clegg","given":"Lindsay"},{"family":"Nowojewski","given":"Andrzej"},{"family":"Kimko","given":"Holly"},{"family":"Olabode","given":"Damilola"},{"family":"Sawant-Basak","given":"Aarti"},{"family":"Vishwanathan","given":"Karthick"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.drudis.2026.104617","URL":"https://doi.org/10.1016/j.drudis.2026.104617","source":"europepmc"},{"id":"doi:10.1002/btpr.70058","type":"article-journal","title":"Use of live digital twin (shadow) soft sensor to monitor membrane degradation in continuous manufacturing single pass tangential flow filtration.","abstract":"Digital twins (DT) are sophisticated mathematical models representing real-world physical processes, equipped with predictive capabilities that adapt alongside the physical system. The successful implementation of DT in bioprocessing offers numerous advantages, including enhanced understanding of processes, accelerated overall development timelines, and effective monitoring of critical process parameters (CPPs). A comprehensive end-to-end DT can facilitate informed control decisions and forecast how disturbances within the process may affect the final output, accelerating the overall development timelines while optimizing process efficiency and productivity. Tangential flow filtration (TFF) is a standard methodology in bioprocessing, commonly employed to concentrate and exchange buffers for bioproducts. The advancement of continuous process technologies has led to the emergence of alternative TFF methods, notably single-pass tangential flow filtration (SPTFF), which streamlines the process by eliminating the need for stream recirculation. Here, we present the development of a live DT of the SPTFF concentration step within the downstream continuous manufacturing line for a monoclonal antibody (mAb) process. A live DT, equipped with a state estimation tool, was implemented via the Siemens' gPROMS Digital Applications (gDAP) platform. The DT demonstrated the ability to monitor changes in membrane resistance, a typical process parameter that is not directly measured. This parameter is crucial for SPTFF control, as it allows for the constant setting of the concentration factor (CF) by adjusting the retentate flow rate based on the measured resistance and calculated transmembrane pressure (TMP). This achievement illustrates the potential of DT as effective tools for accurately tracking the complete state of the bioprocess.","author":[{"family":"Taylor","given":"Robert"},{"family":"Mandur","given":"Jasdeep"},{"family":"Amira","given":"Umme"},{"family":"Alinati","given":"Natalie"},{"family":"Marincelis","given":"Juan"},{"family":"Hatch","given":"Sean"},{"family":"Fernandezcerezo","given":"Lara"},{"family":"Pinto","given":"Nuno"},{"family":"Metsiguckel","given":"Efimia"},{"family":"Matos","given":"Tiago"},{"family":"Brower","given":"Mark"},{"family":"Mehta","given":"Krunal"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/btpr.70058","URL":"https://doi.org/10.1002/btpr.70058","source":"europepmc"},{"id":"doi:10.48550/arxiv.2504.18165","type":"manuscript","title":"PerfCam: Digital Twinning for Production Lines Using 3D Gaussian Splatting and Vision Models","abstract":"We introduce PerfCam, an open source Proof-of-Concept (PoC) digital twinning framework that combines camera and sensory data with 3D Gaussian Splatting and computer vision models for digital twinning, object tracking, and Key Performance Indicators (KPIs) extraction in industrial production lines. By utilizing 3D reconstruction and Convolutional Neural Networks (CNNs), PerfCam offers a semi-automated approach to object tracking and spatial mapping, enabling digital twins that capture real-time KPIs such as availability, performance, Overall Equipment Effectiveness (OEE), and rate of conveyor belts in the production line. We validate the effectiveness of PerfCam through a practical deployment within realistic test production lines in the pharmaceutical industry and contribute an openly published dataset to support further research and development in the field. The results demonstrate PerfCam's ability to deliver actionable insights through its precise digital twin capabilities, underscoring its value as an effective tool for developing usable digital twins in smart manufacturing environments and extracting operational analytics.","author":[{"family":"Khan","given":"Michel"},{"family":"Guarese","given":"Renan"},{"family":"Johnson","given":"Fabian"},{"family":"Wang","given":"Xi"},{"family":"Bergman","given":"Anders"},{"family":"Edvinsson","given":"Benjamin"},{"family":"Romero","given":"Mario"},{"family":"Vachier","given":"Jérémy"},{"family":"Kronqvist","given":"Jan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2504.18165","URL":"https://doi.org/10.48550/arxiv.2504.18165","source":"datacite"},{"id":"doi:10.48550/arxiv.2505.10902","type":"manuscript","title":"Patient-Specific Dynamic Digital-Physical Twin for Coronary Intervention Training: An Integrated Mixed Reality Approach","abstract":"Background and Objective: Precise preoperative planning and effective physician training for coronary interventions are increasingly important. Despite advances in medical imaging technologies, transforming static or limited dynamic imaging data into comprehensive dynamic cardiac models remains challenging. Existing training systems lack accurate simulation of cardiac physiological dynamics. This study develops a comprehensive dynamic cardiac model research framework based on 4D-CTA, integrating digital twin technology, computer vision, and physical model manufacturing to provide precise, personalized tools for interventional cardiology. Methods: Using 4D-CTA data from a 60-year-old female with three-vessel coronary stenosis, we segmented cardiac chambers and coronary arteries, constructed dynamic models, and implemented skeletal skinning weight computation to simulate vessel deformation across 20 cardiac phases. Transparent vascular physical models were manufactured using medical-grade silicone. We developed cardiac output analysis and virtual angiography systems, implemented guidewire 3D reconstruction using binocular stereo vision, and evaluated the system through angiography validation and CABG training applications. Results: Morphological consistency between virtual and real angiography reached 80.9%. Dice similarity coefficients for guidewire motion ranged from 0.741-0.812, with mean trajectory errors below 1.1 mm. The transparent model demonstrated advantages in CABG training, allowing direct visualization while simulating beating heart challenges. Conclusion: Our patient-specific digital-physical twin approach effectively reproduces both anatomical structures and dynamic characteristics of coronary vasculature, offering a dynamic environment with visual and tactile feedback valuable for education and clinical planning.","author":[{"family":"Wang","given":"Shuo"},{"family":"Ren","given":"Tong"},{"family":"Cheng","given":"Nan"},{"family":"Wang","given":"Rong"},{"family":"Zhang","given":"Li"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2505.10902","URL":"https://doi.org/10.48550/arxiv.2505.10902","source":"datacite"},{"id":"doi:10.48550/arxiv.2505.04323","type":"manuscript","title":"A Case Study on the Application of Digital Twins for Enhancing CPS Operations","abstract":"To ensure the availability and reduce the downtime of complex cyber-physical systems across different domains, e.g., agriculture and manufacturing, fault tolerance mechanisms are implemented which are complex in both their development and operation. In addition, cyber-physical systems are often confronted with limited hardware resources or are legacy systems, both often hindering the addition of new functionalities directly on the onboard hardware. Digital Twins can be adopted to offload expensive computations, as well as providing support through fault tolerance mechanisms, thus decreasing costs and operational downtime of cyber-physical systems. In this paper, we show the feasibility of a Digital Twin used for enhancing cyber-physical system operations, specifically through functional augmentation and increased fault tolerance, in an industry-oriented use case.","author":[{"family":"Muntean","given":"Irina"},{"family":"Frasheri","given":"Mirgita"},{"family":"Munaro","given":"Tiziano"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2505.04323","URL":"https://doi.org/10.48550/arxiv.2505.04323","source":"datacite"},{"id":"doi:10.48550/arxiv.2501.07601","type":"manuscript","title":"Real-Time Decision-Making for Digital Twin in Additive Manufacturing with Model Predictive Control using Time-Series Deep Neural Networks","abstract":"Digital Twin -- a virtual replica of a physical system enabling real-time monitoring, model updating, prediction, and decision-making -- combined with recent advances in machine learning, offers new opportunities for proactive control strategies in autonomous manufacturing. However, achieving real-time decision-making with Digital Twins requires efficient optimization driven by accurate predictions of highly nonlinear manufacturing systems. This paper presents a simultaneous multi-step Model Predictive Control (MPC) framework for real-time decision-making, using a multivariate deep neural network, named Time-Series Dense Encoder (TiDE), as the surrogate model. Unlike conventional MPC models which only provide one-step ahead prediction, TiDE is capable of predicting future states within the prediction horizon in one shot (multi-step), significantly accelerating the MPC. Using Directed Energy Deposition (DED) additive manufacturing as a case study, we demonstrate the effectiveness of the proposed MPC in achieving melt pool temperature tracking to ensure part quality, while reducing porosity defects by regulating laser power to maintain melt pool depth constraints. In this work, we first show that TiDE is capable of accurately predicting melt pool temperature and depth. Second, we demonstrate that the proposed MPC achieves precise temperature tracking while satisfying melt pool depth constraints within a targeted dilution range (10\\%-30\\%), reducing potential porosity defects. Compared to PID controller, the MPC results in smoother and less fluctuating laser power profiles with competitive or superior melt pool temperature control performance. This demonstrates the MPC's proactive control capabilities, leveraging time-series prediction and real-time optimization, positioning it as a powerful tool for future Digital Twin applications and real-time process optimization in manufacturing.","author":[{"family":"Chen","given":"Yi"},{"family":"Karkaria","given":"Vispi"},{"family":"Tsai","given":"Ying"},{"family":"Rolark","given":"Faith"},{"family":"Quispe","given":"Daniel"},{"family":"Gao","given":"Robert"},{"family":"Cao","given":"Jian"},{"family":"Chen","given":"Wei"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2501.07601","URL":"https://doi.org/10.48550/arxiv.2501.07601","source":"datacite"},{"id":"doi:10.48550/arxiv.2504.00286","type":"manuscript","title":"Digital Twins in Biopharmaceutical Manufacturing: Review and Perspective on Human-Machine Collaborative Intelligence","abstract":"The biopharmaceutical industry is increasingly developing digital twins to digitalize and automate the manufacturing process in response to the growing market demands. However, this shift presents significant challenges for human operators, as the complexity and volume of information can overwhelm their ability to manage the process effectively. These issues are compounded when digital twins are designed without considering interaction and collaboration with operators, who are responsible for monitoring processes and assessing situations, particularly during abnormalities. Our review of current trends in biopharma digital twin development reveals a predominant focus on technology and often overlooks the critical role of human operators. To bridge this gap, this article proposes a collaborative intelligence framework that emphasizes the integration of operators with digital twins. Approaches to system design that can enhance operator trust and human-machine interface usability are presented. Moreover, innovative training programs for preparing operators to understand and utilize digital twins are discussed. The framework outlined in this article aims to enhance collaboration between operators and digital twins effectively by using their full capabilities to boost resilience and productivity in biopharmaceutical manufacturing.","author":[{"family":"Shahab","given":"Mohammed"},{"family":"Destro","given":"Francesco"},{"family":"Braatz","given":"Richard"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2504.00286","URL":"https://doi.org/10.48550/arxiv.2504.00286","source":"datacite"},{"id":"doi:10.48550/arxiv.2503.02167","type":"manuscript","title":"Leveraging Large Language Models for Enhanced Digital Twin Modeling: Trends, Methods, and Challenges","abstract":"Digital twin technology is a transformative innovation driving the digital transformation and intelligent optimization of manufacturing systems. By integrating real-time data with computational models, digital twins enable continuous monitoring, simulation, prediction, and optimization, effectively bridging the gap between the physical and digital worlds. Recent advancements in communication, computing, and control technologies have accelerated the development and adoption of digital twins across various industries. However, significant challenges remain, including limited data for accurate system modeling, inefficiencies in system analysis, and a lack of explainability in the interactions between physical and digital systems. The rise of large language models (LLMs) offers new avenues to address these challenges. LLMs have shown exceptional capabilities across diverse domains, exhibiting strong generalization and emergent abilities that hold great potential for enhancing digital twins. This paper provides a comprehensive review of recent developments in LLMs and their applications to digital twin modeling. We propose a unified description-prediction-prescription framework to integrate digital twin modeling technologies and introduce a structured taxonomy to categorize LLM functionalities in these contexts. For each stage of application, we summarize the methodologies, identify key challenges, and explore potential future directions. To demonstrate the effectiveness of LLM-enhanced digital twins, we present an LLM-enhanced enterprise digital twin system, which enables automatic modeling and optimization of an enterprise. Finally, we discuss future opportunities and challenges in advancing LLM-enhanced digital twins, offering valuable insights for researchers and practitioners in related fields.","author":[{"family":"Yang","given":"Linyao"},{"family":"Luo","given":"Shi"},{"family":"Cheng","given":"Xi"},{"family":"Yu","given":"Lei"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2503.02167","URL":"https://doi.org/10.48550/arxiv.2503.02167","source":"datacite"},{"id":"doi:10.6084/m9.figshare.28405953.v1","type":"article-journal","title":"Synergistic effects of robot performance on human–robot mutual assistance systems in manufacturing","abstract":"In countries experiencing a growing shortage of human resources, collaboration with robots is indispensable for leveraging a diverse workforce and maintaining productivity. This study proposes a manufacturing system that simultaneously enhances overall productivity and reduces human workload through mutual assistance between humans and robots. By considering the characteristics of both humans and robots, task allocation was performed to balance the trade-off between productivity and workload. Furthermore, this study introduces a method for improving robot performance to maximize the benefit of mutual assistance. The proposed approach utilizes a digital twin, including humans, for a real-time evaluation of the human workload. Moreover, a novel grasp strategy for a magnetic gripper was proposed to improve the robot's picking success rate, thereby enhancing the effectiveness of the mutual assistance. Through a practical example of supply tasks in a real factory setting, we showcased the mutual assistance between a human worker and a mobile manipulator, confirming the potential of the proposed system. Our analysis of the human workload indicated that improvements in robot performance significantly increased the effectiveness of mutual assistance. The results demonstrated that productivity can be enhanced by up to 19% while simultaneously reducing the human workload by up to 15%.","author":[{"family":"Shirakura","given":"Naoki"},{"family":"Maruyama","given":"Tsubasa"},{"family":"Makihara","given":"Koshi"},{"family":"Ueshiba","given":"Toshio"},{"family":"Itadera","given":"Shunki"},{"family":"Endo","given":"Yuki"},{"family":"Tada","given":"Mitsunori"},{"family":"Domae","given":"Yukiyasu"}],"issued":{"date-parts":[[2025]]},"DOI":"10.6084/m9.figshare.28405953.v1","URL":"https://doi.org/10.6084/m9.figshare.28405953.v1","source":"datacite"},{"id":"doi:10.6084/m9.figshare.28405953","type":"article-journal","title":"Synergistic effects of robot performance on human–robot mutual assistance systems in manufacturing","abstract":"In countries experiencing a growing shortage of human resources, collaboration with robots is indispensable for leveraging a diverse workforce and maintaining productivity. This study proposes a manufacturing system that simultaneously enhances overall productivity and reduces human workload through mutual assistance between humans and robots. By considering the characteristics of both humans and robots, task allocation was performed to balance the trade-off between productivity and workload. Furthermore, this study introduces a method for improving robot performance to maximize the benefit of mutual assistance. The proposed approach utilizes a digital twin, including humans, for a real-time evaluation of the human workload. Moreover, a novel grasp strategy for a magnetic gripper was proposed to improve the robot's picking success rate, thereby enhancing the effectiveness of the mutual assistance. Through a practical example of supply tasks in a real factory setting, we showcased the mutual assistance between a human worker and a mobile manipulator, confirming the potential of the proposed system. Our analysis of the human workload indicated that improvements in robot performance significantly increased the effectiveness of mutual assistance. The results demonstrated that productivity can be enhanced by up to 19% while simultaneously reducing the human workload by up to 15%.","author":[{"family":"Shirakura","given":"Naoki"},{"family":"Maruyama","given":"Tsubasa"},{"family":"Makihara","given":"Koshi"},{"family":"Ueshiba","given":"Toshio"},{"family":"Itadera","given":"Shunki"},{"family":"Endo","given":"Yuki"},{"family":"Tada","given":"Mitsunori"},{"family":"Domae","given":"Yukiyasu"}],"issued":{"date-parts":[[2025]]},"DOI":"10.6084/m9.figshare.28405953","URL":"https://doi.org/10.6084/m9.figshare.28405953","source":"datacite"},{"id":"oa:W7153248168","type":"article-journal","title":"The Enduring Promise of Personalising Patient Preference Prediction","abstract":"The challenge of making healthcare decisions for incapacitated patients continues to confront stakeholders worldwide. Annette Rid and David Wendler proposed a Patient Preference Predictor (P3) that uses population-level data to infer an incapacitated patient's likely treatment choices, with the aim of aligning care with the values and preferences they held when last autonomous. Some objectors claimed this would fail to respect patients' (former) autonomy because the basis for prediction would not be specific to the individual (e.g., based on data reflecting their own specific reasons for preferring one course of action over another). In response, we proposed a 'Personalised Patient Preference Predictor' (P4) that would harness the predictive capacities of personalised large language models (LLMs) fine-tuned on individual-level data of various kinds. The envisioned P4, if realized, would be akin to a 'digital psychological twin' or AI simulation of the patient that would encode their unique preferences and values to enable an individualised prediction of their likely treatment preferences. The P4, in turn, has been criticised on various grounds: philosophical, practical, and ethical. Here, we comprehensively evaluate the concerns of our critics based on all known published critiques as of the time of writing. While acknowledging the weight of some of these concerns, we argue that they do not entail that a P4 should not be developed. Rather, the concerns point to areas where thoughtful design choices, responsible regulation, and further philosophical reflection are needed to steer the proposal in a positive direction.","author":[{"family":"Earp","given":"Brian"},{"family":"Mann","given":"SP"},{"family":"Veenendaal","given":"Tessa"},{"family":"Allen","given":"Jemima"},{"family":"Salloch","given":"Sabine"},{"family":"Jongsma","given":"Karin"},{"family":"Braun","given":"Matthias"},{"family":"Sinnott-Armstrong","given":"Walter"},{"family":"Savulescu","given":"Julian"},{"family":"Wendler","given":"David"},{"family":"Rid","given":"Annette"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s12152-026-09635-7","URL":"https://doi.org/10.1007/s12152-026-09635-7","source":"openalex"},{"id":"oa:W4411090315","type":"article-journal","title":"Expected Challenges and Anticipated Benefits of Implementing Remote Train Control and Automatic Train Operation: A Tramway Case Study","abstract":"The digital transformation of the railway industry is necessary for addressing growing challenges and advancing its sustainable development. Digital technologies include Automatic Train Operation (ATO) and Remote Train Control (RTC), which offer opportunities to potentially optimize operations and enhance safety. Both technologies, however, could pose significant challenges that need to be addressed in order to capture the anticipated benefits in an urban public street environment. This study thus bridges the gap between theory and practice by exploring the projected benefits and challenges of implementing RTC and ATO through a case study of a European public transport operator deploying these technologies in tramway operations. Employing a case study methodology, the research draws on 44 semi-structured interviews with stakeholders from the operator and its supplier. The findings highlight significant anticipated benefits, including increased productivity, improved safety, and enhanced sustainability. Yet, prospective challenges such as regulatory hurdles, technical complexities, and organizational changes pose barriers to implementation. Key obstacles include ensuring robust connectivity, addressing cybersecurity concerns, and managing workforce transitions. This study underscores the importance of collaborative approaches, stakeholder engagement, and incremental deployment to mitigate risks and maximize the impact of automation technologies. By providing actionable insights into the practical adoption of RTC and ATO, this research supports the development of advanced urban transport systems.","author":[{"family":"Morin","given":"Xavier"},{"family":"Olsson","given":"Nils"},{"family":"Lau","given":"Albert"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/futuretransp5020073","URL":"https://doi.org/10.3390/futuretransp5020073","source":"openalex"},{"id":"oa:W7160505928","type":"article-journal","title":"Sustainable Manufacturing: Enabling Technologies and Emerging Research Trends—A Scoping Review","abstract":"The current industrial production model faces major environmental, economic, and social challenges due to resource depletion, increasing energy demand, and climate change. Manufacturing significantly contributes to emissions, material consumption, and waste, making sustainable manufacturing (SM) essential for transitioning toward more resource-efficient, circular, and socially responsible systems. This study provides a structured overview of SM, focusing on enabling technologies and emerging research trends. Sustainability is analyzed through approaches such as sustainable development, cleaner production, eco-efficiency, and the circular economy. The role of key technologies—including additive manufacturing, artificial intelligence, big data analytics, the Internet of Things, digital twins, and cyber-physical systems—is examined in improving efficiency, reducing waste, and supporting circular production. A scoping review was conducted following the PRISMA-ScR guidelines using the Web of Science database, focusing on recent publications. The results highlight a growing integration of digital technologies, energy-efficient systems, and circular strategies, alongside the increasing importance of data-driven decision-making. A strong convergence between artificial intelligence, energy transition, circular economy approaches, and digital transformation is also identified. Overall, achieving sustainable manufacturing requires an integrated approach addressing environmental, economic, and social dimensions. This review maps the field and identifies key directions for future research and practice.","author":[{"family":"Martınez","given":"Alejandro"},{"family":"Rubio","given":"E"},{"family":"García-Domínguez","given":"Amabel"},{"family":"Claver","given":"Juan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18094602","URL":"https://doi.org/10.3390/su18094602","source":"openalex"},{"id":"oa:W7162261857","type":"article-journal","title":"Smart Digital Twin: Experimental setup and developed dashboards for real-time production monitoring, machine condition tracking, and LLM-assisted prognostics of a smart retrofitted legacy CNC lathe","abstract":"The figure presents the experimentally developed AI-enabled human-centric digital twin system implemented on a smart retrofitted legacy CNC lathe. The figure illustrates both the physical and digital components developed for real-time production monitoring, machine condition tracking, and LLM-assisted prognostics. The physical layer includes the CNC lathe, industrial predictive maintenance sensors, RFID-based operator interaction system, IoT gateway, edge computing infrastructure, and associated sensing architecture for vibration, temperature, and machine activity acquisition. The digital layer demonstrates the developed Grafana dashboards used for live production monitoring, machine condition visualization, tool wear state estimation, and conversational AI-assisted assessment. The figure was developed as part of the research work titled “AI-Enabled Human-Centric Digital Twin Framework for Real-Time Performance Monitoring and Prognostics of Legacy Machines.” The presented implementation demonstrates the integration of IoT, AI, edge-cloud computing, and large language model-assisted analytics for smart retrofitting of legacy manufacturing systems toward Industry 4.0 and Industry 5.0 applications. Author: Deep Patel, Chayan Maiti, and Sreekumar MuthuswamyAffiliation: Indian Institute of Information Technology, Design and Manufacturing (IIITDM) Kancheepuram, India. © Deep Patel, 2026. All rights reserved.","author":[{"family":"Patel","given":"Deep"},{"family":"Maiti","given":"Chayan"},{"family":"Muthuswamy","given":"Sreekumar"}],"issued":{"date-parts":[[2026]]},"DOI":"10.6084/m9.figshare.32393037","URL":"https://doi.org/10.6084/m9.figshare.32393037","source":"openalex"},{"id":"oa:W7143634761","type":"article-journal","title":"A Prediction Model of Interlayer Bond Strength for 3D-Printed Concrete Considering Printing Interval and Environmental Effects","abstract":"Interlayer bond strength is critical for ensuring the safety and durability of 3D-printed concrete (3DPC) structures. However, there remains a lack of real-time prediction methods addressing interlayer performance under the combined effects of interval time and environmental factors during the in situ printing process. To address this issue, this study conducted experiments considering various printing interval times and environmental conditions, incorporating monitoring of dielectric constant and water evaporation, alongside interlayer splitting tensile tests. By integrating the SHAP interpretability algorithm with nonlinear regression analysis, the results indicate that the printing interval time is the dominant factor inducing interlayer strength decay (with a contribution rate of 68.6%), while relative humidity emerges as the primary environmental variable (with a contribution rate of 21.3%). Mechanism analysis reveals that prolonged printing intervals intensify the hydration of the lower deposited layer, leading to reduced interfacial moisture content and loss of plasticity. Furthermore, environmental evaporation significantly regulates this process, with high-humidity environments notably mitigating the moisture loss and strength reduction caused by time delays. Based on the correlation mechanism between moisture and strength, a dimensionless general prediction model for 3DPC interlayer strength was established, incorporating printing interval time and an evaporation index (goodness of fit, R2 = 0.96). Consequently, a digital twin quality inversion scheme based on companion specimen monitoring and printing timestamps was proposed. This study quantifies the intrinsic relationships among printing interval time, environmental conditions, and interlayer strength, offering a novel approach for determining the construction window and achieving non-destructive quality prediction for 3DPC in complex environments.","author":[{"family":"Xu","given":"Wenbin"},{"family":"Xu","given":"Zihao"},{"family":"Xu","given":"Zihao"},{"family":"Liu","given":"Tao"},{"family":"Ouyang","given":"Jun"},{"family":"Wang","given":"Hao"},{"family":"Wang","given":"Hailong"},{"family":"Xu","given":"Wenqiang"},{"family":"Xu","given":"Wenqiang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/ma19071377","URL":"https://doi.org/10.3390/ma19071377","source":"openalex"},{"id":"oa:W7160522180","type":"article-journal","title":"Digital Twin-Driven Intelligent Transformation of Solid Waste Treatment","abstract":"Rapid global urbanization is driving a surge in solid waste generation, while conventional treatment systems face both environmental risks and operational uncertainty. Digital twins, which enable real-time mapping between physical assets and virtual spaces, offer a computable and verifiable route toward low-carbon, resource-efficient, and intelligent waste management when deeply integrated with the Internet of Things, big data, and artificial intelligence. This study develops a comprehensive review tracing the digital twins from static geometric mirroring to dynamic, cognitive co-symbiosis, and summarizes a multidimensional architecture spanning physical, virtual, data, service, and connectivity layers, together with coupling mechanisms involving IoT sensing, federated learning, multimodal big data, and large model agents. The study aims to provide a theoretical framework and methodological references for advancing digital twin-enabled solid waste valorization. Building on this framework, we examine recent progress in three representative application scenarios for solid waste treatment, and identify key technical bottlenecks, including heterogeneous data fusion, model generalization across facilities and contexts, and real-time computation under constrained resources. We highlight the need for standardization, uncertainty quantification, cybersecurity, and lifecycle evaluation to support reliable prediction, optimization, and decision-making in real operations. Finally, we discuss future directions such as edge intelligence and the integration of city-scale material and energy networks.","author":[{"family":"Li","given":"Junnan"},{"family":"Zhang","given":"Jingxin"},{"family":"Yu","given":"Chen"},{"family":"Hou","given":"Shiqi"},{"family":"Li","given":"PH"},{"family":"Yu","given":"Kaifeng"},{"family":"Guo","given":"Xu"},{"family":"Dou","given":"Fei"},{"family":"Zhang","given":"Xinglin"},{"family":"He","given":"Yiliang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/cleantechnol8030070","URL":"https://doi.org/10.3390/cleantechnol8030070","source":"openalex"},{"id":"oa:W4416966455","type":"manuscript","title":"Inverse Optimality for Fair Digital Twins: A Preference-based approach","abstract":"Digital Twins (DTs) are increasingly used as autonomous decision-makers in complex socio-technical systems. However, their mathematically optimal decisions often diverge from human expectations, revealing a persistent mismatch between algorithmic and bounded human rationality. This work addresses this challenge by proposing a framework that introduces fairness as a learnable objective within optimization-based Digital Twins. In this respect, a preference-driven learning workflow that infers latent fairness objectives directly from human pairwise preferences over feasible decisions is introduced. A dedicated Siamese neural network is developed to generate convex quadratic cost functions conditioned on contextual information. The resulting surrogate objectives drive the optimization procedure toward solutions that better reflect human-perceived fairness while maintaining computational efficiency. The effectiveness of the approach is demonstrated on a COVID-19 hospital resource allocation scenario. Overall, this work offers a practical solution to integrate human-centered fairness into the design of autonomous decision-making systems.","author":[{"family":"Masti","given":"Daniele"},{"family":"Basciani","given":"Francesco"},{"family":"Fedeli","given":"Arianna"},{"family":"Gnecco","given":"Girgio"},{"family":"Smarra","given":"Francesco"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2512.01650","URL":"https://doi.org/10.48550/arxiv.2512.01650","source":"openalex"},{"id":"oa:W7155215792","type":"article-journal","title":"A digital twin for simulating geochemical processes in geothermal power plants","abstract":"The MALEG project involves the development of artificial intelligence to increase the efficiency of geothermal energy production. A digital twin of the geothermal power plant (a cyber-physical system with sensors and actuators) and a digital twin of the hydrogeochemical processes (process simulation) within the thermal water cycle have been established. In terms of the geochemical digital twin, energy production in geothermal power plants is linked to the fundamental hydrochemical conditions of the fluid. Changes in pressure, temperature or pH can alter the chemical equilibrium of the extracted thermal water, potentially leading to uncontrolled processes such as mineral precipitation, outgassing and corrosion. To better map these processes, a digital twin has been developed and applied to several geothermal power plants. The simulations are automatically calculated, transferred and evaluated. This enables the new geochemical equilibrium conditions to be determined and interpreted directly as the power plant parameters change. Combined with the cyber-physical system, these process simulations form the basis for implementing artificial intelligence to increase the efficiency of geothermal power plants.","author":[{"family":"Ystroem","given":"Lars"},{"family":"Trumpp","given":"Michael"},{"family":"Eichinger","given":"Florian"},{"family":"Amtmann","given":"Johannes"},{"family":"Winter","given":"Daniel"},{"family":"Koschikowski","given":"Joachim"},{"family":"Nitschke","given":"Fabian"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5445/ir/1000192461","URL":"https://doi.org/10.5445/ir/1000192461","source":"openalex"},{"id":"oa:W7131717187","type":"article-journal","title":"Dataset for multi-perspective traffic video analysis","abstract":"Multi-angle video recordings are of significant interest as they provide comprehensive and synchronized data from multiple perspectives. This enables advanced analysis and modeling in environments with complex conditions due to their dynamics or the presence of obstacles, which lead to occlusions or loss of information in single-camera setups. This dataset comprises video footage of vehicular and pedestrian activity from three complementary viewpoints: A vehicle-mounted camera, a road side unit-mounted surveillance camera, and a drone-mounted camera. The dataset can be used in several domains including object, event, and activity recognition and tracking, urban analysis and planning, digital twinning, as well as semantic communication. To demonstrate its usefulness, standardized metrics are employed to provide quantitative evidence of the dataset's quality and reliability in comparison with existing datasets. The multi-modal nature of the footage paves the way for novel research in sensor fusion architectures and multi-scale modeling, critical for next-generation smart urban infrastructures.","author":[{"family":"Sanchez-Iborra","given":"Ramon"},{"family":"Kouvakis","given":"Vasileios"},{"family":"Trevlakis","given":"Stylianos"},{"family":"Alarcon-Hellin","given":"Gonzalo"},{"family":"Tsiftsis","given":"Theodoros"},{"family":"Bernal-Escobedo","given":"Luis"},{"family":"Asensio-Garriga","given":"Rodrigo"},{"family":"Boulogeorgos","given":"Alexandros–apostolos"},{"family":"Skármeta","given":"Antonio"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41597-026-06907-y","URL":"https://doi.org/10.1038/s41597-026-06907-y","source":"openalex"},{"id":"oa:W4410721903","type":"article-journal","title":"The Potential of Artificial Intelligence in Pharmaceutical Innovation: From Drug Discovery to Clinical Trials","abstract":"Artificial intelligence (AI) is a subfield of computer science focused on developing systems that can execute tasks traditionally associated with human intelligence. AI systems work through algorithms based on rules or instructions that enable the machine to make decisions. With the advancement of science, more sophisticated AI techniques, such as machine learning and deep learning, have been developed, allowing machines to learn from large amounts of data and improve their performance over time. The pharmaceutical industry has greatly benefited from the development of this technology. AI has revolutionized drug discovery and development by enabling rapid and effective analysis of vast volumes of biological and chemical data during the identification of new therapeutic compounds. The algorithms developed can predict the efficacy, toxicity, and possible adverse effects of new drugs, optimize the steps involved in clinical trials, reduce associated time and costs, and facilitate the implementation of innovative drugs in the market, making it easier to develop precise therapies tailored to the individual genetic profile of patients. Despite significant advancements, there are still gaps in the application of AI, particularly due to the lack of comprehensive regulation. The constant evolution of this technology requires ongoing and in-depth legislative oversight to ensure its use remains safe, ethical, and free from bias. This review explores the role of AI in drug development, assessing its potential to enhance formulation, accelerate discovery, and repurpose existing medications. It highlights AI's impact across all stages, from initial research to clinical trials, emphasizing its ability to optimize processes, drive innovation, and improve therapeutic outcomes.","author":[{"family":"Malheiro","given":"Vera"},{"family":"Santos","given":"Beatriz"},{"family":"Figueiras","given":"Ana"},{"family":"Mascarenhasmelo","given":"Filipa"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/ph18060788","URL":"https://doi.org/10.3390/ph18060788","source":"openalex"},{"id":"oa:W7125945213","type":"article-journal","title":"A Dynamic Digital Twin System with Robotic Vision for Emergency Management","abstract":"Ensuring production safety and enabling rapid emergency response in complex industrial environments remains a critical challenge. Traditional inspection robots are often limited by perception delays when confronted with sudden dynamic threats. This paper presents a vision-driven dynamic digital twin system designed to enhance real-time monitoring and emergency management capabilities. The framework constructs high-fidelity 3D models using SolidWorks 2024, Scaniverse 5.0.0, and 3ds Max 2024, and integrates them into a unified digital twin environment via the Unity 3D engine. Its core contribution is a vision-driven dynamic mapping mechanism: robots operating on the Robot Operating System (ROS) and equipped with ZED stereo cameras and embedded YOLOv5m models perform real-time detection, such as personnel and fire sources. Recognized targets trigger the dynamic instantiation of corresponding virtual models from a pre-built library, enabling automated, real-time reconstruction within the digital twin. An integrated service platform further supports early warning, status monitoring, and maintenance functions. Experimental validation confirms that the system satisfies key performance metrics, including data collection completeness exceeding 99.99%, incident detection accuracy of 80%, and state synchronization latency below 90 milliseconds. The system improves the dynamic updating efficiency of digital twins and demonstrates strong potential for proactive safety assurance and efficient emergency response in dynamic industrial settings.","author":[{"family":"Ma","given":"Zhongli"},{"family":"Zhou","given":"Qiao"},{"family":"Liu","given":"Jiajia"},{"family":"An","given":"Ruojin"},{"family":"Zhang","given":"Ting"},{"family":"Chen","given":"Xu"},{"family":"Dai","given":"Jiushuang"},{"family":"Geng","given":"Ying"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/electronics15030573","URL":"https://doi.org/10.3390/electronics15030573","source":"openalex"},{"id":"oa:W7126218849","type":"article-journal","title":"Hybrid Offshore Wind and Wave Energy Systems: A Review","abstract":"Against the backdrop of the global energy transition, the efficient exploitation of marine renewable energy has become a key pathway toward achieving carbon neutrality. Wind–wave hybrid systems (WWHSs) have attracted growing attention due to their resource complementarity, efficient spatial utilization, and shared infrastructure. However, most existing studies focus on single components or local optimization, while systematic integration of the full technology chain remains limited. This gap hinders the transition from demonstration projects to commercial deployment. This review provides a comprehensive overview of the technological evolution and key characteristics of offshore wind turbine (OWT) foundations and wave energy converters (WECs). Fixed-bottom foundations remain the mainstream solution for near-shore development. Floating offshore wind turbines (FOWTs) represent the core direction for deep-sea deployment. Among WEC technologies, oscillating buoy (OB) WECs are the dominant research pathway. Yet high costs and poor performance under extreme sea states remain major barriers to commercialization. On this basis, the paper summarizes three major integration modes of WWHSs. Among them, hybrid configurations have become the research focus due to their structural sharing, hydrodynamic coupling, and significant cost and energy synergies. Furthermore, the review synthesizes optimization strategies for both technology design and spatial layout, aiming to enhance energy capture, structural stability, and overall economic performance. Finally, the paper critically identifies the main research gaps and technical bottlenecks and outlines key development pathways required to achieve future commercial viability. These include the development of high-performance adaptive power take-off (PTO) systems, deeper understanding of multi-physics coupling mechanisms, intelligent operation and maintenance enabled by digital twins, and comprehensive life-cycle techno-economic and environmental assessments. Through this integrated perspective, the review seeks to provide a systematic reference for the development of multi-energy offshore systems and to support future progress in integrated energy utilization in deep-sea environments.","author":[{"family":"Song","given":"Haoyang"},{"family":"Yu","given":"Tongshun"},{"family":"Tong","given":"Xin"},{"family":"Zhao","given":"Xuewen"},{"family":"Zhang","given":"Zhenyu"},{"family":"Lun","given":"Zhixin"},{"family":"Wang","given":"Li"},{"family":"Wang","given":"Zeke"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19030739","URL":"https://doi.org/10.3390/en19030739","source":"openalex"},{"id":"oa:W7167080950","type":"article-journal","title":"IMMERSIVE LEARNING FOR RESILIENT CLASSROOMS. Digital infrastructure for life-saving furniture","abstract":"In areas of high seismic risk, school safety depends not only on the structural performance of buildings, but also on occupants’ ability to recognise and correctly use protective devices and operational procedures. With this in mind, the paper presents the development of an Immersive Learning Environment (ILE) conceived as a digital socio-technical infrastructure supporting the Life Saving Furniture System (LSFS), developed within the inter-university research programme Vitality. The ILE integrates virtual reality, 360° content and augmented reality, relying on a static digital twin of the classroom. The research adopts a design-led approach, combined with hybrid model-based pilot experimentation. Preliminary results suggest improved understanding of the LSFS, an overall positive usability profile, and encouraging indications of procedural responsiveness. Article info Received: 10/03/2026; Revised: 10/04/2026; Accepted: 13/04/2026","author":[{"family":"Oppedisano","given":"Federico"},{"family":"Rossi","given":"Daniele"},{"family":"Scortichini","given":"Manuel"}],"issued":{"date-parts":[[2026]]},"DOI":"10.69143/2464-9309/19282026","URL":"https://doi.org/10.69143/2464-9309/19282026","source":"openalex"},{"id":"oa:W4412621990","type":"article-journal","title":"QUANTUM SECURITY IN WEB 4.0: A NEW STAGE IN THE DEVELOPMENT OF THE METAVERSE","abstract":"The rapid advancement of Web 4.0, or the Symbiotic Web, marks a pivotal shift in the evolution of the Internet, characterized by immersive digital experiences and intelligent, decentralized ecosystems. This paper explores the intersection of Web 4.0, the Metaverse, and quantum security, focusing on the urgent need to secure digital infrastructures against the growing threat of quantum computing. As the Metaverse becomes a dynamic driver of digital transformation and economic development, the integration of post-quantum cryptography and quantum-resistant systems is essential for ensuring data privacy, digital sovereignty, and cyber resilience. The study examines key technological trends - including AI, blockchain, XR, and the Industrial Metaverse - within the context of current geopolitical risks, particularly the war in Ukraine. It highlights international quantum strategies, post-quantum encryption standards, and emerging architectures such as quantum blockchain. The authors argue that a proactive approach to quantum security is imperative for safeguarding future virtual environments, emphasizing Ukraine’s strategic opportunity to build a robust and ethical quantum ecosystem.","author":[{"family":"Oliіnyk","given":"Danyila"},{"family":"Koshkarov","given":"Stepan"},{"family":"Konizhai","given":"Yurii"}],"issued":{"date-parts":[[2025]]},"DOI":"10.69635/mssl.2025.1.1.16","URL":"https://doi.org/10.69635/mssl.2025.1.1.16","source":"openalex"},{"id":"oa:W7140043998","type":"article-journal","title":"Optimization Research of AI+Digital Twins in Building Equipment System","abstract":"Under the macro background of actively responding to climate change and promoting the “double carbon” strategy, the construction industry, as a key field of energy consumption and carbon emissions, has become a trend of green and low-carbon transformation. The operation efficiency of building equipment system, especially HVAC, electrical lighting and water supply and drainage system, directly determines the overall energy consumption of the building. This study focuses on the frontier technology integration of “ai+digital twins”, and explores its application and implementation path in the optimization of building equipment system. Through systematic literature review, the application status of digital twins and AI technology in the whole life cycle of building equipment design, construction, operation and maintenance is summarized. Through the case analysis of multiple scenarios, the energy efficiency improvement ability and carbon emission reduction benefits of the technology in typical scenarios such as commercial buildings, factories, municipal water supply networks are quantitatively evaluated. Finally, based on the comprehensive research data and AI intelligent analysis, a set of “technology economy policy” collaborative transformation path covering technical standards, business models and policy incentives is constructed, which provides an operable solution for the implementation of the “double carbon” goal in the construction field.","author":[{"family":"Miaomiao","given":"Liu"},{"family":"Jia","given":"Zhan"},{"family":"Jian","given":"Zhao"},{"family":"Huili","given":"Cao"},{"family":"Zaitian","given":"Wu"}],"issued":{"date-parts":[[2026]]},"DOI":"10.22158/grhe.v9n1p108","URL":"https://doi.org/10.22158/grhe.v9n1p108","source":"openalex"},{"id":"oa:W7167344731","type":"article-journal","title":"Agentic LLMs for Scalable, Verifiable System Health Digital Twins","abstract":"System Health Management (SHM) digital twins have evolved from specialized engineering tools into enterprise-wide critical systems supporting diagnostics and lifecycle decision support, yet scaling the creation, validation, and maintenance of detailed causal models remains a bottleneck due to labor-intensive, expert-driven processes that do not scale with system complexity or lifecycle evolution. This paper presents an AI-driven framework addressing this challenge through a tightly integrated neuro-symbolic architecture that combines agentic large language models (LLMs) as constrained knowledge extraction agents with a rigorous symbolic reasoning core grounded in multi-functional causal modelling, enforcing structural, semantic, and logical constraints to transform extracted knowledge into verifiable, executable diagnostic models while shifting human expertise toward validation, governance, and continuous improvement. The framework implements an end-to-end “ingest–extract–structure–verify” pipeline converting artifacts (i.e., technical manuals, schematics, FMECA data) into formal causal models compatible with TEAMS and SysML-based representations, providing a single source of truth for downstream applications including fault detection and isolation, prognostics, sensor optimization, training scenario generation, and lifecycle-informed design. Demonstrated results show up to an 80% reduction in engineering effort and rapid model generation at previously impractical scales, with aerospace and space system deployments confirming accurate, scalable operational reasoning, while an enterprise operating model treats the digital twin as a governed, evolving asset integrated across design, operations, maintenance, and training, enabling continuous adaptation from field data and offering a practical path to trustworthy, adaptive digital twins that deliver sustained enterprise-scale value.","author":[{"family":"Norton","given":"Chris"},{"family":"Pattipati","given":"K"},{"family":"Thurston","given":"Jordan"},{"family":"Haste","given":"D"},{"family":"Ghoshal","given":"Sudipto"},{"family":"Deb","given":"Somnath"},{"family":"Lawless","given":"William"}],"issued":{"date-parts":[[2026]]},"DOI":"10.54941/ahfe1007674","URL":"https://doi.org/10.54941/ahfe1007674","source":"openalex"},{"id":"oa:W7165634533","type":"article-journal","title":"Brief communication: delivering a Digital-Twin-ready snow reanalysis","abstract":"Abstract. We present DTE-SNOW, a Digital-Twin-ready framework for simulating the spatial and temporal dynamics of snow-water resources at 1 km resolution, based on satellite-derived precipitation, snow modeling, and the optional assimilation of Sentinel-1 snow-depth retrievals. Using test simulations over four European mountain basins (Ebro, Rhône, Po, and Inn), we show that DTE-SNOW achieves an average snow-depth bias of only a few centimeters (0.05 m when Sentinel-1 snow-depth assimilation is applied). The simulated spatial patterns successfully reproduce the topographic dependence of snow distribution, with correlations between mean annual Snow Water Equivalent (SWE) and elevation ranging from 0.63 to 0.77. Because DTE-SNOW is independent of in situ observations, it opens new opportunities toward a “SWE of everywhere” paradigm: a globally consistent estimation of snow-water resources within DestinE.","author":[{"family":"Avanzi","given":"Francesco"},{"family":"Lievens","given":"Hans"},{"family":"Matiu","given":"Michael"},{"family":"Filippucci","given":"Paolo"},{"family":"Baezvillanueva","given":"Oscar"},{"family":"Gabellani","given":"Simone"},{"family":"Delogu","given":"Fabio"},{"family":"Alfieri","given":"Lorenzo"},{"family":"Libertino","given":"Andrea"},{"family":"Quintanaseguí","given":"Pere"},{"family":"Miralles","given":"Diego"},{"family":"Brocca","given":"Luca"},{"family":"Massari","given":"Christian"},{"family":"Lannoy","given":"Gabriëlle"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/egusphere-2026-2851","URL":"https://doi.org/10.5194/egusphere-2026-2851","source":"openalex"},{"id":"oa:W7169753178","type":"article-journal","title":"A Self-Adaptive Digital Twin Architecture for Dynamic Resource Management","abstract":"Digital Twins (DTs) are increasingly used to manage systems under fluctuating demand, yet many remain static and cannot adjust their internal models or control policies as the targeted real system changes. We present a self-adaptive DT architecture that supports runtime reconfiguration of resources. The architecture integrates semantic reflection to keep the DT's runtime model aligned with the structural representation of the real system, lifecycle-based state management to trigger reconfiguration at appropriate times, and penalty-guided optimisation for decision-making under constraints, balancing resilience and operational cost when capacity must be reorganised. We realise the approach in DynResDT, a resilient hospital ward prototype for bed bay allocation of patients. Through simulation with realistic patient-arrival patterns and stress peaks, the DT maintains model consistency, opens and closes overflow capacity when needed, and allocates patients while minimising costly room usage and unnecessary moves. Our results show a practical trade-off between correctness and responsiveness: timely and principled adaptions offset potential overhead through reflection and lifecycle logic. The architectural pattern is applicable beyond healthcare to other dynamic resource-management domains. CCS Concepts • Software and its engineering → Layered systems; Software as a service orchestration system; • Computer systems organization → Self-organizing autonomic computing.","author":[{"family":"Sieve","given":"Riccardo"},{"family":"Kobialka","given":"Paul"},{"family":"Pferscher","given":"Andrea"},{"family":"Bencomo","given":"Nelly"},{"family":"Tarifa","given":"Silvia"},{"family":"Rasmussen","given":"B"},{"family":"Johnsen","given":"Einar"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1145/3788550.3794872","URL":"https://doi.org/10.1145/3788550.3794872","source":"openalex"},{"id":"oa:W7171714490","type":"article-journal","title":"Editorial: The future of oncology: digital twins and precision cancer care","abstract":"The papers \"DATA 5.0 -Data Acquisition, Translation & Analysis -a prospective uro-oncological data warehouse for the 21st century\" by Schutz et al. and \"Understanding the need for digital twins' data in patient advocacy and forecasting oncology\" by Chang et al. delve into fundamental elements of the data underlying a successful digital twin in oncology. The collection, aggregation, and ethical sharing of longitudinal data for oncology digital twins are key pillars for the future of cancer patient digital twins. Ensuring data quality, harmonization, and representative sampling across diverse populations is critical, not only to realize the potential of more effective and costeffective clinical trials, but also for ensuring the use of digital twins in oncology to improve outcomes across demographics. The role of AI to aid these efforts is also a key pillar to the future success for oncology digital twins, streamlining areas including collection, featurization, and selection of quality datasets. Furthermore, AI can provide data-driven models to help fill the gap when effective mechanistic approaches are unavailable.The final two papers, \"Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas\" by Chaudhuri et al., and \"Bridging the gap between hepatocellular carcinoma management guidelines and personalised medicine: a Bayesian network study\" by Wang et al., point the way forward with real examples of AI and digital twins in a clinical decision support capacity. While each is unique, both studies reinforce the fact that early-generation digital twins are most effective when engineered to inform on specific clinical questions. There are commonalities in the use of Bayesian methods to incorporate prior insights from both the individual patients and broader populations. The papers also highlight a key value proposition of cancer digital twins to incorporate the ever-expanding domain of patient data and observations in a common approach and framework, supporting the care team with new insights to guide increasingly optimal treatment decisions.Digital twins in oncology research started to gain momentum after NCI and DOE jointly launched the Cancer Patient Digital Twin initiative in July 2020 [3]. Observing across the papers in this Research Topic and the growing number of examples of cancer digital twins [4] and digital twins that have since been developed in other health areas [5], the pace of medical digital twin development is accelerating. Efforts such as the European Union supported Virtual Human Twin [6], the Digital Twins for Health Society [7], the Virtual Human Global Summit [8,9], the Swedish Digital Twin Consortium (SDTC) [10], and the Digital Twin Summit at MD Anderson Cancer Center all stand testament to the growing community involved in the development of medical digital twins.A common theme emerging across these contributions is that the future success of oncology digital twins will depend as much on implementation, validation, and continuous improvement as on model development. While advances in AI, multimodal data integration, and computational modeling have accelerated the creation of increasingly sophisticated digital twins, demonstrating clinical utility and dynamical learning remains a critical next step. Future oncology digital twins must be evaluated not only for predictive accuracy but also for their ability to support clinical decision making, communicate uncertainty, integrate into existing workflows, and improve patient outcomes [11]. Importantly, the most impactful digital twins may not be comprehensive virtual replicas of patients, but rather focused, continuously learning systems designed to support specific clinical decisions. As the field matures, rigorous validation, uncertainty quantification, and prospective evaluation will be essential to translating the promise of digital twins into routine oncology care.As we look to the future for digit","author":[{"family":"Stahlberg","given":"Eric"},{"family":"Deng","given":"Jun"},{"family":"Hernandez-Boussard","given":"Tina"},{"family":"Wang","given":"Qi"},{"family":"Liu","given":"Hongfang"},{"family":"Syeda-Mahmood","given":"Tanveer"},{"family":"Aguilar","given":"Boris"},{"family":"Wu","given":"Huanmei"},{"family":"Zhang","given":"Aidong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/frai.2026.1912241","URL":"https://doi.org/10.3389/frai.2026.1912241","source":"openalex"},{"id":"oa:W7202283563","type":"article-journal","title":"Toward application-driven battery design through digital twins","abstract":"In present energy technology, materials discovery, device design, manufacturing, and operation remain predominantly sequential, with limited cross-stage feedback throughout the development chain. Recent advances are, however, converging toward a common design philosophy, in which the application requirements inform early design decisions at materials and cell level before large-scale physical realization. Using battery systems as a compelling testbed, this Research Highlight explores how digital twins could establish continuous learning from deployment to design, shortening innovation cycles and accelerating industrial implementation.","author":[{"family":"Guo","given":"Wendi"},{"family":"Vegge","given":"Tejs"},{"family":"Brandell","given":"Daniel"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s44503-026-00014-0","URL":"https://doi.org/10.1007/s44503-026-00014-0","source":"openalex"},{"id":"oa:W7117457929","type":"article-journal","title":"High-temperature heat pumps: key technologies and industrial applications toward carbon–neutral process heating","abstract":"Abstract High-temperature heat pumps (HTHPs) are emerging as pivotal technologies for decarbonizing industrial heat supply by upgrading low-grade waste heat to meet diverse thermal demands. This review summarizes and analyzes the current state, applications and future trends of HTHPs from a carbon–neutral perspective. Core technological aspects—including cycle configurations, refrigerants, compressors, and integration strategies—are systematically analyzed. Thermodynamic comparisons reveal that cascade and coupled cycles can achieve temperature lifts above 100 °C under optimized conditions. The transition from high global warming potential (GWP) hydrofluorocarbons toward low-GWP hydrofluoroolefins, hydrochlorofluoroolefins, and natural refrigerants is accelerating. Large-capacity screw and centrifugal compressors are identified as key enablers for industrial-scale deployment. Typical industrial deployments of HTHPs across various fields are introduced, mainly structured around their application potential, integration characteristics, and implementation methods within energy-intensive sectors (e.g., paper manufacturing, textile dyeing). Future development will focus on high-power systems, advanced working fluid design, and digital control integration with renewable power and thermal storage. Collectively, HTHPs constitute an essential electrification pathway for achieving deep industrial decarbonization and carbon–neutral energy systems.","author":[{"family":"Wu","given":"Jiale"},{"family":"Yang","given":"Luwei"},{"family":"Zhang","given":"Chong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s44438-025-00021-z","URL":"https://doi.org/10.1007/s44438-025-00021-z","source":"openalex"},{"id":"oa:W7169783274","type":"article-journal","title":"Ten questions on digital twins of buildings for transforming building operations","abstract":"Buildings are becoming ever more complex to manage during operations, driven by increasing dynamics in energy demand, intermittent on-site power generation, and distributed energy resources, compounded by variable grid pricing signals and the rising threat of extreme weather events causing large-scale power outages. To achieve optimal performance in energy efficiency, demand flexibility, energy resilience, and occupant comfort, new methods and tools are essential for transforming design and operations across a building’s entire life cycle. Digital Twins (DTs), enabled by recent advances in ubiquitous sensing, big data, cloud computing, and AI, offer a transformative approach to creating a real-time, bi-directional digital counterpart of a physical building. This paper presents ten critical questions highlighting the most foundational issues underpinning the successful deployment of digital twins of buildings. The questions are holistically structured around three core themes to provoke significant research and accelerate adoption. The paper first examines the Users and Business aspects, including use cases, stakeholder alignment, business models, and governance structures. It then dives into the Technology foundation, addressing key components, layered software architectures, data integration, semantic interoperability, and the critical issues of cybersecurity and privacy. Finally, it explores Application aspects, such as the role of AI, performance metrics and standards, and the current landscape of software tools. DT technology is still in the early stage of adoption in buildings despite successful pilot applications in preventive maintenance, FDD, and advanced controls to optimize building performance. Several barriers need to be addressed to scale up DT technology in buildings, including high development and maintenance costs, the lack of data-rich infrastructure in buildings, and a shortage of skilled workforce.","author":[{"family":"Hong","given":"Tianzhen"},{"family":"Li","given":"Hui"},{"family":"Zhu","given":"Yimin"},{"family":"Dong","given":"Bing"},{"family":"Zhang","given":"Liang"},{"family":"Choudhary","given":"Ruchi"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.buildenv.2026.115023","URL":"https://doi.org/10.1016/j.buildenv.2026.115023","source":"openalex"},{"id":"oa:W7204077254","type":"article-journal","title":"Role of health digital twins in oncology drug development - a primer","abstract":"Health Digital Twins (HDTs) have attracted increasing interest as a potential tool for improving both patient care and clinical research, particularly in oncology where clinical trials remain slow, costly, and operationally complex. This primer introduces the concept of digital twins in a form accessible to professionals involved in oncology clinical research and outlines the main components of health digital twins, describes how these systems are generated, and highlights their potential relevance to oncology trials. HDTs are personalized, dynamically updated, predictive, and decision−informing computational representations that integrate clinical records, laboratory measurements, imaging, pathology, and molecular data. The generation of an HDT begins with the integration of multiple sources of information to create a digital representation that reflects the patient’s disease state and can be updated as new information becomes available. These systems may be built using data−driven AI models, mechanistic physiological models, or hybrid approaches that combine both. Emerging HDT−based approaches have been proposed as a means of addressing several of the structural limitations of oncology trials by enabling in−silico experimentation, improved biological stratification of patients, and more efficient use of longitudinal real−world and historical data. In early−phase studies, HDTs can support dose selection, safety evaluation, and cohort selection, while in later phases they may contribute to optimized trial designs, synthetic control arms, and adaptive trial methodologies. These applications may reduce patient enrolment time, improve efficiency, and support simulation−driven decision−making. Despite this promise, the application of HDTs remains associated with technical, ethical, regulatory, and data−governance challenges, including data quality, model validity, bias, and uncertainty. Regulatory agencies currently view HDTs as complementary tools within model−informed drug development rather than as replacements for conventional clinical evidence. In conclusion, HDTs have the potential to transform clinical trials by enabling personalized treatments, optimizing trial design, and facilitating predictive analytics, although their applications remain emerging and require further validation, governance frameworks, and regulatory alignment to support widespread adoption.","author":[{"family":"Requesens","given":"Maria"},{"family":"Mankan","given":"Arun"},{"family":"Cantini","given":"Luca"},{"family":"Calabresi","given":"Marco"},{"family":"Vidal","given":"Laura"},{"family":"Brown","given":"Joan"},{"family":"Lang","given":"Steven"},{"family":"Kaura","given":"Bobby"},{"family":"Veselkov","given":"Kirill"},{"family":"Xénarios","given":"Ioannis"},{"family":"Saini","given":"Kamal"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fonc.2026.1885797","URL":"https://doi.org/10.3389/fonc.2026.1885797","source":"openalex"},{"id":"oa:W7165968076","type":"article-journal","title":"A Scoping Review of Digital Twins Across Environmental and Territorial Applications","abstract":"Digital twin (DT) technology has expanded far beyond its industrial origins, increasingly finding application across environmental and territorial domains. This review provides a structured mapping of DT deployments at environmental and territorial scales over the period 2020–2025, examining 117 peer-reviewed publications (109 applied studies and 8 review articles) through a structured 16-parameter classification framework. The review traces three major conceptual shifts in the DT paradigm: from industrial assets to living entities, from discrete systems to Earth-scale representations, and from closed deterministic models to ecological and systemic frameworks, as reflected in the emergence of ecological digital twins (EcoDTs), environmental digital twins (EDTs), and territorial digital twin (TDT) definitions. The results reveal a clear growth trajectory in DT applications across themes, with urban systems as the most consolidated application domain, and progressive diversification into marine, coastal, forestry, river/lake, and Earth system applications from 2022 onward. Institutional actors dominate production in this space, aligned with European flagship initiatives such as Destination Earth (DestinE) and the European Digital Twin of the Ocean (EDITO). The findings position and expand the notion of territorial digital twins as an evolving paradigm, underscoring both the momentum generated by EU digital and environmental policy and the need for integrated tools to answer and respond to key environmental challenges.","author":[{"family":"Artioli","given":"Letizia"},{"family":"Borga","given":"Giovanni"},{"family":"Costa","given":"Pietro"},{"family":"Dacunto","given":"Federica"},{"family":"Iodice","given":"Filippo"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/digital6030053","URL":"https://doi.org/10.3390/digital6030053","source":"openalex"},{"id":"oa:W4411170282","type":"article-journal","title":"The twin transition: Driving sustainability through digital transformation in manufacturing","abstract":"In the context of increasing global competition and rising environmental and social demands, manufacturing companies are under pressure to pursue sustainable growth while maintaining competitiveness. Although the convergence of digitalization and sustainability—known as the \"twin transition\"—has gained significant attention, understanding how digital technologies concretely support sustainability initiatives remains fragmented. This study explores the role of digital transformation in advancing sustainable practices within the manufacturing sector, drawing on empirical evidence from an industrial cluster. The findings reveal that while digital tools offer significant potential for improving resource efficiency, reducing emissions, and supporting sustainable operations, companies face persistent barriers such as stakeholder resistance, high initial costs, limited customer willingness to pay for sustainable products, and fragmented data utilization. Furthermore, organizational challenges, including low digital maturity, cultural resistance, and difficulties in aligning supply chain partners, continue to hinder progress. The study highlights the importance of employee engagement, transparent sustainability reporting, and strategic data management as critical enablers for the successful integration of digitalization and sustainability. By identifying both opportunities and challenges, the paper contributes to a deeper understanding of the systemic changes needed to leverage digital technologies for sustainable manufacturing and outlines avenues for future research across broader industrial contexts.","author":[{"family":"Rahnama","given":"Hossein"},{"family":"Johansen","given":"Kerstin"},{"family":"Rönnbäck","given":"Anna"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.technovation.2026.103582","URL":"https://doi.org/10.1016/j.technovation.2026.103582","source":"openalex"},{"id":"oa:W7172397088","type":"article-journal","title":"Towards a Digital Twin infrastructure for landslides: users and data requirements","abstract":"Abstract. The increasing frequency and magnitude of landslides necessitates a fundamental shift from reactive mitigation to proactive, predictive risk governance. To define the necessary tools for this transition, this study conducts a systematic literature review and operational analysis of current Digital Twin (DT) implementations in the geosciences. Through this review, we identify four primary target user groups (emergency responders, technical experts, public administrators, and citizens) and map their specific 4D data requirements and interaction logics. Our findings highlight that most existing systems function as \"Digital Shadows\" characterised by unidirectional data flows and a topography gap, where dynamic sensor data is superimposed onto static, outdated 3D meshes. Based on these requirements, we propose a theoretical layered architectural framework for a Data Hub designed to bridge these gaps. The conceptual architecture is structured into three interconnected tiers: an Acquisition Layer for multi-scale data ingestion; a Modelling and Processing Layer for AI and physics-based stability assessment; and an Application and Service Layer for translating complex data into actionable intelligence. Finally, this work investigates a possible implementation path for landslides DT projects by outlining technical recommendations. This includes the adoption of cloud-native formats (e.g., Cloud Optimized GeoTIFF, Zarr) and unified interoperability standards (e.g., OGC SensorThings API) to evaluate the feasibility of transitioning towards a true bi-directional cyber-physical system for landslide risk management.","author":[{"family":"Gaspari","given":"Federica"},{"family":"Gentile","given":"Marco"},{"family":"Carrión","given":"Daniela"},{"family":"Barzaghi","given":"Riccardo"},{"family":"Panzeri","given":"Lorenzo"},{"family":"Longoni","given":"Laura"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-archives-xlix-b4-2026-485-2026","URL":"https://doi.org/10.5194/isprs-archives-xlix-b4-2026-485-2026","source":"openalex"},{"id":"oa:W7140160681","type":"article-journal","title":"AI-Based Smart Digital Twin For Industrial Predictive Maintenance","abstract":"Predictive maintenance has become an important application of Artificial Intelligence in modern industries. Traditional maintenance techniques often lead to unexpected machine failures and increased operational costs. This research proposes an AI-based smart digital twin system that monitors machine performance and predicts possible failures before they occur. The digital twin model replicates the physical machine in a virtual environment using sensor data and machine learning algorithms. The system analyzes temperature, vibration, and operational parameters to detect abnormal patterns. Experimental results show that the proposed model can effectively identify potential faults and reduce downtime. This approach improves maintenance efficiency, increases equipment life, and reduces operational costs.","author":[{"family":"Sayyad","given":"Ayesha"},{"family":"Sayyad","given":"Afrin"},{"family":"Khude","given":"Pragati"},{"family":"Bhuruk","given":"Jyoti"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.19202890","URL":"https://doi.org/10.5281/zenodo.19202890","source":"openalex"},{"id":"oa:W7151472604","type":"article-journal","title":"Sustainable Automation of Monitoring and Production Accounting in Greenhouse Complexes Using Integrated AI, Robotics, and Data Systems","abstract":"Production greenhouse complexes increasingly require automation and digitalization to address rising labor costs, improve productivity, and support sustainable resource use. However, most existing solutions target isolated tasks and lack a unified framework for continuous monitoring and production-oriented accounting at facility scale. This paper proposes a system-level architecture that integrates robotic monitoring platforms, AI-based perception, and cloud-based data management into a coherent operational framework. The robotic monitoring platforms operate on rails and concrete surfaces and are capable of elevating cameras and sensors up to 5 m to support plant-health assessment, environmental monitoring, and production accounting. Aggregated data are incorporated into a digital twin that supports spatial traceability, historical analysis, and decision support. The proposed approach enables continuous inspection, improves early detection of crop stress, reduces repetitive manual scouting, and supports targeted interventions. The framework provides a scalable foundation for sustainable, data-driven greenhouse management and practical deployment of robotic monitoring systems in industrial production environments.","author":[{"family":"Uzhinskiy","given":"Alexander"},{"family":"Teryaev","given":"Lev"},{"family":"Dorokhin","given":"Artem"},{"family":"Ivashev","given":"Mikhail"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18073620","URL":"https://doi.org/10.3390/su18073620","source":"openalex"},{"id":"oa:W7160030833","type":"article-journal","title":"Ai-Powered Digital Twin Approach For Personalized Organ Transplantation","abstract":"The rapid advancement of artificial intelligence (AI) in healthcare has created unprecedented opportunities for improving diagnosis, treatment planning, and clinical decision-making. This paper presents DonorSync — an AI-powered Digital Twin system designed to assist physicians in liver and kidney donor-recipient matching using machine learning and medical image analysis. The proposed system combines Logistic Regression-based clinical parameter analysis (age, bilirubin, albumin, creatinine, urea) with a ResNet-50-driven ultrasound image evaluation module to generate ranked donor compatibility scores and transplant success probabilities in real time. Built on a FastAPI backend with MongoDB data storage and an HTML/CSS/JavaScript frontend, the platform provides secure, scalable, and efficient access to donor matching services. Experimental evaluation confirms that the integrated dual-modality approach substantially reduces donor selection time and enhances prediction reliability compared to conventional manual processes. The system aligns with UN Sustainable Development Goal 3 (Good Health and Well-Being) and Goal 9 (Industry, Innovation and Infrastructure).","author":[{"family":"Princy","given":"Mrs"},{"family":"Kp","given":"Pooja"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20023582","URL":"https://doi.org/10.5281/zenodo.20023582","source":"openalex"},{"id":"oa:W7162247743","type":"article-journal","title":"Smart Digital Twin: Experimental setup and developed dashboards for real-time production monitoring, machine condition tracking, and LLM-assisted prognostics of a smart retrofitted legacy CNC lathe","abstract":"The figure presents the experimentally developed AI-enabled human-centric digital twin system implemented on a smart retrofitted legacy CNC lathe. The figure illustrates both the physical and digital components developed for real-time production monitoring, machine condition tracking, and LLM-assisted prognostics. The physical layer includes the CNC lathe, industrial predictive maintenance sensors, RFID-based operator interaction system, IoT gateway, edge computing infrastructure, and associated sensing architecture for vibration, temperature, and machine activity acquisition. The digital layer demonstrates the developed Grafana dashboards used for live production monitoring, machine condition visualization, tool wear state estimation, and conversational AI-assisted assessment. The figure was developed as part of the research work titled “AI-Enabled Human-Centric Digital Twin Framework for Real-Time Performance Monitoring and Prognostics of Legacy Machines.” The presented implementation demonstrates the integration of IoT, AI, edge-cloud computing, and large language model-assisted analytics for smart retrofitting of legacy manufacturing systems toward Industry 4.0 and Industry 5.0 applications. Author: Deep Patel, Chayan Maiti, and Sreekumar MuthuswamyAffiliation: Indian Institute of Information Technology, Design and Manufacturing (IIITDM) Kancheepuram, India. © Deep Patel, 2026. All rights reserved.","author":[{"family":"Patel","given":"Deep"},{"family":"Maiti","given":"Chayan"},{"family":"Muthuswamy","given":"Sreekumar"}],"issued":{"date-parts":[[2026]]},"DOI":"10.6084/m9.figshare.32393037.v3","URL":"https://doi.org/10.6084/m9.figshare.32393037.v3","source":"openalex"},{"id":"oa:W7166835388","type":"article-journal","title":"Digital Twin Vision for Rail Health Monitoring for Freight Railroads","abstract":"This paper presents a vision and case study for a framework to implement the digital twin (DT) concept to support rail health monitoring and management in North American freight railroads. The DT system includes a DT of physical rail, rail maintenance and inspection data, digitalization processes for recording pertinent information, and software and analytics tools. The case study uses the 2.8 mi (4.5 km) Facility for Accelerated Service Testing (FAST®) track to assess the DT’s ability to meet rail owners’ requirements and provide necessary contextual information. At FAST, data streams generated by operations, maintenance, wayside and onboard detector technologies, and individual testing are employed to better understand the effects of heavy axle loads on track components at various stages of wear. The case study also demonstrates that actively managing rail health requires a methodological approach to collecting and managing data for predictive, preventive, and corrective maintenance strategies informed by rail metallurgy, operational factors, environmental factors, and rigorous maintenance techniques. Although the case study considers only FAST rail infrastructure, the DT system’s scalability indicates its potential for larger implementations both within and beyond FAST.","author":[{"family":"Galván-Núñez","given":"Silvia"},{"family":"Poudel","given":"Anish"},{"family":"Banerjee","given":"Ananyo"},{"family":"Johnson","given":"Chris"}],"issued":{"date-parts":[[2026]]},"DOI":"10.32548/2026.me-04582","URL":"https://doi.org/10.32548/2026.me-04582","source":"openalex"},{"id":"oa:W7166396434","type":"article-journal","title":"Digital Twin Aggregates for adaptive MLOps retraining policies in healthcare","abstract":"Digital Twins (DTs) are increasingly adopted as a technical solution for the digital representation of complex physical entities through models that process near-real-time data streams and provide feedback on the state and behavior of the Physical Twin (PT). When DT models are trained using Machine Learning (ML) techniques, their performance may degrade over time as the DT acquires new operational data that may differ from the data observed during initial training. In this paper, following Machine Learning Operations (MLOps) principles, we investigate how Digital Twin Aggregates (DTAs) can be integrated into DT-based systems to enable continuous monitoring of model performance and to support adaptive retraining strategies for the continuous delivery and maintenance of ML models ensuring that the DT remains a reliable representation of the PT throughout its lifecycle. We evaluate the approach in a healthcare case study involving DTs for diabetic patients and compare adaptive with periodic retraining showing that performance-based retraining mantains stable accuracy while reducing model updates. These results suggest that DTA-level monitoring enables more efficient adaptive MLOps lifecycles by triggering retraining in response to actual performance degradation rather than fixed schedules.","author":[{"family":"Domini","given":"Davide"},{"family":"Micelli","given":"Leonardo"},{"family":"Burattini","given":"Samuele"},{"family":"Montagna","given":"Sara"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.future.2026.108674","URL":"https://doi.org/10.1016/j.future.2026.108674","source":"openalex"},{"id":"oa:W7172434932","type":"article-journal","title":"AI-Enabled Digital Twins and Optimization Workflows for Accelerator Control","abstract":"We propose to develop advanced ML models, such as physics informed neural network (PINN) based surrogate models, to accurately represent accelerator phase space transport. These surrogate models will enable precise diagnosis and prediction of beam phase space evolution along the beamline, facilitating real-time control and optimization. The developed models will be tested using the Upgraded Injector Test Facility (UITF) at Thomas Jefferson National Accelerator Facility (JLab), providing a pathway toward ML-driven enhanced diagnostics and beamline control in operational accelerator environments. The primary aim will be to facilitate this by developing machine learning models that outperform traditional simulations in speed and precision. We will build a virtual beamline, train a reinforcement learning (RL) controller across varied calibration scenarios, and then transfer it to the real machine. Beyond operation, fast and accurate models are also essential for design optimization workflows using machine learning methods that iterate through design parameters. A long-term goal of this work will be to establish such workflows and apply them to the design of a compact accelerator at Old Dominion University (ODU).","author":[{"family":"Yadav","given":"M"},{"family":"Seryi","given":"A"},{"family":"Terzic","given":"B"},{"family":"Bird","given":"J"},{"family":"Delayen","given":"J"},{"family":"Makino","given":"K"},{"family":"Ahmed","given":"K"},{"family":"Riesen-Haupt","given":"LV"},{"family":"Su","given":"Q"},{"family":"Silva","given":"SD"},{"family":"Hossain","given":"S"},{"family":"Griffin","given":"T"},{"family":"Satogata","given":"T"}],"issued":{"date-parts":[[2026]]},"DOI":"10.18429/jacow-ipac2026-mop6335","URL":"https://doi.org/10.18429/jacow-ipac2026-mop6335","source":"openalex"},{"id":"oa:W7164922912","type":"article-journal","title":"Data distribution performance for Digital Twin Synchronization: an experimental evaluation","abstract":"Digital Twin Synchronization (DTS) demands robust data distribution to handle heterogeneous flows, yet existing evaluations often overlook large messages and degraded networks. This work experimentally evaluates five middleware protocols, MQTT, AMQP, Kafka, DDS, and Zenoh, within a data-centric DTS architecture. We assess performance metrics such as latency and stability under varying message sizes (up to 2 MiB) and controlled network degradation. Our results highlight trade-offs between broker-based and brokerless architectures, identifying the most suitable solutions for the rigorous synchronization demands of Industry 4.0.","author":[{"family":"Freitas","given":"Eduardo"},{"family":"Filho","given":"Assis"},{"family":"Carmo","given":"Pedro"},{"family":"Dantas","given":"Marrone"},{"family":"Kelner","given":"Judith"},{"family":"Sadok","given":"Djamel"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5753/wgrs.2026.23232","URL":"https://doi.org/10.5753/wgrs.2026.23232","source":"openalex"},{"id":"oa:W7204466842","type":"article-journal","title":"A metrological digital twin of nanoindentation for out-of-control measurements identification","abstract":"Nanoindentation enables the high-resolution characterization of mechanical properties and the study of advanced materials. However, in the measurement practice, several influence factors affect nanoindentation, introducing bias or increasing measurement uncertainty. Some influence factors are internally sourced (force–displacement noise), others are induced by the environment (electro-mechanical vibrations, indenter-sample thermal equilibrium), and some depend on interactions with the measurand (sample surface integrity, indenter tip wear). Digital twins are simulation models that replicate physical systems in a virtual environment, dynamically updating the virtual model to match the observed state of its real counterpart, enabling physical control of the latter. Digital twins allow predicting system response and highlighting anomalies, while identifying critical influence factors causing such out-of-control conditions, and deploying control actions to avoid malfunctions through predictive maintenance, while avoiding wasting resources. However, to ensure appropriate equipment monitoring and decision-making, traceable digital twins that consider measurement uncertainty are needed. While discussing the advantages of alternative modelling pathways, the work demonstrates the creation of a traceable digital twin for nanoindentation on reference materials based on physics-based data-driven approach. Validation strategies for synthetic and real datasets are implemented, and the capability to detect the most common measurement errors in nanoindentation is highlighted. Strategies to eliminate or compensate for sources of identified measurement errors by the digital twin are discussed, outlining a route towards traceable digitization in nanoindentation.","author":[{"family":"Maculotti","given":"Giacomo"},{"family":"Giorio","given":"Lorenzo"},{"family":"Genta","given":"Gianfranco"},{"family":"Bertolini","given":"Rachele"},{"family":"Savio","given":"Enrico"},{"family":"Galetto","given":"Maurizio"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.measurement.2026.122991","URL":"https://doi.org/10.1016/j.measurement.2026.122991","source":"openalex"},{"id":"oa:W7168534971","type":"article-journal","title":"The role of digital twin technology in nursing practice, education, and research","abstract":"Background Digital twin technology, a virtual real-time representation of a physical entity, is gaining traction in healthcare, yet its potential in nursing practice remains underexplored. Objective This review examines current and potential applications of digital twins in nursing, including benefits, challenges, and integration pathways. Method An integrative review synthesised empirical and theoretical literature from PubMed, CINAHL, Scopus, IEEE Xplore, and Web of Science (2015 to 2025), alongside grey literature, with data extracted and analysed thematically. Results Digital twins show potential across patient monitoring, workflow optimisation, education, patient safety, and research, though challenges persist around data interoperability, privacy, consent, and workforce readiness. Conclusion Digital twins offer transformative opportunities for nursing, requiring interdisciplinary collaboration, curriculum integration, and robust regulatory frameworks.","author":[{"family":"David-Olawade","given":"Aanuoluwapo"},{"family":"Fidelis","given":"Sandra"},{"family":"Popoola","given":"Mayowa"},{"family":"Osonuga","given":"Adewoyin"},{"family":"Egbon","given":"Eghosasere"},{"family":"Olawade","given":"David"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.ecns.2026.102028","URL":"https://doi.org/10.1016/j.ecns.2026.102028","source":"openalex"},{"id":"oa:W7119509082","type":"article-journal","title":"Digital Twin Modeling for Landslide Risk Scenarios in Mountainous Regions","abstract":"Background: Rainfall-induced landslides are a widespread and destructive geological hazard that resist precise prediction. They pose serious threats to human lives and property, ecological stability, and socioeconomic development. Methods: To address the challenges in mitigating rainfall-induced landslides in high-altitude mountainous regions, this study proposes a digital twin framework that couples multiple physical fields and is based on the spherical discrete element method. Results: Two-dimensional simulations identify a trapezoidal stress distribution with inward-increasing stress. The stress increases uniformly from 0 kPa at the surface to 210 kPa in the interior. The crest stress remains constant at 1.8 kPa under gravity, whereas the toe stress rises from 6.5 to 14.8 kPa with the slope gradient. While the stress pattern persists post-failure, specific magnitudes alter significantly. This study pioneers a three-dimensional close-packed spherical discrete element method, achieving enhanced computational efficiency and stability through streamlined contact mechanics. Conclusions: The proposed framework utilizes point-contact mechanics to simplify friction modeling, enhancing computational efficiency and numerical stability. By integrating stress, rainfall, and seepage fields, we establish a coupled hydro-mechanical model that enables real-time digital twin mapping of landslide evolution through dynamic parameter adjustments.","author":[{"family":"Li","given":"Lai"},{"family":"Tang","given":"Bo‐hui"},{"family":"Cai","given":"Fangliang"},{"family":"Wei","given":"Lei"},{"family":"Zhu","given":"Xinming"},{"family":"Fan","given":"Dong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/s26020421","URL":"https://doi.org/10.3390/s26020421","source":"openalex"},{"id":"oa:W7172260438","type":"article-journal","title":"Predicting Alzheimer progression using EEG-based digital twins","abstract":"Early and accurate prognosis of Alzheimer’s disease (AD) remains limited by current biomarkers, which are often invasive, require expensive equipment, or fail to predict individual trajectories of cognitive decline. In this study, we evaluated the Digital Alzheimer’s Disease Diagnosis (DADD) model, a digital twin framework that extracts neurodegeneration-related digital biomarkers from non-invasive recordings such as electroencephalography (EEG), mapping early functional neural alterations to latent parameters linked to structural AD mechanisms. DADD was applied to a cohort of 459 participants with Subjective Cognitive Decline (SCD) or Mild Cognitive Impairment (MCI), evaluating its performance against established AD biomarkers like APOE genotype, magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) markers in predicting prognostic outcomes over a 10-year follow-up. Digital biomarkers demonstrated strong prognostic value, predicting participants who converted at follow-up, significantly outperforming standard EEG metrics. They also robustly forecast both risk and timing of clinical conversion, matching the performance of established AD biomarkers and even outperforming them in SCD participants. Moreover, combining established AD biomarkers with digital biomarkers led to a significant increase in prognostic accuracy. DADD represents a robust clinical tool, enabling scalable, affordable, non-invasive AD detection and prognostic stratification across diverse clinical settings.","author":[{"family":"Amato","given":"Lorenzo"},{"family":"Scheijbeler","given":"Elliz"},{"family":"Nifterick","given":"Anne"},{"family":"Lassi","given":"Michael"},{"family":"Haan","given":"Willem"},{"family":"Gouw","given":"Alida"},{"family":"Mazzoni","given":"Alberto"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41746-026-02997-5","URL":"https://doi.org/10.1038/s41746-026-02997-5","source":"openalex"},{"id":"oa:W7148920120","type":"article-journal","title":"Abstract 4153: Advancing precision oncology through tumor digital twins: A versatile ViT-determined margin-consistent model for lung adenocarcinoma histopathologic subtyping in hematoxylin-eosin images","abstract":"Abstract Background: Digital twin frameworks in oncology require a stable, patient-specific histologic representation of tumor architecture. However, current LUAD subtyping models are vulnerable to stain and scanner variability, domain shift, and poor probability calibration. We investigate whether a state-space/Transformer hybrid with attention and margin-aware training can generate a robust, calibrated “morphology twin” suitable for integration into future tumor digital-twin systems. Methods: A uniform patch-aggregation WSI pipeline was implemented with identical tiling, Macenko normalization, augmentations, and optimization across all backbones. From 143 FFPE H&E WSIs in BMIRDS-LUAD, we extracted 203,226 tissue patches (224×224 at 20×). Patches were encoded using ResNet50/101, ViT-L, or a state-space/Transformer hybrid (MambaVision). Slide-level predictions were produced via gated-attention MIL and a linear classifier whose logit gaps define decision margins. Training employed cross-entropy combined with a supervised representation term, without handcrafted harmonization or test-time adaptation. Internal development used a WSI-stratified split across five LUAD growth patterns. Zero-shot external evaluation used WSSS4LUAD. Endpoints included accuracy, subtype-specific AUC, feature-margin concordance, internal-to-external performance drop, calibration (ECE/Brier), and run-to-run variability across 10 seeds. Results: On BMIRDS-LUAD, MambaVision+attention achieved 96.40±3.32% accuracy with ROC-AUC ≥0.99 across all subtypes and strong feature-margin alignment (τ=0.88 train / 0.64 validation). Errors were largely confined to mixed-pattern or low-quality slides. Zero-shot transfer to WSSS4LUAD yielded 83.69±7.76% accuracy—the smallest performance drop (−12.71 points) among all backbones. Calibration improved in-site and out-of-site (ECE/Brier: 0.043/0.098 internal; 0.087/0.154 external), with statistically significant gains over ResNet and ViT baselines. Variability across seeds narrowed (3.32% vs 6.12% for ResNet50), indicating enhanced training stability. Conclusions: This framework addresses key LUAD subtyping failure modes—cross-site instability, overconfident boundary errors, and limited reproducibility. By integrating state-space modeling, Transformer attention, and margin-consistent learning, it produces a calibrated morphology twin that preserves subtype discriminability under domain shift and provides more trustworthy WSI-derived probabilities. While not a complete cancer digital twin, it forms a robust histologic module for integration into next-generation multimodal and temporal LUAD digital-twin systems. Citation Format: Meghdad Sabouri Rad, Mohammad Mehdi Hosseini, Muhammad Hassaan Khalid, Saverio J. Carello, Michel R. Nasr, Rossana Kazemimood, Ola El-Zammar, Bardia Rodd. Advancing precision oncology through tumor digital twins: A versatile ViT-determined margin-consistent model for lung adenocarcinoma histopathologic subtyping in hematoxylin-eosin images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4153.","author":[{"family":"Rad","given":"Meghdad"},{"family":"Hosseini","given":"Mohammad"},{"family":"Khalid","given":"Muhammad"},{"family":"Carello","given":"Saverio"},{"family":"Nasr","given":"Michel"},{"family":"Kazemimood","given":"Rossana"},{"family":"El-Zammar","given":"Ola"},{"family":"Rodd","given":"Bardia"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1158/1538-7445.am2026-4153","URL":"https://doi.org/10.1158/1538-7445.am2026-4153","source":"openalex"},{"id":"oa:W7140221496","type":"article-journal","title":"A Solution for Heritage Monitoring Based on Wireless Low-Cost Sensors and BIM: Application to the Monserrate Palace","abstract":"Conservation and management of built cultural heritage require multidisciplinary approaches and reliable information to support decision-making. In this context, digital transformation strategies that combine Building Information Modeling (BIM) with monitoring technologies offer significant potential to improve heritage management. This paper presents a monitoring solution based on a wireless network of low-cost Internet of Things (IoT) sensors integrated within a Heritage Building Information Model (HBIM), applied to Monserrate Palace in Sintra, Portugal. The proposed approach covers all implementation stages, including HBIM development from as-built data collection, deployment of a wireless monitoring network for acceleration and environmental parameters, and integration of monitoring data into a BIM-based platform. The system aims to create a Digital Shadow of the building as a step towards a Digital Twin framework, enabling centralized visualization and management of structural and environmental information through the HBIM model and dedicated dashboards. Given the lower accuracy of low-cost sensors, in situ calibration with reference equipment was conducted to validate the recorded data. Implementing monitoring systems in heritage contexts presents challenges, such as limited historical documentation and the need for minimally invasive interventions. Despite these constraints, the proposed solution demonstrates the advantages of integrating monitoring data within HBIM, enabling centralized data management and improved understanding of building performance and conservation needs.","author":[{"family":"Machete","given":"Rita"},{"family":"Dias","given":"Fábio"},{"family":"Caetano","given":"Diogo"},{"family":"Falcão","given":"Ana"},{"family":"Gomes","given":"MG"},{"family":"Bento","given":"Rita"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/s26072015","URL":"https://doi.org/10.3390/s26072015","source":"openalex"},{"id":"oa:W7140083543","type":"article-journal","title":"Integrated Management of the Urban Water Cycle: A Synthesis of Impacts and Solutions from Source to Tap","abstract":"Urbanization fundamentally fractures the natural water cycle, leading to a cascade of interconnected problems including increased flood risk, degraded water quality, stressed groundwater resources, and inefficient distribution networks. Traditional, fragmented management approaches that address these issues in isolation have proven inadequate. This research argues for a paradigm shift towards an Integrated Urban Water Management (IUWM) framework anchored in the concept of the “river-aquifer-pipe network continuum”, treating these components as a single, dynamic hydrological and infrastructural entity. Drawing upon a series of detailed case studies from Eastern Romania, this paper synthesizes the systemic impacts of development across the entire urban water system. Evidence from the Prut, Olt, and Bahlui river basins demonstrate how channelization exacerbates flood peaks and leads to severe biochemical degradation. Hydrogeological modeling of the Gherăești-Bacău wellfield reveals the vulnerabilities of over-extraction, while analysis of the Iași water network highlights the challenge of water losses in the aging infrastructure. In response, a modern, multi-tool approach is consolidated into a practical, three-stage framework for action: Diagnose, Prescribe, and Optimize. This framework advocates for (1) a comprehensive diagnosis using a suite of predictive numerical models (a “digital twin”); (2) the prescription of foundational, nature-based solutions, such as floodplain restoration, to heal core ecological functions; and (3) the continuous optimization of engineered infrastructure using smart, real-time control technologies. The synthesis concludes that an integrated, data-driven, and collaborative approach is the only sustainable path forward. Future research should focus on formally coupling these diagnostic models to create true Digital Twins of urban water systems—an essential step towards building resilient, water-secure cities for the 21st century.","author":[{"family":"Marcoie","given":"Nicolae"},{"family":"Iliesi","given":"Elena"},{"family":"Barta","given":"Andras"},{"family":"Rabosapca","given":"Irina"},{"family":"Toma","given":"D"},{"family":"Boboc","given":"Valentin"},{"family":"Balan","given":"Cătălin"},{"family":"Tofanica","given":"Bogdan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/urbansci10030175","URL":"https://doi.org/10.3390/urbansci10030175","source":"openalex"},{"id":"oa:W4415970620","type":"article-journal","title":"APPLICATION OF A DIGITAL TWIN FOR OPTIMIZING THE PERFORMANCE OF AN SLM 3D PRINTER","abstract":"This paper presents the development and experimental validation of a digital twin for a selective laser melting (SLM) system designed for operation under constrained technical conditions. The proposed design includes a custom-built powder feeding and leveling mechanism, along with a telemetry module enabling realtime acquisition and analysis of thermal data. The digital twin is implemented as an integrated model that combines thermomechanical analysis, G-code execution, and corrective control of printing parameters. The mathematical foundation is based on the transient heat conduction equation with a volumetric heat source and a Gaussian distribution of laser power density.An experimental setup employing pyrometers and thermocouples in the melt zone was used to validate the model. The comparison of simulated and measured data showed a mean absolute error of less than 2.5 °C. The application of the digital twin resulted in a 12–15% reduction in residual stresses, as confirmed by X-ray diffraction analysis. The developed system demonstrates high efficiency in predictive quality control and can be integrated into adaptive control loops. The approach aligns with the Industry 4.0 concept, offering increased stability, repeatability, and reliability in SLM processes","author":[{"family":"Zhantlesov","given":"Zh"},{"family":"Altynbek","given":"Serik"},{"family":"Musabayev","given":"A"}],"issued":{"date-parts":[[2025]]},"DOI":"10.53360/2788-7995-2025-3(19)-9","URL":"https://doi.org/10.53360/2788-7995-2025-3(19)-9","source":"openalex"},{"id":"oa:W7201884303","type":"article-journal","title":"A Systematic Review of IoT-Enabled Predictive Drying for Arabica Coffee: Toward a Python-Based Digital Twin Framework for the Gayo Highlands, Aceh Tengah, Indonesia","abstract":"Post-harvest drying is the single most decisive determinant of Arabica coffee quality, yet in the Gayo Highlands of Aceh Tengah (950 - 1,650 m.a.s.l.) it remains an experience based, weather dependent operation conducted largely on tarpaulins and open patios. High relative humidity, frequent rainfall, and low ambient temperature routinely prolong drying beyond ten days, produce non uniform final moisture content, and expose parchment to fungal colonisation and ochratoxin risk, causing smallholders to fail the 12.5% maximum moisture threshold of SNI 01-2907-2008 and to forfeit specialty price premiums. This systematic literature review, conducted following PRISMA guidelines on peer reviewed publications from 2019–2026, synthesises three research streams that have so far evolved in isolation: (i) thin layer drying kinetics of parchment coffee, (ii) Internet of Things (IoT) architectures for solar and hybrid dryers, and (iii) digital twin methodology in food and grain drying. The review finds that existing coffee drying IoT deployments are overwhelmingly reactive while validated kinetic models (modified Midilli, Page) capable of such prediction remain confined to laboratory dryers and are never coupled to field sensor streams. Digital twin research in drying has concentrated on grain and fruit, leaving coffee, and highland smallholder contexts in particular, unaddressed. From this synthesis the review derives seven research gaps and proposes SIKOPI-DT, a contextualised five layer Python based digital twin framework in which a modified Midilli kinetic core is continuously reparameterised by low cost IoT sensors (ESP32, SHT31, load cell) to forecast the time to target moisture content and to drive predictive supplementary-heat control under Gayo weather scenarios. Synthesised evidence indicates that such a system can plausibly reduce drying time by 30–50%, cut specific energy consumption by 15–30%, and improve moisture uniformity relative to open-sun practice. A three phase experimental validation roadmap and a smallholder economic feasibility analysis are presented, positioning this review as the theoretical foundation for a physical prototype in Aceh Tengah.","author":[{"family":"Ihsan","given":"Muhammad"},{"family":"Susanto","given":"H"},{"family":"Fitriadi","given":"Nuzuli"}],"issued":{"date-parts":[[2026]]},"DOI":"10.31572/inotera.vol11.iss2.2026.id721","URL":"https://doi.org/10.31572/inotera.vol11.iss2.2026.id721","source":"openalex"},{"id":"oa:W7203720265","type":"article-journal","title":"Digital Twin-Driven TD3-CPER Control for Continuous Casting","abstract":"Continuous casting is a key process in intelligent steel manufacturing, and mold level control directly affects slab quality and production stability. However, strong nonlinearity, multivariable coupling, time delays, and operating disturbances make real-time control optimization challenging for conventional control strategies. To address this problem, this paper proposes a digital twin-driven reinforcement learning control method based on Twin Delayed Deep Deterministic Policy Gradient with Composite Prioritized Experience Replay, termed TD3-CPER. A data-driven digital twin environment is constructed using real production data to support closed-loop policy training and evaluation. In TD3-CPER, the replay mechanism integrates temporal-difference error, reward feedback, replay frequency, and K-Medoids clustering to improve sample utilization and training stability. Simulation results show that TD3-CPER increases the number of Grade I slabs by 56.2% compared with manual control and achieves a 14.7% higher average cumulative reward than the strongest baseline reinforcement learning method. These results suggest that TD3-CPER is a feasible approach for quality-oriented control optimization in continuous casting.","author":[{"family":"Qiu","given":"Quanhui"},{"family":"Wang","given":"Sen"},{"family":"Zheng","given":"Jiacheng"},{"family":"Ning","given":"Dejun"}],"issued":{"date-parts":[[2026]]},"DOI":"10.70114/acmsr.2026.8.1.p97","URL":"https://doi.org/10.70114/acmsr.2026.8.1.p97","source":"openalex"},{"id":"oa:W7168952585","type":"article-journal","title":"Machine Learning for Concrete Performance Prediction and Intelligent Optimization: A Comprehensive Review","abstract":"With the rapid development of artificial intelligence (AI) technologies, machine learning (ML) has been widely applied in concrete material design, performance prediction, and intelligent structural engineering. Compared with traditional empirical approaches, ML can efficiently establish complex nonlinear relationships among concrete mix proportions, environmental factors, and performance indicators, thereby improving prediction efficiency, reducing experimental costs, and enabling multi-objective optimization of mix proportions. This paper systematically reviews the recent research progress of ML technologies in the field of concrete engineering, with particular emphasis on typical algorithms, including supervised learning, unsupervised learning, and reinforcement learning. Their applications in predicting workability, mechanical properties, durability performance, and mix proportion optimization are comprehensively summarized. In addition, recent advances in ML applications for crack detection and digital twin technologies are also discussed. Moreover, deep learning and computer vision (CV) technologies have significantly promoted the development of crack identification and structural health monitoring, whereas the integration of digital twin and Internet of Things (IoT) technologies has further expanded the application of ML in smart infrastructure. Finally, the current challenges associated with data quality, model interpretability, and engineering applications are summarized, and future research directions are discussed. Overall, by linking algorithm choice to specific concrete performance-prediction tasks, this review clarifies the conditions under which ML delivers reliable results and provides a structured reference for both researchers and practitioners. The comparative analysis indicates that ensemble tree-based models—particularly random forest and gradient-boosting variants such as XGBoost—together with well-tuned neural networks consistently achieve the highest predictive accuracy across most concrete properties, with reported test-set coefficients of determination commonly between 0.90 and 0.99, whereas limited data availability, inconsistent validation protocols, and restricted model interpretability remain the principal obstacles to engineering deployment.","author":[{"family":"Hu","given":"Keqing"},{"family":"Yang","given":"Yi"},{"family":"Wang","given":"Yanfeng"},{"family":"Zhang","given":"J"},{"family":"Liu","given":"Ying"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/buildings16142806","URL":"https://doi.org/10.3390/buildings16142806","source":"openalex"},{"id":"oa:W7167357378","type":"article-journal","title":"Automatic 3D Building Model Generation for Energy Digital Twins","abstract":"Abstract. Digital Twins in the Architecture, Engineering, and Construction (AEC) domain support monitoring, simulation, and increasing levels of automation in building management across scales. Energy Digital Twins are particularly demanding, requiring (i) simulation-grade geometry and (ii) persistent topology and semantics across monitoring- and scenario-driven updates. This paper proposes a unified multi-representation EDT in which (i) a watertight, solid, and (ii) a topology-preserving B-Rep are co-maintained through a mapping layer that preserves object identity and links geometry to a typed property graph. Building on this, the presented Scan-to-Energy Digital Twin pipeline converts raw point clouds into multi-level EDT instances by integrating Scan-to-BIM reconstruction, topological modelling, semantic enrichment and parser–transformer–writer interoperability modules. The graph-backed EDT enables reversible export to epJSON and gbXML (optionally IFC), supporting scenario-based EnergyPlus simulations and incremental retrofit updates, such as insulation thickness and window thermal transmittance value changes. Validation on a set of four buildings achieves 0.86–0.89 mAPv and schema-valid exports, demonstrating the effectiveness of our end-to-end approach for interoperable energy analysis, monitoring, and operational decision support.","author":[{"family":"Roman","given":"OV"},{"family":"Agugiaro","given":"Giorgio"},{"family":"Ohori","given":"Ken"},{"family":"Bassier","given":"Maarten"},{"family":"Farella","given":"Elisa"},{"family":"Remondino","given":"Fabio"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-annals-xi-1-2026-447-2026","URL":"https://doi.org/10.5194/isprs-annals-xi-1-2026-447-2026","source":"openalex"},{"id":"oa:W7172526691","type":"article-journal","title":"Bayesian updating with SC-MCMC for PMSM digital twin models","abstract":"The fidelity of permanent magnet synchronous motor (PMSM) digital twins tends to degrade during operation due to system non-stationarity, which arises from time-varying operating conditions, parameter drift, and environmental disturbances. This degradation significantly limits their effectiveness in predictive maintenance and intelligent operation. This paper presents a chain-splitting self-correcting Markov chain Monte Carlo (SC-MCMC) method for autonomous Bayesian updating of PMSM digital twins. The method employs a residual-variance-driven auxiliary chain to explore inefficient sampling regions and adaptively correct the main chain’s proposal distribution, enhancing sampling efficiency and posterior convergence. A physics-driven PMSM digital twin is constructed by integrating finite element analysis with eddy-current-equivalent reduced-order modelling. Sobol global sensitivity analysis identifies key parameters, incorporated into a Bayesian framework for online updating. Experimental results show the updated digital twin significantly improves phase current prediction, reducing root-mean-square and mean absolute errors by 48.65% and 44.65%, respectively, providing a practical solution for high-fidelity modelling and predictive operation in smart manufacturing.","author":[{"family":"Xu","given":"Haibo"},{"family":"Yang","given":"Zhibin"},{"family":"Qin","given":"Xiaogang"},{"family":"An","given":"Weizheng"},{"family":"Yan","given":"Xiajing"},{"family":"Duan","given":"Lixiang"},{"family":"Wang","given":"Jinjiang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/27525783.2026.2701580","URL":"https://doi.org/10.1080/27525783.2026.2701580","source":"openalex"},{"id":"oa:W7125830663","type":"article-journal","title":"Equ-Axed Fine-Grained and Nanotwinned Cu with Ultrahigh Tensile Strength","abstract":"High Resolution Image Download MS PowerPoint Slide In this study, the Electroplating parameters were systematically tuned to transform Cu microstructures from columnar grains into equ-axed fine grains with high-density nanotwins. The optimized electroplating parameters (0.5 M [Cu 2+ ], 49.13 ppm [Cl – ], 10 °C plating temperature, and 7.11 A/dm 2 (ASD) current density) yielded an average grain size of 0.16 μm and twin spacing of 31.7 nm. These microstructural features enabled a tensile strength of 737.5 ± 7.1 MPa in the as-deposited state and up to 828.6 ± 9.2 MPa after annealing at 100 °C for 2 h, while maintaining 70% conductivity. The complex systems response (CSR) platform served as an auxiliary multivariate optimization tool to locate the process window efficiently. By achieving simultaneous enhancement of ultimate tensile strength, this work provides practical guidance for tailoring nanostructured Cu films and foils for printed circuit boards and advanced interconnects.","author":[{"family":"Ke","given":"Chun"},{"family":"Lee","given":"Kang"},{"family":"Tran","given":"Dinh"},{"family":"Chen","given":"Wen"},{"family":"Yao","given":"Da"},{"family":"Chen","given":"Chih"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1021/acs.cgd.5c01359","URL":"https://doi.org/10.1021/acs.cgd.5c01359","source":"openalex"},{"id":"oa:W7172019824","type":"article-journal","title":"Digital twin for coastal cities: an evaluation from a stakeholder perspective","abstract":"Improving community resilience requires innovative approaches to developing adaptation strategies. The European Union has supported this process through several initiatives focusing on nature-based solutions (NBSs), digital technologies, and promoting co-creation. The Smart Control of the Climate Resilience in European Coastal Cities (SCORE) project, funded by the EU Horizon 2020 program, focused on improving the resilience of coastal cities by promoting new digital tools such as digital twins, citizen science sensing, NBS, and co-creation activities engaging citizens and stakeholders in the design, development, and evaluation of NBS-based resilience solutions. SCORE developed a digital twin for three cutting-edge cities: Massa in Italy, and Vilanova i la Geltrù and Oarsoaldea in Spain, the first two on the Mediterranean coast, and the second in the Basque region on the Atlantic Ocean. The digital twin aims to support both the co-design of NBSs to effectively reduce flood risk and the management of flood-related emergencies by providing a clear representation of scenarios obtained from real-time sensors and short-term forecasts. This article reports and evaluates the co-creation process carried out in these cutting-edge cities following the living lab approach, with particular attention to the usability, utility, and expected impact of these new technologies within an effective climate change resilience strategy.","author":[{"family":"Baldini","given":"Luca"},{"family":"Paranunzio","given":"Roberta"},{"family":"Adirosi","given":"Elisa"},{"family":"Carlini","given":"Beatrice"},{"family":"Serafino","given":"Giovanni"},{"family":"Scognamiglio","given":"Giovanni"},{"family":"Vaccaro","given":"Attilio"},{"family":"Borklund","given":"Casey"},{"family":"Caruso","given":"Rochelle"},{"family":"Binaglia","given":"Federico"},{"family":"Riera-Spiegelhalder","given":"Mar"},{"family":"Arroyo","given":"Ester"},{"family":"Soloaga","given":"Sara"},{"family":"Iglesias","given":"Juan"},{"family":"Sesma","given":"Xabier"},{"family":"Gharbia","given":"Salem"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/29931495.2026.2702755","URL":"https://doi.org/10.1080/29931495.2026.2702755","source":"openalex"},{"id":"oa:W7154762820","type":"article-journal","title":"Defects in Modular Building Construction: A Systematic Lifecycle Review and Implications for Sustainable Delivery","abstract":"Despite its potential to enhance construction quality, efficiency, and sustainability, modular construction continues to experience defects that hinder its broader adoption. Understanding and mitigating defects is essential for maximising the sustainability benefits of modular construction by reducing material waste, minimising rework and improving lifecycle performance. Existing research remains fragmented, with limited synthesis integrating defects with their root causes across the project lifecycle. To address this gap, this study investigates defect types, lifecycle-based causes, and mitigation strategies in modular building projects through a PRISMA-guided systematic literature review of 61 peer-reviewed journal articles published between 2015 and 2025 and retrieved from Scopus and Web of Science. Six major defect categories were identified: geometric and dimensional; material and component; joint and connection integrity; envelope performance and durability; structural; and mechanical, electrical, and plumbing (MEP) defects, with geometric and dimensional defects emerging as the most prevalent, accounting for 26.7% of reported cases. Lifecycle root-cause mapping indicates that poor workmanship during on-site assembly is the dominant contributor, accounting for 44.1% of identified root causes, with manufacturing errors (26.8%) and design limitations (13.4%) acting as critical upstream sources. Mitigation strategies cluster into three groups: general recommendations (39% of reported strategies), mainly focusing on low-cost organisational measures such as logistics coordination and workforce training; structured risk-management frameworks (9.1%), including assembly sequencing and tolerance planning; and digital and data-driven technologies (51.9%), such as laser scanning, AI-based inspection, and digital twins, enabling proactive quality assurance across the lifecycle. The study proposes an integrated lifecycle–defect–mitigation framework to strengthen quality governance and advance sustainable modular delivery.","author":[{"family":"Gurmu","given":"Argaw"},{"family":"Tafti","given":"Fatemeh"},{"family":"Mills","given":"Anthony"},{"family":"Kite","given":"John"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18084000","URL":"https://doi.org/10.3390/su18084000","source":"openalex"},{"id":"oa:W7127176751","type":"article-journal","title":"Living Materials: Preserving Student Innovation in Art and Science through Digital Twins and AI in Partnership with Qatar National Library : What Happens To Your Work After You Graduate?","abstract":"Presentation was part of the Karak Hour Workshop at the Virginia Commonwealth University School of the Arts in Qatar (VCUarts), Doha (Qatar) – 14th of January 2026.This presentation documents a Manara – Qatar Research Repository a Qatar National Library outreach and training session delivered to Virginia Commonwealth University School of the Arts in Qatar (VCUarts) and Hamad Bin Khalifa University (HBKU) students as part of the Living Materials : Preserving Student Innovation in Art and Science Through Digital Twins and AI in Partnership with Qatar National Library, funded under the Qatar Research, Development, and Innovation Council (QRDI) Multiversity Grants Programme (2025-2026).The session addresses a critical but often overlooked question facing graduating students: what happens to creative and research work after graduation? Drawing on real-world examples from art, design, and engineering education, the presentation explores how student projects – particularly material-based, practice-led, and process-driven work are frequently lost due to physical disposal, fragile storage practices, platform dependency, and digital obsolescence.The presentation introduces key concepts in long-term digital curation, including the value of preserving process data alongside final outputs, the limitations of commercial cloud storage, and the role of trusted research repositories in ensuring long-term access, attribution, and reuse. It highlights Manara – Qatar Research Repository, as a platform that enables students to publish creative and research outputs with persistent identifiers (DOIs), appropriate licensing, and active digital preservation supported by Qatar National Library.Through practical guidance on file organisation, copyright and licensing, discoverability, and research visibility, the session demonstrates how students can take control of their digital legacy, enhance employability, and contribute to Qatar’s national knowledge infrastructure. The presentation also situates student work within a broader global research ecosystem, emphasizing citability, verification, and long-term impact in an era increasingly shaped by AI-generated content.This resource is intended for students, educators, librarians, and institutions interested in sustainable models for preserving student innovation, practice-led research, and interdisciplinary creative outputs.Other InformationLicense: http://creativecommons.org/licenses/by/4.0/ See Qatar Research, Development, and Innovation Council (QRDI-C) – Qatar Foundation (QF): Multiversity Grant Project 2025-2026 information on the funder's website: https://www.qf.org.qa/stories/ideas-united-qatar-foundations-multiversity-grants-drive-cross-university","author":[{"family":"Shaon","given":"Arif"},{"family":"Ebrahim","given":"Ya'qub"},{"family":"Cantor","given":"Jennifer"},{"family":"Blatnik","given":"Alenka"}],"issued":{"date-parts":[[2026]]},"DOI":"10.57945/manara.qnl.31122955.v1","URL":"https://doi.org/10.57945/manara.qnl.31122955.v1","source":"openalex"},{"id":"oa:W7203492511","type":"article-journal","title":"Digital modeling of production processes based on Digital Twin technology in the conditions of transition to Industry 5.0","abstract":"The digital transformation of industry, which is taking place in the context of the transition to the Industry 5.0 concept, highlights the need to implement modern digital technologies to increase the efficiency of production processes. One of the most promising digitalization tools is Digital Twin technology, which ensures the integration of physical and virtual production systems, creates the prerequisites for forecasting, optimizing production and supporting management decision-making. The purpose of the study is to substantiate the comprehensive application of digital modeling of production processes using Digital Twin technology in combination with Internet of Things, artificial intelligence, Big Data and corporate information systems ERP and MES to increase the efficiency of industrial enterprises in the context of the implementation of the Industry 5.0 concept. The work uses the methods of system analysis, generalization, comparative analysis, structural and logical modeling, analysis of scientific sources, as well as conceptual modeling of digital production systems. It has been established that the digitalization of production is based on the integrated use of Internet of Things technologies, cloud computing, big data, artificial intelligence, digital twins, robotic automation, modern information management systems and other digital solutions, the synergistic combination of which forms an integrated digital production environment. The use of Digital Twin technology provides real-time modeling of production processes, forecasting the technical condition of equipment, optimizing the use of production resources, reducing production costs, minimizing downtime, increasing productivity, product quality, flexibility and adaptability of production systems. A conceptual model of digital modeling of production processes based on Digital Twin technology has been substantiated, which integrates physical production, digital infrastructure of the enterprise, corporate information systems ERP, MES, WMS, APS, Internet of Things technologies, Big Data, artificial intelligence and a management decision support system, ensuring comprehensive optimization of the functioning of production enterprises. The integrated use of Digital Twin technology in combination with modern digital technologies creates a technological foundation for implementing the principles of Industry 5.0, increasing the efficiency of production processes, the competitiveness of industrial enterprises, their innovative development, resource efficiency, and sustainable operation.","author":[{"family":"Lipych","given":"Lubоv"},{"family":"Хілуха","given":"Оксана"},{"family":"Kushnіr","given":"Myroslаvа"},{"family":"Lipych","given":"Liubov"},{"family":"Khilukha","given":"Oksana"},{"family":"Kushnir","given":"Myroslava"}],"issued":{"date-parts":[[2026]]},"DOI":"10.66556/2663-0117.50.lipych-l","URL":"https://doi.org/10.66556/2663-0117.50.lipych-l","source":"openalex"},{"id":"oa:W7105693022","type":"article-journal","title":"Blue-Cloud 2026 Third Federation Workshop","abstract":"Blue-Cloud partners and collaborators gathered in Brussels from 5 to 7 November 2025 for a three-day series of strategic and technical sessions, anchored by the Third Federation Workshop. The event took place just after the EOSC Symposium, as Blue-Cloud is supporting the creation of a Thematic Node within the EOSC Federation under the name \"EOSC Node Digital Twin of the Ocean\". On 5th November afternoon, the event counted with two hands-on sessions exploring the EOSC Marine Node core and thematic services and cross-node use cases. These interactive demonstrations offered participants a closer look at the technical developments powering Blue-Cloud’s federated services. On 6th November, the Third Federation Workshop brought together project partners, EOSC stakeholders, and Synergy Projects for a full day of in-depth discussion and exchange. The agenda featured an opening overview of key takeaways from the EOSC Symposium, followed by a sequence of panel discussions covering core services, the connection between EOSC and EDITO, the practical challenges of building a federated approach, and capacity-building efforts. Official event page: https://blue-cloud.org/events/blue-cloud-2026-third-federation-workshop","author":[{"family":"Pittonet Gaiarin","given":"Sara"},{"family":"Meijer","given":"Jan"},{"family":"Wyns","given":"Roxanne"},{"family":"Reyes Suarez","given":"Nydia"},{"family":"Palermo","given":"Francesco"},{"family":"Simoncelli","given":"Simona"},{"family":"Nascimento Vitorino","given":"João"},{"family":"Mieruch","given":"Sebastian"},{"family":"Barde","given":"Julien"},{"family":"Pagano","given":"Pasquale"},{"family":"Assante","given":"Massimiliano"},{"family":"Kooyman","given":"Robin"},{"family":"Tedds","given":"Jonathan"},{"family":"Pesant","given":"Stéphane"},{"family":"Wichorowski","given":"Marcin"},{"family":"Rizzo","given":"Alessandro"},{"family":"Bodere","given":"Erwan"},{"family":"Delaney","given":"Conor"},{"family":"Tonani","given":"Marina"},{"family":"Vera","given":"Julia"},{"family":"Fooks","given":"Samuel"},{"family":"Costa","given":"Valentina"},{"family":"Irisson","given":"Jean"},{"family":"Vernet","given":"Marine"},{"family":"Dechenne","given":"Abel"},{"family":"Eparkhina","given":"Dina"},{"family":"Caccavale","given":"Mauro"},{"family":"Sarretta","given":"Alessandro"},{"family":"Janssens","given":"Laurence"},{"family":"Sharma","given":"Shreshtha"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5281/zenodo.17598617","URL":"https://doi.org/10.5281/zenodo.17598617","source":"openalex"},{"id":"oa:W7166714346","type":"article-journal","title":"Digital Twin Technology for Structural Lifecycle Management and Health Monitoring","abstract":"Digital twin (DT) technology is reshaping structural engineering by linking physical assets to dynamic and data-driven virtual counterparts. DTs enable monitoring, predictive analytics, and autonomous decisions across design, construction, operation, and maintenance. Additionally, DTs are updated with real-time streams continuously. This study focuses on the applications of DTs and the intersection between the Internet of Things (IoT), Building Information Modeling (BIM), and artificial intelligence (AI). Applications include structural health monitoring (SHM) and predictive maintenance for bridges and buildings, in addition to construction safety optimization and stewardship of architectural heritage. The paper also examines barriers to adoption, including data interoperability, cybersecurity, upfront cost, and workforce readiness, and discusses standardization needs. In addition, it highlights educational impacts and pathways for small and medium enterprises (SMEs) to adopt scalable DT solutions. By consolidating recent advances, the review shows how DTs can deliver more resilient, efficient, sustainable, and intelligent infrastructure and outlines the research priorities to overcome remaining gaps and fully realize their potential.","author":[{"family":"El-Sisi","given":"Alaa"},{"family":"Cabage","given":"John"},{"family":"Salem","given":"Elsayed"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/app16136524","URL":"https://doi.org/10.3390/app16136524","source":"openalex"},{"id":"oa:W7128532719","type":"article-journal","title":"Digital Twin based Visualization Framework for Computer System Monitoring","abstract":"ABSTRACT Digital Twins are increasingly adopted to enhance system understanding, monitoring, and decision-making across various domains. However, many existing approaches focus on large-scale industrial systems, making them complex and unsuitable for early-stage academic or educational environments. This paper presents a simplified Digital Twin– based visualization framework for monitoring a computer system within an academic laboratory context. The proposed approach integrates a 3D virtual model with live system performance data to provide intuitive visualization and basic monitoring capabilities. The framework demonstrates how Digital Twin concepts can be introduced at a small scale, serving as a foundation for future real-time and large- scale implementations.","author":[{"family":"Ramesh","given":"Harieesh"},{"family":"Divya","given":"M"},{"family":"Jk","given":"Srinath"}],"issued":{"date-parts":[[2026]]},"DOI":"10.55041/ijsrem56424","URL":"https://doi.org/10.55041/ijsrem56424","source":"openalex"},{"id":"oa:W7172381300","type":"article-journal","title":"A Multi-Dimensional Digital Twin Framework for the Low-Altitude Economy","abstract":"Abstract. The Low-Altitude Economy (LAE), driven by the widespread deployment of UAVs and eVTOL aircraft, demands a high-fidelity Digital Twin that extends far beyond static geographic representation. This study presents a critical review of 39 peer-reviewed papers to propose a three-layer mapping framework — Geospatial Infrastructure Layer, Environmental Sensing Layer, and Interaction Layer — and evaluates the Technology Readiness Level (TRL) of each sub-domain. The Geospatial Infrastructure Layer encompasses terrain models, ground facilities, airspace structures, and semantic navigation landmarks. The Environmental Sensing Layer covers electromagnetic modeling, target sensing and countermeasure, and micro-meteorological mapping. The Interaction Layer addresses network trust, data security, swarm coordination, and platform reliability. Our TRL assessment reveals that Environmental Sensing is the most mature layer (mean TRL 4.4, 8 field-validated papers), while cross-layer integration remains the weakest link (mean TRL 3.5, zero field-validated demonstrations). We identify standardization of low-altitude spatial data products, AI-enabled predictive mapping, crowdsourced Digital Twin updating, and closed-loop cross-layer integration as the four priority research directions.","author":[{"family":"Li","given":"Yan"},{"family":"Ye","given":"Chenming"},{"family":"Shi","given":"Wenxuan"},{"family":"Zhang","given":"Wenqing"},{"family":"Zhang","given":"Yuyang"},{"family":"Hu","given":"Teng"},{"family":"Kang","given":"Zhizhong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-archives-xlix-b4-2026-391-2026","URL":"https://doi.org/10.5194/isprs-archives-xlix-b4-2026-391-2026","source":"openalex"},{"id":"oa:W7134925157","type":"article-journal","title":"Broadband multi-beam lens-assisted mmID enabling multi-gigabit backscatter data rates for next-generation wireless networks","abstract":"Abstract The growth of next-generation Internet-of-Things (IoT) and digital-twin systems has created wireless environments where identification must sustain fiber-level data rates with low latency while operating at minimal energy cost and maintaining robust angular coverage. Conventional backscatter at microwave frequencies remains limited to megabit rates, and most millimeter-wave demonstrations operate with limited coverage. This work presents a lens-assisted millimeter-wave identification (mmID) system that unites multi-gigabit connectivity with wide solid-angle coverage. The design integrates a cross-polarized broadband antenna array with a dielectric lens, enabling multi-beam operation with angle-dependent modulation across ± 55° and a peak differential radar cross section of -13.4 dBsm. Demonstrated backscatter performance includes 4 Gbps 32-QAM at 5 m with an energy cost of 0.08 pJ bit −1 and 1 Gbps operation over 20 m. Link-budget analysis projects 1 Gbps backscatter ranges up to 2.6 km under the 75 dBm EIRP permitted in 5G millimeter-wave systems, establishing an energy-efficient pathway for high-capacity, long-range wireless identification.","author":[{"family":"Joshi","given":"Marvin"},{"family":"Lynch","given":"Charles"},{"family":"Hu","given":"Kexin"},{"family":"Mensah","given":"Yaw"},{"family":"Cressler","given":"John"},{"family":"Tentzeris","given":"Manos"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41467-026-70454-8","URL":"https://doi.org/10.1038/s41467-026-70454-8","source":"openalex"},{"id":"oa:W7154474231","type":"article-journal","title":"Pathways to social–ecological indicators in the era of Digital Twins of the Earth","abstract":"Effective ecosystem-based management strategies that prevent further degradation of the ecosystem state and negative impacts on societies are needed but require cross-disciplinary and complex understandings of social–ecological systems (SES). This study defines, evaluates, and operationalises the concept of social–ecological (SE) indicators using the butterfly model based on the DAPSI(W)R(M) framework, linking drivers, activities, pressures, state changes, impacts on human welfare, and responses as measures. A review of 148 indicators developed under the marine strategy framework directive (MSFD), including contributions from HELCOM, OSPAR, the European Environment Agency, and marine-relevant UN sustainable development goals (SDGs), was conducted. Indicators were assessed across four key dimensions: mapping along the DAPSI(W)R(M) cause-effect chain; indicator complexity; normative basis; and the relationship between the indicator and its indicandum. Based on the analysis and a literature study, an SE indicator definition was developed requiring SE indicators to be compound or explicitly connect the ecological and social dimensions. Only nine of the analysed indicators qualify as SE indicators by making traceable connexions across both dimensions of the butterfly model. Existing compound indices, such as the ocean health index (OHI) and its regional adaptation, the Baltic health index (BHI), illustrate how nested, goal-oriented indices can operationalise SE integration while also highlighting challenges related to transparency and aggregation due to their nested nature. Pathways for adapting existing non-SE indicators into SE indicators are outlined, drawing on ongoing work in the SEADITO project (2024–2027) that develops SE modelling tools for the European Digital Twin of the Ocean (EU DTO). To enable compound SE indicators and support implementation within emerging digital twins of the earth, such as the EU DTO, additional criteria for SE indicators are proposed, consisting of the addition of crosscutting interlinkages and digital readiness, respectively, in addition to existing criteria of measurability, sensitivity, specificity, scalability, transferability, and precision. By clarifying what makes an indicator SE and identifying concrete development pathways, this study advances the methodological foundation for integrating SES analysis into marine spatial planning and ecosystem-based management in an era in which digital twins of the earth are accelerating the digital infrastructure for SES.","author":[{"family":"Armoškaitė","given":"Aurelija"},{"family":"Bonnevie","given":"Ida"},{"family":"Depellegrin","given":"Daniel"},{"family":"Cabanillas","given":"Alejandra"},{"family":"Bellon","given":"Giulia"},{"family":"Kastanidi","given":"Erasmia"},{"family":"Neukirch","given":"Maik"},{"family":"Thenen","given":"Miriam"},{"family":"Jimenez","given":"Astrid"},{"family":"Schrøder","given":"Lise"},{"family":"Socrate","given":"Juliana"},{"family":"Strāķe","given":"Solvita"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/focsu.2026.1767068","URL":"https://doi.org/10.3389/focsu.2026.1767068","source":"openalex"},{"id":"oa:W7127118254","type":"article-journal","title":"Living Materials: Preserving Student Innovation in Art and Science through Digital Twins and AI in Partnership with Qatar National Library : What Happens To Your Work After You Graduate?","abstract":"Presentation was part of the Karak Hour Workshop at the Virginia Commonwealth University School of the Arts in Qatar (VCUarts), Doha (Qatar) – 14th of January 2026.This presentation documents a Manara – Qatar Research Repository a Qatar National Library outreach and training session delivered to Virginia Commonwealth University School of the Arts in Qatar (VCUarts) and Hamad Bin Khalifa University (HBKU) students as part of the Living Materials : Preserving Student Innovation in Art and Science Through Digital Twins and AI in Partnership with Qatar National Library, funded under the Qatar Research, Development, and Innovation Council (QRDI) Multiversity Grants Programme (2025-2026).The session addresses a critical but often overlooked question facing graduating students: what happens to creative and research work after graduation? Drawing on real-world examples from art, design, and engineering education, the presentation explores how student projects – particularly material-based, practice-led, and process-driven work are frequently lost due to physical disposal, fragile storage practices, platform dependency, and digital obsolescence.The presentation introduces key concepts in long-term digital curation, including the value of preserving process data alongside final outputs, the limitations of commercial cloud storage, and the role of trusted research repositories in ensuring long-term access, attribution, and reuse. It highlights Manara – Qatar Research Repository, as a platform that enables students to publish creative and research outputs with persistent identifiers (DOIs), appropriate licensing, and active digital preservation supported by Qatar National Library.Through practical guidance on file organisation, copyright and licensing, discoverability, and research visibility, the session demonstrates how students can take control of their digital legacy, enhance employability, and contribute to Qatar’s national knowledge infrastructure. The presentation also situates student work within a broader global research ecosystem, emphasizing citability, verification, and long-term impact in an era increasingly shaped by AI-generated content.This resource is intended for students, educators, librarians, and institutions interested in sustainable models for preserving student innovation, practice-led research, and interdisciplinary creative outputs.Other InformationLicense: http://creativecommons.org/licenses/by/4.0/ See Qatar Research, Development, and Innovation Council (QRDI-C) – Qatar Foundation (QF): Multiversity Grant Project 2025-2026 information on the funder's website: https://www.qf.org.qa/stories/ideas-united-qatar-foundations-multiversity-grants-drive-cross-university","author":[{"family":"Shaon","given":"Arif"},{"family":"Ebrahim","given":"Ya'qub"},{"family":"Cantor","given":"Jennifer"},{"family":"Blatnik","given":"Alenka"}],"issued":{"date-parts":[[2026]]},"DOI":"10.57945/manara.qnl.31122955","URL":"https://doi.org/10.57945/manara.qnl.31122955","source":"openalex"},{"id":"oa:W7141496497","type":"article-journal","title":"Relationships between three-dimensional fibrosis distribution, atrial adiposity, and voltage abnormalities associated with persistent atrial fibrillation","abstract":"AIMS: Persistent atrial fibrillation (PsAF) is often refractory to pulmonary vein isolation, a well-established AF treatment, owing to the fibrosis-remodelled substrates sustaining re-entries. Three-dimensional fibrosis distribution and atrial adiposity have been found to be essential contributors to PsAF arrhythmogenesis. We aimed to utilize late gadolinium enhancement (LGE)-MRI-derived personalized heart digital twins (DTs)-a recent promising tool for non-invasively assessing patient arrhythmogenesis-as well as contrast-enhanced cardiac computed tomography (CCT) images and electroanatomic maps (EAMs) to investigate relationships between fibrosis distribution, including endo-epi differences, adiposity infiltration, and electrophysiological abnormalities, and their influence on PsAF arrhythmogenic substrate. METHODS AND RESULTS: Digital twins incorporating fibrosis distribution were generated from consecutive PsAF patients' LGE-MRIs. Using rapid pacing, potential locations attracting re-entries (LRs) were identified in DTs. Cardiac computed tomographies were used to segment adipose tissue within pericardial sac and evaluate the distance from endocardial surface to closest adipose tissue (DEnCA). Bipolar and unipolar-low-voltage area fractions (LVFs) were extracted from EAMs. Volumetric-fibrosis fraction (FF) and surface-FF on endocardial and epicardial surfaces at LRs and non-LRs were analysed in relation to DEnCA and LVF. In 22 patients, adipose tissue volume correlated with BMI and CHA2DS2-VASc and, together with atrial-FF, predicted number of LRs. At LRs and non-LRs, while volumetric-FF was the sole determinant of LR classification, volumetric-FF correlated with endocardium-predominant fibrosis and bipolar LVF. Endocardium-predominant fibrosis was independently linked to DEnCA. CONCLUSION: This study highlights the complex interactions between structural features, such as three-dimensional fibrosis distribution and atrial adiposity infiltration, electrophysiological features, and PsAF arrhythmogenesis.","author":[{"family":"Sakata","given":"Kensuke"},{"family":"Prakosa","given":"Adityo"},{"family":"Yamamoto","given":"Carolyna"},{"family":"Ali","given":"Syed"},{"family":"Mohsen","given":"Yazan"},{"family":"Loeffler","given":"Shane"},{"family":"Kholmovski","given":"Eugene"},{"family":"Marine","given":"JE"},{"family":"Calkins","given":"Hugh"},{"family":"Spragg","given":"David"},{"family":"Trayanova","given":"N"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1093/europace/euag060","URL":"https://doi.org/10.1093/europace/euag060","source":"openalex"},{"id":"oa:W7167934367","type":"article-journal","title":"Conceptualising value in public sector geospatial information for digital twins","abstract":"Abstract. Digital twins (DTs) are digital representations of physical entities where data connections synchronise the physical and digital states at a specified frequency. While DTs originated in manufacturing and aerospace, they are increasingly applied at geographic scales addressing urban issues. As a result, DTs must utilise geospatial information (GI) to represent the built environment, though this is often an implicit aspect. Public sector geospatial information (PSGI), typically produced by National Mapping and Cadastral Agencies (NMCA) is a particular type of GI that serves as an authoritative, foundational component to geospatial applications. However, the value of this PSGI as foundation component of DTs is not well understood. Existing GI valuation methodologies do not account for the unique characteristics of foundational PSGI, or its role within DTs , leaving NMCAs unable to justify investment, and adapt their contributions, to emerging DTs. To address this gap, this study applies Jabareen’s (2009) conceptual framework analysis methodology to define what value means in the context of PSGI in DTs. The analysis identifies seven value enablers and five value dimensions that characterise PSGI value in DTs and provide the basis for future quantitative valuation methodologies. These concepts are integrated through an urban infrastructure DT example and synthesised through boundary case analysis. The resulting conceptual understanding enables NMCAs to systematically articulate and evidence their contributions to DTs.","author":[{"family":"Metcalfe","given":"Jack"},{"family":"Ellul","given":"Claire"},{"family":"Cavazzi","given":"Stefano"},{"family":"Stoter","given":"Jantien"},{"family":"Morley","given":"Jeremy"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-annals-xi-4-2026-331-2026","URL":"https://doi.org/10.5194/isprs-annals-xi-4-2026-331-2026","source":"openalex"},{"id":"oa:W7169837604","type":"article-journal","title":"Evolving circular pedagogy: a framework for immersive transdisciplinary learning","abstract":"The contemporary world is undergoing profound socio-economic and environmental transformations that necessitate a radical re-evaluation of how we learn, teach, innovate and engage with research. Traditional educational models are increasingly insufficient to address the complexity of the twin transition (i.e. green and digital), in which countries need to identify the most effective strategies to advance the digital and green transformations necessary to support sustainable development. Educational systems and frameworks also need to respond to the United Nations 2030 Agenda for Sustainable Development and its three pillars: environment, society, and economy. This research study offers critical insights into the need to build an actionable framework that supports the development of innovative learning spaces and pedagogies within an Immersive Transdisciplinary Learning framework better attuned to the realities of contemporary society. We propose an innovative approach that integrates immersive technologies, transdisciplinary collaboration, and real-world applications to reshape knowledge exchange processes as the learning loop continues to evolve through the lens of Circular Pedagogy.","author":[{"family":"Morales","given":"Lucía"},{"family":"Hill","given":"Valerie"},{"family":"Pop","given":"Lia"},{"family":"Valtiņš","given":"Kārlis"},{"family":"Oconnor","given":"John"},{"family":"Rajmil","given":"Daniel"},{"family":"Madi","given":"Intesar"},{"family":"Alzankawi","given":"Abrar"},{"family":"Nwanze","given":"Precious"},{"family":"Zherdeva","given":"Anna"},{"family":"Gülmez","given":"Murat"},{"family":"Solak","given":"Çağla"},{"family":"Peev","given":"Ivaylo"},{"family":"Todorov","given":"Todor"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/14681366.2026.2700558","URL":"https://doi.org/10.1080/14681366.2026.2700558","source":"openalex"},{"id":"oa:W4414512160","type":"article-journal","title":"Agroforestry as a Resource for Resilience in the Technological Era: The Case of Ukraine","abstract":"Climate change is intensifying droughts, heatwaves, dust storms, and rainfall variability across Eastern Europe, undermining yields and soil stability. In Ukraine, decades of underinvestment and wartime damage have led to widespread degradation of field shelterbelts, while the adoption of agroforestry remains constrained by tenure ambiguity, fragmented responsibilities, and limited access to finance. This study develops a policy-and-technology framework to restore agroforestry at scale under severe fiscal and institutional constraints. We apply a three-stage approach: (i) a national baseline (post-1991 legislation, statistics) to diagnose the biophysical and legal drivers of shelterbelt decline, including wartime damage; (ii) a comparative synthesis of international support models (governance, incentives, finance); and (iii) an assessment of transferability of digital monitoring, reporting, and verification (MRV) tools to Ukraine. We find that eliminating tenure ambiguities, introducing targeted cost sharing, and enabling access to payments for ecosystem services and voluntary carbon markets can unlock financing at scale. A digital MRV stack—Earth observation, UAV/LiDAR, IoT sensors, and AI—can verify tree establishment and survival, quantify biomass and carbon increments, and document eligibility for performance-based incentives while lowering transaction costs relative to field-only surveys. The resulting sequenced policy package provides an actionable pathway for policymakers and donors to finance, monitor, and scale shelterbelt restoration in Ukraine and in similar resource-constrained settings.","author":[{"family":"Pimenow","given":"Sergiusz"},{"family":"Pimenowa","given":"Olena"},{"family":"Moldavan","given":"Lubov"},{"family":"Prus","given":"Piotr"},{"family":"Sadowska","given":"Katarzyna"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/resources14100152","URL":"https://doi.org/10.3390/resources14100152","source":"openalex"},{"id":"oa:W7148739800","type":"article-journal","title":"Abstract 6724: OncoTwin: A multimodal digital twin framework for predicting treatment response and guiding trial design in ALK-rearranged non-small-cell lung cancer.","abstract":"Abstract Introduction: Despite advances with next-generation tyrosine kinase inhibitors (TKIs), response and progression patterns in ALK-rearranged NSCLC vary widely, and currently no reliable biomarkers can predict individualized outcomes under alternative therapies. Digital-twin models offer a solution by integrating real-world evidence to reconstruct patient-specific counterfactual disease trajectories for single-arm trials and evaluation of escalation strategies. Methods: We integrated real-world and clinical-trial datasets of ALK-rearranged NSCLC treated with TKIs, including MDACC cohort (n = 103, GEMINI database) for model development, Phase III randomized ALTA-1L (n = 207) for external validation, and Phase II BrightStar (n = 32) for clinical application. Tumor burden was quantified at whole-body and organ levels using CT-derived 3D volumetrics, combined with longitudinal routine blood test and demographic variables. Two digital twin models were developed through machine learning: OncoTwin-2D, a parsimonious model based on serial sum of longest diameters (SLD) and demographics, and OncoTwin-3D, an advanced model integrating longitudinal 3D volumetric, blood, and demographic features. Models were evaluated on MDACC and ALTA-1L cohorts by hazard ratio (HR) and log-rank test. The calibrated OncoTwin-3D was further applied to the single-arm BrightStar trial to simulate a counterfactual brigatinib-only control arm and evaluate the added benefit of local consolidation therapy (LCT). Results: Early tumor response patterns and long-term outcomes differed by TKI generation, with second-generation TKIs showing greater overall and organ-level responses and longer median PFS (29 vs 10 months; HR = 0.45; p < 0.001) than first-generation TKI. For our digital twin framework, OncoTwin-2D achieved robust risk stratification (HR = 1.8, p = 0.034 in MDACC cohort; HR = 2.1, p < 0.001 for external ALTA-1L cohort). Furthermore, model predicted survival outcomes aligned consistently with observed outcomes in ALTA-1L for first- and second-generation TKI. The advanced OncoTwin-3D further improved prognostic accuracy with significant risk stratification in MDACC cohort (HR = 3.9, p < 0.0001) and separately for individual TKI subgroups (p = 0.006 and p < 0.001 for first- and second-generation TKI). In the prospective BrightStar phase II trial, OncoTwin-3D was applied to simulate a counterfactual brigatinib-only control arm, which revealed a significant benefit from adding LCT (median PFS 66 vs. 22 months; HR = 2.8, p = 0.002). Conclusion: We introduced OncoTwin, an AI-driven multimodal digital twin for individualized response prediction and novel escalation evaluation. This scalable framework extends beyond thoracic disease, offering a generalizable paradigm that bridges real-world data and clinical trials to accelerate precision oncology. Citation Format: Hui Xu, Yasir Y. Elamin, Lingzhi Hong, Kyle Concannon, Maliazurina Binti Saad, Xinyan Xu, Muneer Amgad, Hui Li, Kang Qin, Xiaoyu Han, Sherif Ismail, Yuliya Kitsel, Saumil Gandhi, Mara B. Antonoff, Carol C. Wu, Brett W. Carter, Girish S Shroff, Simon Heeke, Xiuning Le, Tina Cascone, Natalie Vokes, Mehmet Altan, Don L. Gibbons, David Jaffray, Joe Y Chang, Zhongxing Liao, David Rice, Ara Vaporciyan, Stephen G G. Swisher, J Jack Lee, Jianjun Zhang, John V. Heymach, Jia Wu, . OncoTwin: A multimodal digital twin framework for predicting treatment response and guiding trial design in ALK-rearranged non-small-cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6724.","author":[{"family":"Xu","given":"Hui"},{"family":"Elamin","given":"Yasir"},{"family":"Hong","given":"Lingzhi"},{"family":"Concannon","given":"Kyle"},{"family":"Saad","given":"Maliazurina"},{"family":"Xu","given":"Xinyan"},{"family":"Amgad","given":"Muneer"},{"family":"Li","given":"H"},{"family":"Qin","given":"Kang"},{"family":"Han","given":"Xiaoyu"},{"family":"Ismail","given":"Sohair"},{"family":"Kitsel","given":"Yuliya"},{"family":"Gandhi","given":"Saumil"},{"family":"Antonoff","given":"Mara"},{"family":"Wu","given":"Carol"},{"family":"Carter","given":"B"},{"family":"Shroff","given":"Girish"},{"family":"Heeke","given":"Simon"},{"family":"Le","given":"Xiuning"},{"family":"Cascone","given":"Tina"},{"family":"Vokes","given":"N"},{"family":"Altan","given":"Mehmet"},{"family":"Gibbons","given":"Don"},{"family":"Jaffray","given":"David"},{"family":"Chang","given":"Joe"},{"family":"Liao","given":"Z"},{"family":"Rice","given":"D"},{"family":"Vaporciyan","given":"Ara"},{"family":"Swisher","given":"Stephen"},{"family":"Lee","given":"JJ"},{"family":"Zhang","given":"Jianjun"},{"family":"Heymach","given":"John"},{"family":"Wu","given":"Jia"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1158/1538-7445.am2026-6724","URL":"https://doi.org/10.1158/1538-7445.am2026-6724","source":"openalex"},{"id":"oa:W7170184058","type":"article-journal","title":"A Neuro-Fuzzy Digital Twin for Interpretable Cardiac Disease Recognition","abstract":"We present a neuro-fuzzy digital twin for cardiac disease recognition on the PTB-XL dataset that keeps the accuracy of a strong convolutional model while exposing its reasoning as readable fuzzy rules. The key design choice is to separate the two jobs instead of forcing one network to do both. A convolutional backbone (xresnet1d101 with cross-lead attention) is trained first and acts as the predictor. A second phase then freezes the backbone and trains a five-expert mixture of interval Type-2 Adaptive Neuro-Fuzzy Inference Systems as an interpretation layer, attached through a learnable trust gate. Four experts read complementary signal streams (the raw 12-lead waveform, a Fourier–Bessel Series Expansion, a Tunable-Q Wavelet Transform, and a morphogram); a fifth reads 22 clinical and demographic descriptors. A concept bottleneck maps the backbone embedding to eight named clinical concepts (ST elevation, T inversion, QT prolongation, Sokolov–Lyon and Cornell voltages, RVH, axis deviation, QRS widening), so the downstream rules read in clinical language. Two genetic-algorithm stages keep the model compact: NSGA-II selects the clinical features, and a multi-objective rule-pruning search trades macro-F1 and hypertrophy recall against the number of active rules. On the official test fold the twin reaches a macro-F1 of 0.751 (bootstrap 95% CI 0.740 to 0.767), a macro-AUC of 0.928, a Matthews correlation coefficient of 0.672, and a macro expected calibration error of 0.021, which is above the Strodthoff xresnet1d101 baseline of 0.74 and well below the calibration error of our earlier coupled design. Because the fuzzy layer is attached as a trust-gated residual and the best epoch is chosen on threshold-optimized validation F1, the interpretable twin matches the backbone within about 0.004 (twin 0.751 versus backbone 0.754) rather than paying the usual “interpretability tax”. The fuzzy mixture on its own still reaches a macro-F1 of 0.69, so the rules carry real diagnostic signal. Subgroup macro-F1 stays within about 0.045 across sex, age, and body-mass groups. A concept-level intervention simulator estimates how cardioactive drug classes would shift a patient’s risk by perturbing the named concepts and re-running the same twin.","author":[{"family":"Narigina","given":"Marta"},{"family":"Romānovs","given":"Andrejs"},{"family":"Merkurjevs","given":"Jurijs"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/app16157371","URL":"https://doi.org/10.3390/app16157371","source":"openalex"},{"id":"oa:W7171283587","type":"article-journal","title":"A Framework for the Integration of Hybrid Models in Digital Twin Architectures for PHM","abstract":"Hybrid model structures combine physics-based and machinelearning(ML) models to leverage complementary strengthsin prognostics and health management (PHM). While bothhybrid modeling and digital twin (DT) architectures are widelystudied, their structural interaction is rarely addressed systematically.In practice, hybrid models are often developedapplication-specifically, and their structural integration intoDT architectures remains weakly formalized.This paper analyzes hybrid model structures focusing on theirarchitectural composition and establishes a requirement-drivenconfiguration framework based on core PHM constraints. Fourhybrid coupling strategies are classified according to theirstructural integration principles and positioned within a designspace defined by structural dominance and integrationdepth. Based on this configuration framework, architecturalintegration requirements for DT environments are derived andoperationalized in a project-specific DT implementation.The study contributes (1) a structured classification of hybridcoupling strategies, (2) a requirement-driven configurationframework for hybrid model structures in PHM contexts,and (3) a structured integration workflow for embeddinghybrid models into DT architectures. The results providea consistent foundation for managing hybrid model structureswithin scalable DT environments.","author":[{"family":"Linneweber","given":"Jill"},{"family":"Schultz","given":"Andreas"},{"family":"Müller","given":"Laura"},{"family":"Aimiyekagbon","given":"Osarenren"},{"family":"Mozgova","given":"Iryna"},{"family":"Sextro","given":"Walter"}],"issued":{"date-parts":[[2026]]},"DOI":"10.36001/phme.2026.v9i1.4877","URL":"https://doi.org/10.36001/phme.2026.v9i1.4877","source":"openalex"},{"id":"oa:W7163901513","type":"article-journal","title":"Shaping Smart Supply Chains with AI, IoT & Beyond (FCIII 2026)","abstract":"The International Conference on Future Chains Intelligence, Innovation & Integration: Shaping Smart Supply Chains with AI, IoT & Beyond (FCIII 2026) focuses on transforming supply chains through emerging technologies. Centered on the theme, this conference gathers researchers, practitioners, industry leaders, and innovators to explore how AI, IoT, blockchain, and advanced analytics are reshaping supply chain ecosystems. FCIII 2026 highlights intelligent integration across procurement, production, logistics, and customer engagement. Through keynote sessions, panel discussions, and case studies, participants will gain insights into predictive analytics, real-time visibility, risk management, and digital transformation strategies. The conference aims to foster collaboration and build smart, resilient, transparent, and sustainable supply chains for the future. Measuring progress is essential. Companies should adopt comprehensive frameworks that track metrics such as representation, pay equity, promotion rates, and employee engagement across demographics. Equally important is building awareness among leaders, policymakers, and employees about the systemic barriers-like unconscious bias and exclusionary norms-that hinder inclusion. Education, dialogue, and accountability are key to creating workplaces where everyone can thrive. FCIII 2026 explores the transformation of global supply chains through advanced digital technologies and intelligent ecosystem integration. As supply networks respond to geopolitical shifts, sustainability demands, digital disruption, and changing consumer expectations, building resilient and adaptive systems has become vital. The conference highlights the role of AI, IoT, blockchain, digital twins, generative AI, and cognitive control towers in enhancing decision- making across procurement, logistics, finance, marketing, and customer engagement. Bringing together researchers, practitioners, industry leaders, and policymakers, FCIII 2026 promotes discussions on smart logistics, circular economy models, supply chain innovation, and human– AI collaboration, aiming to bridge theory and practice for sustainable, future-ready solutions.","author":[{"family":"Vijaya","given":"Dr"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20566092","URL":"https://doi.org/10.5281/zenodo.20566092","source":"openalex"},{"id":"oa:W7128928712","type":"article-journal","title":"Fold Sensing Origami Gestures—A Case Study with Kresling Kinematics","abstract":"Abstract We extend previous work in the field of origami robotics by exploring the question of fold sensing. Fold sensing is the process of sensing the angle between two adjacent folding planes and can be used to approximate an origami structure as it folds and unfolds. Our work shows that capacitive sensing can be used to detect four distinct types of interactions from the same sensor data stream. Our capacitive fold sensing design can detect touch as a Boolean state, pressure as a scalar value, single-fold gestures as a scalar value measured between two panels, and multi-fold gestures as a multi-dimensional vector, comprised of single-fold values. Our case study considers single and multi-fold gestures for the unique origami kinematics of the Kresling-ori. We present a prototype fold sensing instrument and two digital twins. The unique folding kinematics of the Kresling-ori has distinct folding gestures such as compression, rotation, twisting, and bending, making it ideal for this case study. We detail our methods for translating sensor data into gestural data for each type. We include a partial characterisation of the sensor design, sensor calibration process, single-fold and multi-fold gesture recognition methods. Our study points to further work towards a generalised model for sensing the complex kinematic structures in origami, in rigid and flexible origami structures.","author":[{"family":"Gardiner","given":"Matthew"},{"family":"Oelsch","given":"Anna"},{"family":"Schmid","given":"Simon"},{"family":"Bezri","given":"Alexandre"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/978-981-96-8661-2_1","URL":"https://doi.org/10.1007/978-981-96-8661-2_1","source":"openalex"},{"id":"oa:W7105668144","type":"article-journal","title":"Blue-Cloud 2026 Third Federation Workshop","abstract":"Blue-Cloud partners and collaborators gathered in Brussels from 5 to 7 November 2025 for a three-day series of strategic and technical sessions, anchored by the Third Federation Workshop. The event took place just after the EOSC Symposium, as Blue-Cloud is supporting the creation of a Thematic Node within the EOSC Federation under the name \"EOSC Node Digital Twin of the Ocean\". On 5th November afternoon, the event counted with two hands-on sessions exploring the EOSC Marine Node core and thematic services and cross-node use cases. These interactive demonstrations offered participants a closer look at the technical developments powering Blue-Cloud’s federated services. On 6th November, the Third Federation Workshop brought together project partners, EOSC stakeholders, and Synergy Projects for a full day of in-depth discussion and exchange. The agenda featured an opening overview of key takeaways from the EOSC Symposium, followed by a sequence of panel discussions covering core services, the connection between EOSC and EDITO, the practical challenges of building a federated approach, and capacity-building efforts. Official event page: https://blue-cloud.org/events/blue-cloud-2026-third-federation-workshop","author":[{"family":"Pittonet Gaiarin","given":"Sara"},{"family":"Meijer","given":"Jan"},{"family":"Wyns","given":"Roxanne"},{"family":"Reyes Suarez","given":"Nydia"},{"family":"Palermo","given":"Francesco"},{"family":"Simoncelli","given":"Simona"},{"family":"Nascimento Vitorino","given":"João"},{"family":"Mieruch","given":"Sebastian"},{"family":"Barde","given":"Julien"},{"family":"Pagano","given":"Pasquale"},{"family":"Assante","given":"Massimiliano"},{"family":"Kooyman","given":"Robin"},{"family":"Tedds","given":"Jonathan"},{"family":"Pesant","given":"Stéphane"},{"family":"Wichorowski","given":"Marcin"},{"family":"Rizzo","given":"Alessandro"},{"family":"Bodere","given":"Erwan"},{"family":"Delaney","given":"Conor"},{"family":"Tonani","given":"Marina"},{"family":"Vera","given":"Julia"},{"family":"Fooks","given":"Samuel"},{"family":"Costa","given":"Valentina"},{"family":"Irisson","given":"Jean"},{"family":"Vernet","given":"Marine"},{"family":"Dechenne","given":"Abel"},{"family":"Eparkhina","given":"Dina"},{"family":"Caccavale","given":"Mauro"},{"family":"Sarretta","given":"Alessandro"},{"family":"Janssens","given":"Laurence"},{"family":"Sharma","given":"Shreshtha"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5281/zenodo.17598616","URL":"https://doi.org/10.5281/zenodo.17598616","source":"openalex"},{"id":"oa:W7163878361","type":"article-journal","title":"Shaping Smart Supply Chains with AI, IoT & Beyond (FCIII 2026)","abstract":"The International Conference on Future Chains Intelligence, Innovation & Integration: Shaping Smart Supply Chains with AI, IoT & Beyond (FCIII 2026) focuses on transforming supply chains through emerging technologies. Centered on the theme, this conference gathers researchers, practitioners, industry leaders, and innovators to explore how AI, IoT, blockchain, and advanced analytics are reshaping supply chain ecosystems. FCIII 2026 highlights intelligent integration across procurement, production, logistics, and customer engagement. Through keynote sessions, panel discussions, and case studies, participants will gain insights into predictive analytics, real-time visibility, risk management, and digital transformation strategies. The conference aims to foster collaboration and build smart, resilient, transparent, and sustainable supply chains for the future. Measuring progress is essential. Companies should adopt comprehensive frameworks that track metrics such as representation, pay equity, promotion rates, and employee engagement across demographics. Equally important is building awareness among leaders, policymakers, and employees about the systemic barriers-like unconscious bias and exclusionary norms-that hinder inclusion. Education, dialogue, and accountability are key to creating workplaces where everyone can thrive. FCIII 2026 explores the transformation of global supply chains through advanced digital technologies and intelligent ecosystem integration. As supply networks respond to geopolitical shifts, sustainability demands, digital disruption, and changing consumer expectations, building resilient and adaptive systems has become vital. The conference highlights the role of AI, IoT, blockchain, digital twins, generative AI, and cognitive control towers in enhancing decision- making across procurement, logistics, finance, marketing, and customer engagement. Bringing together researchers, practitioners, industry leaders, and policymakers, FCIII 2026 promotes discussions on smart logistics, circular economy models, supply chain innovation, and human– AI collaboration, aiming to bridge theory and practice for sustainable, future-ready solutions.","author":[{"family":"Vijaya","given":"Dr"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.20566093","URL":"https://doi.org/10.5281/zenodo.20566093","source":"openalex"},{"id":"oa:W7167795073","type":"article-journal","title":"Shaping Smart Supply Chains with AI, IoT & Beyond (FCIII 2026)","abstract":"The International Conference on Future Chains Intelligence, Innovation & Integration: Shaping Smart Supply Chains with AI, IoT & Beyond (FCIII 2026) focuses on transforming supply chains through emerging technologies. Centered on the theme, this conference gathers researchers, practitioners, industry leaders, and innovators to explore how AI, IoT, blockchain, and advanced analytics are reshaping supply chain ecosystems. FCIII 2026 highlights intelligent integration across procurement, production, logistics, and customer engagement. Through keynote sessions, panel discussions, and case studies, participants will gain insights into predictive analytics, real-time visibility, risk management, and digital transformation strategies. The conference aims to foster collaboration and build smart, resilient, transparent, and sustainable supply chains for the future. Measuring progress is essential. Companies should adopt comprehensive frameworks that track metrics such as representation, pay equity, promotion rates, and employee engagement across demographics. Equally important is building awareness among leaders, policymakers, and employees about the systemic barriers-like unconscious bias and exclusionary norms-that hinder inclusion. Education, dialogue, and accountability are key to creating workplaces where everyone can thrive. FCIII 2026 explores the transformation of global supply chains through advanced digital technologies and intelligent ecosystem integration. As supply networks respond to geopolitical shifts, sustainability demands, digital disruption, and changing consumer expectations, building resilient and adaptive systems has become vital. The conference highlights the role of AI, IoT, blockchain, digital twins, generative AI, and cognitive control towers in enhancing decision- making across procurement, logistics, finance, marketing, and customer engagement. Bringing together researchers, practitioners, industry leaders, and policymakers, FCIII 2026 promotes discussions on smart logistics, circular economy models, supply chain innovation, and human– AI collaboration, aiming to bridge theory and practice for sustainable, future-ready solutions.","author":[{"family":"Vijaya","given":"Dr"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.21237421","URL":"https://doi.org/10.5281/zenodo.21237421","source":"openalex"},{"id":"doi:10.54941/ahfe1007965","type":"article-journal","title":"Marine Protected Area (MPA) Digital Twin Framework and Its Perspectives","abstract":"Marine Protected Areas (MPAs) are increasingly recognised as critical infrastructures for biodiversity conservation, climate regulation, and the resilience of coastal socio-ecological systems, while also supporting emerging Blue Economy strategies. Among the ecosystems they safeguard, Posidonia oceanica meadows represent a particularly valuable and vulnerable component of the Mediterranean seascape, providing long-term carbon sequestration. This paper proposes a Digital Twin (DT) framework for the Marine Protected Area of Ischia (Regno di Nettuno), conceived as a dynamic, data-driven system to support continuous monitoring, adaptive governance, and the development of Blue Carbon initiatives. By integrating heterogeneous data streams across ecological, infrastructural, and socio-economic dimensions, the system aims to support continuous monitoring, risk assessment, and evidence-based governance.The methodology combines an analysis of data availability and accessibility with a systematic mapping of stakeholders and activities. The DT is designed as a circular data–action–feedback chain, transforming input data into descriptive and predictive outputs—such as what-if scenarios and dynamic cartographies—which are disseminated through web, mobile, and Digital Twin interfaces. These outputs inform stakeholder activities and are enacted through a set of regulatory, ecological, socio-economic, participatory, and technical actuators, generating real-world interventions and new data inputs. The proposed framework shows the MPA DT designed as a socio-technical interface that connects marine ecosystems, informed decision-making, and civic engagement, fostering more resilient and inclusive approaches to marine conservation.","author":[{"family":"Artioli","given":"Letizia"},{"family":"Borga","given":"Giovanni"},{"family":"Costa","given":"Pietro"}],"issued":{"date-parts":[[2026]]},"DOI":"10.54941/ahfe1007965","URL":"https://doi.org/10.54941/ahfe1007965","source":"openalex"},{"id":"oa:W7164492202","type":"article-journal","title":"Digital twins in agriculture: A systematic literature review on modeling, semantics, and interoperability","abstract":"The adoption of Digital Twins in agriculture has increased significantly in recent years, driven by advances in sensing technologies, computational modeling, and data-driven analytics. As agricultural systems become increasingly complex and interconnected, the ability to integrate heterogeneous data sources and enable consistent data exchange across platforms has become a critical requirement. However, challenges related to interoperability and data integration continue to hinder the effective deployment of agricultural Digital Twins. This paper presents a Systematic Literature Review on the application of Digital Twins in agriculture, focusing on modeling approaches, semantic representations, and interoperability mechanisms. Following a structured review protocol, studies published between 2016 and January 2026 were retrieved from major scientific digital libraries. The multi-stage screening process reduced an initial dataset of 6,968 records to a final corpus of 62 primary studies. The results show a strong concentration of research in semantic and knowledge modeling, interoperability and integration mechanisms, and analytics-driven decision support. Crop- and plant-oriented Digital Twins dominate the literature, while the digitalization of agricultural machinery and large-scale integrated farming systems remains comparatively limited. The review also identifies key research gaps related to the lack of standardized architectures, limited cross-asset integration, and scarce large-scale field validation. These findings provide a consolidated perspective on the current state of Digital Twin research in agriculture and outline future research directions toward more interoperable and scalable digital agricultural ecosystems.","author":[{"family":"Pereira","given":"Pedro"},{"family":"Piazza","given":"Giovana"},{"family":"Usman","given":"Khalid"},{"family":"Silveira","given":"Luan"},{"family":"Ceriotti","given":"Vincius"},{"family":"Pazin","given":"Yuri"},{"family":"Freitas","given":"Edison"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.atech.2026.102283","URL":"https://doi.org/10.1016/j.atech.2026.102283","source":"openalex"},{"id":"oa:W4414270257","type":"article-journal","title":"Digital Twins in Manufacturing: A Systematic Literature Review With Retrieval-Augmented Generation","abstract":"This paper presents a systematic literature review on the use of digital twins in manufacturing, with the goal of developing a comprehensive taxonomy that synthesizes existing categorizations. Given the increasing complexity and volume of literature in this domain, conventional review methods are becoming insufficient. To address this challenge, the study applies a novel approach named retrieval augmented generation. This is a technique that combines large language models with real-time information retrieval, enabling the automated identification and summarization of typologies across a broad corpus of publications. A total of 1,354 publications were initially screened, leading to 144 distinct categorizations relevant to digital twins in industrial contexts. The resulting taxonomy classifies digital twins along multiple dimensions, including life cycle stages, physical domain and hierarchy levels, model characteristics, digital thread connectivity and deployment strategies. This work provides both researchers and practitioners with a structured approach to understanding and implementing digital twins in manufacturing environments, as well as a guideline to completely describe a specific implementation. The taxonomy serves as a foundation for future research and as a practical tool for industrial applications, since it defines design decisions, which have to be made.","author":[{"family":"Seipolt","given":"Arne"},{"family":"Buschermöhle","given":"Ralf"},{"family":"Hasselbring","given":"Wilhelm"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/access.2025.3611269","URL":"https://doi.org/10.1109/access.2025.3611269","source":"openalex"},{"id":"oa:W4411889930","type":"article-journal","title":"Digital Twins in Security Operations: State of the Art and Future Perspectives","abstract":"In an era of rapid technological advancements, digital twins are gaining attention in industry and research. These virtual representations of real-world entities, enabled by the Internet of Things (IoT), offer advanced simulation and analysis capabilities. Their application spans various sectors, from smart manufacturing to healthcare, highlighting their versatility. However, the rise of digital technologies has also escalated cybersecurity concerns. Historical cyberattacks underscore the urgency for enhanced security operations. In this context, digital twins represent a novel approach to cybersecurity. Industry and academic research are increasingly exploring their potential to protect their assets. Despite growing interest and applications, more comprehensive research synthesis needs to be done, particularly in security operations based on digital twins. Our article aims to fill this gap through a structured literature review aggregating knowledge from 201 publications. We focus on defining the digital twin in cybersecurity, exploring its applications, and outlining implementations and challenges. To maintain transparency, our data is documented and is publicly available. This survey serves as a crucial guide for academic and industry stakeholders, fostering digital twins in security operations.","author":[{"family":"Empl","given":"Philip"},{"family":"Koch","given":"D"},{"family":"Dietz","given":"Marietheres"},{"family":"Pernul","given":"Günther"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1145/3746279","URL":"https://doi.org/10.1145/3746279","source":"openalex"},{"id":"oa:W4411950016","type":"article-journal","title":"Risk Management and Macroeconomic Disruptions in Supply Chains: The Role of Blockchain, Digital Twins, Generative AI, and Quantum Computing","abstract":"The global economy faces increasing vulnerabilities from macroeconomic disruptions, such as regulatory changes, trade tensions, geopolitical conflicts, currency volatility, pandemics, and energy crises, that undermine the resilience of operations and supply chain management (OSCM) systems. These disruptions exacerbate risks, including supply chain breakdowns, operational inefficiencies, and systemic weaknesses, with energy challenges emerging as a key concern due to their effects on production costs, inflation, and sustainability goals. Advanced technologies, such as blockchain, digital twins, generative artificial intelligence (AI), and quantum computing, offer transformative potential to enhance transparency, predictive accuracy, and decision-making agility. However, their adoption introduces inherent trade-offs, as they can lead to energy-intensive operations, cybersecurity risks, and economic burdens. To make sense of these dynamics, this paper develops a conceptual framework based on a multi-layered information system architecture that links specific disruptions to corresponding digital responses. This framework is grounded in a thorough review of both conceptual and empirical literature, along with extensive discussions among the authors. It explores how these technologies can address the risks stemming from macroeconomic disruptions while also considering their broader economic implications and challenges. It argues that simplistic solutions fail to account for the duality of these technologies' impacts and highlights the need for a systemic approach to integrate these technologies within OSCM. The paper concludes by proposing actionable research directions for OSCM scholars and managers to navigate these complexities.","author":[{"family":"Yoon","given":"Jiho"},{"family":"Alkhudary","given":"Rami"},{"family":"Talluri","given":"Srinivas"},{"family":"Féniès","given":"Pierre"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/tem.2025.3585433","URL":"https://doi.org/10.1109/tem.2025.3585433","source":"openalex"},{"id":"oa:W7131355483","type":"article-journal","title":"Digital Twins in Neonatology: Current Applications and Future Directions: A Narrative Review","abstract":"Digital Twins (DTs) are virtual, patient-specific representations that integrate real-time data to model, predict, and optimize biological and clinical processes. In neonatology, DTs are gaining attention as powerful tools for managing the profound physiological complexity and variability of newborns, particularly preterm infants requiring intensive care. Emerging applications include cardiopulmonary modeling, prediction of sepsis and necrotizing enterocolitis (NEC), optimization of mechanical ventilation, individualized nutrition, and longitudinal monitoring of neuromotor development. This review synthesizes current research on neonatal digital twins, highlighting clinical use cases and ethical considerations. We discuss persistent challenges, including limited data availability, rapid developmental change, model validation, and regulatory oversight. Finally, we outline a roadmap for integrating DTs into neonatal intensive care units (NICUs) and identify future research priorities, including multi-organ integration, predictive closed-loop systems, and personalized life-course care trajectories.","author":[{"family":"Savvidou","given":"Dimitra"},{"family":"Dermitzaki","given":"Niki"},{"family":"Baltogianni","given":"Maria"},{"family":"Nikolaou","given":"Aikaterini"},{"family":"Giapros","given":"Vasileios"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/app16052198","URL":"https://doi.org/10.3390/app16052198","source":"openalex"},{"id":"oa:W7125894073","type":"manuscript","title":"Digital Twins in Neonatology: Current Applications and Future Directions. A Narrative Review","abstract":"Digital Twins (DTs) are virtual, patient-specific representations that integrate re-al-time data to model, predict, and optimize biological and clinical processes. In neo-natology, DTs are gaining attention as powerful tools for managing the profound physiological complexity and variability of newborns, particularly preterm infants re-quiring intensive care. Emerging applications include cardiopulmonary modeling, prediction of sepsis and necrotizing enterocolitis (NEC), optimization of mechanical ventilation, individualized nutrition, and longitudinal monitoring of neuromotor de-velopment. This review synthesizes current research on neonatal digital twins, high-lighting clinical use cases and ethical considerations. We discuss persistent challenges, including limited data availability, rapid developmental change, model validation, and regulatory oversight. Finally, we outline a roadmap for integrating DTs into neo-natal intensive care units (NICUs) and identify future research priorities, including multi-organ integration, predictive closed-loop systems, and personalized life-course care trajectories.","author":[{"family":"Savvidou","given":"Dimitra"},{"family":"Dermitzaki","given":"Niki"},{"family":"Baltogianni","given":"Maria"},{"family":"Nikolaou","given":"Aikaterini"},{"family":"Giapros","given":"Vasileios"}],"issued":{"date-parts":[[2026]]},"DOI":"10.20944/preprints202601.2008.v1","URL":"https://doi.org/10.20944/preprints202601.2008.v1","source":"openalex"},{"id":"oa:W7136425764","type":"article-journal","title":"Digital Twin Technology in Wind Turbine Condition Monitoring, Predictive Maintenance, and RUL Estimation: A Systematic Literature Review","abstract":"The rapid growth of wind energy has increased the need for advanced condition monitoring (CM), predictive maintenance, and remaining useful life (RUL) estimation strategies for wind turbines. In this context, digital twins (DTs) have emerged as a key tool for improving reliability, availability, and operational efficiency by integrating physical models, operational data, and artificial intelligence (AI). This paper presents a systematic literature review (SLR) aimed at analyzing the state of the art, classifying the main applications, and identifying research gaps. A rigorous search protocol was applied across scientific databases, considering inclusion and exclusion criteria and analysis categories aligned with four research questions. The results show a high concentration of studies on critical wind turbine components, a predominance of hybrid physics-based and data-driven approaches, and an increasing use of deep learning (DL) models. However, several research gaps remain, including the predominance of component-level digital twin implementations rather than system-level architectures, the lack of standardized datasets and benchmarking frameworks, and challenges related to SCADA data heterogeneity and real-time scalability. It is concluded that DTs are evolving toward more autonomous and prescriptive systems; however, they still require further maturation for widespread industrial adoption.","author":[{"family":"Maldonado-Correa","given":"Jorge"},{"family":"Cuenca","given":"José"},{"family":"Torres-Cabrera","given":"Joel"},{"family":"Mejía","given":"Galo"},{"family":"Barragan","given":"Wilson"},{"family":"Guapulema","given":"Rocío"},{"family":"Paccha-Herrera","given":"Edwin"},{"family":"Solano","given":"Juan"},{"family":"Tapia-Peralta","given":"Darwin"},{"family":"Maldonado","given":"José"},{"family":"Laverde-Albarracín","given":"Cristian"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19061477","URL":"https://doi.org/10.3390/en19061477","source":"openalex"},{"id":"oa:W4409919426","type":"article-journal","title":"Application-Wise Review of Machine Learning-Based Predictive Maintenance: Trends, Challenges, and Future Directions","abstract":"This systematic literature review (SLR) provides a comprehensive application-wise analysis of machine learning (ML)-driven predictive maintenance (PdM) across industrial domains. Motivated by the digital transformation of industry 4.0, this study explores how ML techniques optimize maintenance by predicting faults, estimating remaining useful life (RUL), and reducing operational downtime. Sixty peer-reviewed articles published between 2020 and 2024 were selected using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines, and were analyzed based on industrial sector, ML techniques, datasets, evaluation metrics, and implementation challenges. Results show that combining ML with diverse sensor data enhances predictive performance under varying operational conditions across manufacturing, energy, healthcare, and transportation. Frequently used open datasets include the commercial modular aero-propulsion system simulation (CMAPSS), the malfunctioning industrial machine investigation and inspection (MIMII), and the semiconductor manufacturing process (SECOM) datasets, though data heterogeneity and imbalance remain major barriers. Emerging paradigms such as hybrid modeling, digital twins, and physics-informed learning show promise but face issues like computational cost, interpretability, and limited scalability. The findings highlight future research needs in model generalizability, real-world validation, and explainable artificial intelligence (AI) to bridge gaps between ML innovations and industrial practice.","author":[{"family":"Tsallis","given":"Christos"},{"family":"Papageorgas","given":"Panagiotis"},{"family":"Piromalis","given":"Dimitrios"},{"family":"Munteanu","given":"Radu"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15094898","URL":"https://doi.org/10.3390/app15094898","source":"openalex"},{"id":"oa:W7163555772","type":"article-journal","title":"Cognitive Digital Twins: A Systematic Review of Definitions, Applications, and a Unified Definition","abstract":"Cognitive Digital Twins (CDTs) are regarded as an evolved version of existing Digital Twin (DT) systems and are capable of certain cognitive abilities. However, the various introduced definitions and characteristics of CDTs, and different understandings of “cognition”, create conceptual ambiguity around CDTs. This paper critically reviews key definitions, application domains, capabilities, and proposed architectures of CDTs. Following PRISMA 2020 guidelines, a systematic review methodology is conducted across Scopus and Web of Science to map existing definitions, cognitive capabilities, and application domains of CDTs. Studies that explicitly implement or conceptualise a DT and explicitly mention cognitive, intelligent, autonomous, or AI-driven properties are included. Conversely, conference papers, book chapters, editorial pieces, review articles, and non-English publications are excluded from this review. The results of 59 reviewed studies present bibliometric metadata and a thematic analysis of early and recent definitions and applications of CDTs across various domains, such as manufacturing, which is the most studied discipline in terms of CDT implementation. Findings show that the understanding of cognitive enhancement has shifted toward the semantic enrichment of DT systems, with a significant emphasis on knowledge-driven approaches. The discussion focuses on identifying key differences between DTs and CDTs and synthesising existing definitions. The key contribution of this study is a unified definition of CDT, a mapping of cognitive capabilities and application domains, and a future research agenda. The review is not registered. The review is limited to journal articles, and the enabling CDT technologies, along with their implementations, are not addressed within this paper.","author":[{"family":"Bacnak","given":"Tugce"},{"family":"Arayici","given":"Yusuf"},{"family":"Doukari","given":"Omar"},{"family":"Rogage","given":"Kay"},{"family":"Laing","given":"Richard"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/info17060556","URL":"https://doi.org/10.3390/info17060556","source":"openalex"},{"id":"oa:W7133943002","type":"article-journal","title":"A review of digital twin applications for optimizing grain drying: Challenges and opportunities","abstract":"In the face of global food security challenges and the continuously increasing pressure of drying energy consumption, problems such as uneven grain quality, local overheating and excessive humidity, and low energy efficiency caused by opaque processes and reliance on experience-based operations in traditional grain drying technologies have become increasingly prominent. Digital twin technology, as a new paradigm of dynamic interaction and mapping between virtual and real Spaces, is providing a revolutionary solution to the predicament of grain drying. This article systematically expounds the core composition, current development status and inherent limitations of digital twin technology, deeply analyzes its key role in predictive maintenance and product optimization, and compares the fundamental differences in its application paradigms in the industrial and agricultural fields. By comprehensively reviewing the research and application of digital twin technology in the field of grain drying, this paper demonstrates that as a key enabling technology, it can achieve visual monitoring, precise regulation and dynamic optimization of the drying process through the deep integration of Internet of Things perception, multi-scale modeling and intelligent algorithms. Research shows that the in-depth application of this technology can not only effectively solve the pain points such as uneven temperature and humidity distribution and excessive reliance on experience in traditional drying, but also significantly improve the quality of grains (such as reducing cracks and retaining nutrients), and at the same time achieve personalized process customization and a significant reduction in energy consumption, thereby strongly promoting the digital transformation of the grain drying industry toward high efficiency, low carbon and intelligence.","author":[{"family":"Li","given":"Jin"},{"family":"Liu","given":"Chunshan"},{"family":"Chang","given":"Kezhen"},{"family":"Chen","given":"Siyu"},{"family":"Jin","given":"Yi"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/07373937.2026.2631682","URL":"https://doi.org/10.1080/07373937.2026.2631682","source":"openalex"},{"id":"oa:W4409470448","type":"article-journal","title":"Physical twinning for joint encoding-decoding optimization in computational optics: a review","abstract":"Computational optics introduces computation into optics and consequently helps overcome traditional optical limitations such as low sensing dimension, low light throughput, low resolution, and so on. The combination of optical encoding and computational decoding offers enhanced imaging and sensing capabilities with diverse applications in biomedicine, astronomy, agriculture, etc. With the great advance of artificial intelligence in the last decade, deep learning has further boosted computational optics with higher precision and efficiency. Recently, there developed an end-to-end joint optimization technique that digitally twins optical encoding to neural network layers, and then facilitates simultaneous optimization with the decoding process. This framework offers effective performance enhancement over conventional techniques. However, the reverse physical twinning from optimized encoding parameters to practical modulation elements faces a serious challenge, due to the discrepant gap in such as bit depth, numerical range, and stability. In this regard, this review explores various optical modulation elements across spatial, phase, and spectral dimensions in the digital twin model for joint encoding-decoding optimization. Our analysis offers constructive guidance for finding the most appropriate modulation element in diverse imaging and sensing tasks concerning various requirements of precision, speed, and robustness. The review may help tackle the above twinning challenge and pave the way for next-generation computational optics.","author":[{"family":"Bian","given":"Liheng"},{"family":"Zhan","given":"Xinrui"},{"family":"Yan","given":"Rong"},{"family":"Chang","given":"Xuyang"},{"family":"Huang","given":"Hua"},{"family":"Zhang","given":"Jun"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41377-025-01810-4","URL":"https://doi.org/10.1038/s41377-025-01810-4","source":"openalex"},{"id":"oa:W4409253351","type":"article-journal","title":"Explainable artificial intelligence for energy systems maintenance: A review on concepts, current techniques, challenges, and prospects","abstract":"The rising demand for energy requires high investments in network extensions and renewable sources, alongside replacing inefficient systems. Smart maintenance is important in minimizing unscheduled outages, reducing costs, improving network security, and increasing equipment’s life expectancy. The vast amount of data collected by sensors and measurements in energy networks makes it hard for humans to detect failures continuously. Thanks to recent breakthroughs in AI, the energy sector has boosted the use of intelligent algorithms in this field. Despite the widespread popularity and great results of machine learning (ML) models in many applications, they are mostly nevertheless considered ”black boxes” as understanding their functionality and transparency in real-world applications is challenging. Explainable Artificial Intelligence (XAI) tackles this by making AI systems’ decision-making processes transparent and interpretable. This review paper will not only make the roadmap clear but also ensure an in-depth awareness of the challenges, opportunities, and developments associated with this path by presenting two comprehensive taxonomies. Various XAI methods are compared; as an example, our findings show that SHAP offers high trustworthiness but is less suited for real-time use, while LIME provides faster solutions with lower trustworthiness. To the best of the authors’ knowledge, this is the first survey that provides an overview of XAI methods for energy systems maintenance (ESM). It addresses challenges like integrating XAI with IoT-powered digital twins, balancing explainability with cybersecurity, and ensuring scalability while proposing solutions to enhance reliability and efficiency. • Clear and detailed taxonomy for energy systems maintenance. • Holistic understanding of XAI in energy systems maintenance. • Challenges and solutions for implementing XAI in energy systems maintenance. • Overview of ML/DL-appropriate XAI algorithms, such as SHAP and LIME. • Emphasis on the need for standardized XAI evaluation metrics.","author":[{"family":"Shadi","given":"Mohammad"},{"family":"Mirshekali","given":"Hamid"},{"family":"Shaker","given":"Hamid"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.rser.2025.115668","URL":"https://doi.org/10.1016/j.rser.2025.115668","source":"openalex"},{"id":"oa:W4407683030","type":"article-journal","title":"Digital Twin and Artificial Intelligence in Machining: A Bibliometric Analysis","abstract":"The past decade has witnessed an exodus toward smart and lean manufacturing methods. The trend includes integrating intelligent methods into sustainable manufacturing systems purposely to improve the machining efficiency, reduce waste and also optimize productivity. Manufacturing systems have seen transformations from conventional methods, leaning towards smart manufacturing in line with the industrial revolution 4.0. Since the manufacturing process encompasses a wide range of human development capacity, it is essential to analyze its developmental trends, thereby preparing us for future uncertainties. In this work, we have used a Bibliometric analysis technique to study the developmental trends relating to machining, digital twins and artificial intelligence techniques. The review comprises the current activities in relation to the development to this area. The article comprises a Bibliometric analysis of 464 articles that were acquired from the Web of Science database, with a search period until November 2024. The method of obtaining the data includes retrieval from the database, qualitative analysis and interpreting the data via visual representation. The raw data obtained were redrawn using the origin software, and their visual interpretations were represented using the VOSviewer software (VOSviewer_1.6.19). The results obtained indicate that the number of publications related to the searched keywords has remarkably increased since the year 2018, achieving a record maximum of over 80 articles in 2024. This is indicative of its increasing popularity. The analysis of the articles was conducted based on the author countries, journal types, journal names, institutions, article types, major and micro research areas. The findings from the analysis are meant to provide a bibliometric explanation of the developmental trends in machining systems towards achieving the IR 4.0 goals. Additionally, the results would be helpful to researchers and industrialists that intend to achieve optimum and sustainable machining using digital twin technologies.","author":[{"family":"Suleiman","given":"Dambatta"},{"family":"Li","given":"QX"},{"family":"Li","given":"Benkai"},{"family":"Zhang","given":"Yanbin"},{"family":"Zhang","given":"Bo"},{"family":"Liu","given":"Danyang"},{"family":"Zhang","given":"Wenqiang"},{"family":"Zhou","given":"Zhigang"},{"family":"Feng","given":"Yuewen"},{"family":"Bie","given":"Qingfeng"},{"family":"Yin","given":"Xianxin"},{"family":"Wang","given":"Lesan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.70322/ism.2025.10005","URL":"https://doi.org/10.70322/ism.2025.10005","source":"openalex"},{"id":"oa:W4415989401","type":"article-journal","title":"Digital twins in stroke rehabilitation: a scoping review of objectives, data sources, mechanisms, outcomes, and desirable properties","abstract":"BACKGROUND: Digital Twins (DTs) have transitioned from theory to reality, with growing applications in healthcare. Data generated by technologies (e.g. rehabilitation robots), essential for DT implementation, though widely produced in clinical settings, remains untapped in DT stroke rehabilitation, highlighting a gap compared to broader healthcare use. OBJECTIVES: We conducted a scoping review to i) define DT rehabilitation objectives, their input data, generation methods and user involvement; ii) analyze mechanisms underpinning DT models and outputs; iii) map key stakeholders driving innovation; iv) identify desirable properties for DT studies from broader healthcare literature and map them to stroke rehabilitation DT studies. METHODS: Following PRISMA-ScR guidelines, PubMed, Scopus, Web of Science and Google Scholar were searched for studies including only empirical data. Full-text reviews were conducted by three reviewers through repeated calibration. RESULTS: Sixteen studies were included, addressing five rehabilitation objectives: upper-limb (10), gait (3), and engagement, mental health, and general/planning (1 each). Patient sample sizes varied widely, with one retrospective study including 1,216 patients, while 15 studies involved 54 patients in total (median = 1).We identified 16 DTs mechanisms (e.g. variational autoencoders, Hill muscle models) and outcomes (e.g. exoskeleton control, upper-limb exercise delivery, gait torque estimation, impaired hand-mobility quantification). Academic institutions conducted 12 studies, Europe contributed 8 studies across 6 countries. Of 25 desirable properties identified, 8 (e.g. reproducible algorithms) showed high adoption, while 15 (e.g. cost-effectiveness, clinical integration) showed low/very low adoption by included studies. CONCLUSIONS: DTs in stroke rehabilitation show promise, though challenges remain (e.g. patient involvement, scalability).","author":[{"family":"Garcíarudolph","given":"Alejandro"},{"family":"Wright","given":"Mark"},{"family":"Teixidó-Font","given":"Claudia"},{"family":"Sánchez-Carrión","given":"Rocío"},{"family":"Cedersund","given":"Gunnar"},{"family":"Opisso","given":"Eloy"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/10749357.2025.2584031","URL":"https://doi.org/10.1080/10749357.2025.2584031","source":"openalex"},{"id":"oa:W7126247625","type":"article-journal","title":"Advancing bridge health assessment and management through Digital Twins: a comprehensive review","abstract":"In recent centuries, millions of bridges have been constructed as vital infrastructure components. However, a significant proportion are operating beyond their intended service life, increasing their vulnerability to deterioration and natural hazards. Conventional inspection and maintenance practices, primarily based on manual observations and non-destructive testing, are often inefficient and incapable of providing continuous, real-time insights into structural performance. To address these challenges, Digital Twin technology has emerged as a transformative solution, enabling the creation of dynamic, data-driven virtual replicas of physical assets that facilitate intelligent, adaptive and predictive maintenance, real-time monitoring and infrastructure assessment. This study presents a comprehensive review of the application of Bridge Digital Twins for structural health assessment, consolidating the latest advancements in their conceptual frameworks, enabling technologies, sensory systems and real-world implementations. The paper presents a structured framework that maps the technological, analytical and operational layers of Bridge Digital Twins, identifying key performance indicators associated with resilience and adaptability. The review systematically examines the essential components of Bridge Digital Twins, maturity levels, classification schemes and model updating techniques, and critically discusses their limitations and practical challenges in real bridge applications. Critical challenges hinder large-scale adoption, data interoperability, standardisation, model validation and computational efficiency. Research gaps and future research directions are identified to guide the widespread adoption of Digital Twins in bridge infrastructure.","author":[{"family":"Yousuf","given":"MM"},{"family":"Saravanan","given":"TJ"},{"family":"Dash","given":"Suresh"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1177/14759217251403381","URL":"https://doi.org/10.1177/14759217251403381","source":"openalex"},{"id":"oa:W4408186454","type":"article-journal","title":"Enhanced Solar Photovoltaic System Management and Integration: The Digital Twin Concept","abstract":"The rapid acceptance of solar photovoltaic (PV) energy across various countries has created a pressing need for more coordinated approaches to the sustainable monitoring and maintenance of these widely distributed installations. To address this challenge, several digitization architectures have been proposed, with one of the most recently applied being the digital twin (DT) system architecture. DTs have proven effective in predictive maintenance, rapid prototyping, efficient manufacturing, and reliable system monitoring. However, while the DT concept is well established in fields like wind energy conversion and monitoring, its scope of implementation in PV remains quite limited. Additionally, the recent increased adoption of autonomous platforms, particularly robotics, has expanded the scope of PV management and revealed gaps in real-time monitoring needs. DT platforms can be redesigned to ease such applications and enable integration into the broader energy network. This work provides a system-level overview of current trends, challenges, and future opportunities for DTs within renewable energy systems, focusing on PV systems. It also highlights how advances in artificial intelligence (AI), the internet-of-Things (IoT), and autonomous systems can be leveraged to create a digitally connected energy infrastructure that supports sustainable energy supply and maintenance.","author":[{"family":"Olayiwola","given":"Olufemi"},{"family":"Cali","given":"Ümit"},{"family":"Elsden","given":"Miles"},{"family":"Yadav","given":"Poonam"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/solar5010007","URL":"https://doi.org/10.3390/solar5010007","source":"openalex"},{"id":"oa:W7157040855","type":"article-journal","title":"Digital Twins for Thermal Comfort and Energy Efficiency in Buildings: A Systematic Review","abstract":"This systematic review builds upon 51 published empirical studies out of 354 studies that were published between 2020 and 2025 to assess the effectiveness of building-scale digital twins (DTs) in providing thermal comfort and energy efficiency, and improving the indoor environment and system reliability. The results show that there is a rapidly developing field focused on five thematic clusters: system architecture, artificial intelligence and machine learning (AI/ML)-driven control, human-centric engagement, predictive maintenance, and blockchain-enabled cybersecurity. Existing DT frameworks not only achieve real-time building information modeling (BIM)–Internet of Things (IoT) integration with prediction errors under 10%, but reinforcement learning controllers are also able to achieve 25–40% heating, ventilation, and air conditioning (HVAC) energy savings, and human-centric interfaces increase thermal satisfaction from 0.64 up to 1.2 Likert points. Predictive maintenance models have diagnostic accuracies of 91–97%, and new blockchain applications enhance data integrity, but largely at the prototype level. The cross-cluster convergence signifies the transition towards adaptive, socio-technical systems with an equilibrium of efficiency, comfort, reliability, and trust. The major weaknesses identified in this paper were a lack of longitudinal validation, climatic bias and ethical governance. A framework of a modular six-layer architecture is proposed after the review of 51 studies, which facilitates scalable, interoperable, and ethically robust DT deployments.","author":[{"family":"Basunbul","given":"Anwar"},{"family":"Anwar","given":"Raneem"},{"family":"Shafei","given":"Rana"},{"family":"Baamer","given":"Abrar"},{"family":"Elkhateeb","given":"Samah"},{"family":"Abouhassan","given":"Marwa"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/buildings16091715","URL":"https://doi.org/10.3390/buildings16091715","source":"openalex"},{"id":"oa:W4407262313","type":"article-journal","title":"IIoT and Digital Twin: A Systematic Literature Review and Looking Beyond the State","abstract":"ABSTRACT The fourth industrial revolution has driven the emergence of Digital Twins (DTs) and Industrial Internet of Things (IIoT) in manufacturing. However, the use of different definition has led to varied interpretations and inconsistent understanding of DTs. Thus, by exploring the gap between theoretical frameworks and practical implementations of IIoT‐based DTs in manufacturing, this paper aims to shed light on the DT phenomenon by considering the historical evolution and fundamental concepts of IIoT‐based DTs. Therefore, a systematic literature review was conducted to assess the ambiguity concerning DTs, particularly in distinguishing architectures and types. Therefore, this paper identifies IIoT‐based DTs in manufacturing by reviewing application‐oriented literature. As a result of a subsequent classification, this paper proposes a hierarchical classification based on communication dynamics (i.e., Uni‐directional and Bi‐directional) and information processing (i.e., use or non‐use of machine learning). Conclusively, this study proposes a comprehensive classification approach for IIoT‐based DTs and thus contributes to a more consistent understanding of the DT phenomenon. Moreover, this paper discusses key findings, as well as implications for research and practice. Finally potential avenues for future research are derived and the limitations of this study are discussed.","author":[{"family":"Bleistein","given":"Thomas"},{"family":"Paulus","given":"Moritz"},{"family":"Gani","given":"Kiran"},{"family":"Becker","given":"Robert"},{"family":"Werth","given":"Dirk"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/asmb.2923","URL":"https://doi.org/10.1002/asmb.2923","source":"openalex"},{"id":"oa:W4408277532","type":"article-journal","title":"Is it possible to develop a digital twin for noise monitoring in manufacturing?","abstract":"Noise monitoring is important in the context of manufacturing because it can help maintain a safe and healthy workspace for employees. Current approaches for noise monitoring in manufacturing are based on acoustic sensors, whose measured sound pressure levels (SPL) are shown as bar/curve charts and acoustic heat maps. In such a way, the noise emission and propagation process is not fully addressed. This paper proposes a digital twin (DT) for noise monitoring in manufacturing using augmented reality (AR) and the phonon tracing method (PTM). In the proposed PTM/AR-based DT, the noise is represented by 3D particles (called phonons) emitting and traversing in a spatial domain. Using a mobile AR device (HoloLens 2), users are able to visualize and interact with the noise emitted by machine tools. To validate the feasibility of the proposed PTM/AR-based DT, two use cases are carried out. The first use case is an offline test, where the noise data from a machine tool are first acquired and used for the implementation of PTM/AR-based DT with different parameter sets. The result of the first use case is the understanding between the AR performance of HoloLens 2 (frame rate) and the setting of the initial number of phonons and sampling frequency. The second use case is an online test to demonstrate the in-situ noise monitoring capability of the proposed PTM/AR-based DT. The result shows that our PTM/AR-based DT is a powerful tool for visualizing and assessing the real-time noise in manufacturing systems.","author":[{"family":"Yi","given":"Li"},{"family":"Ruediger-Flore","given":"Patrick"},{"family":"Karnoub","given":"Ali"},{"family":"Mertes","given":"Jan"},{"family":"Glatt","given":"Moritz"},{"family":"Aurich","given":"Jan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.12688/digitaltwin.17931.2","URL":"https://doi.org/10.12688/digitaltwin.17931.2","source":"openalex"},{"id":"oa:W4412520032","type":"article-journal","title":"A Technological Review of Digital Twins and Artificial Intelligence for Personalized and Predictive Healthcare","abstract":"Digital transformation is reshaping the healthcare field by streamlining diagnostic workflows and improving disease management. Within this transformation, Digital Twins (DTs), which are virtual representations of physical systems continuously updated by real-world data, stand out for their ability to capture the complexity of human physiology and behavior. When coupled with Artificial Intelligence (AI), DTs enable data-driven experimentation, precise diagnostic support, and predictive modeling without posing direct risks to patients. However, their integration into healthcare requires careful consideration of ethical, regulatory, and safety constraints in light of the sensitivity and nonlinear nature of human data. In this review, we examine recent progress in DTs over the past seven years and explore broader trends in AI-augmented DTs, focusing particularly on movement rehabilitation. Our goal is to provide a comprehensive understanding of how DTs bolstered by AI can transform healthcare delivery, medical research, and personalized care. We discuss implementation challenges such as data privacy, clinical validation, and scalability along with opportunities for more efficient, safe, and patient-centered healthcare systems. By addressing these issues, this review highlights key insights and directions for future research to guide the proactive and ethical adoption of DTs in healthcare.","author":[{"family":"Chaparro-Cárdenas","given":"Silvia"},{"family":"Ramirez-Bautista","given":"Julian"},{"family":"Terven","given":"Juan"},{"family":"Córdovaesparza","given":"Diana‐margarita"},{"family":"Romero-González","given":"Julio"},{"family":"Ramírez-Pedraza","given":"Alfonso"},{"family":"Chávezurbiola","given":"Edgar"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/healthcare13141763","URL":"https://doi.org/10.3390/healthcare13141763","source":"europepmc"},{"id":"oa:W4406642000","type":"article-journal","title":"Using the Integral Digital Twin for Product Carbon Footprint calculation","abstract":"Sustainable product development and manufacturing rely heavily on digital technology, as evaluating sustainability metrics requires the systematic gathering and organization of information throughout the product life cycle (PLC). A suitable technology to utilize the potential for sustainability improvement of products is the Digital Twin (DT). This paper introduces the concept of the Integral Digital Twin (IDT) in the context of ecological sustainability as a central data space and application hub for data-driven sustainability. It integrates horizontal communication with clients and suppliers and vertical communication within a company's information systems . The IDT incorporates data generated at various product life phases, providing interfaces for integrating external and the creation of internal eco-databases, along with sustainability metrics calculation tools. Central to this framework is the data model, facilitating the management and distribution of sustainability-relevant data within the IDT. The proposed concept adds value by integrating sustainability assessment in the form of the Product Carbon Footprint (PCF) into DT technology, establishing a dedicated data space within the IDT for this purpose. The novelty of the approach lies in the linking of different DT and software systems across several PLC phases, enabling holistic sustainability management for different perspectives such as product or factory level perspectives. The data model of the IDT provides a basis for an interoperable and seamless data exchange of sustainability relevant data such as the PCF across all stakeholders in the PLC.","author":[{"family":"Winter","given":"Sven"},{"family":"Quernheim","given":"Niklas"},{"family":"Arnemann","given":"Lars"},{"family":"Bausch","given":"Phillip"},{"family":"Frick","given":"Nicholas"},{"family":"Metternich","given":"Joachim"},{"family":"Schleich","given":"Benjamin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.cesys.2025.100258","URL":"https://doi.org/10.1016/j.cesys.2025.100258","source":"openalex"},{"id":"oa:W4406231998","type":"article-journal","title":"Sustainable Additive Manufacturing: An Overview on Life Cycle Impacts and Cost Efficiency of Laser Powder Bed Fusion","abstract":"This overview study investigates integrating advanced manufacturing technologies, specifically metal additive manufacturing (AM) and laser powder bed fusion (LPBF) processes, within Industry 4.0 and Industry 5.0 frameworks, to enhance sustainability and efficiency in industrial production and prototyping. The manufacturing sector, a significant contributor to global greenhouse gas emissions and resource consumption, is increasingly adopting technologies that reduce environmental impact while maintaining economic growth. Selective laser melting (SLM), as the subsection LPBF technologies, is highlighted for its capability to produce high-performance, lightweight, and complex components with minimal material waste, thus aligning with circular economy goals for metal alloys. Life cycle assessment (LCA) and life cycle costing (LCC) analyses are essential methods for evaluating the sustainability of any new technology. Sustainable technologies could support the concepts of the factory of the future (FoF), fulfilling the requirements of digital transformation and digital twins. This overview study reveals that implementing AM—specifically SLM—has the potential to reduce the environmental impact of manufacturing. It underscores the ability of these technologies to promote sustainable and efficient manufacturing practices, thereby accelerating the shift from Industry 4.0 to Industry 5.0.","author":[{"family":"Rahmani","given":"Ramin"},{"family":"Bashiri","given":"Bashir"},{"family":"Lopes","given":"Sérgio"},{"family":"Hussain","given":"Abrar"},{"family":"Maurya","given":"HS"},{"family":"Vilu","given":"Raivo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/jmmp9010018","URL":"https://doi.org/10.3390/jmmp9010018","source":"openalex"},{"id":"oa:W4406239429","type":"article-journal","title":"Digital twin enabled smart microgrid system for complete automation: An overview","abstract":"• This paper provides a structured framework for constructing Digital Twin-enabled Smart Microgrids, emphasizing automation to enhance device intelligence. • It identifies critical automation standards and proposes adaptable modifications to support evolving DT applications within smart grids. • Through a comparative analysis, the paper highlights key challenges in situational awareness, security, and resilience, offering potential DT-based solutions. • The study introduces new use cases for Digital Twin technology in optimizing energy management and grid reliability in microgrid environments. • By envisioning future applications, this paper outlines the role of DT in advancing sustainable, resilient, and efficient energy systems. Recent advancements in communication technology (CT) have ignited significant interest in the cutting-edge concept of the digital twin (DT), which holds the potential to revolutionize smart microgrid systems (SMGs). This study delves into the concepts and essential steps involved in constructing a DT-enabled smart microgrid (DT-SMG), emphasizing the necessity for complete automation to enhance device intelligence. Additionally, the paper discusses implementation standards for automation and the need for further modifications to accommodate future applications. The objective is to explore important DT-SMG use cases, and discuss the associated problems and potential solutions within DT-based automation frameworks. Recognizing the criticality of situational awareness, security, and resilience in DT-SMGs, the paper conducts a comparative study, highlighting the pros and cons gleaned from existing literature. These findings offer readers a comprehensive perspective, empowering them to develop and deploy DT technology across a spectrum of power system applications. Finally, the paper looks ahead to the future horizon of DT-SMGs.","author":[{"family":"Sahoo","given":"Buddhadeva"},{"family":"Panda","given":"Subhasis"},{"family":"Rout","given":"Pravat"},{"family":"Bajaj","given":"Mohit"},{"family":"Blazek","given":"Vojtech"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.rineng.2025.104010","URL":"https://doi.org/10.1016/j.rineng.2025.104010","source":"openalex"},{"id":"oa:W7127900063","type":"article-journal","title":"From Digital Twins to Immersive Manufacturing: XR and Gesture‐Based Control for Enhancing Human–Robot Collaboration","abstract":"ABSTRACT Digital twins (DTs) and immersive extended reality (XR) interfaces offer new opportunities for intuitive, human‐centred interaction in smart manufacturing. However, implementations often lack rigorous validation, quantitative performance analysis and assessment of scalability and robustness, especially in small‐scale or resource‐constrained manufacturing settings. This work proposes a modular metaverse framework integrating ROS2, Unity and Meta Quest devices to develop interactive, bidirectional DTs enhanced with gesture‐based and mixed reality (MR) control. The framework is demonstrated through a lab‐scale case study combining a robotic Wire Arc Additive Manufacturing (WAAM) system and a collaborative robot‐based laser‐cleaning station, showing broad applicability across industrial robotics. To evaluate usability, a preliminary user study with 17 participants was conducted, comparing a standard teach pendant with the proposed XR interface for a tool‐inspection task. Results show an 80% reduction in programming time and significant decreases in perceived workload. Measured end‐to‐end gesture‐to‐action latency ranged from 430 to 450 ms, representing suitable timeframe for high‐level interaction and task initiation. The study provides empirical user‐centred evidence for metaverse‐enabled interaction and discusses scalability, latency and industrial constraints. Aligned with the human‐centric intelligence principles of Industry 5.0, the proposed approach improves accessibility, operator well‐being and adaptability, contributing towards more inclusive and robust smart manufacturing systems.","author":[{"family":"Manoli","given":"Eleni"},{"family":"Mattera","given":"Giulio"},{"family":"Caggiano","given":"Alessandra"},{"family":"Marzano","given":"Adelaide"},{"family":"Nele","given":"Luigi"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1049/cim2.70055","URL":"https://doi.org/10.1049/cim2.70055","source":"openalex"},{"id":"oa:W4411990492","type":"article-journal","title":"Digital twins for dynamic life cycle assessment in the built environment","abstract":"Dynamic life cycle assessment (LCA) integrated with digital twin technologies is emerging as a transformative approach to evaluating and managing environmental performance in the built environment. This study presents the Building Life-cycle Digital Twin (BLDT) framework-a novel methodology that combines real-time data from Internet of Things (IoT) devices, machine learning algorithms, and semantic interoperability to deliver dynamic, predictive, and high-resolution LCA for construction and infrastructure systems. The framework, developed within the Computational Urban Sustainability Platform (CUSP), addresses the limitations of traditional static LCA by enabling continuous, data-driven sustainability assessments. Incorporating predictive modelling, BLDT empowers stakeholders with timely insights into energy use, emissions, and health and safety performance, supporting proactive environmental decision-making. Validated through a case study at the Port of Grimsby, the BLDT framework facilitated a 25% reduction in energy consumption while enhancing operational efficiency. These results demonstrate the model's potential to support decarbonisation strategies, regulatory compliance, and long-term planning in the construction sector. By operationalising dynamic LCA through digital twins, this research contributes to the advancement of real-time sustainability analytics and resilient urban development.","author":[{"family":"Petri","given":"Ioan"},{"family":"Amin","given":"Amin"},{"family":"Ghoroghi","given":"Ali"},{"family":"Hodorog","given":"Andrei"},{"family":"Rezgui","given":"Yacine"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.scitotenv.2025.179930","URL":"https://doi.org/10.1016/j.scitotenv.2025.179930","source":"openalex"},{"id":"oa:W4414350755","type":"article-journal","title":"A new era for digital twins: progress and industry adoption","abstract":"This systematic review provides a comprehensive evaluation of the core components and diverse applications of digital twin (DT) technology, emphasising its transformative influence across key sectors. A DT is a dynamic digital replica of a physical asset or system, developed through the integration of real-time sensor data, advanced communication protocols, and computational intelligence. Essential elements include machine learning for predictive analytics, edge computing for low-latency decision-making, and high-resolution imaging and 3D visualisation for enhanced model fidelity. Blockchain technologies strengthen data security and integrity, while adaptive feedback mechanisms enable continuous learning and system optimisation. DT applications span various industries. In manufacturing, they enhance productivity through predictive maintenance and process refinement. In healthcare, DTs support personalised diagnostics, treatment optimisation, and telemedicine. Urban planning benefits from DTs in the creation of smart, sustainable infrastructure. In the energy sector, they facilitate grid stability and renewable integration. Additionally, DTs are used in immersive training simulations, autonomous vehicle validation, and resilient supply chain management. Industries such as aerospace, automotive, marine, oil and gas, and transportation increasingly adopt DTs to boost operational efficiency, minimise risks, and foster innovation. This review synthesises recent technological advances and identifies critical research directions for advancing secure, scalable, and interoperable DT ecosystems.","author":[{"family":"Hasan","given":"Sk"},{"family":"Crawford","given":"Colin"},{"family":"Hasan","given":"SKK"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/27525783.2025.2555877","URL":"https://doi.org/10.1080/27525783.2025.2555877","source":"openalex"},{"id":"oa:W4407343310","type":"article-journal","title":"The philosophical foundations of digital twinning","abstract":"Abstract Digital twins are a new paradigm for our time, offering the possibility of interconnected virtual representations of the real world. The concept is very versatile and has been adopted by multiple communities of practice, policymakers, researchers, and innovators. A significant part of the digital twin paradigm is about interconnecting digital objects, many of which have previously not been combined. As a result, members of the newly forming digital twin community are often talking at cross-purposes, based on different starting points, assumptions, and cultural practices. These differences are due to the philosophical world-view adopted within specific communities. In this paper, we explore the philosophical context which underpins the digital twin concept. We offer the building blocks for a philosophical framework for digital twins, consisting of 21 principles that are intended to help facilitate their further development. Specifically, we argue that the philosophy of digital twins is fundamentally holistic and emergentist. We further argue that in order to enable emergent behaviors, digital twins should be designed to reconstruct the behavior of a physical twin by “dynamically assembling” multiple digital “components”. We also argue that digital twins naturally include aspects relating to the philosophy of artificial intelligence, including learning and exploitation of knowledge. We discuss the following four questions (i) What is the distinction between a model and a digital twin? (ii) What previously unseen results can we expect from a digital twin? (iii) How can emergent behaviours be predicted? (iv) How can we assess the existence and uniqueness of digital twin outputs?","author":[{"family":"Wagg","given":"David"},{"family":"Burr","given":"Christopher"},{"family":"Shepherd","given":"Jason"},{"family":"Conti","given":"Zack"},{"family":"Enzer","given":"Mark"},{"family":"Niederer","given":"Steven"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1017/dce.2025.4","URL":"https://doi.org/10.1017/dce.2025.4","source":"openalex"},{"id":"oa:W4415171625","type":"article-journal","title":"Multi-level dynamics response-based resilient production control for digital twin-enabled modular manufacturing systems","abstract":"The increasing demand for customized products and the highly competitive market have driven a shift from conventional manufacturing to flexible modular manufacturing. Although the flexibility in operations and process routes of modular manufacturing systems (MMS) helps address the complexities of mass-customized production, this high flexibility also increases the complexity of production operations, causing frequent production dynamics. To mitigate the adverse effects of these dynamics on production plans in MMS, a multi-level dynamic response-based resilient production control concept was proposed for digital twin-enabled MMS. The architecture of digital twin-enabled MMS was designed to simulate production schemes and predict performance indicators, and its digital space layer consisted of three-level digital twin models corresponding to workstation, process route, and manufacturing system levels. To effectively manage production dynamics across these levels, a resilient production control mechanism was proposed within the digital twin-enabled MMS. A completion delay prediction-based dynamic production scheduling approach and three levels of dynamic response strategies for reconfiguring process service routes was then developed, respectively. The feasibility and effectiveness of the proposed method were validated through theory-based comprehensive simulations, demonstrating a general way to achieving resilient production control in highly dynamic manufacturing environments by digital twin technology and flexible manufacturing resource reconfigurations.","author":[{"family":"Liu","given":"Lei"},{"family":"Shen","given":"Weiming"},{"family":"Thürer","given":"Matthias"},{"family":"Ma","given":"Lin"},{"family":"Zhang","given":"Zhongfei"},{"family":"Yuan","given":"Mingze"},{"family":"Shen","given":"Weiming"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/0951192x.2025.2563255","URL":"https://doi.org/10.1080/0951192x.2025.2563255","source":"openalex"},{"id":"oa:W7134918708","type":"article-journal","title":"Synergy between Digital Twin and Cyber-Physical System in Manufacturing","abstract":"The rapid digitalization of manufacturing systems has led to the emergence of Cyber-Physical Systems (CPS) and Digital Twins (DTs) as key enablers of the Industry 4.0 revolution. While CPS provides real-time sensing, communication, and control across physical and cyber domains, DT offers a virtual mirror of assets and processes, enabling simulation, prediction, and optimization. The integration of these two paradigms creates a synergistic framework that enhances adaptability, resilience, and sustainability in modern manufacturing. This chapter explores the synergy between CPS and DT, emphasizing how their convergence enables real-time decision-making, predictive maintenance, process optimization, and lifecycle management. The conceptual architecture of DT–CPS integration is presented, highlighting data acquisition, interoperability, and feedback mechanisms. Representative applications in smart manufacturing, energy management, and automation are discussed to demonstrate their potential for sustainable industrial transformation. Finally, the chapter outlines implementation challenges, emerging research directions, and the evolving role of DT–CPS ecosystems in shaping intelligent, resource-efficient manufacturing systems aligned with the goals of Industry 5.0.","author":[],"issued":{"date-parts":[[2026]]},"DOI":"10.1201/9781003504825-9","URL":"https://doi.org/10.1201/9781003504825-9","source":"openalex"},{"id":"oa:W4408179778","type":"article-journal","title":"Towards safe motion planning for industrial human-robot interaction: A co-evolution approach based on human digital twin and mixed reality","abstract":"Advanced human-robot interaction (HRI) is essential for the next-generation human-centric manufacturing mode such as “Industry 5.0”. Despite recent mutual cognitive approaches can enhance the understanding and collaboration between humans and robots, these methods often rely on predefined rules and are limited in adapting to new tasks or changes of the working environment. These limitations can hinder the popularization of collaborative robots in dynamic manufacturing environments, where tasks can be highly variable, and unforeseen operational changes frequently occur. To address these challenges, we propose a co-evolution approach for the safe motion planning of industrial human-robot interaction. The core idea is to promote the evolution of human worker’s safe operation cognition as well as the evolution of robot’s safe motion planning strategy in a unified and continuous framework by leveraging human digital twin (HDT) and mixed reality (MR) technologies. Specifically, HDT captures real-time human behaviors and postures, which enables robots to adapt dynamically to the changes of human behavior and environment. HDT also refines deep reinforcement learning (DRL)-based motion planning, allowing robots to continuously learn from human actions and update their motion strategies. On the other hand, MR superimposes rich information regarding the tasks and robot in the physical world, helping human workers better understand and adapt to robot’s actions. MR also provides intuitive gesture-based user interface, further improving the smoothness of human-robot interaction. We validate the proposed approach’s effectiveness with evaluations in realistic manufacturing scenarios, demonstrating its potential to advance HRI practice in the context of smart manufacturing.","author":[{"family":"Feng","given":"Bohan"},{"family":"Wang","given":"Zeqing"},{"family":"Yuan","given":"Lianjie"},{"family":"Zhou","given":"Qi"},{"family":"Chen","given":"Yulin"},{"family":"Bi","given":"Youyi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.rcim.2025.103012","URL":"https://doi.org/10.1016/j.rcim.2025.103012","source":"openalex"},{"id":"oa:W7133198036","type":"article-journal","title":"Digital Twin-Driven Lean Manufacturing: Optimizing Value Stream Flow","abstract":"This research investigates the integration of Digital Twin (DT) technology within Lean Manufacturing frameworks to optimize value stream flow, minimize waste, and enhance real-time decision-making capabilities. By synthesizing foundational concepts of Lean Manufacturing and DT, the paper examines the layered DT architecture, covering the physical, virtual, and communication interfaces, alongside Lean tools like Kaizen, Kanban, and Just-in-Time (JIT) that facilitate continuous process improvement. Case studies, particularly in the automotive sector, demonstrate DT's ability to increase production efficiency through predictive maintenance and simulation-based scenario planning, supporting Lean's waste reduction objectives. However, the paper identifies key implementation challenges, including legacy system integration, workforce adaptation, and data interoperability. Additionally, cybersecurity and data integrity concerns are analysed to highlight essential protocols for safe DT deployment. Future research directions propose advancements like AI-powered DTs, blockchain for enhanced traceability, and edge computing for low-latency applications. Key insights from industry case studies underscore the transformative impact of DTs on production efficiency, organizational resilience, and sustainable manufacturing outcomes, positioning Digital Twin technology as a cornerstone for next-generation lean manufacturing systems","author":[{"family":"Nwamekwe","given":"Charles"},{"family":"Vitalis","given":"Ewuzie"},{"family":"Chidiebube","given":"Igbokwe"},{"family":"Nwabunwanne","given":"Emeka"},{"family":"Ono","given":"Chukwuma"}],"issued":{"date-parts":[[2025]]},"DOI":"10.17977/um010v8i12025p1-13","URL":"https://doi.org/10.17977/um010v8i12025p1-13","source":"openalex"},{"id":"oa:W4415737254","type":"article-journal","title":"Barriers and Overcoming Strategies for Adopting Digital Twin in the Manufacturing Industry","abstract":"This study investigates the main barriers and overcoming strategies for the implementation of digital twin (DT) technology in the manufacturing industry. The research, conducted in a two-step process, first employed a modified Delphi method with seasoned industry experts to identify and classify main barriers. Later, the best-worst method (BWM) ranked main barriers and mitigation strategies. The most critical challenges determined are the integration of legacy systems, high implementation cost, and data quality. Retrofitting hardware, rolling out cloud services, and edge computing were determined as the best solutions. The findings give real-world insights for organizations seeking to deploy DTs in a prioritized set of tasks and activities applicable to the manufacturing context.","author":[{"family":"Larmelina","given":"Stefano"},{"family":"Silva","given":"Alessandro"},{"family":"Risso","given":"Lucas"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1142/s0219686727500260","URL":"https://doi.org/10.1142/s0219686727500260","source":"openalex"},{"id":"oa:W4411342719","type":"article-journal","title":"Digital Twins to Support Smart Manufacturing System Design and Ramp up","abstract":"Although there is a significant amount of research done on Digital Twin (DT) for Smart Manufacturing Systems, there is a lack of research focused on implementing DT in the design and ramp-up phases of companies. This research aims to explore possibilities for the effective implementation of DT in Smart Manufacturing Systems Design (SMSD) and ramp-up processes for Small and Medium-sized Enterprises (SMEs) and the findings may also be applicable to larger companies. Different case studies were conducted to gain insightful information on the actual implementation of digital twinning. During the initial case study, a DT prototype was developed on a DT software package to investigate the essential steps to create a successful DT. In the second case study, a DT Instance was developed. This study specifically investigated the application of DTs for virtual commissioning and connection to the IoT. The third case study examined the support among stakeholders. This research identified a manner for the successful implementation of digital twinning during smart manufacturing systems design and highlights the benefits that can be achieved by implementing DT during design processes.","author":[{"family":"Ginkel","given":"Marco"},{"family":"Yazdi","given":"Poorya"},{"family":"Rupert","given":"Thijs"},{"family":"Reijers","given":"Johan"},{"family":"Thiede","given":"Sebastian"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.procir.2025.02.221","URL":"https://doi.org/10.1016/j.procir.2025.02.221","source":"openalex"},{"id":"oa:W7125001568","type":"article-journal","title":"Leveraging Blockchain and Digital Twins for Low-Carbon, Circular Supply Chains: Evidence from the Moroccan Manufacturing Sector","abstract":"As global supply chains face increasing pressure to reconcile economic efficiency, environmental responsibility, and ethical transparency, emerging digital technologies offer unprecedented opportunities for sustainable transformation. This article examines this dynamic in the context of the Moroccan industrial sector, with particular reference to blockchain and digital twin technologies. The study employs a rigorous mixed-methods design, combining an in-depth qualitative exploration with 30 industry professionals and a Partial Least Squares Structural Equation Modeling (PLS-SEM) model based on survey data from 125 Moroccan manufacturing firms. The findings highlight the synergistic contribution of blockchain and digital twins in enabling circular, low-carbon, and resilient supply chains. Blockchain adoption strengthens environmental impact traceability, data reliability, and responsible governance, while digital twin systems enhance eco-efficiency through real-time modeling and predictive flow simulation. Circular integration emerges as a critical enabler, significantly amplifying the positive effects of both technologies by aligning physical and informational flows within closed-loop processes. With its strong empirical grounding and contextual relevance to an emerging economy, this research provides actionable insights for policymakers, industrial managers, and supply chain practitioners committed to accelerating the sustainable transformation of production systems. It also offers a renewed understanding of how digitalization and circularity jointly support environmental performance within industrial ecosystems.","author":[{"family":"Abdallah-Ou-Moussa","given":"Soukaina"},{"family":"Wynn","given":"Martín"},{"family":"Rouaine","given":"Zakaria"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18020991","URL":"https://doi.org/10.3390/su18020991","source":"openalex"},{"id":"doi:10.1145/3746709.3746777","type":"article-journal","title":"A Digital Twin Case Study on Prefabricated Component Factory for Offsite Manufacturing of Buildings","abstract":"With the transformation of the construction manufacturing industry, off-site manufacturing technologies are gradually becoming mainstream. The existing digital systems of Prefabricated Component (PC) factories have problems such as incomplete presentation, inaccurate expression of physical entities in the information space, and weak real-time synchronization ability. To address these issues, we propose a digital twin system architecture applied to PC factories, which is divided into the physical entity layer, the digital twin entity layer, and the user entity layer. On this basis, relying on the Hannan PC Factory of China Construction Third Engineering Bureau Science and Technology Innovation Industry Development Co., Ltd., and based on physical systems such as the Internet of Things (IoT), Programmable Logic Controllers (PLC), central control systems, and Manufacturing Execution Systems (MES), a complete digital twin system has been designed and implemented. Through the association and mapping between digital twin virtual entities and physical entities, staff can monitor the production operation status in a realistic three-dimensional visual way in real time and make decisions. The actual operation effect has verified the effectiveness of the system framework, solved the problems that traditional PC factory digital systems cannot comprehensively present and accurately express the physical entities of PC factories and synchronize the production process in real time, and can lay a solid foundation for the subsequent dynamic prediction and decision optimization of prefabricated component production facilities.","author":[{"family":"Tan","given":"Zhenyuan"},{"family":"Tu","given":"Ming"},{"family":"He","given":"Xinglin"},{"family":"Chen","given":"Bingyong"},{"family":"Zhao","given":"Yishi"},{"family":"Shang","given":"Jianga"},{"family":"Tan","given":"Z"},{"family":"He","given":"Xinsheng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1145/3746709.3746777","URL":"https://doi.org/10.1145/3746709.3746777","source":"openalex"},{"id":"oa:W4407793420","type":"article-journal","title":"Polycaprolactone/F18 Bioactive Glass Scaffolds Obtained via Fused Filament Fabrication","abstract":"High Resolution Image Download MS PowerPoint Slide The treatment duration for tissue defects, such as bone fractures, can be minimized by employing scaffolds. These structures can provide mechanical stability and stimulate cell adhesion and proliferation upon implantation. Fused filament fabrication allows the production of scaffolds from biodegradable polymers while enabling control over geometry and architecture for specific biomedical applications. Cellular activity can be enhanced by incorporating bioactive glasses into the polymer. In this investigation, 10% by weight of F18, a highly bioactive glass that can be obtained as continuous fibers, was incorporated into polycaprolactone via twin-screw extrusion molding. The bioactive fibers were mechanically characterized, and a polymer composite containing F18 was three-dimensional (3D) printed for the first time. Compounding resulted in a significant reduction in fiber length. The composites were assessed for thermal stability, mechanical properties, morphology, pore size, wettability, mineralization, and cell viability. Thermogravimetric analyses indicated that the bioactive glass lowers the decomposition temperature of polycaprolactone, a phenomenon commonly observed in polyesters. Although no improvements in mechanical properties were observed, incorporating F18 significantly enhanced cell viability after 7 days of in vitro testing, highlighting the potential of this composite for Bone Tissue Engineering.","author":[{"family":"Augusto","given":"Thiago"},{"family":"Crovace","given":"Murilo"},{"family":"Pinto","given":"Leonardo"},{"family":"Costa","given":"L"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1021/acsapm.4c03439","URL":"https://doi.org/10.1021/acsapm.4c03439","source":"openalex"},{"id":"oa:W7117305020","type":"article-journal","title":"State Regulation and Strategic Management of Water Resources and Wastewater Treatment at the Regional Level: Institutional and Technological Solutions","abstract":"Regional water systems face growing pressure from climate variability, water scarcity, and increasingly complex wastewater pollution. These challenges require governance models that integrate institutional coordination with effective technological solutions. This review is based on a structured analysis of peer-reviewed literature indexed in Scopus, Web of Science, and ScienceDirect, covering publications from approximately 2014 to 2025. The findings show that clearly defined institutional roles, basin-level coordination, stable financing mechanisms, and active stakeholder participation significantly improve governance outcomes. Technological advances such as membrane filtration, advanced oxidation processes, nature-based treatment systems, and digital monitoring platforms enhance treatment efficiency, resilience, and opportunities for resource recovery. Regions differ widely in their ability to adopt these solutions, mainly due to variations in governance coherence, investment capacity, and climate-adaptation readiness. The review highlights the need for policy frameworks that align institutional reforms with technological modernization, including the adoption of basin-based planning, digital decision-support systems, and circular water-economy principles. These measures provide actionable guidance for policymakers and regional authorities seeking to strengthen long-term water security and wastewater management performance.","author":[{"family":"Kudaibergenova","given":"Rabiga"},{"family":"Bolatbek","given":"Asparukh"},{"family":"Spanov","given":"Magbat"},{"family":"Baibazarova","given":"Elvira"},{"family":"Orynbayev","given":"Seitzhan"},{"family":"Murzakasymova","given":"Nazgul"},{"family":"Kabdushev","given":"Arman"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/w18010063","URL":"https://doi.org/10.3390/w18010063","source":"openalex"},{"id":"oa:W7164653706","type":"article-journal","title":"Framework for Integrating Digital Twin Technology in the Real Estate Industry (CREST)","abstract":"The majority of commercial real estate (CRE) Digital Twin (DT) pilots do not progress to production. The core obstacle is not technology, it is the persistent fragmentation of lifecycle data across BIM platforms, building automation systems, IoT networks, and enterprise software. Systems that were never designed to share information cannot simply be integrated by building another platform atop them. This paper introduces CREST, the Commercial Real Estate Smart Twin framework; a seven-tier implementation pathway that links strategic business intent to measurable operational outcomes across the CRE lifecycle. The seven tiers are: Strategic Canvas, Value Streams, Adoption Model, Reference Architecture, Deployment Playbook, Maturity Model, and ROI & Benefits Matrix. CREST draws on foundational DT literature, industrial reference architectures from the Industry IoT Consortium, and learnings from 80+ engagements within global CRE organizations. The framework directly confronts four challenges that repeatedly kill CRE twin programmes: fragmented data across lifecycle stages, reactive maintenance cultures, mounting ESG/CSRD reporting obligations, and post-pandemic space utilization volatility. For each, CREST embeds minimum data requirements, governance protocols, and integration patterns into its deployment playbook and reference architecture. Case evidence shows a 20% drop in delayed projects and a 30% gain in Net Promoter Score, alongside documented reductions in operating cost. CREST’s contribution is deliberately practitioner-facing: a repeatable integration blueprint that reduces delivery risk at both building and portfolio scale. Keywords: sustainability reporting; Internet of things; Digital Twin (DT); Commercial Real Estate (CRE); Building Information Management (BIM); Facility Management; Maturity Model; CREST framework; Environmental Social and Governance (ESG) Reporting","author":[{"family":"Koppalkar","given":"Shivanand"},{"family":"Krishan","given":"Vivek"},{"family":"Gupte","given":"Yogesh"},{"family":"Gunasekaran","given":"Arunkumar"},{"family":"Udayakumar","given":"Kathiravan"},{"family":"Kadam","given":"Prachi"}],"issued":{"date-parts":[[2026]]},"DOI":"10.64823/ijter.2606008","URL":"https://doi.org/10.64823/ijter.2606008","source":"openalex"},{"id":"oa:W7124263296","type":"article-journal","title":"Large language models in global health","abstract":"Large language models (LLMs) are emerging as powerful tools in healthcare, with a growing role in global health, particularly in low- and middle-income countries (LMICs). This Perspective examines the current progress, challenges and prospects of LLMs in addressing health system disparities and supporting the achievement of the Sustainable Development Goals (SDGs). While high-income countries dominate the development and deployment of LLMs, LMICs face substantial barriers. These include limited digital infrastructure, a scarcity of locally relevant data, regulatory gaps, under-representation of local languages and dialects, and challenges related to privacy and data security. The limited availability of local expertise, capacity building programmes and sustained technical support remains a key barrier to scaling LLMs in LMICs. Nonetheless, case studies highlight how mobile-based LLM applications, hybrid artificial intelligence systems and open-weight models like DeepSeek are enhancing access to care, improving diagnostics and supporting clinical decision-making in resource-limited settings. Key risks include model hallucinations, equity concerns and environmental impacts. These underscore the need for rigorous validation, localized fine-tuning and global governance frameworks. The implementation of LLMs with contextual sensitivity, responsible oversight and codevelopment partnerships is important to avoid perpetuating health inequities. With the right safeguards and strategic investments in capacity building, LLMs have the potential to transform global health by bridging divides in access, augmenting overburdened health workforces, and enabling scalable and cost-effective innovations for the most underserved communities. Large language models (LLMs) are emerging as powerful tools in healthcare, with a growing role in global health, particularly in low- and middle-income countries. This Perspective examines the current progress, challenges and prospects of LLMs in addressing health system disparities and supporting achievement of the Sustainable Development Goals.","author":[{"family":"Ong","given":"Jasmine"},{"family":"Ning","given":"Yilin"},{"family":"Yang","given":"Rui"},{"family":"Bitterman","given":"Danielle"},{"family":"Liu","given":"Xiaoxuan"},{"family":"Tham","given":"Yih"},{"family":"Collins","given":"Gary"},{"family":"Tavárez","given":"Michelle"},{"family":"Mateen","given":"Bilal"},{"family":"Amissah-Arthur","given":"Kwesi"},{"family":"Sheng","given":"Bin"},{"family":"Tan","given":"Iain"},{"family":"Hong","given":"Chuan"},{"family":"Cheng","given":"Lionel"},{"family":"Goldstein","given":"Benjamin"},{"family":"Le","given":"Phuoc"},{"family":"Liu","given":"Yun"},{"family":"Tan","given":"Hiang"},{"family":"Ong","given":"Marcus"},{"family":"Wagner","given":"Siegfried"},{"family":"Denniston","given":"Alastair"},{"family":"Keane","given":"Pearse"},{"family":"Car","given":"Josip"},{"family":"Chapman","given":"Wendy"},{"family":"Moons","given":"Karel"},{"family":"Wong","given":"Tien"},{"family":"Topol","given":"Eric"},{"family":"Liu","given":"Nan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s44360-025-00024-7","URL":"https://doi.org/10.1038/s44360-025-00024-7","source":"openalex"},{"id":"oa:W7130828561","type":"article-journal","title":"AI-Driven Virtual Power Plants: A Comprehensive Review","abstract":"The rapid proliferation of distributed energy resources (DERs), including photovoltaics, wind power, battery energy storage, and electric vehicles, has transformed traditional power systems into highly decentralized and data-rich environments. Virtual power plants (VPPs) have emerged as a key mechanism for aggregating these heterogeneous assets and enabling coordinated control, market participation, and grid-support functions. Recent advances in artificial intelligence (AI) have further elevated the scalability, autonomy, and responsiveness of VPP operations. This paper presents a comprehensive review of AI for VPPs, organized around a taxonomy of machine learning, deep learning, reinforcement learning, and hybrid approaches, and examines how these methods map to core VPP functions such as forecasting, scheduling, market bidding, aggregation, and ancillary services. In parallel, we analyze enabling architectural frameworks—including centralized cloud, distributed edge, hybrid cloud–edge collaboration, and emerging 5G/LEO satellite communication infrastructures—that support real-time data exchange and scalable deployment of intelligent control. By integrating methodological, functional, and architectural perspectives, this review highlights the evolution of VPPs from rule-based coordination to intelligent, autonomous energy ecosystems. Key research challenges are identified in data quality, model interpretability, multi-agent scalability, cyber-physical resilience, and the integration of AI with digital twins and edge-native computation. These findings outline promising directions for next-generation intelligent VPPs capable of delivering secure, flexible, and self-optimizing DER aggregation at scale.","author":[{"family":"Li","given":"Jian"},{"family":"Wang","given":"Chenxi"},{"family":"Liu","given":"Yonghe"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19041084","URL":"https://doi.org/10.3390/en19041084","source":"openalex"},{"id":"oa:W7163653407","type":"article-journal","title":"From Aqueous Stability to Mpro Inhibition: A Five-Layer Digital Twin Framework Integrating Molecular Dynamics Data for Allicin/Al12N12 Nanocomplexes against SARS-CoV-2","abstract":"Building upon the previously published Allicin Digital Twin v2.0 (Morais et al., IJRPAS 2026), this study presents Digital Twin v3.0 — a five-layer computational framework that integrates, for the first time, real molecular dynamics (MD) trajectory data from Discovery Studio CHARMm36 simulations (Li & Cheng, 2023) for the alliin–6LU7 and allicin–6LU7 complexes into an adaptive multi-scale model. Layer 4 assimilates the RMSD and RMSF trajectories from Li & Cheng, establishing a structural calibration anchor for the SARS-CoV-2 main protease (Mpro, PDB: 6LU7) active pocket (HIS41, CYS44, MET49, PRO52, TYR54, MET165, ASP187, ARG188, GLN189, GLN192). Layer 5 introduces two novel metrics: the Nanocage Enhancement Factor for Inhibition (NEFI) and the Stability–Binding Integrated Score (SBIS), derived from a Hill–Langmuir pharmacodynamic model coupled to the ODE degradation engine. The Allicin/Al₁₂N₁₂ complex achieves NEFI = 14.0× and SBIS = 320.7 relative to free allicin against Mpro. Integration of real MD data reduced the predicted mean RMSF in the Mpro active pocket from 1.088 Å (allicin–6LU7, Li & Cheng) to a predicted 0.163 Å for Allicin/Al₁₂N₁₂, a 6.66-fold reduction consistent with the 44-fold B-factor decrease already established in v2.0. The Digital Twin framework's Gaussian Process surrogate (RMSD equilibrium: 0.485 Å, SASA: 6.96 nm²) is validated against the real CHARMm36 RMSD plateau of 1.10 nm for alliin–6LU7. The study closes the gap between static DFT thermodynamics and time-resolved binding dynamics, while identifying in vitro stability assays for Allicin/Al₁₂N₁₂ under physiological conditions as the critical next experimental step.","author":[{"family":"Morais","given":"Jefferson"},{"family":"Sena","given":"Heliel"},{"family":"Barbosa","given":"Larissa"},{"family":"Gomes","given":"Lanna"}],"issued":{"date-parts":[[2026]]},"DOI":"10.71431/ijrpas.2026.5503","URL":"https://doi.org/10.71431/ijrpas.2026.5503","source":"openalex"},{"id":"oa:W7156605582","type":"article-journal","title":"From Digital Twin to Digital Cognition: A Multilevel Model of Algorithmic Intelligence in Smart Manufacturing Systems","abstract":"This study extends the dominant digital twin paradigm by introducing the concept of digital cognition to explain the evolving nature of smart manufacturing systems. While prior research largely conceptualizes digital twins as passive representations for monitoring and simulation, we argue that advanced manufacturing systems increasingly exhibit algorithmic intelligence through the integration of predictive models, real-time control, and adaptive feedback mechanisms. Drawing on an in-depth case study of a fully automated precision grinding system, this paper develops a multilevel model that explains how algorithmic intelligence emerges from the interaction of three interdependent layers: (1) a perceptual infrastructure enabled by high-resolution sensor networks and real-time data acquisition; (2) an algorithmic reasoning layer driven by machine learning models such as LSTM-based prediction and thermal deformation compensation algorithms; and (3) an autonomous actuation layer realized through high-speed synchronized control architectures. The findings show that the emergence of digital cognition transforms manufacturing systems from reactive optimization tools into proactive and self-adaptive agents, significantly enhancing precision, efficiency, and operational reliability. This transformation also reconfigures control structures by shifting decision-making authority from human operators to algorithmically mediated systems, raising important implications for governance and human–machine interaction.","author":[{"family":"Ruan","given":"Xiaole"},{"family":"Zeng","given":"Yiyang"},{"family":"Shao","given":"Hongjian"},{"family":"Zhipeng","given":"Zhipeng"},{"family":"Ying","given":"Ying"},{"family":"Jin","given":"Junjiang"},{"family":"Lin","given":"Jijun"},{"family":"Ni","given":"Enwei"}],"issued":{"date-parts":[[2026]]},"DOI":"10.65192/xpk5hs34","URL":"https://doi.org/10.65192/xpk5hs34","source":"openalex"},{"id":"oa:W4411568663","type":"article-journal","title":"Green and intelligent: the role of AI in the climate transition","abstract":"Abstract Artificial Intelligence (AI) can play a powerful role in supporting climate action while boosting sustainable and inclusive economic growth. However, limited research exists on the potential influence of AI on the low-carbon transition. Here we identify five areas through which AI can help build an effective response to climate threats. We estimate the potential for greenhouse gas (GHG) emissions reductions through AI applications in three key sectors—power, food, and mobility—which collectively contribute nearly half of global emissions. This is compared with the increase in data centre-related emissions generated by all AI-related activities.","author":[{"family":"Stern","given":"Nicholas"},{"family":"Romani","given":"Mattia"},{"family":"Pierfederici","given":"Roberta"},{"family":"Braun","given":"Manuel"},{"family":"Barraclough","given":"Daniel"},{"family":"Lingeswaran","given":"Shajeeshan"},{"family":"Weirich-Benet","given":"Elizabeth"},{"family":"Niemann","given":"Niklas"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s44168-025-00252-3","URL":"https://doi.org/10.1038/s44168-025-00252-3","source":"openalex"},{"id":"oa:W7123356034","type":"article-journal","title":"Evolution and Emerging Frontiers in Point Cloud Technology","abstract":"Point cloud intelligence integrates advanced technologies such as Light Detection and Ranging (LiDAR), photogrammetry, and Artificial Intelligence (AI) to transform transportation infrastructure management. This review highlights state-of-the-art advancements in denoising, registration, segmentation, and surface reconstruction. A detailed case study on three-dimensional (3D) mesh generation for railway fastener monitoring showcases how these techniques address challenges like noise and computational complexity while enabling precise and efficient infrastructure maintenance. By demonstrating practical applications and identifying future research directions, this work underscores the transformative potential of point cloud intelligence in supporting predictive maintenance, digital twins, and sustainable transportation systems.","author":[{"family":"Wang","given":"Wenjuan"},{"family":"Ehsan","given":"Haleema"},{"family":"Qiu","given":"Shi"},{"family":"Rahman","given":"Tariq"},{"family":"Wang","given":"Jin"},{"family":"Zaheer","given":"Qasim"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/electronics15020341","URL":"https://doi.org/10.3390/electronics15020341","source":"openalex"},{"id":"oa:W4415503820","type":"article-journal","title":"Aspects and Ideas for the FMI-based Modeling of Railway Digital Twins","abstract":"This papers reports on activities in the European projectMOTIONAL that aims at the development of a digital twinenvironment which facilities the modularity,interoperability and composability of complex digital twinassemblies of railway systems. The approach that refers tothe Functional Mock-up Interface is justified by adiscussion of the comparable activities in industry and inthe automotive field compared to particularities in therailway system. The work was initiated by the selection andanalysis of nine use cases. An introductory digital twinexample illustrates the current implementation status andrelated aspects, while an outlook presents the integrationinto the Federated Rail Data Space as the business case andas a vision of the activity.","author":[{"family":"Heckmann","given":"Andreas"},{"family":"Poßeckert","given":"Alexander"},{"family":"Adusumalli","given":"Vijaya"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3384/ecp21891","URL":"https://doi.org/10.3384/ecp21891","source":"openalex"},{"id":"oa:W4416386384","type":"article-journal","title":"Laser Technologies of Welding, Surfacing and Regeneration of Metals with HCP Structure (Mg, Ti, Zr): State of the Art, Challenges and Prospects","abstract":"Metals with a hexagonal close-packed (HCP) structure such as magnesium, titanium and zirconium constitute key structural materials in the aerospace, automotive, biomedical and nuclear energy industries. Their welding and regeneration by conventional methods is hindered due to the limited number of slip systems, high reactivity and susceptibility to the formation of defects. Laser technologies offer precise energy control, minimization of the heat-affected zone and the possibility of producing joints and coatings of high quality. This article constitutes a comprehensive review of the state of knowledge concerning laser welding, cladding and regeneration of HCP metals. The physical mechanisms of laser beam interactions are discussed including the dynamics of the keyhole channel, Marangoni flows and the formation of gas defects. The characteristics of the microstructure of joints are presented including the formation of α' martensite in titanium, phase segregation in magnesium and hydride formation in zirconium. Particular attention is devoted to residual stresses, techniques of cladding protective coatings for nuclear energy with Accident Tolerant Fuel (ATF) and advanced numerical modeling using artificial intelligence. The perspectives for the development of technology are indicated including the concept of the digital twin and intelligent real-time process control systems.","author":[{"family":"Zwoliński","given":"Adam"},{"family":"Samborski","given":"Sylwester"},{"family":"Rzeczkowski","given":"Jakub"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/ma18225237","URL":"https://doi.org/10.3390/ma18225237","source":"openalex"},{"id":"oa:W7141494263","type":"article-journal","title":"“Interaction Twin in the middle”: a distributed digital twin architecture to model team interactions and dynamics for deep space missions","abstract":"NASA’s Moon to Mars campaign emphasizes the need for crews and habitat systems to operate with increasing autonomy as communication delays with Earth grow beyond 5 minutes. The digital twin framework has emerged as a promising solution to monitor, diagnose, predict, and optimize space systems, but prior aerospace applications have largely centered on system autonomy rather than crew autonomy. As a result, current approaches under-represent the interaction dynamics needed by mission control to continuously evolve procedure and accomplish mission objectives. This work introduces an Interaction Digital Twin (IDT) framework that twins the interactions between humans and systems rather than focusing only on individual entities. Built on a distributed digital twin architecture with bidirectional information flow, the framework integrates three complementary types of twins: Digital Twins for habitat systems, Human Digital Twins (HDTs) for individual crew members, and Interaction Digital Twins that capture emergent phenomena such as team cohesion, trust calibration, coordination, and adaptive autonomy. Twinning the interactions moves aspects of command and control on-board, giving crew mission-control-like capabilities even during periods of communication delay. We apply the framework to an Artemis Phase II mission scenario, demonstrating how interaction-level twinning extends system-level modeling to support cognitive workload management, information sharing, and human–autonomy teaming. By elevating interactions to first-class, inference-capable elements within the digital twin architecture, this framework bridges the gap between technical system models and the human teaming constructs essential for self-sufficient deep space exploration.","author":[{"family":"Pischulti","given":"Patrick"},{"family":"Hwang","given":"Min"},{"family":"Mccomb","given":"Christopher"},{"family":"Arquilla","given":"Katya"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fpace.2026.1736392","URL":"https://doi.org/10.3389/fpace.2026.1736392","source":"openalex"},{"id":"oa:W4416418991","type":"article-journal","title":"Strategies to Enhance Stability of Cryopreservation Processes for Cell-Based Products","abstract":"The projected expansion of the global market for cell manufacturing, which contributes to regenerative medicine and cell therapies, warrants the designing and development of scalable cryopreservation processes for cell-based products (CBPs) for use in both standard and personalized therapies. However, the change in scale causes variations in process parameters, which affects the stability of the CBP quality. Therefore, the cryopreservation process for CBPs needs to be designed based on the concept of cell manufacturability and consideration of both engineering and biological aspects. In this review, we discussed strategies to enhance the quality stability of CBPs during cryopreservation, focusing primarily on four key processes: dispensing, freezing, storage, and thawing. Additionally, we discussed the application of simulation technologies because they aid in constructing digital twins for the designing and development of the cryopreservation process and facilitate efficiency with limited time and resources.","author":[{"family":"Uno","given":"Yuki"},{"family":"Hayashi","given":"Yusuke"},{"family":"Sugiyama","given":"Hirokazu"},{"family":"Okuda","given":"Jun"},{"family":"Nakamura","given":"Tetsuji"},{"family":"Kinooka","given":"Masahiro"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.biotechadv.2025.108763","URL":"https://doi.org/10.1016/j.biotechadv.2025.108763","source":"openalex"},{"id":"oa:W7203717547","type":"article-journal","title":"Digital technologies in rice blast disease management: a comprehensive systematic review of artificial intelligence, IoT, blockchain, and emerging digital tools","abstract":"Rice blast, caused by Magnaporthe oryzae (syn. Pyricularia oryzae ), is the most destructive fungal disease of rice, posing a major threat to global food security. Recent advances in artificial intelligence (AI) and digital agriculture have transformed disease detection, monitoring, and management; however, evidence on their effectiveness remains fragmented. This study presents a PRISMA 2020-compliant systematic review of AI-driven and digital technologies for rice blast management. A total of 2,056 records published between January 2021 and May 2026 were retrieved from PubMed, Scopus, Google Scholar, and Semantic Scholar, of which 109 peer-reviewed studies met the eligibility criteria following duplicate removal and multi-stage screening. Deep learning, particularly convolutional neural networks, dominated the literature, with reported detection accuracies reaching 99.75% under controlled conditions. YOLO-family models were the most widely used object detectors, while hyperspectral imaging, UAV-based remote sensing, and IoT-enabled sensing systems showed considerable promise for early and large-scale disease surveillance. Explainable AI was incorporated in only seven studies, and just 7% validated their models under real field conditions, highlighting a substantial gap between laboratory performance and practical deployment. No eligible studies investigated blockchain, digital twins, or federated learning for rice blast management. The review identifies key research priorities, including field-scale validation, pre-symptomatic detection, explainable AI, low-cost IoT platforms, blockchain-enabled traceability, and digital twin frameworks to enable robust, scalable, and trustworthy AI-driven rice blast management.","author":[{"family":"Garai","given":"Sandip"},{"family":"Manik","given":"Suryakant"},{"family":"Kanaka","given":"KK"},{"family":"Kumar","given":"Sudhir"},{"family":"Bhadana","given":"VP"},{"family":"Malviya","given":"Nishit"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.atech.2026.102488","URL":"https://doi.org/10.1016/j.atech.2026.102488","source":"openalex"},{"id":"oa:W7117582076","type":"article-journal","title":"The Mechanism of Holistic Smart Service Based on Digital Twin in the Metaverse Scenario","abstract":"The Metaverse, as the next evolutionary stage of the internet, is redefining interaction paradigms between humans, objects, and environments. In this context, traditional smart service models face challenges such as insufficient immersion, delayed personalization, and physical-virtual disconnection. This study explores how to construct a new \"Holistic Smart Service (HSS)\" mechanism in the Metaverse using Digital Twin (DT) technology. We first define HSS as a closed-loop service system integrating high-fidelity perception, real-time intelligent decision-making, immersive interaction, and value co-creation. Then, we propose a three-layer M-DT-HSS (Metaverse-Digital Twin-Holistic Smart Service) model and formally define its core components—service state space, user intention recognition function, and physical-digital synergy optimization function. Based on this model, we design a five-layer system architecture (perception, twin construction, AI engine, interaction presentation, and value co-creation layers) and elaborate on the implementation path from data fusion to service generation. Finally, we validate the proposed mechanism through a virtual smart community service prototype system. Experiments show that our approach outperforms traditional models in critical indicators: user satisfaction increases by 28.7%, service response latency decreases by 63.2%, and resource utilization efficiency improves by 41.5%. This research provides a theoretical framework for smart services in the Metaverse era and guides their engineering implementation.","author":[{"family":"Zhao","given":"Weibin"},{"family":"Zhang","given":"Jing"},{"family":"Li","given":"Xueyong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.54097/gxrbas91","URL":"https://doi.org/10.54097/gxrbas91","source":"openalex"},{"id":"oa:W7128498769","type":"manuscript","title":"Emerging Technologies as Enablers of Sustainable Management: A Comprehensive Framework — The Role of Saudi Arabia’s Vision 2030","abstract":"Emerging technologies are increasingly recognized as key drivers of sustainable man-agement, and Saudi Arabia presents a unique context in which digital transformation and sustainability have been strategically integrated under the Vision 2030 national reform agenda. While digitalization and sustainability have been examined inde-pendently in international scholarship, fewer studies have explored how emerging technologies enable sustainable management within national transformation contexts. This conceptual review synthesizes recent interdisciplinary literature to examine the enabling role of artificial intelligence (AI), blockchain, the Internet of Things (IoT), big data analytics, and cloud computing in advancing sustainability-oriented management practices in Saudi Arabia. Drawing on technology adoption and sustainability transition perspectives, the paper develops a conceptual framework linking technological capa-bilities to sustainability performance across environmental, social, economic, and gov-ernance (ESG) dimensions. The study outlines theoretical, managerial, and policy im-plications and proposes a future research agenda relevant to Saudi Arabia’s ongoing digital and sustainability transition. The paper contributes to bridging digital trans-formation and sustainability scholarship and provides a conceptual foundation for empirical studies within Gulf and emerging economy contexts.","author":[{"family":"Abaker","given":"Ahmed"},{"family":"Elgili","given":"Mustafa"},{"family":"Arees","given":"Bushara"}],"issued":{"date-parts":[[2026]]},"DOI":"10.20944/preprints202602.0741.v1","URL":"https://doi.org/10.20944/preprints202602.0741.v1","source":"openalex"},{"id":"oa:W7133241728","type":"article-journal","title":"AI-Driven Thermal Management Optimization for Lithium-Ion Battery Packs: A Surrogate Model Approach to Cell Spacing Design","abstract":"The article presents the possibilities of integrating artificial intelligence (through specific machine learning techniques) in the design and construction process of a battery in order to optimize its thermal management. The workflow starts from CFD thermal simulations (1C-rate) of a battery (16 Li-ion cells, type 18650, 4 × 4 arrangement), and based on the results, a complex thermal landscape is created through radial basis function (Rbf) interpolation. Furthermore, a robust neural network (NN) model is proposed and validated through the obtained performances, which is used further for the optimization of the design space (DSO) and multi-objective optimization (MOO) processes. The obtained results show that for DSO, a cell spacing of 1.37 mm is proposed for a maximum cell temperature of 25.53 °C, and in the case of MOO, a cell spacing of 2.64 mm (for minimum fan energy consumption). The main conclusion of the obtained results shows that the use of the NN model as a surrogate (the Digital Twin of a physical model) presents two great advantages in the process of designing a battery: running a CFD simulation for each point on the 2D grid would take hours, while the NN model can generate the entire map and find the optimum in less than 2 s, and moreover, thousands of additional points can be evaluated to find the thin limit of optimal models, effectively filtering out thousands of energy-consuming “suboptimal” configurations.","author":[{"family":"Mariașiu","given":"Florin"},{"family":"Szabo","given":"I"},{"family":"Mariasiu","given":"George"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/batteries12030086","URL":"https://doi.org/10.3390/batteries12030086","source":"openalex"},{"id":"oa:W7160085659","type":"article-journal","title":"Capacity Building in Africa: Training the Next Generation of Surveyors in Building High-Accuracy Digital Twins in South Africa","abstract":"Abstract. During the Federation Internationale des Geometres (FIG) Annual Meeting 2026 in Cape Town, the Department: Land Reform and Rural Development (DLRRD) will demonstrate its approach to high-resolution 3D mapping. By combining long-dwell DGNSS surveying, Continuously Operating Receiver Stations (CORS) DGNSS, and DGNSS-enabled drones, we have been able to map urban, rural, remote, and indigenous regions with 5 cm absolute accuracy, with a significant increase in efficiency over traditional ground surveying.The intention of the training is to provide a comprehensive and detailed demonstration of the methodology. For executives and directors, we will focus the first and last sessions on understanding how to be an effective consumer of high-accuracy 3D collection programmes. The intermediate sessions will take the participants through an accelerated collection program, including participating in the collection of a site in the Cape Town area. Participants will perform mission planning, collection planning, collection execution (including ground control surveying in the field), post-processing, quality control, exploitation into GIS/GISc and digital twins, and post-mission documentation, including an out brief to the executive/director participants.Historically, the maintenance of authoritative geodetic databases is the function of the national geodetic survey organizations, such as the Chief Directorate: National Geo-spatial Information (CD: NGI) in South Africa and their equivalent organizations worldwide. Every authoritative 3D database suffers from a burden of currency and completeness, in which the time between resurvey events defines an epoch during which the previous survey ages sufficiently to be marginally adequate for current needs. Issues of cost, access, and update frequency limit the quality, coverage, and currency of any curated database.The transition to hybrid surveying using drones provides a unique opportunity in that the drones directly exploit the local and national geodetic DGNSS framework and produce dense, high-resolution, highly accurate 3D imagery. This hybrid surveying approach was pioneered by the Survey of India in the Survey of Villages Abadi and Mapping with Improvised Technology in Village Area) (SVAMITVA) project that successfully mapped 60 million rural land parcels.South Africa has embraced this model and applied it directly to mapping 836 Indigenous regions that lack detailed property maps. DGNSS-enabled drone surveys extend the precision and accuracy of RSA’s DGNSS network (TrigNet) for cadastral mapping of property suitable for its Land Planning Programme (LPP). DLRRD is building a prototype of an off-grid, locally managed, and operated GISc work site built into transportable containers that bring the GISc, communications, and drone infrastructure to the local community.","author":[{"family":"Abrams","given":"MC"},{"family":"Heimann","given":"C"},{"family":"Minnie","given":"S"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-archives-xlviii-m-10-2025-1-2026","URL":"https://doi.org/10.5194/isprs-archives-xlviii-m-10-2025-1-2026","source":"openalex"},{"id":"oa:W7148696961","type":"article-journal","title":"Artificial intelligence in orthopedics: current applications, challenges, and future directions","abstract":"BACKGROUND: Artificial intelligence research in orthopedics has grown rapidly, yet a substantial gap remains between technical development and clinical translation. This narrative review summarizes current applications of artificial intelligence in orthopedic practice and highlights barriers to implementation. MAIN BODY: Current work converges on three domains: machine learning for structured perioperative risk prediction, deep learning for standardized musculoskeletal imaging, and large language models for workflow and decision support. Applications such as automated fracture detection, Kellgren-Lawrence grading for osteoarthritis, and transfusion risk modeling are approaching clinical maturity. However, routine adoption is limited by algorithmic opacity, performance degradation in new clinical environments, and poor fit within existing workflows. We argue that progress should shift from increasing model complexity toward rigorous evaluation, including external validation on independent cohorts. In addition, probability calibration and uncertainty estimation are important for trustworthy risk communication. Future directions may include multimodal \"digital twin\" approaches that integrate electronic medical records, imaging phenotypes, and intraoperative data into patient-specific trajectories. CONCLUSIONS: The clinical impact of artificial intelligence in orthopedics will depend on life-cycle governance and demonstrated net benefit, prioritizing reliability and implementation science over retrospective benchmark performance.","author":[{"family":"Kim","given":"Sang"},{"family":"Choi","given":"Byung"},{"family":"Han","given":"Hyuk"},{"family":"Ro","given":"Du"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1186/s43019-026-00317-5","URL":"https://doi.org/10.1186/s43019-026-00317-5","source":"openalex"},{"id":"oa:W7128688587","type":"article-journal","title":"A Review of Artificial Intelligence-Driven Smart Treatment of Aquaculture Effluent: Technical Framework, Application Scenarios, and Development Outlook","abstract":"Efficient treatment of aquaculture effluent is a crucial measure for ensuring the green and sustainable development of fisheries and alleviating pressure on aquatic ecosystems. However, traditional treatment technologies face bottlenecks of low efficiency and poor adaptability, making it difficult to meet the pollution control demands of large-scale aquaculture development. This is a systematic review focusing on artificial intelligence (AI) applications in aquaculture effluent treatment, aiming to clarify the technical framework, core application scenarios, industry trends, challenges, and future directions of AI-driven aquaculture effluent treatment. It first outlines core machine learning technologies, compares model adaptability, and analyzes AI synergies with IoT and digital twins. It then details AI implementation pathways across four core scenarios: precision feeding for pollution reduction, water quality monitoring and prediction, development of denitrifying and phosphorus-removing engineering bacteria, and system module control. Finally, it validates technical effectiveness through case studies, identifies industry trends toward integrated models and predictive monitoring, highlights existing challenges, such as data quality bottlenecks, system coupling complexity, and insufficient implementation economics, and proposes future research directions. This study provides theoretical foundations and practical references for the intelligent upgrading of aquaculture effluent treatment and the high-quality development of the fisheries industry.","author":[{"family":"Wang","given":"Zhaoxin"},{"family":"Tang","given":"Rong"},{"family":"Chen","given":"Guanda"},{"family":"Li","given":"Hui"},{"family":"Deng","given":"Yale"},{"family":"Shen","given":"Jingfang"},{"family":"Li","given":"Dapeng"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/w18040470","URL":"https://doi.org/10.3390/w18040470","source":"openalex"},{"id":"oa:W7169841137","type":"article-journal","title":"A Bibliometric Mapping of Digital Twins and AI: Scientific Trends and Research Frontiers","abstract":"This study examines the literature on integrating digital twins and Artificial Intelligence using bibliometric data to analyze productivity and collaboration.It presents publication distribution by year, leading countries, institutions, and authors, and identifies research trends through keyword and thematic cluster analyses.The results highlight the increasing importance of this integration and the growing trend of international collaboration.Data were collected on June 23, 2025, from the Web of Science Core Collection (WoS) using the query '(TI=(Digital Twin) AND TS=(AI)) AND (DT==(\"ARTICLE\"))', yielding 657 articles analyzed with VOSviewer (v1.6.20).Findings show that authors such as Tao and Fei, despite few publications, have high influence, while Fan and Zhong gained recognition with a single highly cited study.Strategic connectors include Wang, Fei-Yue, and Lv, while Zhang and Meng serve as \"hidden stars.\"Institutionally, NTNU stands out for centrality, while Nanjing University of Aeronautics and Astronautics leads in publication quantity but lags in impact.China dominates output, while the U.S., the U.K., and Canada excel in collaborative efforts.Thematic results reveal applications across manufacturing, healthcare, engineering, and city management, supported by machine learning, deep learning, 6G, and edge computing, as well as important social aspects like ethics and governance.","author":[{"family":"Doğan","given":"Ahmet"},{"family":"Yurtsal","given":"Ahmet"},{"family":"Keleş","given":"Şerife"}],"issued":{"date-parts":[[2026]]},"DOI":"10.30855/gmbd.070526n09","URL":"https://doi.org/10.30855/gmbd.070526n09","source":"openalex"},{"id":"oa:W7204493374","type":"article-journal","title":"The Digital Frontier: A Narrative Review of Bio-Digital Twins, AI-Driven Orthodontics, and Ethical Clinical Integration","abstract":"The transition from static digital records to dynamic Bio-Digital Twins is reshaping orthodontics by combining anatomical and functional data to simulate physiological behavior and improve diagnostic accuracy. This narrative review examines how artificial intelligence, including dynamic Bio-Digital Twins, can predict treatment duration, identify patients at risk of unplanned prolongation, and support personalized decision-making. A search of PubMed, ScienceDirect, Scopus, and Google Scholar was performed, focusing on digital workflows, precision orthodontics, aligner biomaterials, patient-reported outcomes, teleorthodontics, and the ethics of explainable AI. The evidence indicates that dynamic twins are more informative than conventional images because they integrate functional and biological data, while machine learning models estimate treatment time from clinical, imaging, and behavioral variables. Genetic, epigenetic, and multi-omics data further advance precision orthodontics. Successful implementation depends on high-quality data, explainable AI, reduction of algorithmic bias, and continued clinician oversight so that computational tools support rather than replace clinical judgment.","author":[{"family":"Diaz","given":"Adriana"},{"family":"Lopez","given":"Andrea"},{"family":"Martinez","given":"Laritza"},{"family":"Bellinghieri","given":"Naira"},{"family":"Hernandez","given":"Rocio"},{"family":"Albornoz","given":"Mary"}],"issued":{"date-parts":[[2026]]},"DOI":"10.70829/ijrmcs.v04.i02.008","URL":"https://doi.org/10.70829/ijrmcs.v04.i02.008","source":"openalex"},{"id":"oa:W7166891276","type":"article-journal","title":"Counterfactual Enabled Neuro-Symbolic Digital Twins for Intelligent Industrial Maintenance","abstract":"Industrial predictive maintenance is a critical challenge in modern manufacturing, where unexpected equipment failures cause significant economic losses through downtime, repair costs, and disrupted production. Conventional maintenance approaches, whether reactive or schedule-based, are becoming inadequate to manage the high-dimensional sensor information of the IoT-enabled machineries. The paper presents a novel hybrid neuro-symbolic digital twin that builds upon Remaining Useful Life (RUL) estimation by combining temporal transformers, physics-informed constraints, and counterfactual reasoning. The model integrates complementary approaches into a single and interpretable predictive system. A temporal transformer backbone is a model of long-range dependencies in multivariate sensor time-series data allowing the detection of gradual patterns of degradation that are frequently overlooked by traditional models of recurrence. The learning objective contains physics-informed constraints that guarantee that predictions are consistent with the principles of thermodynamic, mechanical, and material fatigue, connecting data-driven learning to domain knowledge. A Conditional Variational Autoencoder (CVAE) produces counterfactual failure events, simulating alternative histories of operation, under hypothetical conditions. This mechanism increases data diversity, enables interpretable diagnostics, and reinforces neuro-symbolic reasoning. A method of improving maintenance policies with the help of multi-objective reinforcement learning (MORL) is applied to minimize downtime, unnecessary maintenance, and equipment life. The results of the experiments on 24,042 sensor measurements of CNC machines, pumps, compressors, and robotic arms show good results. The framework has attained RMSE of 21.52 h and a 0.918 score, R2 which is 25.1 percent better as compared to the baseline models. The accuracy of prediction of failures was 94.2 percent, and the maintenance policies were optimized to achieve a reduction in equipment failures by 51.7 percent compared to the rule-based scheduling, which is based on the fact that CVAE-generated counterfactual state transitions were used to train the Q-learning agent, which indicates the practicality of the framework.","author":[{"family":"Alzaben","given":"Nada"},{"family":"Khan","given":"Muhammad"},{"family":"Siddiqui","given":"Hafeez"},{"family":"Mirdad","given":"Abeer"},{"family":"Bahaj","given":"Saeed"}],"issued":{"date-parts":[[2026]]},"DOI":"10.32604/cmc.2026.083649","URL":"https://doi.org/10.32604/cmc.2026.083649","source":"openalex"},{"id":"oa:W7128001098","type":"article-journal","title":"Mathematical Approaches for the Characterization and Analysis of Molecular Markers in the Study of the Progression and Severity of Amyotrophic Lateral Sclerosis","abstract":"Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder for which despite its severity, no validated biomarker currently exists to support early diagnosis, limiting therapeutic effectiveness and patient survival. In this context, mathematical modeling therefore becomes essential: it allows us to maximize the information obtainable from a limited number of samples, identify patterns that may not be directly observable, and estimate the relative contribution of different molecular markers to ALS progression. In this work, we propose methods for qualitatively and quantitatively evaluating the relevance of selected biomarkers in ALS classification and disease-state identification and laying the foundations for the definition of a protocol useful for constructing “digital twins” of the entire process of study, diagnosis, and treatment of the disease from the perspective of innovative precision medicine.","author":[{"family":"Carracciuolo","given":"Luisa"},{"family":"Damora","given":"Ugo"},{"family":"Dubbioso","given":"Raffaele"},{"family":"Fasolino","given":"Ines"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/appliedmath6020022","URL":"https://doi.org/10.3390/appliedmath6020022","source":"openalex"},{"id":"oa:W7202345108","type":"manuscript","title":"AgenticTwin: An Agentic LLM Framework Integrated with Digital Twin for Anomaly Detection","abstract":"Digital twins are increasingly used to monitor and simulate the behavior of cyber-physical systems. Even with skilled operators, interpreting anomalies detected within digital twin pipelines is challenging, as the sheer complexity and volume of raw sensor data make thorough analysis difficult. Recent advances in large language models (LLMs) offer promising capabilities for reasoning and explanation, yet their integration into digital twin-driven anomaly analysis remains underexplored. In this work, we propose AgenticTwin, an agentic framework that integrates LLM-driven reasoning with a digital twin-based anomaly detection pipeline. The framework grounds LLM-generated explanations in outputs from a digital twin-driven anomaly classifier and enables human operators to ask relevant natural-language questions about the system. Beyond the framework itself, we introduce a benchmark-oriented evaluation pipeline constructed over synthetic anomalies injected into a real-world weather sensor dataset, enabling controlled generation of operator queries over anomaly events. We further evaluate the feasibility of deploying lightweight, open-source LLMs for practical cyber-physical environments. Experimental results demonstrate that structured agent collaboration and knowledge-grounded reasoning improve diagnosis quality, contextual retrieval, and mitigation quality across diverse possible anomaly scenarios.","author":[{"family":"Hasan","given":"Tammem"},{"family":"Ghanta","given":"Mounika"},{"family":"Sarkar","given":"Souvika"},{"family":"Guin","given":"Ujjwal"}],"issued":{"date-parts":[[2026]]},"DOI":"10.48550/arxiv.2608.11679","URL":"https://doi.org/10.48550/arxiv.2608.11679","source":"openalex"},{"id":"oa:W7203666874","type":"manuscript","title":"PRISM: Decision-Centric Predictive Sensing for Cognitive Digital Twins in 6G","abstract":"Integrated sensing and communication (ISAC) and Digital Twin (DT) technology have emerged as complementary for future wireless networks that require autonomous operations involving continuous interaction between physical and digital worlds. However, existing DT-assisted ISAC frameworks sense continuously and indiscriminately while optimizing only a single task, leaving little room for persistent, multi-domain knowledge or proactive sensing control. This article proposes a Predictive, Reasoning-driven, Intelligent Sensing Module (PRISM) engine that transforms the DT from a passive, domain-specific optimizer into a persistent, network-wide reasoning system. PRISM enables decision-centric predictive perception, proactively directing sensing toward anticipated decisions needs rather than following fixed sensing schedules. Using an illustrative extremely large multiple-input multiple-output (XL-MIMO) deployment scenario with a mixed eMBB, URLLC, and mMTC device population, we show how this principle benefits visibility-region sensing for channel acquisition and supports slice-aware operation. Preliminary simulations, including this deployment scenario and the resulting knowledge error, overhead, and latency results, confirm that this decision-centric approach substantially reduces sensing overhead while preserving decision reliability and latency, supporting the proposed architecture as a practical step toward self-aware, autonomously orchestrated 6G networks.","author":[{"family":"Ali","given":"Afan"},{"family":"Costa","given":"Daniel"},{"family":"Nasir","given":"Ali"}],"issued":{"date-parts":[[2026]]},"DOI":"10.48550/arxiv.2608.16197","URL":"https://doi.org/10.48550/arxiv.2608.16197","source":"openalex"},{"id":"oa:W7203706847","type":"manuscript","title":"Hierarchical Agentic Incident Response with Digital-Twin-Validated Attack Inference","abstract":"Network incident response remains slow and labor-intensive as the defender must infer multi-stage attacks from partial observations and translate recovery decisions into reliable system commands. Decision-theoretic planners provide principled optimization but typically rely on abstract states and predefined actions, while large language model (LLM) agents can reason over operational context but may hallucinate attacks and responses. Toward automating response planning, we present a hierarchical agentic response framework that integrates LLM-based attack inference, rollout planning, and digital-twin validation. A fine-tuned LLM infers the attack progression and affected hosts from security alerts and system measurements. An emulated network digital twin replays the inferred attack and returns discrepancies between predicted and observed effects to calibrate the inference. A separately fine-tuned planning agent uses the rollout planning method to prioritize affected components at the tactical layer. At the operational layer, the planning agent proposes high-level recovery actions, and an execution agent translates selected actions into recovery and verification commands that are validated in the digital twin. We evaluate the framework on a 33-component enterprise-network testbed under three multi-stage attack scenarios. The results show that our framework outperforms frontier-LLM baselines in recovery success rate by 18--31%.","author":[{"family":"Gao","given":"Yiran"},{"family":"Chen","given":"Juntao"},{"family":"Li","given":"Tao"}],"issued":{"date-parts":[[2026]]},"DOI":"10.48550/arxiv.2608.15016","URL":"https://doi.org/10.48550/arxiv.2608.15016","source":"openalex"},{"id":"oa:W7170075412","type":"article-journal","title":"A pipeline for automatic building reconstruction for Digital Twins in complex urban environments","abstract":"Abstract. Automatic building reconstruction is a strategic component for creating urban Digital Twins (DTs), enabling the generation of accurate and interoperable Level of Detail 2 (LOD2) models. These models provide an essential standard for applications such as Geographic Information Systems (GIS), energy and hydraulic simulations, and urban planning. To address these needs, the MEDUSA (MEDiterraneo: Uso Sostenibile dell’Ambiente) project, promoted by the University of Salerno and funded by the Italian Space Agency (ASI), developed an innovative pipeline. The method was optimized to model areas with complex geometries and articulated roofs, utilizing the Amalfi Coast as a test area. The developed workflow is based on the City3D algorithm, integrating LiDAR (Light Detection And Ranging) data with building footprints derived from the Regional Topographic Database (RTDB). The process involves point cloud segmentation to isolate buildings and the generation of a Triangulated Irregular Network (TIN) mesh. Roof contours are identified using edge detection operators, simplified into polylines, and regularized using geometric constraints like parallelism and orthogonality to ensure LOD2 compliance. Finally, polygons are vertically extruded and optimized through the PolyFit framework, ensuring closed and topologically correct polygonal models. To overcome computational challenges and LiDAR data variability, significant improvements were introduced, including process parallelization, alignment with the Digital Terrain Model (DTM), and batch management of GeoJSON files. These enhancements successfully increased the pipeline's robustness and efficiency. The enriched pipeline produces high-quality LOD2 models, laying a solid foundation for next-generation urban modeling capable of meeting the scalability and interoperability requirements of future smart cities.","author":[{"family":"Candela","given":"Laura"},{"family":"Damato","given":"Luigi"},{"family":"Benedetto","given":"Alessandro"},{"family":"Fiani","given":"Margherita"},{"family":"Gujski","given":"Lucas"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-archives-xlix-b1-2026-553-2026","URL":"https://doi.org/10.5194/isprs-archives-xlix-b1-2026-553-2026","source":"openalex"},{"id":"oa:W7126046836","type":"article-journal","title":"Metaverse-Enabled Digital Twins for Business and Smart Cities: Toward A Human-Centered Framework for Digital Transformation","abstract":"Abstract. Digital Twin (DT) technologies are increasingly changing how businesses and cities model, assess, and enhance complex systems. Traditional DTs have served as static representations of tangible assets, providing monitoring and predictive functionalities. However, minimal stakeholder engagement and a focus on specific sectors have often limited their full potential. The rise of the metaverse, reinforced by Extended Reality (XR) technologies, presents a unique chance to evolve DTs into immersive, interactive, and human-centered platforms for collaborative decision-making. This integration allows stakeholders to visualize and engage with multidimensional data in real time, facilitating predictive analysis, scenario planning, and participatory governance. In business environments, DTs enhanced by the metaverse improve supply chain modelling, aid corporate strategy formulation, and foster innovation in customer experiences, ultimately increasing resilience and adaptability. In urban settings, they support smart infrastructure management, sustainability oversight, and collaborative planning by integrating IoT, Building Information Modeling (BIM), and geospatial data into engaging simulations. This research presents a conceptual framework that links business ecosystems and smart cities through a DT layer mediated by the metaverse, and GIS work for a GeoAI-enabled urban development system may address the political, societal, legal, and technical-instrumental challenges currently affecting cities and those expected in the foreseeable future. This framework, supported by enabling technologies and designed for inclusivity and scalability, illustrates a multidisciplinary approach to digital transformation applicable to both private and public sectors.","author":[{"family":"Qudaih","given":"Rasem"},{"family":"Caldwell","given":"Nicholas"},{"family":"Salem","given":"Imen"},{"family":"Karthi","given":"A"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-archives-xlviii-4-w18-2025-273-2026","URL":"https://doi.org/10.5194/isprs-archives-xlviii-4-w18-2025-273-2026","source":"openalex"},{"id":"oa:W7166578177","type":"article-journal","title":"SIMULATION MODEL OF A DIGITAL TWIN FOR AN NPP POWER UNIT TECHNOLOGICAL PROCESS","abstract":"Background. Modern nuclear power plant (NPP) units are characterised by high structural complexity, multi-level hierarchical Information and Control (I&C) systems, and a vast number of interconnected technological parameters. Existing digital twin models primarily focus on individual physical processes – such as neutron kinetics, thermal hydraulics, or protection logic – often overlooking the comprehensive structure of control systems. The lack of a formalised approach for real-time assessment of subsystems’ hierarchical integrity limits the early detection of pre-accident states and proactive safety management. Objective. The paper aims to develop a simulation model of a digital twin for the NPP technological process based on a system-cluster approach. This method enables the assessment of the hierarchical, self-similar scaled structure of subsystems using fractal dimension as a quantitative metric. Methods. The study utilises a system-cluster approach, decomposing the power unit into functional sub-clusters: power control, protection system, coolant parameter regulation, and emergency shutdown. The mathematical framework integrates neutron kinetics equations, thermal-hydraulic relations, and logical-dynamic algorithms. To quantify structural complexity, the information space coverage method was employed to calculate fractal dimensions. The digital twin was implemented as a hardware-and-software complex integrated with the I&C, incorporating modules for data acquisition, structural identification, and predictive analytics. Results. Fractal dimension values were obtained for key subclusters of the power unit, reflecting their hierarchical complexity (notably, the maximum of 1.83 for the coolant control system and the minimum of 1.0 for the protection system). Normalised ranges of fractal dimension were determined as indicators of normal operation. Furthermore, a monitoring algorithm was developed to detect the loss of structural levels or subsystem degradation before functional failures manifest. Practical implementation demonstrated the feasibility of real-time structural diagnostics and adaptive response. Conclusions. The proposed fractal-cluster approach ensures comprehensive modelling of the NPP technological process by accounting for its hierarchical structure. Utilising fractal dimension as a structural diagnostic parameter expands the capabilities of traditional control methods and establishes the necessary framework for proactive safety management strategies based on digital twin technology.","author":[{"family":"Brovko","given":"Kostiantyn"},{"family":"Budanov","given":"Pavlo"},{"family":"Velykohorskyi","given":"O"},{"family":"Oliinyk","given":"Yuliia"},{"family":"Vynokurova","given":"N"},{"family":"Voitenko","given":"S"}],"issued":{"date-parts":[[2026]]},"DOI":"10.20535/kpisn.2026.2.352429","URL":"https://doi.org/10.20535/kpisn.2026.2.352429","source":"openalex"},{"id":"oa:W7203909396","type":"article-journal","title":"Supplementary dataset: A digital twin and SOAR-based cybersecurity testbed for automated threat detection and response in smart ships","abstract":"Supplementary dataset: A digital twin and SOAR-based cybersecurity testbed for automated threat detection and response in smart shipsThis record contains the demonstration video and experimental data supporting the manuscript:J.-K. Lim, H.-S. Song, J.-W. Kim, and Y.-H. Choi, \"A Digital Twin and SOAR-based Cybersecurity Testbed for Automated Threat Detection and Response in Smart Ships,\" submitted to IEEE Access, 2026.Funding: Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. RS-2024-00400955, Development of core security technology to respond to international smart ship regulations).CONTENTS- blackhawk_demo_video.mp4 — Recorded demonstration of the BLACK HAWK digital twin security-monitoring dashboard (84 s, 1280x720). Shows real-time ECDIS visualization, alarm history, and attack-detection overlay corresponding to Fig. 6 of the manuscript. A live interactive instance is additionally available at https://koreanregister.dev-timmanage.com/ (availability not guaranteed long-term; this archived video is the permanent record).- malware_corpus_sha256.csv — The 111-sample malware corpus used in detection Track 2 (Section V-A): SHA-256 hash, file type, category (53 trojan / 6 phishing / 52 ransomware), per-sample detection outcome (105 detected / 6 missed), and per-sample provenance (105 in-house / 6 vendor-supplied). Hashes only — no malware binaries are distributed. Samples can be retrieved from public malware repositories (e.g., VirusTotal, MalwareBazaar) by hash.- e2e_pipeline_stage_timings_ms.csv — Stage-level timings (n = 40) for the end-to-end event-to-visualization pipeline (TABLE 5): detection-to-SOAR-trigger and trigger-to-isolation, in milliseconds. The attack-event-to-detection stage coincided with injection at the 1-second log resolution of the SIEM in all 40 trials.- isolation_path_timings_ms.csv — Per-execution timings (n = 100) for the three parallel network-isolation paths — FW Deny (FortiGate), EMS Deny (FortiClient EMS / FortiEDR), FSW Port Down (FortiSwitch) — in milliseconds (TABLE 9), with per-execution playbook completion (slowest path).- playbook_execution_timings_ms.csv — Per-execution completion times (n = 100 per playbook, 500 total) for the five maritime-specific SOAR playbooks (TABLE 8), in milliseconds.- kafka_topics.zip — Avro schema definitions (.avsc) for the nine topic categories of TABLE 2, as registered in the Schema Registry. Field sets correspond to the Key Fields column of that table. OT telemetry (dt.sensor) arrives as custom JSON and is normalized to the SensorLog record before publication.- playbook_pseudocode.md — Vendor-neutral pseudocode for the five SOAR playbooks of TABLE 8, stating the abstract capability each step requires rather than the product-specific connector used. Includes the scope statements for the Notification & Escalation and Asset Recovery & Unblock playbooks, whose automated scope is narrower than the manual procedures they are compared against.- CHANGELOG.md — Record of what changed between versions of this dataset, with the derived figures that follow from each file.- README.md — This description, included as a file.NOTES ON METHODOLOGY- Detection Track 1: a trial is counted as detected if FortiSIEM or CEREBRO-XTD raised an alert correlated to the injected instance within 60 s of injection. Result: 40/47 detected (85.1%). Per-trial injection records for Track 1 were not retained; Track 1 detection outcomes are therefore reported in aggregate only.- Detection Track 2: a sample is counted as detected if the endpoint protection platform raised a detection alarm upon ZIP-archive extraction. Result: 105/111 detected (94.6%). Per-sample outcomes are provided in malware_corpus_sha256.csv.- Corpus provenance: six samples, all in the phishing category, were supplied by an engineer of Fortinet, the endpoint protection vendor whose product was under test; the remaining 105 were drawn from an in-house m","author":[{"family":"Lim","given":"Jeoung"},{"family":"Song","given":"Hee"},{"family":"Kim","given":"Jong"},{"family":"Choi","given":"Yoon"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.22019801","URL":"https://doi.org/10.5281/zenodo.22019801","source":"openalex"},{"id":"oa:W7165013107","type":"article-journal","title":"Digital Twin Based Intelligent Routing Optimization in Autonomous Transportation Systems","abstract":"Digital Twin (DT) technology has emerged as a transformative approach for modelling, monitoring, and optimizing complex cyber-physical systems. In recent years, the integration of digital twins with autonomous vehicles and intelligent transportation systems has attracted significant research attention due to the need for efficient routing, improved energy management, and enhanced system performance. Traditional optimization methods often struggle to handle dynamic environments, uncertain traffic conditions, and real-time decision requirements. Digital twins address these challenges by creating a dynamic virtual representation of physical systems that continuously updates through real-time data, enabling predictive analysis and intelligent decision-making. This review paper presents a comprehensive overview of DT based optimization approaches focusing on routing efficiency, energy efficiency, and system performance. The study analyses the architecture and functional components of DTs, explores optimization techniques integrated with DT frameworks, and evaluates how these technologies improve system reliability and operational efficiency in autonomous mobility systems. Furthermore, the paper highlights current challenges including data reliability, computational complexity, scalability, and real-time implementation issues. Finally, future research directions are discussed to support the development of intelligent, energy-efficient, and high-performance transportation systems using digital twin technology.","author":[{"family":"Saha","given":"Bibhas"},{"family":"Maity","given":"Mrinmoy"},{"family":"Maity","given":"Mriganka"}],"issued":{"date-parts":[[2026]]},"DOI":"10.65525/jmea.v3i1.40","URL":"https://doi.org/10.65525/jmea.v3i1.40","source":"openalex"},{"id":"oa:W7171538818","type":"article-journal","title":"Research on the Theoretical Evolution of Digital Twin Technology Intelligent Library Development","abstract":"Based on the database of WOS and CNKI, this study uses bibliometrics and visualization methods to quantitatively analyze the related literatures of digital twin-driven smart libraries from 2003 to 2025, and systematically sorts out their theoretical evolution, research hotspots, cooperation modes, and application characteristics. The results show that China leads the world in the field of digital twins, but the interdisciplinary depth is insufficient. The research of smart library forms a dual-core pattern between China and the United States, with China, the United States, and Germany as the core intermediaries of international cooperation. They are highly coupled in data, service, and user experience. The research reveals three evolution trends, and suggests strengthening strategic planning and resource input, promoting interdisciplinary integration and service innovation, and providing quantitative support for the construction of smart libraries.","author":[{"family":"Chen","given":"Kun"},{"family":"Hao","given":"Xie"},{"family":"苟金霞"},{"family":"Xiao","given":"Daibo"}],"issued":{"date-parts":[[2026]]},"DOI":"10.4018/ijkm.417248","URL":"https://doi.org/10.4018/ijkm.417248","source":"openalex"},{"id":"oa:W7203706317","type":"article-journal","title":"Digital twins in precision pharmacotherapy: emerging applications, challenges, and future directions","abstract":"Digital twin technology, defined as dynamic digital models that represent individual patients, is emerging as a promising paradigm in precision pharmacotherapy. The integration of pharmacokinetic and pharmacodynamic (PK/PD) modeling, clinical data, genomic information, and real-time patient monitoring enables digital twins to shift drug therapy away from population-based averages toward individualized, adaptive decisions. This narrative review explores conceptual frameworks, emerging applications, methodological approaches, clinical value, limitations, and future directions of digital twins in pharmacotherapy, with particular emphasis on the role of clinical pharmacists. Unlike broader digital twin reviews that primarily emphasize technical architectures, disease-specific applications, or pharmaceutical research and development, this review focuses on the clinical-pharmacy translation layer: how digital twin outputs can be interpreted, validated, communicated, and converted into actionable medication decisions at the bedside and across ambulatory care settings. Key applications include precision dosing, polypharmacy management, antimicrobial stewardship, and the optimization of complex therapies, alongside important ethical, regulatory, and implementation challenges.","author":[{"family":"Jarab","given":"Anan"},{"family":"Al-Qerem","given":"Walid"},{"family":"Jarab","given":"Hamza"},{"family":"Jrab","given":"Omar"},{"family":"Elsherif","given":"Rahma"},{"family":"Meslamani","given":"Ahmad"},{"family":"Hamarneh","given":"Yazid"},{"family":"Aburuz","given":"Salahdein"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fdgth.2026.1881217","URL":"https://doi.org/10.3389/fdgth.2026.1881217","source":"openalex"},{"id":"oa:W7161831056","type":"article-journal","title":"Optimizing assembly line productivity in passenger car manufacturing: a comprehensive review with evidence from the Pune automotive region","abstract":"Passenger car manufacturing in India is undergoing a rapid transformation driven by growing demand for high productivity, sustainability, and more flexible assembly systems. Even though significant progress has been made, existing studies mostly focus on individual techniques such as Lean, automation, or digitalization and rarely provide a unified framework for productivity improvement. This review tries to fill that research gap by analyzing productivity drivers across multiple dimensions, including technical, ergonomic, digital, policy, and regional aspects, with a focus on Pune’s automotive cluster. The objective is to synthesize evidence-based strategies to optimize assembly line performance. A mixed-method approach was used, consisting of a literature review covering 2010 to 2025, along with a regional benchmarking meta-analysis on industrial case data. Metrics such as overall equipment effectiveness, process cycle efficiency, and takt time are used as core indicators in the study. Key findings indicate that Lean Six Sigma implementation improved process cycle efficiency (PCE) from 19.9% to 66.7%, cobot integration increased overall equipment effectiveness (OEE) from 80% to 87.74%, while scrap generation reduced from 0.06% to only 0.02%. Ergonomic redesigns of workstations led to a 9.7% gain in productivity. Digital twin simulations have shown that throughput increases up to 20%, and IRPA adoption resulted in a simulated workforce reduction of 45.69%. Policies such as Make in India PLI hold promise, yet challenges remain in terms of EV infrastructure localization. An integrated Lean–AI–digital model, when supported with ergonomic design and policy alignment, can possibly deliver 25%–40% improvement in productivity, especially in manufacturing hubs like Pune.","author":[{"family":"Gosavi","given":"Avinash"},{"family":"Shahare","given":"Padmakar"},{"family":"Gund","given":"Swapnil"},{"family":"Paraye","given":"Prashant"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fmech.2026.1808820","URL":"https://doi.org/10.3389/fmech.2026.1808820","source":"openalex"},{"id":"oa:W7131125902","type":"article-journal","title":"Research on the Optimisation of Natural Gas Layered Scheduling for Offshore Platforms Based on Improved GA and MPC","abstract":"ABSTRACT Natural gas scheduling on offshore platforms is essential for ensuring safe and economically efficient production. Traditional control methods, such as PID, often exhibit limited robustness and slow response under nonlinear dynamics, disturbances and fluctuating demand. This paper proposes a hierarchical scheduling optimisation framework that integrates an improved genetic algorithm (GA) with model predictive control (MPC), aiming to achieve long‐term global optimisation together with real‐time dynamic control. The improved GA incorporates adaptive crossover and mutation rates, simulated binary crossover (SBX), polynomial mutation and an elitism strategy to enhance search efficiency and avoid premature convergence. A simulation‐driven digital‐twin prototype is constructed using representative operating conditions—normal, high‐demand, low‐demand and fault—to evaluate flow and pressure regulation performance. The optimisation objective minimises total operating cost subject to physical feasibility, safety limits and equipment performance constraints, with decision variables including valve openings and compressor speeds. The GA generates hourly reference trajectories for global scheduling, whereas MPC ensures minute‐level tracking under disturbances and operational variability. Comparative results demonstrate that the hierarchical GA + MPC approach outperforms standalone MPC, reducing operating cost by 9.4%, accelerating convergence by 34.2% and lowering steady‐state tracking error by 18.6%. Relative to PID control, convergence speed improves by 43.5% and steady‐state error decreases by 35.1%. In addition, the improved GA achieves a 65.6% reduction in convergence generations compared with the traditional GA, confirming its superior efficiency and robustness. These results, validated within the simulation‐driven digital‐twin prototype, highlight the hierarchical architecture's ability to combine global optimisation with real‐time dynamic control, demonstrating its practicality, robustness and potential for broader application in intelligent offshore energy systems.","author":[{"family":"Zhang","given":"Xiaoguang"},{"family":"He","given":"Xiaoyong"},{"family":"Zhong","given":"Yutong"},{"family":"Gao","given":"Xiaoyong"},{"family":"Zhan","given":"Wenxin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1049/dgt2.70018","URL":"https://doi.org/10.1049/dgt2.70018","source":"openalex"},{"id":"oa:W7172272597","type":"article-journal","title":"Research on a Digital Twin-Based Local Penetration Algorithm for UAV Swarms","abstract":"To address the challenges faced by UAV swarms in local narrow-space penetration missions, including constrained passages, dense obstacles, and the difficulty of balancing formation stability and traversability, this paper proposes a local penetration method that integrates virtual–center consensus-based formation control with a V-shaped formation self-reconfiguration strategy. First, a virtual geometric center is introduced as the consensus reference to replace the traditional physical leader node, thereby reducing the risk of single-point failure and improving swarm coordination consistency. Second, geometric constraints, including the effective channel width, lateral formation width, and safety margin, are incorporated to construct a channel-constraint-driven formation self-reconfiguration mechanism, enabling the swarm to contract its formation, avoid obstacles during traversal, and recover the formation after passing through the constrained region. Finally, a digital twin-based virtual–real interactive validation platform is constructed to verify the formation maintenance, formation reconfiguration, and virtual–real trajectory consistency of the proposed method. Experimental results show that the proposed method can maintain favorable formation consistency and safe inter-UAV distances in constrained channel environments while demonstrating good stability and scenario adaptability during formation adjustment and recovery.","author":[{"family":"Qu","given":"Shaochun"},{"family":"Cai","given":"Yuhuan"},{"family":"Wan","given":"Shiyan"},{"family":"Fu","given":"Yanfang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/drones10080591","URL":"https://doi.org/10.3390/drones10080591","source":"openalex"},{"id":"oa:W7127967070","type":"article-journal","title":"Technological Innovation and Sustainability in Public Administration: A Systematic Review and Research Agenda","abstract":"This study examines how technological innovation and sustainability jointly reshape contemporary public administration by integrating digital transformation with public value creation. Using a mixed-method approach, we compile a Scopus-based bibliographic dataset and conduct descriptive and network analyses on 199 articles to map publication trends, methodological patterns, and core keyword clusters. We then perform an in-depth qualitative content analysis of 83 papers, coding public sector domains, actors, technological innovations, and sustainability dimensions. Findings highlight a shift from early e-government, centered on administrative efficiency, toward a paradigm of “sustainable digital governance”, where AI, IoT, blockchain and data analytics drive the twin digital–green transition. Five conceptual clusters and several application domains show that public value increasingly emerges within collaborative ecosystems involving administrations, firms, universities, citizens and digital platforms. The study offers an integrated overview of this evolving field and clarifies technology’s role as an enabling factor in sustainable governance. Building on the review results, we propose the Sustainable Public Innovation Ecosystem (SPIE) framework, which links systemic enablers (technological and sustainability innovation) governance efficiency and sustainable public value through ecosystem dynamics and governance mechanisms. It also outlines a future research agenda on hybrid actors ethical and regulatory issues, and approaches to measuring sustainable public value, providing guidance for scholars and policymakers designing digitally enabled and sustainability-oriented public reforms.","author":[{"family":"Pini","given":"Benedetta"},{"family":"Petroni","given":"Alberto"},{"family":"Bigliardi","given":"B"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/admsci16020080","URL":"https://doi.org/10.3390/admsci16020080","source":"openalex"},{"id":"oa:W7159780197","type":"article-journal","title":"Digital Twin for Integration of Control and Diagnostics of Electromechanical Systems Under Uncertainty","abstract":"The study aimed to create a digital twin for the integration of control and diagnostics of electromechanical systems under conditions of uncertainty, with minimal reliance on physical sensors. The research was conducted at Mykolaiv National Agrarian University. Physically based models were developed for thermal processes in windings, assessment of losses in magnetic conductors, and wear indicators for components, virtual sensors, signal filtering algorithms and degradation prediction were implemented, and verification was conducted on test benches and in computer modelling. Quantitative results were obtained, which constitute the main contribution of the work: the accuracy of reproducing hidden parameters was 93.6-97%, the relative error of reproducing losses in the transformer was 3%, the relative error of thermal estimates was 3.5-6.8%, the correlation with reference measurements reached 0.99; the reduction in the dispersion of noisy signals was 33-41%, the signal-to-noise ratio increased by 4.2-6.7 decibels, and the root mean square error decreased by 35-44% with an additional delay of no more than 0.04 seconds. The forecast of the time to failure of the hydraulic unit provided 92% correct estimates within a tolerance of ±10% for a 48-hour horizon; in the traction electric drive, a drop in efficiency (efficiency) by 6.7 percentage points under conditions of magnetic saturation was confirmed; in ship drives, peak torsional loads were reduced by 11%; in biogas plants, the energy balance error was 5.4%; in irrigation systems, energy consumption was reduced by 9%; in robotics, the accuracy of deviation detection was increased by 14%. The models can be used in ship drives, biogas plants, robotic lines, irrigation pumping stations, transformer substations, hydraulic drives and traction electric drives, reducing downtime and energy consumption without changing the existing control infrastructure.","author":[{"family":"Koshkin","given":"Dmytro"},{"family":"Vakhonina","given":"Larisa"},{"family":"Tsyganov","given":"AD"},{"family":"Sukovitsyna","given":"Iryna"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5935/jetia.v12i58.3405","URL":"https://doi.org/10.5935/jetia.v12i58.3405","source":"openalex"},{"id":"oa:W7134894034","type":"article-journal","title":"Dynamic stress monitoring and analysis of cranes based on digital-twin modeling","abstract":"Abstract. Cranes used in factories and ports are frequently exposed to potential risks arising from complex operating conditions. To comprehensively assess operational reliability, digital technologies are being increasingly employed for dynamic monitoring and optimization during crane operations. This study focuses on the dynamic stress variations in the main truss of cranes during operations. First, a digital mapping model between a scaled physical crane and its virtual counterpart was developed using a parametric design approach based on a real-world engineering crane. Using this model, a digital-twin representation of the crane's dynamic stress field was constructed. Nodal stresses of the twin crane were obtained using radial basis function (RBF) interpolation in conjunction with finite-element stress field calculations. Subsequently, the K-nearest-neighbor algorithm was used to select relevant nodes for training an interpolation-based surrogate model, enabling end-to-end stress prediction at the crane's nodes. Finally, dynamic stress rendering using the HSV (hue, saturation, value)-color-model-enabled synchronized visualization of the stress field within the digital twin, supporting real-time monitoring, simulation-based optimization, and dynamic life cycle management of the crane. Experimental comparisons of three different lifting conditions show that the average error between finite-element analysis and stress-rendering results is 8.29 %, while the average error between measured data and stress-rendering results is 9.98 %, verifying the predictive reliability of the interpolation model. These findings guide the application of dynamic digital twins of stress fields in industries such as construction, manufacturing, and energy.","author":[{"family":"Yan","given":"Guoping"},{"family":"Yang","given":"Xiaowei"},{"family":"Zhang","given":"Jiansheng"},{"family":"Tao","given":"Qi"},{"family":"Li","given":"Yang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/ms-17-207-2026","URL":"https://doi.org/10.5194/ms-17-207-2026","source":"openalex"},{"id":"oa:W7129073664","type":"manuscript","title":"Dynamic Traceability and Reliability Management: Integrating the Digital Product Passport with Digital Twins and IoT for Batteries and Electronics","abstract":"The mandates of the Circular Economy (CE) and Industry 5.0 necessitate unprecedented life cycle traceability and management for complex products, such as electronics and lithium-ion batteries. The Digital Product Passport (DPP) has emerged as the centralized data framework for this transition. However, effective DPP implementation requires the robust integration of technologies to overcome the technical challenges of scalability, data integrity, and legacy system management. This work shifts from a high-level conceptual overview to an in-depth technical analysis, detailing the integration architecture of the DPP with the Internet of Things (IoT), Digital Twins (DTs), and Artificial Intelligence (AI). Specifically, we focus on how IoT, via embedded sensors and NFC/RFID tags, acts as the dynamic data carrier that feeds DT. For the battery sector, we propose a technical framework that utilizes the DPP to continuously track State of Health (SoH) and State of Charge (SoC), throughout the entire life cycle. AI/Machine Learning is then integrated within the DT to enable accurate predictions of degradation and failure, directly addressing reliability concerns and optimizing the second life and recycling phases. Our focus is on tackling critical bottlenecks, such as interoperability between IT systems and data storage scalability (e.g., via robust Cloud or Blockchain solutions), ensuring the DPP is established not just as a static data repository, but as a dynamic and predictive tool for product reliability management and regulatory compliance.","author":[{"family":"Brasil","given":"Gabriel"},{"family":"Oliveira","given":"Carlos"},{"family":"Silveira","given":"Allan"},{"family":"Filho","given":"Sebastião"},{"family":"Peruzzi","given":"Vinicius"},{"family":"Pimentel","given":"Marcos"}],"issued":{"date-parts":[[2026]]},"DOI":"10.20944/preprints202602.1155.v1","URL":"https://doi.org/10.20944/preprints202602.1155.v1","source":"openalex"},{"id":"oa:W7116866262","type":"article-journal","title":"Four-Dimensional Printing of Shape Memory Polymers for Biomedical Applications: Advances in DLP and SLA Manufacturing","abstract":"Shape memory polymers (SMPs) represent an innovative class of materials that possess programmed, reversible shape-changing capabilities in response to external stimuli. The recent emergence of SMPs' advanced manufacturing, specifically 4D printing, has created exceptional opportunities for use in biomedical engineering. This review presents a critical synthesis of the latest advances in the chemistry, biomedical applications, manufacturing strategies, and clinical translation of SMPs, highlighting vat photopolymerization techniques, such as stereolithography (SLA) and digital light processing (DLP). Notably, 4D-printed SMPs can promote spatiotemporally controlled architectures, and applications include minimally invasive implants, dynamic tissue scaffolds, and multifunctional drug delivery. This paper focuses on recent advances in resin design, multi-responsive and nanocomposite resins, AI-guided material discovery, and emerging biocompatible and biodegradable formulations, while outlining current roadblocks to clinical implementation, including cytotoxicity, sterilization, regulatory compliance, and device shelf-life. Our goal is to elucidate the relationship between material design, processing, and biomedical performance to inform researchers of potential future directions for 4D-printed SMPs and next-generation, patient-centered medical devices.","author":[{"family":"Pittala","given":"Raj"},{"family":"Torres","given":"Marc"},{"family":"Reddy","given":"Neha"},{"family":"Swank","given":"Sara"},{"family":"Ecker","given":"Melanie"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/polym18010024","URL":"https://doi.org/10.3390/polym18010024","source":"openalex"},{"id":"oa:W7166005752","type":"article-journal","title":"Methodology of Multisensory Data Integration for Creating a Digital Twin of Destroyed Objects","abstract":"Abstract This study presents a methodology for multisensory data integration combining terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry to create highly accurate digital twins of destroyed or damaged architectural heritage. The relevance of the research is driven by the urgent need to document and reconstruct cultural monuments affected by military aggression. While existing single-sensor approaches often leave data gaps in complex structures, the proposed integration of Leica RTC360 and ScanStation P30 scanners with UAV imaging provides complete, geometrically consistent coverage of facades, enclosed courtyards, and destroyed roofs. The developed workflow encompasses high-precision geodetic network establishment, data collection, noise reduction, and multisensor alignment. The results demonstrate that combining ground and aerial data ensures high geometric accuracy, eliminating distortions and providing detailed texturing for models. Furthermore, the study highlights the critical role of high-performance computing in processing massive datasets (over 45 GB) to create optimized models suitable for web publication, GIS, CAD, and BIM applications. The proposed scalable approach provides a sustainable solution for digital heritage preservation, offering a reliable spatial foundation for future architectural and restoration projects without losing historical authenticity.","author":[{"family":"Mamonov","given":"Kostiantyn"},{"family":"Kasyanov","given":"Volodymyr"},{"family":"Holovachov","given":"Vitalіі"},{"family":"Gorb","given":"Oleksandr"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1088/1755-1315/1638/1/012060","URL":"https://doi.org/10.1088/1755-1315/1638/1/012060","source":"openalex"},{"id":"oa:W7203663728","type":"article-journal","title":"Digital twins as a catalyst for sustainable construction transport policies? A critical review","abstract":"The construction industry plays a critical role in shaping urban freight systems while contributing to environmental impacts through material transport and on-site activities.These activities exacerbate congestion, noise and air pollution, particularly due to inefficient planning and limited coordination of material flows.As Europe advances toward climate-neutral urban freight targets, the sector faces a major challenge: absence of integrated systems planning to support sustainable transport policies.Despite isolated examples of logistics control such as cross-site material consolidation, there remains a lack of scalable and data-driven approaches to manage construction logistics sustainably.This study critically reviews how digital twins (DT) can act as catalysts for zero-emission construction logistics planning.Drawing on an analysis of literature, EU policies and expert interviews, it identifies key gaps in current practices.The results translate into DT requirements for measurable, coordinated and policyrelevant construction transport planning capable of supporting life cycle emissions accounting based on logistics and on-site activity.By synthesizing knowledge across construction, logistics, digitalization and sustainability domains, this study proposes a strategic framework showing how DTs act as a catalyst for sustainable construction transport and informing policy innovation.","author":[{"family":"Tetik","given":"Müge"},{"family":"Brusselaers","given":"Nicolas"},{"family":"Pikas","given":"Ergo"}],"issued":{"date-parts":[[2026]]},"DOI":"10.24928/2026/0208","URL":"https://doi.org/10.24928/2026/0208","source":"openalex"},{"id":"oa:W7127165058","type":"article-journal","title":"Smart Technologies in Food Safety and Quality Monitoring: A Review of Technological Advances, Opportunities and Challenges","abstract":"ABSTRACT Food safety is a critical component of the global food production and consumption system, as contaminated foods continue to trigger outbreaks, recalls, and substantial public health and economic burdens. This review examines recent technological advancements that strengthen food safety monitoring and quality assessment. Emerging analytical tools—supported by artificial intelligence, smartphone‐assisted diagnostics, sensor arrays, and portable detection systems—enable rapid, accurate, and non‐invasive evaluation of contaminants. These innovations enhance decision‐making capabilities for producers, regulators, and consumers, thereby reducing risks and improving traceability across the supply chain. Smart packaging solutions, including Radio Frequency Identification (RFID) indicators, freshness and gas sensors, and biosensor‐embedded films, enable real‐time monitoring of storage conditions, microbial activity, and product integrity. The integration of predictive microbiology software, big data analytics, and cloud‐based platforms further supports proactive, risk‐based food safety management by enabling improved prediction of microbial growth and facilitating standardized data sharing. Overall, advanced digital and sensor‐based tools are reshaping food safety practices by enabling continuous monitoring, rapid diagnostics, and transparent traceability. Future research should prioritize developing interoperable, supply chain–specific smart systems and enhancing their scalability, cost‐effectiveness, and adaptability. These advancements will accelerate the transition toward a more reliable, sustainable, and intelligent global food safety ecosystem. Smart technologies are extensively utilized across the food supply chain to guarantee real‐time monitoring of food safety and quality. Intelligent sensors and IoT‐enabled devices are employed in agricultural fields, processing facilities, and cold chains to incessantly monitor temperature, humidity, gas composition, and microbial activity, facilitating the early identification of deterioration and contamination. Intelligent packaging solutions that utilize biosensors and indicators deliver visual or digital data regarding freshness, shelf life, and product integrity to retailers and consumers alike. Blockchain‐enabled monitoring systems improve traceability, transparency, and swift recall management in food safety events. In processing sectors, AI‐driven vision systems facilitate automated inspection, fault identification, and quality assessment. These applications collectively minimize food waste, enhance regulatory adherence, bolster consumer confidence, and promote sustainable, data‐informed food safety management practices.","author":[{"family":"Dhar","given":"Payel"},{"family":"Bhowmik","given":"Abhijit"},{"family":"Nath","given":"Pinku"},{"family":"Patel","given":"DJ"},{"family":"Shankar","given":"Amar"},{"family":"Tomar","given":"Prakhar"},{"family":"Sinha","given":"Aashna"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1111/jfpe.70367","URL":"https://doi.org/10.1111/jfpe.70367","source":"openalex"},{"id":"oa:W7165575132","type":"article-journal","title":"Development of a Digital Twin for Anionic Polymerization–The Importance of Reliable Substance Data","abstract":"High Resolution Image Download MS PowerPoint Slide Anionic polymerization of vinyl monomers enables exceptional control over the molar mass distribution of the synthesized polymers. Still, it requires highly stringent reaction conditions and is extremely sensitive to impurities. These demands necessitate closed reaction setups with minimal external interference, such as dosing or sampling, which in turn limits real-time insight into the process, rendering it effectively a black-box operation. To overcome this limitation, we present a digital twin approach that integrates inline analytics with reaction kinetic modeling, enabling an innovative method for real-time monitoring and control of the polymerization process. This methodology is demonstrated through the synthesis of polystyrene- block -polyisoprene in cyclohexane using a stirred tank batch reactor. By using heat balance data, the developed model predicts the concentration of active species in the reactor and, consequently, the molar mass characteristics of the resulting polymer. Incorporating this predictive capability into a dynamic dosing strategy ensures the targeted synthesis of the desired product, significantly reducing the risk of unsuccessful polymerizations.","author":[{"family":"Kandelhard","given":"Felix"},{"family":"Schymura","given":"Juliane"},{"family":"Georgopanos","given":"Prokopios"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1021/acsomega.6c00051","URL":"https://doi.org/10.1021/acsomega.6c00051","source":"openalex"},{"id":"oa:W7170050867","type":"article-journal","title":"Integrating Advanced AI techniques to assist Urban Digital Twins Generation","abstract":"Abstract. Digital twins play a crucial role in autonomous driving applications and transportation system simulations. The need for large scale and dynamic information has increased interest in generating urban digital twins from remote sensing data. Aerial high resolution imagery of urban areas serves as the one of the most important data sources for this task. Advances in deep learning and machine learning allow more accurate and automated extraction of urban elements. In recent years, we have developed and integrated advanced deep learning models to extract various land cover types surrounding road networks, including buildings, roads, and vegetation. Furthermore, we have conducted proof of concept studies aimed at detecting and delineating linear landmarks from aerial imagery, including curbstones and road borders. These developments contribute to the creation of more accurate and detailed urban digital twins, which are essential for advanced urban analytics and intelligent transportation systems.Results from the deep learning models are presented for the Schwarzer Berg district in Brunswick, Germany, which is a test region for the development of mobility services and technologies at the German Aerospace Center (DLR). The AI models are trained using benchmark datasets from other urban regions, indicating that the proposed approaches can be readily transferred and evaluated in other European cities.","author":[{"family":"Tian","given":"Jiaojiao"},{"family":"Weishaupt","given":"Mareike"},{"family":"Gstaiger","given":"Veronika"},{"family":"Mutreja","given":"Guneet"},{"family":"Amrullah","given":"Chaikal"},{"family":"Henry","given":"Corentin"},{"family":"Krauß","given":"Thomas"},{"family":"Dangelo","given":"Pablo"},{"family":"Jangir","given":"Sandeep"},{"family":"Auer","given":"Stefan"},{"family":"Kurz","given":"Franz"},{"family":"Bittner","given":"Ksenia"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-archives-xlix-b1-2026-607-2026","URL":"https://doi.org/10.5194/isprs-archives-xlix-b1-2026-607-2026","source":"openalex"},{"id":"oa:W7162763349","type":"article-journal","title":"A Hybrid Digital Twin and AI Framework for Traffic Simulation and Route Finding","abstract":"Abstract. Urban traffic congestion poses significant challenges for today's cities, affecting mobility, productivity, and environmental quality. The present study proposes a data-driven framework that integrates deep learning specifically Recurrent Neural Networks (RNNs) with Digital Twin (DT) technology to enhance travel time prediction and traffic management. The model utilizes real-time and historical data from sources such as Google Maps, weather services, and traffic sensors to capture temporal dynamics and external factors influencing traffic patterns. The RNN model exhibited a high degree of predictive accuracy, as evidenced by its R² value of approximately 0.94. Furthermore, its incorporation into a DT environment facilitated dynamic 3D simulations and route optimization. A comparative analysis revealed that the DT system exhibited a marked superiority over conventional navigation tools in congested scenarios, with a travel time reduction of up to 26%. The findings indicate the potential for a synergistic integration of artificial intelligence (AI) and data technology (DT) to facilitate the development of intelligent, adaptable urban transportation systems.","author":[{"family":"Rezaei","given":"Zahra"},{"family":"Vahidnia","given":"Mohammad"},{"family":"Aghamohammadi","given":"Hossein"},{"family":"Azizi","given":"Zahra"},{"family":"Behzadi","given":"Saeed"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-annals-x-4-w8-2025-617-2026","URL":"https://doi.org/10.5194/isprs-annals-x-4-w8-2025-617-2026","source":"openalex"},{"id":"oa:W7140142093","type":"article-journal","title":"Lithium-ion Battery Energy Storage Digital Twin System and Applications","abstract":"Under the background of large-scale development of new energy, the operation and management of lithium battery energy storage systems face many challenges. Digital twin technology provides effective solutions for the intelligent upgrading of energy storage systems. This article focuses on the research of digital twin technology for lithium battery energy storage. Firstly, it clarifies the core connotation and composition architecture of digital twin technology, and then focuses on sorting out its research achievements in key areas such as model construction, real-time monitoring, life monitoring and management, and application scenarios. The model construction adopts a \"bottom-up\" multi-scale modeling and hybrid driving strategy, which can achieve accurate simulation of multiple physical fields; Real time monitoring relies on the \"edge computing+5G+industrial Ethernet\" architecture and hybrid data fusion algorithm to ensure the real-time and reliability of data transmission; Establish a \"assessment prediction maintenance\" full chain control mode for life management; This technology has been successfully applied in multiple practical scenarios such as power grid peak shaving and frequency regulation. Combined with monitoring practice, it has been shown that the core indicators of the constructed system, such as simulation accuracy and fault warning accuracy, meet the design standards, which can significantly improve the operational efficiency of energy storage power stations and reduce maintenance costs. Finally, summarize the core advantages and current problems of this technology, and look forward to future research directions such as multi-scale modeling optimization and cross domain technology integration, providing theoretical support and practical reference for the large-scale promotion and application of lithium battery energy storage digital twin technology.","author":[{"family":"Zhang","given":"Zhi"},{"family":"Zhou","given":"Zhaoming"},{"family":"He","given":"Yanqin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.54691/c2xqn614","URL":"https://doi.org/10.54691/c2xqn614","source":"openalex"},{"id":"oa:W7143780745","type":"article-journal","title":"Precision nutrition through diet-gut microbiome interactions: Emerging insights driven by artificial intelligence, microbiome health metrics, and mechanistic modeling","abstract":"Diet-gut microbiome interactions drive substantial inter-individual variability in metabolic responses to food, a fact that challenges the efficacy of uniform dietary recommendations. To address this complexity, advances in multi-omics profiling, dietary assessment technologies, and host clinical phenotyping now generate high-resolution multimodal datasets. However, managing these vast amounts of data necessitates the integration of artificial intelligence (AI) and machine learning (ML) approaches. In this review, we first delineate the multimodal data landscape and its associated computational workflows. These range from the initial preprocessing of heterogeneous inputs (filtering, normalization, dimensionality reduction) to ML modeling strategies designed to address high dimensionality, sparsity, and compositionality through feature engineering and regularization. We then summarize core ML applications, including the classification of habitual dietary patterns from microbiome signatures, prediction of postprandial metabolic responses, responder stratification, and in silico simulation of dietary perturbations. Furthermore, recent randomized controlled trials demonstrate the tangible clinical potential of AI-guided personalization. Next, we highlight composite microbiome health metrics and diet-specific indices, such as GMWI2 and DI-GM. These tools are essential because they condense high-dimensional taxonomic profiles into interpretable wellness scores for monitoring diet-induced shifts. We subsequently examine genome-scale metabolic models and microbiome “digital twins” that mechanistically link dietary substrates to community metabolism and host-relevant metabolites. We also discuss emerging hybrid AI-mechanistic frameworks that enhance interpretability, biological plausibility, and scalability. Finally, we outline translational priorities—including the development of diverse longitudinal cohorts, standardized benchmarking, and clinically trustworthy AI—that are required to realize equitable, microbiome-informed precision nutrition.","author":[{"family":"Barrera-Suarez","given":"Maria"},{"family":"Zhao","given":"Conan"},{"family":"Karnatovskaia","given":"Lioudmila"},{"family":"Sung","given":"Jaeyun"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/29933935.2026.2650247","URL":"https://doi.org/10.1080/29933935.2026.2650247","source":"openalex"},{"id":"oa:W7158874068","type":"article-journal","title":"Decentralised Manufacturing as a Networked Cyber–Physical System: Formalising Free and Open-Source Software Governance and ML Adaptation for Distributed Robustness","abstract":"Decentralised manufacturing is expanding as digitally controlled fabrication tools become accessible to SMEs, independent operators, and community workshops outside traditional factory settings, but the resulting heterogeneous, autonomously operated network introduces systemic uncertainty that no central authority governs. This paper proposes a systems-theoretic framework in which Free and Open-Source Software (FOSS) governance acts as the structural interoperability layer of a distributed cyber–physical manufacturing system (CPS), and node-local digital twins—each hosting a machine learning (ML) disturbance estimator—provide local adaptive compensation without centralised data aggregation. A defining property of the architecture is automatic improvement propagation: learned corrections distribute via federated learning to structurally similar nodes without operator intervention, and the open, observable FOSS ecosystem enables advances in one fabrication modality to transfer to others through shared interface standards. The framework is applied analytically to three disturbance classes: regulatory restriction, technical process variability, and supply chain disruption. Across cases, the analysis shows how open modular interfaces and local adaptation preserve functional continuity under perturbations that would more strongly affect centralised architectures. The contribution is a unified mathematical basis for robustness analysis in decentralised manufacturing CPS and a foundation for future simulation and empirical validation.","author":[{"family":"Dogančić","given":"Bruno"},{"family":"Rožić","given":"Jurica"},{"family":"Jokić","given":"Marko"},{"family":"Čeredar","given":"Marko"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/systems14050469","URL":"https://doi.org/10.3390/systems14050469","source":"openalex"},{"id":"oa:W7203764398","type":"article-journal","title":"THE DIGITAL TWIN OF THE AEROTANK IN THE TASKS OF INTELLIGENT MANAGEMENT OF SEWAGE TREATMENT PLANTS","abstract":"In the context of water scarcity and tightening environmental requirements, improving the energy efficiency of biological wastewater treatment processes has become particularly important. The aeration tank is one of the most energy-intensive and dynamically complex components units, strongly affected by the variability in influent flow and composition. Conventional PID control, do not provide predictive disturbance compensation and often result in excessive aeration and increased energy consumption. The study proposes an intelligent control approach based on a digital twin, neural network-based influent flow forecasting, and model predictive control (MPC). The digital twin represents a dynamic model of the biological process incorporating key state variables, including substrate, activated sludge, and dissolved oxygen concentrations. A neural network model is used to predict the diurnal variability coefficient of influent flow based on long-term statistical observations. The predicted values are incorporated into the MPC algorithm as measured disturbances, enabling anticipatory aeration system. Simulation results show stabilisation of dissolved oxygen under variable inflow conditions and reduces energy consumption by preventing over-aeration. The proposed architecture is suitable for implementation within existing industrial PLC-SCADA systems in advisory MPC mode and improves energy efficiency, robustness, and environmental performance.","author":[{"family":"Zhylkybayev","given":"TS"},{"family":"Zolotov","given":"AV"},{"family":"Ospanov","given":"Yerbol"},{"family":"Myassoedov","given":"D"},{"family":"Nazarov","given":"R"}],"issued":{"date-parts":[[2026]]},"DOI":"10.53360/2788-7995-2026-2(22)-21","URL":"https://doi.org/10.53360/2788-7995-2026-2(22)-21","source":"openalex"},{"id":"oa:W7143433946","type":"article-journal","title":"A Four Layer Cybersecurity Framework for Digital Twin Systems in the Food Industry","abstract":"This paper demonstrates an innovative four-layer cybersecurity framework specifically developed for digital twin environments in the food industry. The suggested architecture integrates machine learning-based real-time anomaly detection (including large language patterns), blockchain-based data integrity, and process mining for advanced operational control. The system was examined in a simulated dairy processing plant with real industrial control system (ICS) components. Notable enhancements were observed, attaining 95% attack detection rate, minimizing false positives to 5%, and lowering an average threat response time to 200 milliseconds. These outcomes demonstrate the effectiveness of integrated highly developed AI algorthims and blockchain technology to preserve digital twin systems in critical production environments. The present method offers a scalable and adaptable approach to address traditional and emerging cybersecurity threats in the food industry sector.","author":[{"family":"Adilzhanova","given":"Saltanat"},{"family":"Rakhysh","given":"Aigerim"},{"family":"Kunelbayev","given":"Murat"},{"family":"Amirkhanova","given":"Gulshat"},{"family":"Amirkhanov","given":"Bauyrzhan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.37394/23202.2026.25.12","URL":"https://doi.org/10.37394/23202.2026.25.12","source":"openalex"},{"id":"oa:W4411086864","type":"article-journal","title":"Prediction of Wireless Channel Statistics With Ray Tracing and Uncalibrated Digital Twin","abstract":"We introduce a framework for predicting wireless channel statistics based on digital twin (DT) and ray tracing. The DT is derived from satellite images and is uncalibrated, as it does not assume precise information on the electromagnetic properties of the materials in the environment. The uncalibrated DT is utilized to derive a geometric prior that informs a Gaussian process (GP) and thereby predict channel statistics using only a few measurements. The framework also quantifies uncertainty, offering statistical guarantees for rate selection in ultra-reliable low-latency communication (URLLC). Experimental validation demonstrates the efficacy of the proposed framework using measurement data.","author":[{"family":"Abouamer","given":"Mahmoud"},{"family":"Williams","given":"Robin"},{"family":"Popovski","given":"Petar"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/lwc.2025.3577135","URL":"https://doi.org/10.1109/lwc.2025.3577135","source":"openalex"},{"id":"oa:W7168349030","type":"article-journal","title":"Improving the Management of Loading Docks using Booking Systems with Digital Twins","abstract":"Carriers often experience delays when accessing loading docks to deliver goods to customers in urban activity hubs. Efficient deliveries are important for the productivity of carriers and reliable deliveries are essential for many receivers. Booking systems provide a means of improving the efficiency of deliveries. However, booking systems need to be well-configured to manage loading docks effectively. Facility managers require improved decision support methods for configuring loading dock booking systems. Determining the optimal settings to achieve desired outcomes requires advanced modelling and monitoring. This paper provides a framework for implementing digital twins to enhance the performance of booking systems at loading docks. The roles and interactions of key stakeholders are described. A range of analytical procedures are outlined. A systems analysis of factors and parameters necessary for developing a digital twin for loading docks is presented.","author":[{"family":"Thompson","given":"Russell"},{"family":"Mohri","given":"Seyed"},{"family":"Zhang","given":"Lele"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.trpro.2026.04.113","URL":"https://doi.org/10.1016/j.trpro.2026.04.113","source":"openalex"},{"id":"oa:W7128390346","type":"article-journal","title":"From Smart Ports to Sustainable Port Ecosystems: The Transformative Role of Artificial Intelligence","abstract":"Ports are critical nodes in global supply chains and play a central role in sustainability transitions in trade and logistics. This study investigates how Artificial Intelligence (AI) contributes to sustainable innovation within port ecosystems, focusing on efficiency, transparency, resilience, and environmental performance. To address the research question—how has AI supported sustainability in maritime ports?—we conducted a systematic screening combined with bibliometric performance analysis and science mapping. A total of 80 peer-reviewed articles published between 2019 and 2025 (Scopus) were analysed. The results show a strong acceleration of publications in 2025, alongside a citation–time lag for recent studies. The findings indicate three dominant application streams: (1) operational efficiency and optimisation (terminal operations, forecasting, routing, scheduling); (2) digital and smart-port enablement through IoT and data infrastructures; and (3) governance, risk, and compliance (e.g., Port State Control, inspection analytics, cyber-resilience). The mapping also evidences increasing convergence of AI with complementary technologies—particularly IoT and, in a smaller but visible subset, blockchain—to enhance trust, accountability, and interoperability. By synthesising the field’s intellectual structure and thematic evolution, this study outlines research gaps and proposes future directions toward integrated frameworks for sustainable port ecosystems and Sustainable Commerce 4.0.","author":[{"family":"Castro","given":"Marcela"},{"family":"Sabino","given":"Maria"},{"family":"Cabrita","given":"Maria"},{"family":"Mendes","given":"Ana"},{"family":"Pinho","given":"Tiago"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/systems14020187","URL":"https://doi.org/10.3390/systems14020187","source":"openalex"},{"id":"oa:W7151405370","type":"article-journal","title":"DIGITAL TWINS UNTUK MANAJEMEN BANJIR PERKOTAAN: TINJAUAN LITERATUR SISTEMATIS","abstract":"Banjir perkotaan yang semakin kompleks akibat perubahan iklim menuntut adopsi teknologi adaptif seperti Digital Twin (DT). Namun, implementasinya masih menghadapi kendala fragmentasi data, interoperabilitas sensor, dan kebutuhan visualisasi untuk keputusan cepat. Penelitian ini bertujuan memetakan perkembangan terkini dan arah masa depan melalui metode Systematic Literature Review (SLR) terhadap 50 studi terpilih periode 2021–2025. Hasil penelitian mengidentifikasi tiga tren solusi utama dalam diskusi global: (1) Hibridisasi Kecerdasan Buatan, yakni integrasi Graph Neural Networks (GNN) dan Large Language Models (LLM) untuk meningkatkan presisi prediksi; (2) Arsitektur Cloud-Multimodal, menggunakan kerangka kerja serverless untuk fusi data IoT dan satelit secara near real-time ; serta (3) Sistem Pendukung Keputusan Interaktif yang memanfaatkan Game Engines sebagai instrumen simulasi risiko imersif. Kesimpulannya, evolusi DT kini bertransformasi dari pemantauan pasif menjadi ekosistem cerdas yang mengintegrasikan AI tingkat lanjut dengan visualisasi interaktif sebagai standar baru manajemen banjir perkotaan.","author":[{"family":"Ripai","given":"Ipan"},{"family":"Baswardono","given":"Wiyoga"},{"family":"Abdurahman","given":"Nanang"},{"family":"Rijanto","given":"Estiko"},{"family":"Afrianto","given":"Irawan"},{"family":"Sumitra","given":"ID"}],"issued":{"date-parts":[[2026]]},"DOI":"10.36040/jati.v10i2.17252","URL":"https://doi.org/10.36040/jati.v10i2.17252","source":"openalex"},{"id":"oa:W7166664645","type":"article-journal","title":"Federated digital twins for intelligent decision-making in circular supply networks","abstract":"Despite intensified recycling efforts, global material consumption has more than tripled over the past five decades, while the global circularity rate has declined. This widening gap reveals that incremental improvements are insufficient and that a transition toward circular economy must be structural. This transition is constrained by fragmented data ecosystems, limited transparency among stakeholders, and conventional digital twin architectures that struggle to represent the dynamic, multi-loop nature of circular supply networks. To address these challenges, this position paper discusses a conceptual Federated Digital Twin framework that integrates federated system architectures to protect data sovereignty, intelligent agents to enable real-time negotiation and synchronization, and knowledge graphs to ensure semantic interoperability across distributed actors. The framework serves as a decision-support backbone for circular manufacturing, aiming for a coordinated management and systemic coherence of value-retention strategies and production planning for circular supply chains.","author":[{"family":"Karaduman","given":"Burak"},{"family":"Challenger","given":"Moharram"},{"family":"Lugaresi","given":"Giovanni"}],"issued":{"date-parts":[[2026]]},"DOI":"10.7148/2026-0287","URL":"https://doi.org/10.7148/2026-0287","source":"openalex"},{"id":"oa:W7147670393","type":"article-journal","title":"Digital Twin Integration for Enhancing Robotic Fastening Systems in Industrial Automation","abstract":"Digital twin (DT) technologies are increasingly applied in manufacturing to support monitoring, optimization, and predictive maintenance; however, most implementations remain operationally focused and disconnected from system-level decision-making and lifecycle engineering. This limitation is particularly critical in manufacturing environments that exhibit System-of-Systems (SoS) characteristics, where performance emerges from the interactions among autonomous, interdependent subsystems. This study proposes an integrated systems engineering framework in which the digital twin functions as a system-level integrator rather than a standalone simulation tool. The framework embeds Quality Function Deployment (QFD), Analytic Hierarchy Process (AHP), Reliability and Safety analysis (RAMST), and Statistical Process Control (SPC) within a unified digital twin architecture, enabling explicit traceability from stakeholder requirements to design decisions, operational control, and lifecycle performance. The framework is demonstrated through a robotic fastening system operating under high variability, multi-vendor integration, and reliability constraints. A high-fidelity digital twin was developed in MATLAB Simscape and synchronized with operational data via virtual sensors and SPC-based monitoring. Results from a 35-month simulation study (n = 1050 operations) show a 30% reduction in system downtime and a 15% improvement in fastening quality (torque and angle compliance), supported by 95% confidence intervals, alongside enhanced fault detection and preventive maintenance capabilities. The findings demonstrate that integrating decision-making, monitoring, and learning within a single DT environment supports resilient, adaptive manufacturing systems aligned with Industry 4.0–5.0 objectives.","author":[{"family":"Levi","given":"Eliasaf"},{"family":"Kordova","given":"Sigal"},{"family":"Tahan","given":"Meir"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/systems14040372","URL":"https://doi.org/10.3390/systems14040372","source":"openalex"},{"id":"oa:W7131628284","type":"article-journal","title":"Navigating Earth governance: A cybernetic and pragmatic pathway to digital twin Earth","abstract":"Digital Twin Earth (DTE) stands at a transformative crossroads: evolve beyond sophisticated “digital mimicry” into a revolutionary planetary governance engine or remain confined to passive observation. We propose that DTE's transformative potential lies in integrating Human-AI synergy to enable proactive Earth governance through continuous intervention-feedback loops connecting real Earth systems, digital simulations, and policy implementation. This paradigm transforms passive environmental monitoring into active navigation of Earth's trajectory within planetary boundaries. While deliberate large-scale intervention carries inherent risks, the potential benefits—building systemic resilience against cascading environmental crises—substantially outweigh the drawbacks of continued passive evolutionary approach. We posit DTE as the high-fidelity simulation environment and AI as the core analytical intelligence within this dynamic governance loop, enabling human stakeholders to continuously design, test, implement, and refine governance strategies. We propose Digital Cousins as a pragmatic implementation pathway that balances scientific robustness with computational feasibility, offering targeted regional governance solutions. By operationalizing AI-powered DTE as an adaptive decision-making system, humanity can consciously navigate Earth’s futures through integrated sensing, simulation, and policy implementation.","author":[{"family":"Li","given":"Xin"},{"family":"Su","given":"Jianbin"},{"family":"Yuan","given":"Shiwei"}],"issued":{"date-parts":[[2026]]},"DOI":"10.59717/j.xinn-geo.2026.100203","URL":"https://doi.org/10.59717/j.xinn-geo.2026.100203","source":"openalex"},{"id":"oa:W4412907242","type":"article-journal","title":"Applications of Robotic Exoskeletons as Motion-Assistive Systems in Cancer Rehabilitation","abstract":"Robotic exoskeletons have emerged as promising motion-assistive technologies to meet the growing demand for structured, personalized cancer rehabilitation. This review critically examines their application in enhancing functional recovery, alleviating cancer-related fatigue, and improving quality of life among cancer patients and survivors. We first outline current evidence-based exercise strategies in cancer rehabilitation, followed by an analysis of how robotic exoskeletons complement and extend these approaches by restoring mobility, strengthening musculature, and supporting psychological well-being. Additionally, we assess how well they combine with multimodal interventions like nutritional, psychological, and digital therapeutics and their benefits. The convergence of artificial intelligence, wearable sensors, and telemedicine is also reshaping the landscape of remote, adaptive rehabilitation. Despite encouraging preliminary data, widespread clinical adoption remains limited due to challenges related to cost, exoskeleton system accessibility, safety, and long-term efficacy. We call for large-scale clinical trials, interdisciplinary collaboration, and policy reforms to promote equitable access to robotic-assisted rehabilitation. Collectively, this review offers a comprehensive perspective on the technical principles, therapeutic potential, and future directions of robotic exoskeletons as innovative tools in cancer recovery.","author":[{"family":"Chen","given":"Yisheng"},{"family":"Wu","given":"Guanghui"},{"family":"Wang","given":"Qiangqiang"},{"family":"Ding","given":"Ye"},{"family":"Wu","given":"Li"},{"family":"Shi","given":"Haojun"},{"family":"Sun","given":"Zijin"},{"family":"Ou","given":"Zemin"},{"family":"Miao","given":"Yunxuan"},{"family":"Ji","given":"XB"},{"family":"Wu","given":"Ke"},{"family":"Luo","given":"Zhiwen"}],"issued":{"date-parts":[[2025]]},"DOI":"10.34133/research.0855","URL":"https://doi.org/10.34133/research.0855","source":"openalex"},{"id":"oa:W7138014453","type":"article-journal","title":"A Systematic Review of the Trajectory of Urban Resilience Research: A Bibliometric Perspective on Global Trends and China’s Pathway","abstract":"This study employs bibliometric analysis, utilizing the visualization tools CiteSpace 6.3.R1 and VOSviewer 1.6.18, to systematically examine 8727 documents from the Web of Science Core Collection (2000–2024) related to “resilient cities” and “urban resilience.” It explores the evolution of resilient city research, current international trends, practical developments in China, and future directions. The study addresses key questions concerning the theoretical foundations of resilient cities, research advances in the security field, China’s implementation pathways, and emerging trends. Findings indicate that resilient city discourse has evolved from a narrow focus on engineering-based disaster prevention toward a multidimensional, socio-ecological–economic adaptive system. This progression can be divided into three phases: the theoretical foundation period (2000–2008), the technological integration period (2009–2018), and the complex crisis response period (2019–present). Internationally, practices are increasingly centered on climate change adaptation, supported by multi-level governance frameworks such as the MCR2030 initiative. China demonstrates a “dual-track” approach that combines policy-driven initiatives with localized innovations, advancing through international pilot projects, domestic policy experimentation, and grassroots exploration. The study also highlights differences between Chinese and Western research in perspectives, methodologies, and theoretical frameworks. Future resilient city development is expected to emphasize systematization, digitalization, and equity, leveraging technologies such as digital twins and artificial intelligence while fostering community participation and multi-scale collaborative governance. By systematically outlining the theoretical evolution and practical logic of resilient cities, this study offers insights for urban resilience building in developing countries and provides a methodological reference for enhancing resilience capabilities across different administrative levels.","author":[{"family":"Han","given":"Meng"},{"family":"Fu","given":"Gui"},{"family":"Wu","given":"Zhirong"},{"family":"Lu","given":"Yao"},{"family":"Xie","given":"Xuecai"},{"family":"Xu","given":"Surui"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18062945","URL":"https://doi.org/10.3390/su18062945","source":"openalex"},{"id":"oa:W7160497847","type":"article-journal","title":"Digital Twin-Based Self-Adaptation: Value-at-Risk and Learning-to-Synchronize","abstract":"Digital twins enable safe experimentation and adaptation of mission-critical systems by providing replicas of complex environments. However, their reduced complexity and partial observability can cause underspecification, leading to overfitting in simulation and unstable behavior after deployment. Underspecification manifests as a distribution mismatch between simulated and real systems and as the result of simplified models that miss important structural dependencies. Existing safety techniques, such as shielding and uncertainty quantification, mainly target physical systems, which typically have fewer and simpler internal dependencies than software systems. Our approach extends digital twins to learning-enabled self-adaptive systems affected by underspecification and evaluates two mitigation concepts: Value-at-Risk (VaR) and learning-to-synchronize. VaR captures the trade-off between maximizing learning in the twin and minimizing hazardous interactions with the real system, while learning-to-synchronize decides when and how often to switch training between the twin and the real system. We use these concepts to design an architecture combining a digital twin, a self-adaptation agent, a propagation model, and coordination mechanisms, and evaluate it by injecting failures that propagate through a component-based system. Our results show that an appropriate synchronization rate improves the VaR trade-off by boosting performance and reducing real-environment training, while also revealing how quickly the agent can overfit to the twin, motivating further work on underspecification and better-calibrated learning-to-synchronize strategies.","author":[{"family":"Adriano","given":"C"},{"family":"Alder","given":"Nicolas"},{"family":"Hildebrandt","given":"Philipp"},{"family":"Schniese","given":"Til"},{"family":"Schulze","given":"Maximilian"},{"family":"Ghahremani","given":"Sona"},{"family":"Giese","given":"Holger"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5772/intechopen.1015304","URL":"https://doi.org/10.5772/intechopen.1015304","source":"openalex"},{"id":"oa:W7197002986","type":"article-journal","title":"Digital Twin Applications in Food Processing and Supply Chains: A Systematic Review","abstract":"Digital twin technology creates dynamic, real-time virtual replicas of physical entities across their full lifecycle. Enabled by real-time data acquisition, multi-physics coupled simulation, and intelligent decision optimization, it can accurately characterize the core inherent laws of food systems, including heat and mass transfer, dynamic microbial evolution, and quality deterioration during processing, thus emerging as a key enabler for the digital and intelligent transformation of the global food industry. The food sector faces persistent systemic challenges, including skilled labor shortages, raw material batch variability, processing quality fluctuations, high supply chain losses, and limited responsiveness to diversified consumer demands. By integrating Internet of Things (IoT), artificial intelligence (AI), advanced simulation, and big data analytics, digital twin technology enables precise end-to-end control across the food processing value chain. This paper proposes a four-tier technical architecture (perception, model, simulation, and application layers) and a scenario-based implementation framework for core food processing domains, systematically analyzing the technical pathways, operational boundaries, and research gaps of digital twin applications. We further identify cross-cutting coupling challenges across data, model, process, and governance dimensions, along with corresponding mitigation strategies. Our analysis confirms that digital twin adoption delivers real-time monitoring, predictive quality assurance, and holistic process optimization across the food chain, reducing manual reliance, operational losses, and improving product consistency and production efficiency. Finally, we outline priority research directions to advance the inclusive, standardized, and sustainable application of digital twin technology in the food industry.","author":[{"family":"Li","given":"Xiaoman"},{"family":"Zhang","given":"Shunliang"},{"family":"Liang","given":"E"},{"family":"Li","given":"Jiapeng"},{"family":"Su","given":"Li"},{"family":"Li","given":"Dan"},{"family":"Zhang","given":"Kaihua"},{"family":"Wang","given":"Hui"},{"family":"Liu","given":"Meng"},{"family":"Wang","given":"Shouwei"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.jfutfo.2026.08.012","URL":"https://doi.org/10.1016/j.jfutfo.2026.08.012","source":"openalex"},{"id":"oa:W7172442832","type":"article-journal","title":"An Environment-Aware Indoor-Outdoor Integrated Digital Twin for Healthy Mobility","abstract":"Abstract. Existing building digital twins treat indoor environments as static geometric containers, ignoring the dynamic coupling between ventilation structure states and indoor environmental quality. Furthermore, managing indoor and outdoor spaces as separate data silos prevents the continuous assessment of occupant exposure across building boundaries. This paper proposes an environment-aware, indoor-outdoor integrated digital twin framework coupling geometric entity states with physical environmental fields for healthy mobility assessment. The framework utilizes a three-layer architecture. First, the Geometric-Semantic Layer provides a seamless LOD4 model with topologically stitched spaces, modeling ventilation facilities as first-class entities with mutable state attributes (Full Closed, Half Open, Full Open). Second, the Physical Field Layer maps mobile sensing data (PM2.5, CO2) onto semantic entities using a semantic-constrained method, treating walls and closed windows as aggregation barriers. Finally, the Behavioral Response Layer combines entity-level pollution values with pedestrian counts to compute a cumulative Crowd Exposure Index (CEI). Implemented on a Cesium platform, the framework was validated through a week-long university building experiment. Results show indoor PM2.5 in a fully enclosed study room averaged 61.2 μg/m³—1.6 times the outdoor level and 4.1 times the WHO guideline. This resulted in a CEI 12 times higher than in outdoor transit areas. Semantic correlation confirms the \"Full Closed\" window state primarily drives pollutant accumulation. This validates the framework's core geometry-physics coupling, demonstrating its potential to guide intelligent ventilation interventions and healthy building management.","author":[{"family":"Li","given":"Yan"},{"family":"Ye","given":"Chenming"},{"family":"Shi","given":"Wenxuan"},{"family":"Zhang","given":"Wenqing"},{"family":"Zhang","given":"Yuyang"},{"family":"Hu","given":"Teng"},{"family":"Kang","given":"Zhizhong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-archives-xlix-b4-2026-555-2026","URL":"https://doi.org/10.5194/isprs-archives-xlix-b4-2026-555-2026","source":"openalex"},{"id":"oa:W4414947044","type":"article-journal","title":"Research on Intelligent Monitoring of Ship Piping System Based on Digital Twin","abstract":"With the concept of Intelligent Manufacturing 2025, the shipbuilding industry, as one of the important manufacturing industries in China, needs to address the issue of intelligent and digital transformation. Ship piping system is distributed in various parts of the ship, the number is huge, the spacing is small, and contained in a variety of hull structure, not only is it not easy to find its abnormality, and the alarm cannot determine the location of the fault, which affects the operation and safety of the ship, so there is an urgent need for a visualisation of a new method for monitoring and management. This paper proposes an intelligent monitoring method of pipe system based on three-dimensional digital twin, studies the key technology and architecture of digital twin implementation in the field of ships, and proposes an effective monitoring method. By constructing an equal-scale digital pipe system model of the ship, real-time display of the physical information spatial data of the pipeline and the output data of the pipe line digital twin, and real-time monitoring and abnormal alarm of the ship’s pipe line based on the digital twin, dynamically displaying the abnormal location, thus improving the safety of the ship.","author":[{"family":"Jiao","given":"Tingyu"},{"family":"Zeng","given":"Ji"},{"family":"Zhang","given":"Yu"},{"family":"Gu","given":"Huaning"},{"family":"Ding","given":"Weiqi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/978-981-95-1487-8_57","URL":"https://doi.org/10.1007/978-981-95-1487-8_57","source":"openalex"},{"id":"oa:W7133357740","type":"article-journal","title":"Graph-based Analysis and Visualization of Metadata in the Context of Urban Digital Twins","abstract":"Abstract. Urban Digital Twins (UDT) depend on integrating various heterogeneous data sources to represent complex urban environments. Metadata management is an essential component of such systems. This paper introduces a framework for analyzing and visualizing semantic relationships between digital resources in the UDT metadata catalogs, focusing on the Smart District Data Infrastructure (SDDI). Conversion of metadata relationships into directed graphs enables intuitive exploration of the dependencies between resources. Utilizing technologies such as CKAN, NetworkX, Cytoscape, and Dash allows users to perform advanced analytic tasks such as detecting important resources, community detection, detection of isolated resources, cycle detection, and link prediction. It will show how graph theory can help in improving the quality evaluation of metadata, enhance transparency and usability, and contribute to the scalable and effective implementation of UDTs.","author":[{"family":"Knezevic","given":"Marija"},{"family":"Fuchsloch","given":"Felix"},{"family":"Donaubauer","given":"Andreas"},{"family":"Kolbe","given":"Thomas"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5194/isprs-archives-xlviii-4-w19-2025-71-2026","URL":"https://doi.org/10.5194/isprs-archives-xlviii-4-w19-2025-71-2026","source":"openalex"},{"id":"oa:W7140226103","type":"article-journal","title":"Emerging Technologies as Enablers of Sustainable Management: A Comprehensive Framework—The Role of Saudi Arabia’s Vision 2030","abstract":"Emerging technologies are increasingly positioned as key enablers of sustainable management; however, existing research largely examines digital transformation and sustainability as parallel rather than integrated processes, particularly within national transformation contexts. Moreover, prior studies tend to focus on individual technologies or environmental outcomes, offering limited insight into how emerging technologies are embedded within ESG-oriented management systems and institutional governance frameworks. To address this gap, this study adopts a structured conceptual literature review methodology guided by a systematic PRISMA-informed selection process. Based on the qualitative synthesis of 76 peer-reviewed studies, the paper develops an integrative framework explaining how emerging technologies enable sustainable management and digital transformation within the context of Saudi Arabia’s Vision 2030. Drawing on sustainability transitions, digital transformation, and ESG management literature, emerging technologies are conceptualized as combinatorial digital capabilities operating through a recursive capability loop (Sense–Analyze–Decide–Act–Verify). These capabilities influence sustainability outcomes through four mediating mechanisms—measurement, optimization, transparency, and institutionalization—and are conditionally shaped by national institutional enablers. The proposed framework positions ESG-oriented management systems as a mediating layer between technological capabilities and multi-dimensional sustainability outcomes, while explicitly addressing the double transition paradox, which recognizes both the sustainability benefits and environmental costs of digital infrastructures. The study advances theory by integrating ESG mediation, institutional moderation, and capability-based mechanisms into a unified analytical architecture and formulates six theoretically grounded propositions to guide future empirical research. The framework also provides actionable insights for managers and policymakers seeking to align digital transformation, ESG integration, and national sustainability agendas in Saudi Arabia and comparable emerging economy contexts.","author":[{"family":"Abaker","given":"Ahmed"},{"family":"Elgili","given":"Mustafa"},{"family":"Arees","given":"Bushara"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/su18073168","URL":"https://doi.org/10.3390/su18073168","source":"openalex"},{"id":"oa:W7143376695","type":"article-journal","title":"MONITORING AND MODELING OF THERMODYNAMIC PROCESSES IN THE FOOD INDUSTRY FOR THE DEVELOPMENT OF DIGITAL TWINS","abstract":"This article discusses an approach to developing digital twins for the food industry based on monitoring and numerical modeling of thermodynamic processes in a baking chamber (electric oven). The professional electric oven ASTAR, designed for the thermal processing of bakery products, was used as the experimental object. As part of the monitoring system, an infrared pyrometer (VICTOR 304F), a thermal imaging camera (UNI-T UTi120S), and an analog thermometer (MGprof) installed inside the oven chamber were employed. This setup allowed for the acquisition of reliable temperature data within the working chamber. Temperature data were collected periodically throughout the baking process, and based on these measurements, a temperature field map was generated. A mathematical model of heat transfer, implemented in two-dimensional (2D) format using MATLAB PDE Toolbox and incorporating Dirichlet and Neumann boundary conditions, was validated through comparison with the experimental results. The obtained results not only enable accurate modeling of temperature gradients and heat fluxes inside the baking chamber, but also lay the foundation for the creation of a digital twin capable of predicting system behavior in real time. The proposed approach can be applied to improve energy efficiency, automate quality control, and optimize technological processes in the food industry. This research contributes to addressing the challenges encountered in modeling and designing thermodynamic processes during the development of digital twins.","author":[{"family":"Makhambetov","given":"KI"},{"family":"Belgibaev","given":"BA"},{"family":"Kunicina","given":"Nadezhda"},{"family":"Amirkhanova","given":"GA"}],"issued":{"date-parts":[[2026]]},"DOI":"10.55452/1998-6688-2026-23-1-10-21","URL":"https://doi.org/10.55452/1998-6688-2026-23-1-10-21","source":"openalex"},{"id":"oa:W7154458446","type":"article-journal","title":"OpenDT: Exploring Datacenter Performance and Sustainability with a Self-Calibrating Digital Twin","abstract":"Datacenters are the backbone of our digital society, but raise numerous operational challenges. We envision digital twins becoming primary instruments in datacenter operations, continuously and autonomously helping with major operational decisions and with adapting ICT infrastructure, live, with a human-in-the-loop. Although fields such as aviation and autonomous driving successfully employ digital twins, an open-source digital twin for datacenters has not been demonstrated to the community. Addressing this challenge, we design, implement, and experiment using OpenDT, an Open-source, Digital Twin for monitoring and operating datacenters through a continuous integration cycle that includes: (1) live and continuous telemetry data; (2) discrete-event simulation using live telemetry from the physical ICT, with self-calibration; and (3) SLO-aware and human-approved feedback to physical ICT. Through trace-driven experiments with a prototype mainly covering stages 1 and 2 of the cycle, we show that (i) OpenDT can be used to reproduce peer-reviewed experiments and extend the analysis with performance and energy-efficiency results; (ii) OpenDT's online re-calibration can increase digital-twinning accuracy, quantified to a MAPE of 4.39% vs. 7.86% in peer-reviewed work. OpenDT adheres to FAIR/FOSS principles and is available at: https://github.com/atlarge-research/opendt/tree/hcp.","author":[{"family":"Nicolae","given":"Radu"},{"family":"Toorn","given":"Jules"},{"family":"Kraniti","given":"Stavriana"},{"family":"Liu","given":"H"},{"family":"Iosup","given":"Alexandru"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1145/3777911.3800634","URL":"https://doi.org/10.1145/3777911.3800634","source":"openalex"},{"id":"oa:W4413393021","type":"article-journal","title":"Digital Twins as Enablers of Sustainable and Resilient Industry 5.0 Infrastructure: A Review","abstract":"The advent of Industry 5.0 heralds a paradigm shift toward human-centric, sustainable, and resilient industrial systems. Central to this transformation is the integration of Digital Twins (DTs), virtual replicas of physical entities that enable real-time monitoring, predictive analysis, and dynamic decision-making. This paper presents a comprehensive review of the current state and future potential of DTs in facilitating sustainable and resilient infrastructure within Industry 5.0. By synthesizing insights from 60 academic papers, the study explores key applications, including smart manufacturing, urban planning, and supply chain resilience, where DTs optimize resource usage, minimize environmental impact, and enhance operational efficiency. The convergence of enabling technologies such as IoT, AI, blockchain, and edge computing is discussed, highlighting their role in overcoming challenges like data integration, high implementation costs, and cybersecurity risks. Through an in-depth analysis, this paper identifies research gaps and proposes a conceptual framework to advance the adoption of DTs in Industry 5.0, emphasizing their potential to create a sustainable, human-centered industrial future.","author":[{"family":"Mannu"},{"family":"Rawat","given":"Riya"},{"family":"Nagal","given":"Kritika"},{"family":"Sharma","given":"Rakhee"}],"issued":{"date-parts":[[2025]]},"DOI":"10.23919/indiacom66777.2025.11115543","URL":"https://doi.org/10.23919/indiacom66777.2025.11115543","source":"openalex"},{"id":"oa:W4409581216","type":"article-journal","title":"Digital Twin Technologies for Vehicular Prototyping: A Survey","abstract":"Digital Twin (DT) technology is widely regarded as one of the most promising tools for industry development, demonstrating substantial application across numerous cyber-physical systems. Gradually, this technology has been introduced into modern vehicular systems focusing on its application in intelligent driving, connected vehicles, automotive engineering, aircraft health, and many more. By creating dynamic, virtual replicas of physical vehicles and their associated components, DT enables unprecedented levels of analysis, simulation, and real-time monitoring, thereby enhancing performance, safety, and sustainability. This paper offers a comprehensive review, extending beyond digital twins to include various prototyping approaches for target-specific applications focusing on the smart vehicular systems across automotive, aviation, and maritime domains driving the evolution of next-generation vehicular infrastructure.","author":[{"family":"Kabir","given":"Md"},{"family":"Ravi","given":"Bhagawat"},{"family":"Ray","given":"Sandip"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/ojits.2025.3562504","URL":"https://doi.org/10.1109/ojits.2025.3562504","source":"openalex"},{"id":"oa:W4411431272","type":"article-journal","title":"Transforming nano grids to smart grid 3.0: AI, digital twins, blockchain, and the metaverse revolutionizing the energy ecosystem","abstract":"This review explores the transformative architecture of Smart Grid 3.0 by integrating cutting-edge technologies. It presents novel architectural frameworks to transform nanogrid, microgrid, and VPP topologies to their Grid 3.0 counterparts. This study systematically analyzes the application of advanced algorithms and technologies across all hierarchical subsystems—nanogrid 3.0, microgrid 3.0, VPP 3.0, and Smart Grid 3.0. These digital technologies have transformative capabilities. The digital twins can perform real-time monitoring, simulation, and predictive analysis; blockchain ensures secure, decentralized energy transactions; and the metaverse creates immersive, interactive environments for system management. This review also explores the role of AI in power grid which is to optimize energy scheduling, fault detection, and energy management. This paper adds to the literature by systematically addressing subsystems of Smart Grid 3.0, including energy generation, transmission, distribution, communication, and storage. Challenges such as interoperability, scalability, data integrity, and cybersecurity are discussed, and solutions are proposed which highlights the need of interdisciplinary approach. These include cyber-attack detection and mitigation mechanisms, advanced simulation tools, and robust policy frameworks. A thorough review of literature enabled this paper to present practical implementation strategies and real-world examples of digital technologies integrated smart grids. By integrating these technologies across hierarchical energy systems, this study establishes a foundation for future research in transforming conventional smart grid infrastructure into a resilient, efficient, and interconnected cyber-physical energy network called Smart Grid 3.0 as the peak of this evolution so far.","author":[{"family":"Zahid","given":"Herman"},{"family":"Zulfiqar","given":"Adil"},{"family":"Adnan","given":"Muhammad"},{"family":"Iqbal","given":"Muhammad"},{"family":"Shah","given":"Anwar"},{"family":"Abbasi","given":"Usman"},{"family":"Mohamed","given":"Salah"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.rineng.2025.105850","URL":"https://doi.org/10.1016/j.rineng.2025.105850","source":"openalex"},{"id":"oa:W4412788138","type":"article-journal","title":"Supply Chain Resilience: A Critical Review of Risk Mitigation, Robust Optimisation, and Technological Solutions and Future Research Directions","abstract":"Abstract This study systematically evaluates the literature of supply chain resilience by integrating bibliometric and network analysis techniques. This analysis is conducted following the dynamic capability, as a theoretical lens, to understand and analyse supply chain resilience. We extracted and curated 294 peer‐reviewed articles from leading academic databases, Web of Science and Scopus, covering the period from January 2000 to 2024. We applied two complementary network analysis methods, a keyword co‐occurrence network (KCON) to analyse the frequency and interrelationships among key terms, and a research focus parallelship network (RFPN) to map the connectivity among research streams. These analytical approaches revealed three distinct research clusters, optimisation for supply chain resilience, technology adoption for supply chain resilience, and resilience strategies against disruptions and risk management. By linking emerging trends in digital transformation with traditional risk management practices, this study offers a new perspective for both academic inquiry and managerial practice. Practically, integrating digital technologies, especially digital twin and machine learning, into risk management processes offers a strategic roadmap for real-time monitoring and decision-making in supply chain resilience. Furthermore, this study identifies significant research gaps, including an exploration of micro‐level dynamics within organisations, and the development of advanced simulation techniques and robust approaches to manage uncertainties.","author":[{"family":"Shekarabi","given":"Seyed"},{"family":"Mavi","given":"Reza"},{"family":"Macau","given":"Flávio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s40171-025-00458-8","URL":"https://doi.org/10.1007/s40171-025-00458-8","source":"openalex"},{"id":"oa:W4411379553","type":"article-journal","title":"Hospital at home digital twin for the management of patients with frailty: a scoping review protocol","abstract":"INTRODUCTION: Patients with frailty are at risk of adverse outcomes such as mortality, falls, deconditioning and hospital readmissions. With an increasingly ageing population and a greater likelihood of frailty, there is a significant need to ensure that patients are managed in the right place and at the right time. There has been a focus on offering hospital-level care at home as a way to meet this need, incorporating strategies to integrate care and use digital solutions. Digital twin (DT) technology is one advancement, offering a virtual replica of an object/environment, which has the potential to make use of real-time data personalised for an individual patient and/or setting to inform and support patient management decisions. We are yet to realise the full potential of this new way of integrated working and technological advancements. This scoping review aims to ascertain the current evidence for the components of the DT architecture to enable the monitoring and management of patients with frailty living at home. METHODS: This scoping review will follow the Joanna Briggs Institute methodology for scoping reviews and will be reported following the Preferred Reporting Items for Systematic Reviews Extension for Scoping Reviews guidelines. The following electronic databases will be searched: Medline, Embase, CINAHL, Cochrane CENTRAL, Web of Science and Scopus. Relevant websites will be searched for grey literature or case reports to capture the required information, as well as any documents provided by stakeholders. Primary studies, published in the English language from 2019 to the present day, which report on the monitoring or management of patients with long-term conditions and frailty within their home environment, will be included. Screening will be conducted by at least two independent reviewers against eligibility criteria, and a piloted data extraction form will be used to align with the research questions. Qualitative content analysis will be used. Data will be presented in tabular form, as well as descriptive and illustrative formats, to address the objectives of this review. ETHICS AND DISSEMINATION: This scoping review does not require ethical approval. The findings of this review will be disseminated through peer-reviewed journals and conferences and will support the development of a conceptual model of a hospital-at-home DT for the management of patients with frailty.","author":[{"family":"Yahya","given":"Faiza"},{"family":"Cooper","given":"Matthew"},{"family":"Kassem","given":"Mohamad"},{"family":"Nazar","given":"Hamde"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1136/bmjopen-2024-093418","URL":"https://doi.org/10.1136/bmjopen-2024-093418","source":"europepmc"},{"id":"oa:W7129105533","type":"article-journal","title":"Variational Mechanics for Mining Infrastructure Design: A Systematic Review from Hamilton’s Principle to Physics-Constrained Optimization and Digital Twins","abstract":"This article presents a systematic synthesis of variationally grounded approaches for the design and optimization of mining structural infrastructure. This study is motivated by the critical need to ensure stiffness, reliability, and operational availability under severe loading, mass constraints, and aggressive environmental conditions. Methodologically, the study situates structural modeling and synthesis within the continuity of the principle of stationary action. It demonstrates that, in the quasi-static regime, structural equilibrium is obtained as the stationarity of the total potential energy; consequently, the finite element method (FEM) arises naturally as a Ritz–Galerkin approximation of this underlying variational statement. On this basis, topology optimization is interpreted as a physics-constrained optimization problem wherein the design is posed as an outer optimality level acting over an energetically defined state. It is worth noting that SIMP-based formulations require explicit regularization to define the effective problem being solved. Emphasis is placed on the traceability between physical assumptions, discretization choices, regularization, and the resulting structural interpretations. The core contribution of this paper is a systematic literature review that consolidates evidence across variational mechanics, FEM-based optimization, and industrial applications, identifying recurrent methodological patterns and gaps that currently limit transfer to mining practice. Furthermore, a fully specified illustrative case is included to demonstrate reporting discipline and methodological consistency, rather than as a validation of a new optimization method. The conclusions highlight that a variational reading provides a coherent theoretical backbone for structural analysis, synthesis, simulation, and physics-based digital twins, while also clarifying the extensions required for industrial deployment, such as stability constraints, manufacturability, and multiphysics coupling within Mining 4.0 workflows.","author":[{"family":"Rojas","given":"Luis"},{"family":"Martinez","given":"Yuniel"},{"family":"Paz","given":"Álex"},{"family":"Peña","given":"Álvaro"},{"family":"García","given":"José"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/math14040689","URL":"https://doi.org/10.3390/math14040689","source":"openalex"},{"id":"oa:W7117311628","type":"article-journal","title":"Bridging Cognitive Digital Twins and Cognitive User Interfaces: A Systematic Literature Review","abstract":"Industry 5.0 emphasizes human-centered design in smart manufacturing environments, where Cognitive Digital Twins (CDTs) and Cognitive User Interfaces (CUIs) emerge as critical technologies for enhanced decision-making and system interaction. Despite sharing similar cognitive characteristics, CDTs and CUIs have been studied in isolation, which resulted in a fragmented landscape, limiting their integration into intelligent human-computer collaboration. This systematic literature review, guided by the PRISMA framework, investigates the integration opportunities between CDTs and CUIs to bridge this disciplinary gap. A comprehensive search in Scopus identified 227 papers, which were systematically filtered to 49 relevant studies for content analysis The review synthesizes a set of requirements essential for designing integrated CDT–CUI systems. Findings highlight that while CDTs rely on static interfaces, CUIs demonstrate advanced adaptability capabilities, including dynamic user interface adaptation through User Mentality Models and multimodal interaction support, significantly enhancing current rudimentary CDT interaction approaches.","author":[{"family":"Cardamone","given":"Martina"},{"family":"Elbasheer","given":"Mohaiad"},{"family":"Facchini","given":"Francesco"},{"family":"Mirabelli","given":"Giovanni"},{"family":"Padovano","given":"Antonio"},{"family":"Sammarco","given":"Chiara"},{"family":"Vitti","given":"Micaela"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.procs.2025.12.116","URL":"https://doi.org/10.1016/j.procs.2025.12.116","source":"openalex"},{"id":"oa:W4406577344","type":"article-journal","title":"Integrating circular economy while adopting digital twin for enhancing logistics efficiency: a hybrid Fuzzy Delphi-FUCOM based approach","abstract":"This study integrates both concepts of Circular Economy (CE) and Digital Twin (DT) and uses a hybrid approach to prioritise Digital-based Circular economy potentials for enhancing logistics efficiency. In total, 21 potential factors were identified through literature review and experts’(Eps) responses, categorised into the three main aspects (economic, social, and circular). The Fuzzy Delphi approach (FDA) was used to screen out four factors. Later, the weights of the significant factors were computed using the Fuzzy Full Consistency Method (F-FUCOM). The hybrid approach’s results were validated through sensitivity and comparative analysis. The study proposes a Digital Twin-based Circular Economy framework and technology, organisation, environment (TOE) based taxonomy, providing researchers and policymakers valuable insights for decision-making (DM) to enhance logistics efficiency. The proposed results highlight that critical potentials such as ‘Reverse logistics (P14)’, ‘Operational cost (P1)’, ‘Route optimization (P2)’, and ‘Environmental impact (P15)’ played a significant role in enhancing the efficacy of logistics operations. This study provides the integrated framework that helps the researchers understand and analyse the potentials of digital twin in circular economy and provides insights for industrial managers for its implementation in logistics operations.","author":[{"family":"Shoaib","given":"Muhammad"},{"family":"Zhang","given":"Shengzhong"},{"family":"Ali","given":"Hassan"},{"family":"Ahmad","given":"Muhammad"},{"family":"Khan","given":"Muhammad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/13675567.2025.2451750","URL":"https://doi.org/10.1080/13675567.2025.2451750","source":"openalex"},{"id":"oa:W7123362569","type":"article-journal","title":"Digital Twins in Sustainability Initiatives: A Review From Life Cycle Assessment Perspective","abstract":"The use of Digital Twins (DTs) to aid decision-making has grown significantly in recent years, especially with the rise of Industry 4.0. Among the various goals and applications, DTs are particularly noteworthy in sustainability initiatives and Life Cycle Assessment (LCA). In LCA, DTs can replicate physical systems using real-time data, supporting various stages of the analysis. Despite its potential, there is a noted lack of theoretical foundation in this area. Therefore, this article aims to provide a systematic literature review on the use of DTs for decision-making in LCA studies. The review includes 57 studies published in scientific journals and conference proceedings available in the main scientific databases. Unlike prior reviews that have examined DTs in sustainability more broadly, this work consolidated evidence and provided a comprehensive mapping based on key research questions. We highlight that the literature on this topic is recent and growing, with applications concentrated mainly in construction and manufacturing, but also extending to supply chains, energy, mining, and consumer products. Most studies apply DTs in the Life Cycle Inventory phase to support real-time data collection via Industry 4.0 technologies, while more advanced works extend their use to impact assessment, interpretation, and scenario optimization. Overall, DTs show strong potential to enable dynamic, data-driven, and decision-oriented LCA, although challenges related to data quality, interoperability, scalability, and standardization still limit their widespread adoption.","author":[{"family":"Santos","given":"Carlos"},{"family":"Wooley","given":"Ana"},{"family":"Romano","given":"André"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/access.2026.3652173","URL":"https://doi.org/10.1109/access.2026.3652173","source":"openalex"},{"id":"oa:W4410287237","type":"article-journal","title":"Digital transformation in the real estate industry: A systematic literature review of current technologies, benefits, and challenges","abstract":"The digital transformation of the real estate sector constitutes a pivotal and dynamic field of inquiry as emergent technologies incessantly alter conventional methodologies. This systematic literature review evaluates the integration, utilization, and ramifications of significant digital transformation technologies within the real estate sector, with a particular focus on artificial intelligence (AI), the Internet of Things (IoT), blockchain technology, augmented reality (AR), virtual reality (VR), and digital twins. Employing the PRISMA methodology, an exhaustive search across four principal academic databases yielded 36 studies that provide a solid foundation for comprehensive analysis. This review elucidates how these technologies fundamentally restructure real estate operations, encompassing property management, investment evaluation, consumer interaction, and operational frameworks. The findings demonstrate that digital transformation yields substantial advantages for stakeholders, including property managers, investors, purchasers, and tenants. Principal benefits comprise enhanced operational efficiency, improved data-driven decision-making, and augmented user engagement. Nevertheless, the review underscores significant obstacles, such as elevated implementation costs, apprehensions regarding data security, resistance to technological advancement, and integration challenges that may obstruct seamless assimilation. By furnishing precise analyses regarding these advantages and obstacles, this review presents pragmatic methodologies for industry practitioners to maneuver through digital transformation effectively. It advocates for implementing modular technology to optimize financial expenditures and emphasizes the necessity of resilient cybersecurity protocols to mitigate data-related apprehensions. Subsequent investigations ought to concentrate on the enduring implications of these technologies on market dynamics and the fulfillment of stakeholders.","author":[{"family":"Al-Haimi","given":"Basheer"},{"family":"Khalid","given":"Haliyana"},{"family":"Zakaria","given":"Nor"},{"family":"Jasimin","given":"Tuti"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jjimei.2025.100340","URL":"https://doi.org/10.1016/j.jjimei.2025.100340","source":"openalex"},{"id":"oa:W7163700245","type":"article-journal","title":"Impact of Data Collection on Digital Shadow Modeling in Manufacturing: A Digital Twin Approach","abstract":"ABSTRACT In the era of Industry 4.0, digital twin (DT) has gained substantial attention across industries for its capability to create dynamic digital representations of physical systems. A DT facilitates continuous data exchange between a physical asset and its virtual counterpart, enabling real-time monitoring and predictive analysis. A critical precursor to developing a full DT is digital shadow (DS), which digitally mirrors the behavior of a physical system using simulation tools. The effectiveness of a DS largely depends on the accuracy and fidelity of the input data. This paper proposes a step-by-step methodology for developing a DS using Discrete event simulation (DES) in FlexSim. The approach begins with a product architecture analysis to identify key process variables, enabling effective product family classification. This is followed by the selection of suitable DES software, with a focus on accommodating high product variability typical in complex manufacturing systems. A dual-mode data acquisition strategy, combining manual time studies with sensor-generated data, is then applied to capture both observable and high-resolution operational data. A comparative case study is conducted using two DS models, one based on manually collected data and the other on high-fidelity sensor data, within a high-mix, high-volume manufacturing setting. Results demonstrate that DS models built with high-fidelity data significantly enhance simulation precision. The second model successfully identified a production line imbalance and provided actionable insights through a micro study of manual activities that were executed in the assembly process. Furthermore, the proposed future state, modeled through the DS, showed a potential 20 % increase in production output, contributing to operational efficiency. This study aims to underscore the value of DS as a reliable and scalable tool for analyzing complex systems, supporting informed decision-making, and serving as a critical step toward the implementation of a complete DT.","author":[{"family":"Rivera","given":"Braian"},{"family":"Zehra","given":"Faiza"},{"family":"Zaman","given":"Uzair"},{"family":"Butt","given":"Sajid"},{"family":"Qureshi","given":"Ahmed"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1520/ssms20240039","URL":"https://doi.org/10.1520/ssms20240039","source":"openalex"},{"id":"oa:W4406851005","type":"article-journal","title":"Digital twins: Transforming the chemical process industry—A review","abstract":"Abstract Digital twin (DT) technology represents a significant advancement in the digital transformation of the chemical process industry (CPI), offering innovative capabilities for real‐time monitoring, predictive maintenance, and process optimization. This review investigates the current deployment status, frameworks, architectures, and applications of DTs within CPI, highlighting their transformative potential in improving operational efficiency, enhancing safety, and promoting sustainability. By examining case studies from industry leaders and analyzing recent advancements, this study elucidates the critical roles of DTs in asset health monitoring, process optimization, and environmental performance. The review identifies key components of DT frameworks, including data integration, hybrid modelling, and real‐time analytics, which are essential for effective implementation. It further explores challenges such as high computational requirements, integration with legacy systems, cybersecurity risks, and the lack of standardization, which impede widespread adoption. Despite these challenges, the paper emphasizes opportunities for leveraging advanced technologies such as artificial intelligence, edge computing, and 5G connectivity to enhance DT capabilities and scalability. In addition, this review underscores the importance of DTs in addressing global sustainability goals, mainly through their ability to optimize energy consumption, reduce emissions, and facilitate circular economy practices. By synthesizing insights from academia and industry, this study provides a comprehensive understanding of DTs' current state and future potential in CPI, offering strategic directions for research and development. The findings contribute to advancing the deployment of DTs as a cornerstone technology in achieving operational excellence, safety, and sustainability in the chemical process industry.","author":[{"family":"Pal","given":"Pratyush"},{"family":"Hens","given":"Abhiram"},{"family":"Behera","given":"Narottam"},{"family":"Lahiri","given":"Sandip"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/cjce.25611","URL":"https://doi.org/10.1002/cjce.25611","source":"openalex"},{"id":"oa:W4406035242","type":"article-journal","title":"A Blockchain-Assisted Federated Learning Framework for Secure and Self-Optimizing Digital Twins in Industrial IoT","abstract":"Optimizing digital twins in the Industrial Internet of Things (IIoT) requires secure and adaptable AI models. The IIoT enables digital twins, virtual replicas of physical assets, to improve real-time decision-making, but challenges remain in trust, data security, and model accuracy. This paper presents a novel framework combining blockchain technology and federated learning (FL) to address these issues. By deploying AI models on edge devices and using FL, data privacy is maintained while enabling collaboration across industrial assets. Blockchain ensures secure data management and transparency, while explainable AI (XAI) enhances interpretability. The framework improves transparency, control, security, privacy, and scalability for self-optimizing digital twins in IIoT. A real-world evaluation demonstrates the framework’s effectiveness in enhancing security, explainability, and optimization, offering improved efficiency and reliability for industrial operations.","author":[{"family":"Ababio","given":"Innocent"},{"family":"Bieniek","given":"Jan"},{"family":"Rahouti","given":"Mohamed"},{"family":"Hayajneh","given":"Thaier"},{"family":"Aledhari","given":"Mohammed"},{"family":"Verma","given":"Dinesh"},{"family":"Chehri","given":"Abdellah"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/fi17010013","URL":"https://doi.org/10.3390/fi17010013","source":"openalex"},{"id":"oa:W4411768731","type":"article-journal","title":"A Systematic Literature Review on Digital Twins in Circular Supply Chain Management","abstract":"ABSTRACT This study presents a systematic literature review exploring the role of Digital Twins (DTs) in Circular Supply Chain Management (CSCM). Employing a structured methodology based on the PRISMA protocol and analyzed through the Theory, Context, Characteristics, and Method (TCCM) framework, the review synthesizes 109 peer‐reviewed articles published between 2000 and 2024. Using bibliographic coupling, the research identifies six thematic clusters: (1) Integration of DT in Supply Chain; (2) DT and Industry 4.0; (3) Big Data, AI, and Circular Economy; (4) Risk Management and Supply Chain Resilience; (5) Additive Manufacturing and Spare Parts Logistics; and (6) Metaverse and Smart Factory Operations. Additionally, the study categorizes 86 unique theories applied in the DT‐CSCM literature, with Resource‐Based Theory, Complexity Theory, and Control Theory among the most cited. Key contributions include clarifying the intellectual structure of DT‐CSCM research, highlighting emerging research directions, and offering practical recommendations for industry practitioners and policymakers seeking to enhance supply chain sustainability and digital transformation. These deeply meaningful findings considerably improve our comprehension of the rapid pace of technological improvement in DT and its significant implications for the development of resilient, sustainable supply chains.","author":[{"family":"Polimetla","given":"Jeremiah"},{"family":"Sindhwani","given":"Rahul"},{"family":"Bag","given":"Surajit"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/bse.70038","URL":"https://doi.org/10.1002/bse.70038","source":"openalex"},{"id":"oa:W4415741374","type":"article-journal","title":"Operational resilience of additively manufactured parts to stealthy cyberphysical attacks using geometric and process digital twins","abstract":"Cyberphysical attacks on the digital backbone of Additive Manufacturing (AM) can compromise the printed part’s functionality. They can alter features in the digital geometry to introduce geometric defects (e.g., missing fillets) or alter process parameters to create local defects (e.g., voids). Addressing the downtime, waste, and quality deterioration associated with existing solutions requires operational resilience, i.e., rapid elimination or disruption of defect formation (to retain part function) without production stoppage or part disposal (to retain yield). This need is unmet due to the inherently unpredictable nature of attack-induced alterations, lack of access to the original geometric model for identification of altered geometric features, and in-process imposition of unknown process dynamics via attack-driven alteration of real-time-uncontrolled (or exogenous) parameters. This work establishes the above-mentioned operational resilience for the first time by creating two Digital Twins (DT). The Geometric DT (Geo-DT) is based on a unique physical-field-driven soft sensor and topology optimization method. The Process Digital Twin (Pro-DT) combines local defect quantification with a novel Reinforcement Learning formulation and training method. The importance of these methodological advances and the scalability of our approach are examined on a real AM testbed. It is shown that Geo-DT can correct geometric defects without access to the original digital geometry or explicit knowledge of attack-altered geometric features. Further, Pro-DT can accelerate real-time disruption of local defects despite attack-driven imposition of unknown process dynamics. We discuss how our framework goes beyond the contemporary focus on pre-attack security and in-attack detection towards resilience for AM and beyond.","author":[{"family":"Cleeman","given":"Jeremy"},{"family":"Jackson","given":"Adrian"},{"family":"Patel","given":"Anandkumar"},{"family":"Wang","given":"Zihan"},{"family":"Feldhausen","given":"Thomas"},{"family":"Shao","given":"Chenhui"},{"family":"Xu","given":"Hongyi"},{"family":"Malhotra","given":"Rajiv"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jmsy.2025.10.009","URL":"https://doi.org/10.1016/j.jmsy.2025.10.009","source":"openalex"},{"id":"oa:W4409609440","type":"article-journal","title":"Intelligent real-time tool life prediction for a digital twin framework","abstract":"Abstract A key challenge in the machining manufacturing industry is real-time tool wear prediction, as conventional methods rely on conservative tool changes, causing premature replacement or excessive wear that risks failure, part damage, or poor surface quality. Monitoring and predicting the wear condition of a cutting tool is key to guarantee the cutting quality and saving costs. This study presents an AI-driven digital twin framework for real-time tool life prediction to address these limitations by integrating multiple modules. These modules include an on-machine direct inspection system, a seamless connectivity integration module for real-time data management, and a deep learning module for tool wear prediction. Long Short-Term Memory networks were trained, optimised and tested on a milling dataset to then deploy onto a real-time implementation of the digital twin framework. A comprehensive design of experiments (DOE) was used to validate the real-time tool life prediction framework of a dynamic milling toolpath strategy of a Ti-6Al-4 V alloy. The models were able to predict tool maximum flank wear based on sensor data from the machining tests DOE with RMSE of 33.17 µm, whilst the real-time implementation yielded a minimum of RMSE of 119.36 µm. These results motivate further research for enabling real-time closed-loop control for a future digital twin system implementation.","author":[{"family":"Dominguez-Caballero","given":"Javier"},{"family":"Ayvar-Soberanis","given":"Sabino"},{"family":"Curtis","given":"David"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s10845-025-02606-4","URL":"https://doi.org/10.1007/s10845-025-02606-4","source":"openalex"},{"id":"oa:W4409978762","type":"article-journal","title":"Towards Human Modeling for Human-Robot Collaboration and Digital Twins in Industrial Environments: Research Status, Prospects, and Challenges","abstract":"• Review the research status on human modelling in Human-Robot Collaboration and Digital Twins. • Present models for multiple aspects of humans and related modeling technologies systematically. • Present the applications of human models throughout various lifecycle stages. • Discuss human modelling prospects and challenges in Human-Robot Collaboration and Digital Twins. Human-Robot Collaboration (HRC) and Digital Twins (DT) have significantly advanced industrial development and digital transformation. Human representations and models are essential in Industry 5.0, where human-centric is one of the key features. Despite the growing interest in human models for HRC and DT, a comprehensive overview of these models and enabling technologies currently needs to be provided. This paper aims to present the research status, prospects, applications, and challenges of human modeling for HRC and DT in industrial environments. This paper adopts a Systematic Literature Review (SLR) approach. Moreover, a framework is proposed to systematize human modeling aspects, the technologies used by robots for modeling, and the applications of human models throughout various lifecycle stages. The modeled aspects are categorized into physical and behavior models, with behavior models further divided into perception, cognition, and execution models. The technology is structured hierarchically into input, process, and output layers. Applications of the models are discussed across design, manufacturing, and service phases. The research status is examined in terms of human aspects and relevant technologies, identifying current limitations. Based on this, future prospects to address these limitations are discussed. Furthermore, the challenges in advancing current research towards these prospects are identified, focusing on model fidelity, individual-specific models, sensing, and computation. This research aims to support future human modeling in HRC and DT, contributing to safety, efficiency, and human well-being in industrial environments.","author":[{"family":"Xia","given":"Guoyi"},{"family":"Ghrairi","given":"Zied"},{"family":"Wuest","given":"Thorsten"},{"family":"Hribernik","given":"Karl"},{"family":"Heuermann","given":"Aaron"},{"family":"Liu","given":"Fei‐fei"},{"family":"Liu","given":"Hui"},{"family":"Thoben","given":"Klaus‐dieter"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.rcim.2025.103043","URL":"https://doi.org/10.1016/j.rcim.2025.103043","source":"openalex"},{"id":"oa:W4412484910","type":"article-journal","title":"APPLICATION OF DIGITAL TWIN IN ENSURING CYBER-SECURITY IN MANUFACTURING PROCESSES MANAGEMENT","abstract":"Purpose: The objective of the paper is twofold: firstly, to analyze the applications of Digital Twin (DT) technology in ensuring cybersecurity in manufacturing processes; and secondly, to identify key thematic areas, research gaps, and potential practical applications. Design/methodology/approach: The research was conducted based on a systematic literature review, using bibliometric analysis and advanced data analysis tools such as VOSviewer and Latent Dirichlet Allocation (LDA). Findings: The literature analysis revealed that current studies focus on the analysis of DT use in risk management and security testing without interference in real manufacturing systems. DT facilitates the emulation of a variety of threat scenarios, the evaluation of the efficacy of implemented security measures, and the optimization of preventive strategies. However, the analysis also identified significant research gaps, including the lack of unified implementation methodologies and insufficient exploration of the impacts of DT deployment in cybersecurity at operational and strategic levels. Practical implications: The implementation of DT has the potential to enhance cybersecurity risk management in manufacturing enterprises by facilitating earlier threat detection, minimizing potential losses, and expediting incident response times. DT provides enterprises with tools for continuous monitoring of manufacturing processes, enabling proactive threat management and increasing system resilience. Originality/value: The study proposes an interdisciplinary approach, with a view to identifying a research niche related to the integration of DT with other information technologies. Furthermore, it outlines directions for developing methodologies and standards for DT implementation in manufacturing processes, with a view to ensuring their cybersecurity.","author":[{"family":"Smagowicz","given":"Justyna"},{"family":"Szwed","given":"Cezary"},{"family":"Wiśniewski","given":"Michał"}],"issued":{"date-parts":[[2025]]},"DOI":"10.29119/1641-3466.2025.224.25","URL":"https://doi.org/10.29119/1641-3466.2025.224.25","source":"openalex"},{"id":"oa:W4406427602","type":"article-journal","title":"Critical factors affecting digital transformation in manufacturing companies","abstract":"Abstract Digital transformation represents a compelling opportunity for manufacturing companies to enhance their competitiveness. This transformative journey offers myriad possibilities, including improved connectivity between workers and machines, as well as seamless machine-to-machine interactions. However, many manufacturing companies encounter challenges when attempting to implement digital transformation effectively. The process of digital transformation is often slow, and most companies find themselves in the early stages of adoption, grappling with the ambiguity surrounding the associated technologies. A systematic approach for the implementation of digital transformation is still elusive for many manufacturing companies. The number of studies exploring digital transformation is increasingly growing, encompassing various sectors and domains. However, within the manufacturing sector, there remains a need for further research and clarity on systematic implementation approaches. To address these issues, this research undertakes a comprehensive analysis to identify the critical factors that influence digital transformation in the manufacturing sector. The objective of this research is to identify the factors that drive the success of digital transformation in manufacturing companies while also uncovering factors that, when neglected, could lead to failure. Through a systematic literature review, this research identifies 11 critical factors. These factors serve as the basis for developing the ARTO model, a structured framework comprising four distinct categories: \"Awareness-related factors,\" \"Readiness-related factors,\" \"Technology Selection-related factors,\" and \"Operations-related factors.\" Moreover, this research incorporates expert perspectives gathered through a survey to refine the ARTO model. This study offers the ARTO model and digital transformation definition as practical tools for successfully implementing digital transformation in manufacturing companies, while also delineating the intricate relationships among the crucial factors. By shedding light on the factors underpinning digital transformation in the manufacturing sector, this research contributes to the ongoing discourse and facilitates more effective adoption of digital transformation strategies.","author":[{"family":"Chirumalla","given":"Koteshwar"},{"family":"Oghazi","given":"Pejvak"},{"family":"Nnewuku","given":"Rosa"},{"family":"Tuncay","given":"Hatice"},{"family":"Yahyapour","given":"Nima"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s11365-024-01056-3","URL":"https://doi.org/10.1007/s11365-024-01056-3","source":"openalex"},{"id":"oa:W4413472111","type":"article-journal","title":"Technologies, Applications, and Challenges of Digital Twin Across Industries: A Systematic Review of the State-of-the-Art Literature","abstract":"Digital twins can be defined as a virtual representation of a physical object that can replicate its behavior in a virtual environment. This concept involves the integration of three distinct components: the physical space, the virtual space, and the communication between these two spaces. Digital twins are recognized as one of the key driving forces in various industries, and a comprehensive understanding is necessary to utilize them. A thorough review of the advantages and disadvantages of digital twins, including their value, characteristics, applications, and challenges, is essential to analyze their growth potential and investment value. This paper comprehensively reviews the digital twin applications being studied across industries. To this end, we propose three research questions and address them through a structured literature review. First, we examine the core technologies of digital twins and find that they form an integrated framework combining modeling, sensing, and real-time data processing. Second, we analyze their adoption across industries and observe widespread use in aerospace and aeronautics, manufacturing, healthcare, energy, and urban systems with domain-specific objectives. Third, we explore life-cycle applications and identify digital twins as enablers of continuity from design to operation and evolution. These findings offer a broad perspective on the current state and future potential of digital twin applications.","author":[{"family":"Bae","given":"Chang"},{"family":"Choi","given":"Eu"},{"family":"Lee","given":"Seongjin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/access.2025.3601615","URL":"https://doi.org/10.1109/access.2025.3601615","source":"openalex"},{"id":"oa:W4412954268","type":"article-journal","title":"A System Dynamics-Based Hybrid Digital Twin Model for Driving Green Manufacturing","abstract":"Green manufacturing has emerged as a critical objective in the evolution of advanced production systems. Although digital twin technology is widely recognized for enhancing efficiency and promoting sustainability, the majority of existing research focuses exclusively on physical systems. They neglect the impact of soft systems, including human behavior, decision-making, and operational strategies. To address this limitation, the present study introduces an innovative hybrid digital twin model that integrates both physical and soft systems to support green manufacturing initiatives comprehensively. The primary contributions of this work are threefold. First, a novel hybrid architecture is developed by coupling real-time physical data with virtual soft system components that simulate factory operations. Second, lean production principles are systematically incorporated into the soft system, thereby facilitating reduced energy consumption and minimizing environmental impact. Third, a parameter-driven programming model is formulated to correlate critical variables with green performance metrics, and a genetic algorithm is utilized to optimize these variables, ultimately enhancing sustainability outcomes. This integrated approach not only expands the applicability of digital twin technology but also offers a data-driven decision-support tool for the advancement of green manufacturing practices.","author":[{"family":"Fan","given":"Sucheng"},{"family":"Tong","given":"Huagang"},{"family":"Wang","given":"Song"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/systems13080651","URL":"https://doi.org/10.3390/systems13080651","source":"openalex"},{"id":"oa:W4411342862","type":"article-journal","title":"Identifying and Prioritizing Essential Data Attributes for Discrete Event Simulation-Based Digital Twins: Implications for Manufacturing Optimization","abstract":"The rise of Digital Twin (DT) and Discrete Event Simulation (DES) technologies in manufacturing underscores the critical importance of accurate data. Without key data attributes, DT models become unreliable for system optimization and decision-making support. Through a case study, this research contributes to the knowledge domain by identifying essential data attributes for effective DES-based DT implementation and categorizing them according to their availability and relevance to various optimization objectives. To achieve this, a mixed method approach was employed, combining a literature review, semi-structured interviews, and consultations with industrial practitioners, including simulation specialists, manufacturing execution system experts, and shop floor managers. The study’s findings reveal significant data gaps when using DES-based DT in the manufacturing sector and, through Quality Function Deployment (QFD) analysis, provide industry practitioners with actionable insights for prioritizing data collection efforts. Ultimately, this research facilitates data-driven decision-making in large-scale manufacturing environments by offering a structured framework for identifying key data attributes necessary to enhance DES-based DT.","author":[{"family":"Inginshetty","given":"Anirudh"},{"family":"Bellure","given":"Swadesh"},{"family":"Ocaña","given":"Adrian"},{"family":"Fathi","given":"Masood"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.procir.2025.02.162","URL":"https://doi.org/10.1016/j.procir.2025.02.162","source":"openalex"},{"id":"oa:W4414433671","type":"article-journal","title":"Requirement-Driven Sharing of Manufacturing Digital Twins Along the Value Chain","abstract":"Digital Twins (DTs) are key enablers of Smart Manufacturing, yet their adoption across the value chain is hindered by the lack of a standardized sharing framework. This paper addresses this challenge by identifying essential descriptive and qualitative elements of DTs based on standards and literature. Leveraging the Asset Administration Shell (AAS), it proposes a Submodel Template, which standardizes the packaging of DT models, interfaces, and computational and network requirements thus going beyond, and combining, existing AAS Submodels, i.e. for simulation models, to encapsulate the full multidimensionality of DTs. A case study on a Quality Monitoring DT (QM-DT) demonstrates the template’s ability to support seamless DT deployment, aggregation, and operation across heterogeneous manufacturing environments. Results show that the template enables structured transfer of subject matter expertise captured in DT models, real-time constraint support, and interoperability, laying the groundwork for improved DT integration and exchange.","author":[{"family":"Gnadlinger","given":"Michael"},{"family":"Tilbury","given":"Dawn"},{"family":"Barton","given":"Kira"},{"family":"Wilch","given":"Jan"},{"family":"Vogelheuser","given":"Birgit"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/case58245.2025.11164130","URL":"https://doi.org/10.1109/case58245.2025.11164130","source":"openalex"},{"id":"oa:W4408305379","type":"article-journal","title":"Development and Validation of Digital Twin Behavioural Model for Virtual Commissioning of Cyber-Physical System","abstract":"Modern manufacturing systems are influenced by the growing complexity of mechatronics, control systems, IIoT, and communication technologies integrated into cyber-physical systems. These systems demand flexibility, modularity, and rapid project execution, making digital tools critical for their design. Virtual commissioning, based on digital twins, enables the testing and validation of control systems and designs in virtual environments, reducing risks and accelerating time-to-market. This research explores the development of digital twin models to bridge the gap between simulation and real-world validation. The models identify design flaws, validate the PLC control code, and ensure interoperability across software platforms. A case study involving a modular Festo manufacturing system modelled in Tecnomatix Process Simulate demonstrates the ability of digital twins to detect inefficiencies, such as collision risks, and to validate automation systems virtually. This study highlights the advantages of virtual commissioning for optimizing manufacturing systems. Communication testing showed compatibility across platforms but revealed limitations with certain data types due to software constraints. This research provides practical insights into creating robust digital twin models, improving the flexibility, efficiency, and quality of manufacturing system design. It also offers recommendations to address current challenges in interoperability and system performance.","author":[{"family":"Ružarovský","given":"Roman"},{"family":"Horák","given":"Tibor"},{"family":"Zelník","given":"Roman"},{"family":"Skýpala","given":"Richard"},{"family":"Csekei","given":"Martin"},{"family":"Šido","given":"Ján"},{"family":"Nemlaha","given":"Eduard"},{"family":"Kopček","given":"Michal"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app15052859","URL":"https://doi.org/10.3390/app15052859","source":"openalex"},{"id":"oa:W4408960508","type":"article-journal","title":"A Review on Integrating IoT, IIoT, and Industry 4.0: A Pathway to Smart Manufacturing and Digital Transformation","abstract":"The industrial Internet of Things (IIoT) has become an innovative technology that has brought many benefits to industries and organizations. This review presents a comprehensive analysis of IIoT’s applications, highlighting its ability to optimize industrial operations through advanced connectivity, real‐time data exchange, automation, and its importance in the context of Industry 4.0. Emphasizing the distinction between IIoT and traditional IoT, the paper explores how IIoT focuses on enhancing industrial ecosystems and integrating cyber‐physical systems (CPSs). This article explains how to establish a highly linked infrastructure to support cutting‐edge services and ensure greater flexibility and efficiency. It emphasizes the role of the CPS and industrial automation and control systems (IACSs) in realizing the potential of IIoT. Security concerns, an important part of IIoT, are addressed through conversations on protecting networked systems, assuring operational reliability, and emphasizing the need for strong security measures to prevent potential threats and vulnerabilities. Furthermore, critical technologies such as machine learning (ML), artificial intelligence (AI), and various communication protocols, including fifth generation (5G) and message queuing telemetry transport (MQTT), are investigated for their potential to improve system performance and decision‐making processes. In addition, the article also discusses the safety precautions and challenges of using IIoT. Finally, the article emphasizes the importance of addressing security issues in promoting the successful adoption of the IIoT and achieving its expected benefits. This study offers valuable resources for researchers, academics, and decision‐makers to implement IIoT in industrial environments.","author":[{"family":"Qiu","given":"Fujun"},{"family":"Kumar","given":"Ashwini"},{"family":"Jiang","given":"Hu"},{"family":"Sharma","given":"Poorva"},{"family":"Tang","given":"Yanping"},{"family":"Xiang","given":"Y"},{"family":"Hong","given":"Jie"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/ise2/9275962","URL":"https://doi.org/10.1049/ise2/9275962","source":"openalex"},{"id":"oa:W4412417953","type":"article-journal","title":"Digital Twin Technology for Renewable Energy, Smart Grids, Energy Storage and Vehicle‐to‐Grid Integration: Advancements, Applications, Key Players, Challenges and Future Perspectives in Modernising Sustainable Grids","abstract":"ABSTRACT To address the challenges faced by modern power systems—such as efficiency, dynamics, reliability, control, stability, economy and planning—significant efforts have been made to develop advanced techniques, tools and scientific innovations across various disciplines. Among these, the ‘digital twin’ (DT) has emerged as one of the most reliable and rapidly evolving technologies, now widely integrated into diverse applications. The incorporation of DT technology into energy systems marks a paradigm shift in achieving sustainable, efficient and resilient modern power grids. Although considerable research has been conducted on DT applications in the power sector, comprehensive reviews of its role in transforming power grids to accommodate high levels of renewable energy sources (RESs), smart grid technologies, vehicle‐to‐grid (V2G) systems and energy storage solutions remain limited. This paper seeks to bridge that gap by exploring the critical role of DT technology in this transformation. It examines the historical evolution, fundamental components and diverse applications of DT technology across modern grid systems. Detailed analyses focus on DT's application in modernising power grids, particularly in RES integration, energy storage, transmission and distribution, smart grid advancements and V2G systems. Additionally, the paper reviews progress, investments, standards, regulations and the key stakeholders driving DT advancements in power grids. Finally, major challenges, limitations and future perspectives for DT applications in next‐generation power grids are discussed. Key findings reveal that while DT technology delivers significant benefits—such as improved operational efficiency, enhanced grid stability, greater reliability, cost reduction, cybersecurity and resilience through real‐time monitoring, predictive maintenance and optimised energy management—addressing existing limitations is crucial to maximising DT's potential in advancing and modernising sustainable power grids.","author":[{"family":"Alshetwi","given":"Ali"},{"family":"Atawi","given":"Ibrahem"},{"family":"Elhameed","given":"Mohamed"},{"family":"Abuelrub","given":"Ahmad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/stg2.70026","URL":"https://doi.org/10.1049/stg2.70026","source":"openalex"},{"id":"doi:10.1201/9781003686736","type":"article-journal","title":"Digital Twin for Gear Wear Monitoring and Prediction","abstract":"This book presents recent research developments and integrated methodologies for digital twin gear wear monitoring and remaining useful life prediction for rotating machinery. It describes a comprehensive framework for identifying wear mechanisms, developing dynamic gearbox models, and implementing online monitoring schemes that track the evolution of abrasive wear and fatigue pitting. The methodologies introduced allow for accurate assessment of tooth profile changes and surface integrity without requiring operational stoppage. Simulations and dynamic model implementations in this book are constructed using the MATLAB® and Simulink® software packages. Features:• Gives a systematic investigation of vibration-based techniques to distinguish between fatigue pitting and abrasive wear.• Develops an integrated monitoring and prediction framework using a dynamic gear model and wear model.• Includes a novel digital-twin approach that regularly updates model coefficients using measured vibration data to ensure prediction accuracy.• Discusses the impact of macro- and micro-level wear on dynamic contact forces and vibration characteristics.• Provides experimental validation through run-to-failure tests conducted under both dry and lubricated conditions. This book is aimed at researchers and graduate students in mechanical engineering, signal processing, machine condition monitoring, and reliability engineering.","author":[{"family":"Feng","given":"Ke"},{"family":"Ni","given":"Qing"},{"family":"Zhou","given":"Hanbin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1201/9781003686736","URL":"https://doi.org/10.1201/9781003686736","source":"openalex"},{"id":"doi:10.29284/5j105z61","type":"article-journal","title":"Towards Human-Centric Smart Manufacturing: A Digital Twin Enabled Affective Ergonomic Framework For Adaptive Human Robot Collaboration","abstract":"The advent of Industry 4.0 has ushered in an era of Smart Manufacturing, where Human-Robot Collaboration (HRC) is pivotal for enhancing productivity and flexibility. However, existing HRC paradigms often overlook the dynamic internal states of human operators, focusing primarily on task efficiency and physical safety. This oversight can lead to suboptimal performance, increased stress, ergonomic risks, and reduced job satisfaction. This paper proposes a novel Digital Twin (DT) enabled Affective-Ergonomic Framework designed to foster truly human-centric adaptive HRC. Our framework integrates real-time multi-modal sensing to continuously monitor human operators' affective (e.g., stress, fatigue) and ergonomic (e.g., posture, physical load) states. These data feed into a sophisticated Human Digital Twin (HDT), which leverages machine learning models to infer and predict human states. An adaptive decision-making engine then utilizes this HDT data, alongside Robot and Environment Digital Twins, to dynamically adjust robot behavior (e.g., speed, task allocation, assistance level) in real-time. We present the architectural design, illustrative mathematical models for state inference, and a conceptual case study demonstrating the framework's potential to significantly improve human well-being, mitigate ergonomic risks, enhance safety, and ultimately boost overall system performance in smart manufacturing environments. This approach paves the way for intelligent HRC systems that proactively respond to human needs,","author":[{"family":"Khan","given":"Waleed"},{"family":"Rasheed","given":"Muhammad"},{"family":"Akram","given":"Muhammad"},{"family":"Imran","given":"Muhammad"},{"family":"Ahmed","given":"Rana"},{"family":"Rauf","given":"Abdul"}],"issued":{"date-parts":[[2025]]},"DOI":"10.29284/5j105z61","URL":"https://doi.org/10.29284/5j105z61","source":"openalex"},{"id":"oa:W7202090690","type":"article-journal","title":"Digital twins in poultry farming management: A review","abstract":"Digital twins, defined as dynamic virtual representations of physical systems, offer potential to facilitate real-time monitoring, improve predictive capabilities, and support data-driven decision-making. The application of digital twins in poultry farming management has attracted increasing attention, however, it remains insufficiently explored, particularly in terms of framework development and layer-wise functionalities. This review presents a comprehensive study of digital twin development and components in poultry farming management, addressing the current lack of structured frameworks and systematic analysis in this domain. In this context, poultry farming management is defined as the strategic planning and implementation of a series of farm operations, including monitoring, detection, and prediction, to enhance production efficiency and achieve economic sustainability. Based on the existing literature, a three-layer digital twin framework is proposed, consisting of a data collection layer, a model layer, and an application layer. Within this framework, farm data are first captured and gathered in the data collection layer, then processed and simulated in the model layer, and finally utilized to support decision-making in the application layer. Through a detailed layer-wise analysis, the study highlights the critical role of model calibration and synchronization in ensuring consistency between physical and virtual systems. While offering promising potential, the adoption of digital twin technology in poultry farming faces several challenges, including challenges in real-world deployment, limited system integration, issues related to data quality and ownership, and insufficient solutions to ensure animal health and welfare. Finally, the study summarizes future research directions for digital twin applications in livestock production systems.","author":[{"family":"Li","given":"Jingxi"},{"family":"Sulaiman","given":"Aisha"},{"family":"Liu","given":"Qingzhi"},{"family":"Gavai","given":"Anand"},{"family":"Bouzembrak","given":"Yamine"},{"family":"Tekinerdogan","given":"Bedir"},{"family":"Catal","given":"Cagatay"},{"family":"Marvin","given":"HJP"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.compag.2026.112248","URL":"https://doi.org/10.1016/j.compag.2026.112248","source":"openalex"},{"id":"oa:W7166850560","type":"article-journal","title":"Digital twin in the structure of the modern educational environment","abstract":"In today's world, the advantage of digital twins is the ability to create copies of various physical objects, systems or learning environments, etc. This is especially true in engineering disciplines, where models of digital twins of a given accuracy provide research and experimentation without physical risks and significant financial costs. In the context of the educational environment, this means ensuring the effective functioning of virtual educational laboratories equipped with real equipment. The article develops an educational environment using a digital twin of a SMART laboratory, which functions as a cyber-physical system with end-to-end integration of a sensor network, actuators and a virtual model of the room. The purpose of the work is to theoretically substantiate and experimentally verify the educational environment, that includes a digital twin, focused on improving energy efficiency, comfort and safety of educational spaces. The methodological basis of the study includes system analysis, mathematical modelling of microclimate dynamics, as well as imperative control logic using typical regulators. Within the framework of the proposed architecture, a microclimate model has been developed that combines the subsystems of monitoring, forecasting and adaptive control. Actualization of the real and virtual state is carried out in real time, which provides the possibility of preliminary testing of control actions and assessment of their impact without risk to the material base. A series of simulations and experiments confirmed the ability of the developed system to reduce resource consumption and stabilize microclimate parameters under the influence of external disturbances. At the same time, the system maintains pedagogical flexibility, supporting various formats of organizing the educational process. The obtained results testify to the scientific novelty of the proposed approach, which consists in combining models and control systems with educational scenarios in a single software environment. The practical significance of the work is determined by the possibility of scaling the developed solution to other types of laboratories and academic disciplines, as well as the promoting the formation of digital competencies of future specialists in the field of information technology and cyber-physical systems.","author":[{"family":"Савченко","given":"Тетяна"},{"family":"Lutska","given":"Nataliia"},{"family":"Vlasenko","given":"Lidiia"},{"family":"Parkhomenko","given":"Ivan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.17721/1812-5409.2026/1.32","URL":"https://doi.org/10.17721/1812-5409.2026/1.32","source":"openalex"},{"id":"oa:W7162287315","type":"article-journal","title":"Digital Twin in Smart Manufacturing: A Systematic Literature Review on Predictive Decision-Making, Industrial Sustainability, and Process Optimization","abstract":"The rapid advancement of Industry 4.0 has accelerated the adoption of Digital Twin (DT) technology in smart manufacturing systems. DT enables virtual replication of physical assets, supporting real-time monitoring, predictive analytics, simulation, and data-driven decision-making. This systematic literature review investigates the role of Digital Twin technology in predictive decision-making, process optimization, and industrial sustainability within smart manufacturing environments. The review synthesizes recent peer-reviewed studies from Scopus, Web of Science, and IEEE Xplore databases. Findings show that DT enhances operational efficiency through integration with machine learning, cyber-physical systems, and Industrial Internet of Things (IIoT), enabling improved maintenance strategies, energy efficiency, and production optimization. In addition, DT contributes to sustainability by reducing waste generation and supporting circular manufacturing practices. Despite its advantages, implementation challenges remain, including high deployment costs, interoperability issues, cybersecurity risks, and lack of data standardization. Overall, the study concludes that Digital Twin is a key enabling technology for future smart factories, particularly when integrated with artificial intelligence, edge computing, and cloud-based manufacturing systems.","author":[{"family":"Dewadi","given":"Fathan"},{"family":"Royan","given":"Ahmad"},{"family":"Nurcholis","given":"Muhammad"},{"family":"Pratama","given":"Muhammad"}],"issued":{"date-parts":[[2026]]},"DOI":"10.66865/bdb53m45","URL":"https://doi.org/10.66865/bdb53m45","source":"openalex"},{"id":"oa:W7167892364","type":"article-journal","title":"Machine Learning in Architectural Heritage Conservation: A Systematic Review and Thematic Synthesis of Applications, Challenges, and Future Directions","abstract":"Machine learning (ML) is increasingly used in architectural cultural heritage conservation, but existing evidence remains fragmented across tasks, data types, and technical workflows. This systematic review synthesizes 33 studies on machine learning applications in architectural heritage conservation and identifies major application domains, methodological patterns, evidence gaps, and future research directions. Following a PRISMA-oriented review process, the literature was searched in Web of Science, Scopus, IEEE Xplore, ScienceDirect, SpringerLink, and Google Scholar up to 31 January 2026. Eligible studies were screened according to predefined inclusion and exclusion criteria, extracted using a structured coding form, and synthesized through qualitative thematic analysis. The included studies were grouped into three major domains: semantic understanding of heritage data, multi-scale damage detection and structural health monitoring, and system-level integration through heritage building information models (HBIM), multimodal data fusion, and digital twins. The evidence indicates a transition from isolated data-driven analysis toward predictive and decision-support systems, while persistent limitations remain in model generalization, benchmark datasets, semantic-to-HBIM transformation, multimodal fusion, and real-world deployment. Machine learning has substantial potential to support preventive, interpretable, and context-aware conservation, but future research requires more transparent reporting, shared datasets, external validation, and closer integration with conservation expertise.","author":[{"family":"Li","given":"Kaiming"},{"family":"Du","given":"Baitong"},{"family":"Li","given":"Dailuo"},{"family":"Zhang","given":"Xi"},{"family":"Kim","given":"Haeyoon"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/buildings16142745","URL":"https://doi.org/10.3390/buildings16142745","source":"openalex"},{"id":"oa:W7162526769","type":"article-journal","title":"Challenges of digital twin applications for radio telescopes","abstract":"Large-aperture, high-frequency radio telescopes are prone to structural deformation under the influence of gravity, temperature, wind load and other environmental factors, which in turn affects the shape of the main reflector and pointing accuracy. Therefore, this paper systematically reviews the virtual-real fusion diagnosis mechanism and application progress of digital twins in radio telescopes. Firstly, the differences and boundaries between digital twins and traditional digital simulation and state monitoring are clarified. Then, the methods in FAST, QTT, and other projects are summarized, and the current main challenges such as multi-source heterogeneous and multi-scale fusion, robust prediction under model uncertainty and real-time constraints, as well as communication delay and system complexity in engineering implementation are summarized. Looking to the future, in order to improve environmental adaptability and high-frequency observation capabilities, combined with deep learning, a mechanism-data deeply coupled digital twin model is constructed to provide new ideas and paths for the robust operation and performance improvement of the next generation of radio telescopes.","author":[{"family":"Feng","given":"Chen"},{"family":"Liu","given":"Yuanjie"},{"family":"Cheng","given":"Anyu"},{"family":"Chen","given":"Yong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1360/sspma-2025-0491","URL":"https://doi.org/10.1360/sspma-2025-0491","source":"openalex"},{"id":"oa:W7168080651","type":"article-journal","title":"Digital Twins in Education: Conceptual Foundations, Applications and Challenges","abstract":"Abstract Although originally developed as part of an industry, digital twin (DT) technologies are now being adapted for education. Digital twins (DTs) can integrate artificial intelligence, Internet of Things technologies, learning analytics and immersive environments to model learners, learning processes and educational settings in a dynamic and data-informed manner. This paper conducts a review of academic articles between 2020 and 2026 to ascertain definitions, application areas, and areas regarding integration between humans and technology to better understand how DTs can be integrated in educational settings. Personalised learning, simulation-based training and immersive learning settings created using DT technology have shown to provide benefits to both educators and learners in terms of enhanced adaptability, engagement and improved decision-making based on the results of research studies. There are several significant barriers to widespread adoption of DT in education, including the technical complexity of implementation, high implementation costs, data privacy issues, and lack of a research-based pedagogical framework. The paper contributes by proposing a classification of educational digital twins according to the entity being modelled. Although the potential for DTs to transform education is great, further research is needed to develop standardized models to ensure DTs are successfully integrated into the teaching and learning process.","author":[{"family":"Zeicu","given":"Fabiana"},{"family":"Gligorea","given":"Ilie"},{"family":"Gorski","given":"Hortensia"}],"issued":{"date-parts":[[2026]]},"DOI":"10.2478/kbo-2026-0062","URL":"https://doi.org/10.2478/kbo-2026-0062","source":"openalex"},{"id":"oa:W7163817112","type":"article-journal","title":"Environmental Digital Twins: a review of challenges and opportunities","abstract":"Digital Twin (DT) technology has emerged as a transformative paradigm for environmental monitoring, modelling, and sustainability governance, yet its development across ecological and territorial domains remains fragmented and unevenly documented in the literature. This review provides a systematic mapping of Ecological Digital Twin (EcoDT) and Environmental Digital Twin applications published between 2020 and 2025, analysing a corpus of 121 peer-reviewed studies spanning urban environments, agriculture, marine and coastal systems, river and lake networks, forestry, ecology, glaciers, Earth system science, and building sustainability. Drawing on a structured analytical matrix , the review focuses on Technology Readiness Level (TRL), remote sensing integration, data-related challenges, and future development priorities, interrogating Dts technological maturity, sustainability framing, and data readiness in practice. Results reveal a field in active but early-stage development: the TRL distribution is concentrated between levels 2 and 6, with no study in the corpus reaching deployment-ready status, and sustainability framing remains predominantly environmental in orientation, with social and economic co-benefits systematically underrepresented across nearly all application themes. Integration, interoperability, and calibration emerge as the most pervasive and structurally recurring technical constraints. Scaling and deployment, alongside governance and institutional alignment, dominate the stated future priorities of reviewed studies. The review concludes by advocating for the adoption of F.A.I.R., C.A.R.E., and T.R.U.S.T. data governance principles as a foundational framework for advancing EcoDTs and Environmental DTs towards integrated, equitable, and policy-relevant implementation at territorial and ecosystem scales.","author":[{"family":"Artioli","given":"Letizia"},{"family":"Borga","given":"Giovanni"},{"family":"Costa","given":"Pietro"}],"issued":{"date-parts":[[2026]]},"DOI":"10.54941/ahfe1007273","URL":"https://doi.org/10.54941/ahfe1007273","source":"openalex"},{"id":"oa:W7160873913","type":"article-journal","title":"Identifying and characterising uncertainty in digital twin engineering","abstract":"Digital twin technologies are increasingly deployed in complex industrial systems where uncertainty management is critical to ensure their reliability, robustness, and resilience. However, there is currently limited literature on the management of uncertainties for digital twins, and even less a structured framework for a better understanding of the uncertainties, focusing on the identification and characterisation of uncertainties within the context of digital twin engineering. In this work, a conceptual framework is proposed, structured around three key pillars: a conceptual model, a lifecycle, and maturity levels of the digital twin. A systematic literature review, following the PRISMA methodology, is conducted to identify and map four major categories of uncertainty across these pillars. The findings show how uncertainty types correspond to the 5D conceptual model of the digital twin, at which lifecycle stages they become most critical, and how they evolve as the digital twin progresses towards higher maturity levels. The proposed framework positions uncertainty characterisation as a core engineering principle of digital twins, paving the way for future research on structuring uncertainty management across digital twin engineering practices.","author":[{"family":"Tiali","given":"Bouthayna"},{"family":"Creff","given":"Stephen"},{"family":"Kallel","given":"Achraf"},{"family":"Anwer","given":"Nabil"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/27525783.2026.2668886","URL":"https://doi.org/10.1080/27525783.2026.2668886","source":"openalex"},{"id":"oa:W7204094905","type":"article-journal","title":"Digital Twin composition through causal analysis","abstract":"Digital Twins (DTs) are often engineered as modular models, but in real deployments they operate as interconnected subsystems whose variables influence each other. Composing DTs requires recovering cross-module dependencies interpretably and reusably. Causal discovery methods like the Independent Component Analysis-based Linear Non-Gaussian Acyclic Model (ICA-LiNGAM) are attractive for this, inferring directed acyclic graphs (DAGs) from observational data under linear, non-Gaussian assumptions; however, when extending an initially known causal structure with additional candidate variables, purely noisy or irrelevant signals can severely degrade LiNGAM’s separation step, producing spurious edges and unstable graphs. This paper proposes NA-LiNGAM (Noise-Aware LiNGAM), a LiNGAM-based algorithm applied to DT composition that screens candidate variables before integrating them into the causal graph. NA-LiNGAM augments ICA-LiNGAM with a graph validation score quantifying edge robustness through three statistical checks: (i) conditional regression significance, (ii) permutation-based significance, and (iii) bootstrap stability. Using this score, NA-LiNGAM selects new variables that improve graph fidelity while discarding noise. We also introduce a fast variant reducing search complexity from exponential to linear. We validate NA-LiNGAM on synthetic benchmarks and real-world datasets, using Area Under the Curve for Precision-Recall (AUC-PR), Structural Hamming Distance (SHD), and Structural Intervention Distance (SID). Results show NA-LiNGAM substantially reduces spurious edges and preserves the true causal structure under high-noise settings, yielding more stable compositions than baseline LiNGAM and competitive performance against state-of-the-art methods.","author":[{"family":"Martín-Albo","given":"Sergio"},{"family":"Llopis","given":"Luis"},{"family":"Díáz","given":"Manuel"},{"family":"Martín","given":"Cristian"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.engappai.2026.116031","URL":"https://doi.org/10.1016/j.engappai.2026.116031","source":"openalex"},{"id":"oa:W7172225358","type":"article-journal","title":"A Digital Twin for Brake Wear Predictive Maintenance","abstract":"Brake pad wear is governed by coupled thermo-mechanical interactions in which degradation alters braking behaviour. This altered braking behaviour, in turn, affects vehicle dynamics, which, in turn, influences future wear evolution. Existing diagnostic and prognostic approaches typically neglect this dynamics–wear coupling, potentially limiting their ability to accurately predict remaining useful life under evolving operating conditions. This work proposes a digital-twin framework for brake wear prognosis that integrates state estimation, parameter adaptation, and dynamics-aware degradation modelling. The approach combines brake pad volume estimation from vehicle operational data, online identification of the brake wear coefficient through inverse modelling, and forward propagation of degradation using a wear-dependent dynamics model. The proposed digital-twin predictive maintenance framework is evaluated using simulated run-to-failure datasets for a mining load-haul-dumper and compared against data-driven and physics-based predictive maintenance models. Results show that the digital-twin approach improves the accuracy and stability of remaining useful life prediction, particularly under anomalous degradation conditions, and achieves earlier convergence to practically useful predictions. These findings demonstrate that accurate brake wear prognosis requires integrating degradation modelling with vehicle dynamics and online parameter updating. The proposed digital twin provides a practical pathway towards more reliable predictive maintenance in systems where degradation and system behaviour are strongly coupled.","author":[{"family":"Eyk","given":"Luke"},{"family":"Moes","given":"Johannes"},{"family":"Ellis","given":"BR"},{"family":"Schmidt","given":"Stephan"},{"family":"Heyns","given":"PS"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/mca31040146","URL":"https://doi.org/10.3390/mca31040146","source":"openalex"},{"id":"oa:W7167692015","type":"article-journal","title":"Supporting Cryptographic Migration with an IT Infrastructure Digital Twin","abstract":"Modern IT infrastructures are composed of heterogeneous services with complex dependencies and security configurations. During migration or modernization efforts, incomplete or outdated knowledge about communication relationships, protocol usage, and cryptographic dependencies represents a major source of risk. This paper presents an approach for the automated construction of a graph-based digital twin of an IT infrastructure, developed using Design Science Research (DSR). It collects data in transit using a dedicated, extensible processing pipeline that extracts, parses, and transforms network-, protocol-, and cryptography-level information into a unified graph representation. The resulting digital twin is implemented using a graph database, enabling interactive exploration through graph queries and visualizations. The graph-based model explicitly represents communication relationships, protocols, and associated cryptographic properties, allowing heterogeneous infrastructure information to be integrated into a coherent schema. Based on this representation, the digital twin is the first solution that supports the cataloging and analysis of cryptographic mechanisms including dependencies, providing a structured foundation for post-quantum cryptography (PQC) migration planning and improved cryptographic agility in complex IT environments.","author":[{"family":"Herzinger","given":"Daniel"},{"family":"Näther","given":"Christian"},{"family":"Gazdag","given":"Stefan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/978-3-032-28946-9_3","URL":"https://doi.org/10.1007/978-3-032-28946-9_3","source":"openalex"},{"id":"oa:W7162289409","type":"article-journal","title":"Autonomous Smart Manufacturing Systems in the Era of Industry 5.0: A Systematic Review of AI-Driven Decision Intelligence and Industrial Optimization","abstract":"The emergence of Industry 5.0 has accelerated the transformation of manufacturing industries toward autonomous, intelligent, and human-centric production systems. Smart manufacturing technologies increasingly integrate Artificial Intelligence (AI), Internet of Things (IoT), Digital Twin, and Cyber-Physical Systems (CPS) to support predictive decision-making and industrial optimization. This study aims to analyze the development of autonomous smart manufacturing systems through a systematic literature review approach. The review process followed the PRISMA methodology using publications indexed in Scopus, Web of Science, and Google Scholar from 2016–2026. The results indicate that AI-driven manufacturing systems significantly improve predictive maintenance, operational efficiency, production flexibility, and industrial sustainability. However, challenges related to cybersecurity, infrastructure readiness, implementation costs, and ethical AI governance remain significant barriers. This study concludes that autonomous smart manufacturing systems possess strong potential to support intelligent and sustainable industrial transformation in the Industry 5.0 era.","author":[{"family":"Suhara","given":"Ade"},{"family":"Setiawan","given":"Dibyo"},{"family":"Dewadi","given":"Fathan"},{"family":"Putra","given":"Fisika"},{"family":"Musyaffa","given":"Gunawan"},{"family":"Nabawiyah","given":"Surotun"}],"issued":{"date-parts":[[2026]]},"DOI":"10.66865/xv9yr868","URL":"https://doi.org/10.66865/xv9yr868","source":"openalex"},{"id":"oa:W4416383404","type":"article-journal","title":"A Multi-Simulation Bridge for IoT Digital Twins","abstract":"The increasing capabilities of Digital Twins (DTs) in the context of the Internet of Things (IoT) and Industrial IoT (IIoT) call for seamless integration with simulation platforms to support system design, validation, and real-time operation. This paper introduces the concept, design, and experimental evaluation of the DT Simulation Bridge - a software framework that enables diverse interaction patterns between active DTs and simulation environments. The framework supports both the DT development lifecycle and the incorporation of simulations during active operation. Through bidirectional data exchange, simulations can update DT models dynamically, while DTs provide real-time feedback to adapt simulation parameters. We describe the architectural design and core software components that ensure flexible interoperability and scalable deployment. Experimental results show that the DT Simulation Bridge enhances design agility, facilitates virtual commissioning, and supports live behavioral analysis under realistic conditions, demonstrating its effectiveness across a range of industrial scenarios.","author":[{"family":"Picone","given":"Marco"},{"family":"Burattini","given":"Samuele"},{"family":"Melloni","given":"Marco"},{"family":"Talasila","given":"Prasad"},{"family":"Ziglioli","given":"Davide"},{"family":"Martinelli","given":"Matteo"},{"family":"Bicocchi","given":"Nicola"},{"family":"Larsen","given":"Peter"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/percomworkshops68308.2026.11585411","URL":"https://doi.org/10.1109/percomworkshops68308.2026.11585411","source":"openalex"},{"id":"oa:W7133677635","type":"article-journal","title":"Integration of Digital Twin Technology and Industry 4.0 Principles for Real-Time Structural Health Monitoring in Smart Manufacturing Facilities","abstract":"Within Industry 4.0 manufacturing environments, Structural Health Monitoring (SHM) is recognized as mission-critical; nevertheless, extant Digital Twin (DT) implementations seldom achieve deep fusion with the production layer and consequently struggle to co-optimize structural integrity alongside operational efficiency. This paper therefore introduces, and subsequently validates, an integrated DT framework expressly conceived to close that lacuna. Four objectives guided the inquiry: first, to architect a distributed digital-twin topology underpinned by edge–cloud analytics capable of real-time SHM; second, to operationalize a machine-learning-driven predictive-maintenance regime that causally couples structural response data with both manufacturing process signatures and ambient environmental variables; third, to embed the resultant framework within incumbent MES/ERP ecosystems spanning multiple production facilities; and fourth, to quantify the concomitant reductions in maintenance expenditure, production downtime, and energy utilization. A longitudinal, 24-month, multi-site investigation furnished empirical corroboration. The framework couples a high-fidelity DT to legacy MES/ERP strata through a distributed edge-cloud fabric; an ensemble of machine-learning algorithms—Long Short-Term Memory networks prominent among them—was deployed for predictive anomaly detection. The system attained 96 % anomaly-detection accuracy (F1-score: 0.95) and translated this diagnostic precision into demonstrable operational gains: maintenance costs fell by 42.1 %, downtime by 31.1 %, and energy intensity by 23.2 % (p < 0.001). The edge-centric architecture reduced processing latency by 67 %, thereby enabling sub-50 ms integration with MES/ERP layers, while inter-site model transfer achieved 94.0 % adaptation efficacy. These findings substantiate the contention that principled integration of DTs with Industry 4.0 paradigms furnishes a transformative yet pragmatic pathway for manufacturing-oriented SHM. The framework’s verified capacity to enhance prognostic fidelity while simultaneously yielding sizeable operational dividends delineates a clear trajectory toward more resilient and resource-efficient industrial assets.","author":[{"family":"Davlatov","given":"Salim"},{"family":"Zayniyev","given":"Alisher"},{"family":"Zokirov","given":"Javohir"},{"family":"Temirova","given":"Matluba"},{"family":"Uljaeva","given":"Shohistahon"},{"family":"Xudayberganov","given":"Xudaybergan"},{"family":"Matkarimov","given":"Inomjon"},{"family":"Truong","given":"Chu"}],"issued":{"date-parts":[[2026]]},"DOI":"10.24867/ijiem-400","URL":"https://doi.org/10.24867/ijiem-400","source":"openalex"},{"id":"oa:W4406015793","type":"article-journal","title":"Blockchain in the banking industry: Unravelling thematic drivers and proposing a technological framework through systematic review with bibliographic network mapping","abstract":"Abstract In the new era of adopting and managing new and robust technologies in banking, the use of blockchain technology has significantly transformed overall banking systems. To add new insights to the body of existing knowledge, the authors conducted a systematic review with bibliographic network mapping to identify and analyse the factors contributing to adopting blockchain in the banking industry. Following the latest protocols of the PRISMA flowchart, this study acknowledged 16 relevant publications from 2590 papers in the databases, namely Scopus, ScienceDirect, Web of Science, and IEEE Xplore. The bibliographic data were grouped and analysed using VOSviewer to create network visualization maps that included citation and co‐citation, bibliographic coupling, co‐authorship, and co‐occurrence of terms. Subsequently, significant terms were identified through the analyses and compared with those found in the 16 relevant papers. The aggregate findings suggest that multiple influencing factors have been recognized and later categorized into three thematic drivers: transparency‐driven security, collaborative interoperability, and organizational infrastructure. The current research provides valuable insights for policymakers, technologists, researchers, consultants, and practitioners of information systems by proposing a technological framework, which will aid in developing tailored strategies to facilitate the sustainable practice of blockchain in the banking industry to a wider extent.","author":[{"family":"Rahman","given":"SMM"},{"family":"Saif","given":"Abu"},{"family":"Kabir","given":"Sadman"},{"family":"Bari","given":"Md"},{"family":"Alom","given":"Md"},{"family":"Rayhan","given":"Md"},{"family":"Zan","given":"Fangfang"},{"family":"Chu","given":"Mingyue"},{"family":"Talukder","given":"Ashis"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/blc2.12093","URL":"https://doi.org/10.1049/blc2.12093","source":"openalex"},{"id":"oa:W4414298181","type":"article-journal","title":"The Technical Hypothesis of a Missile Engine Conversion and Upgrade for More Sustainable Orbital Deployments","abstract":"The conversion of legacy missile engines into space propulsion systems represents a strategic opportunity to accelerate Europe’s access to orbit while advancing sustainability and circular-economy goals. Rather than discarding decommissioned hardware, repurposing missile propulsion can reduce development timelines, retain valuable materials, and leverage proven architectures for new applications. This perspective outlines the potential of the Soviet-era Isayev S2.720 engine as a representative case, drawing on historical precedents of missile-to-launcher conversions worldwide. A three-pillar methodology is proposed to frame such efforts: (i) the adoption of cleaner propellants such as LOX–LCH4 in place of toxic hypergolics; (ii) remanufacturing and upgrading of key subsystems through additive manufacturing, AI-assisted inspection, and digital twin modelling; and (iii) validation supported by dedicated testing, life-cycle assessment (LCA), and life-cycle costing (LCC). Beyond the technical aspects, the paper discusses retrofit applicability, cost considerations, and the role of standardization in enabling future certification. By positioning the S2.720 as a model, this study highlights the broader strategic value of adapting decommissioned propulsion systems for modern orbital use, providing insight into how Europe might integrate legacy assets into a more sustainable and resilient space transportation framework.","author":[{"family":"Prisăcariu","given":"Emilia"},{"family":"Dumitrescu","given":"Oana"},{"family":"Battista","given":"Francesco"},{"family":"Maligno","given":"Angelo"},{"family":"Munk","given":"Juri"},{"family":"Ricci","given":"Daniele"},{"family":"Haubrich","given":"Jan"},{"family":"Cardillo","given":"Daniele"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/aerospace12090833","URL":"https://doi.org/10.3390/aerospace12090833","source":"openalex"},{"id":"oa:W7164342378","type":"article-journal","title":"Software and Hardware Tools for Modeling Digital Twins","abstract":"Introduction. A digital twin dynamically reflects and simulates the behavior of its physical counterpart. To predict the behavior of a digital twin under certain conditions, it is necessary to create a large database and develop a software model. Artificial intelligence, smart sensors, 5G, cloud computing, VR/AR and blockchain are technologies that provide digital twins with intelligence, the ability to work constantly in real time and increased security. The purpose of the study is to demonstrate the possibilities of using digital twin technology to predict the remaining life of aircraft structures in order to ensure timely maintenance and optimize costs. Results. The paper substantiates the use of software and hardware for digital twins, which provides significant potential for optimizing processes and increasing efficiency in many industries The main hardware includes sensors and transducers: sensors for temperature, pressure, humidity and other physical parameters; cameras for visual monitoring. Computing devices: servers for real-time data processing, graphics processing units (GPUs) for processing complex models; data transmission devices: network devices for fast data transmission (5G, LoRaWAN); cloud services for data storage and synchronization (AWS, Azure). Further development of the technology is important to ensure greater accuracy and integration. Conclusions. Digital twins help improve productivity by enabling teams to collaborate in real time to accelerate and improve decision-making. Their wide range of possible applications is making them increasingly important in business and industry. The use of digital twins provides a comprehensive effect, which is manifested in reducing costs and waste, increasing productivity, improving product quality and storage conditions, as well as reducing production cycle times and lead times. Keywords: digital twins, virtual information constructs, software model, artificial intelligence.","author":[{"family":"Timashov","given":"Oleksandr"},{"family":"Sosnenko","given":"Kateryna"},{"family":"Samoliuk","given":"Tamara"}],"issued":{"date-parts":[[2026]]},"DOI":"10.34229/2707-451x.26.2.12","URL":"https://doi.org/10.34229/2707-451x.26.2.12","source":"openalex"},{"id":"oa:W7138840457","type":"article-journal","title":"Smart wearable and implantable biosensors for continuous health monitoring: materials, biocompatibility, and AI integration","abstract":"Abstract Smart wearable and implantable biosensors enable continuous, real-time monitoring of biophysical and biochemical signals for personalized and preventive healthcare. Advances in flexible, stretchable, and biocompatible materials ensure long-term comfort and seamless body integration, while multimodal and multi-analyte sensing improves robustness. AI enhances signal processing and predictive insights, yet challenges remain in motion artifacts, energy autonomy, data privacy, and clinical interpretability. This review summarizes materials, device architectures, and AI-assisted strategies applications.","author":[{"family":"Suryaprabha","given":"Thirumalaisamy"},{"family":"Choi","given":"Chunghyeon"},{"family":"Wu","given":"Yanfang"},{"family":"Liu","given":"Liyang"},{"family":"Hwang","given":"Byungil"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41528-026-00560-6","URL":"https://doi.org/10.1038/s41528-026-00560-6","source":"openalex"},{"id":"oa:W7125116382","type":"article-journal","title":"Cloud-Native Enterprise Resource Management for Multi-Sector Operations","abstract":"Enterprise Resource Management (ERM) systems play a vital role in integrating and coordinating organizational resources across finance, operations, human resources, procurement, and supply chains. Despite their importance, traditional on premise ERM solutions often face challenges related to limited scalability, high infrastructure and maintenance costs, and poor adaptability to rapidly changing operational requirements. These limitations become more pronounced in multi sector environments, such as manufacturing, healthcare, education, and logistics, where diverse workflows and regulatory constraints must be managed simultaneously. To address these challenges, this paper proposes a cloud native Enterprise Resource Management framework specifically designed to support multi sector operations. The proposed framework adopts a modular microservices architecture, enabling independent deployment, flexible scaling, and efficient integration of core ERM functions. Cloud based data management and real time analytics are incorporated to enhance operational visibility and decision making capabilities. The methodology outlines system architecture, deployment strategy, and data integration mechanisms within a cloud environment. Discussion and performance observations demonstrate that the cloud native approach significantly improves system responsiveness, resource utilization, and operational flexibility when compared to conventional ERM systems. Furthermore, the proposed solution reduces system downtime and maintenance complexity while enabling seamless cross sector coordination. The study concludes that cloud native ERM platforms provide a scalable, cost effective, and future ready solution for organizations managing complex, multi sector operations.","author":[{"family":"Rahman","given":"Florina"},{"family":"Nahar","given":"Shamsun"},{"family":"Mim","given":"Mahrima"}],"issued":{"date-parts":[[2026]]},"DOI":"10.30574/gjeta.2026.26.1.0012","URL":"https://doi.org/10.30574/gjeta.2026.26.1.0012","source":"openalex"},{"id":"oa:W7160236162","type":"manuscript","title":"2026 Roadmap on Artificial Intelligence and Machine Learning for Smart Manufacturing","abstract":"The evolution of artificial intelligence (AI) and machine learning (ML) is reshaping smart manufacturing by providing new capabilities for efficiency, adaptability, and autonomy across industrial value chains. However, the deployment of AI and ML in industrial settings still faces critical challenges, including the complexity of industrial big data, effective data management, integration with heterogeneous sensing and control systems, and the demand for trustworthy, explainable, and reliable operation in high-stakes industrial environments. In this roadmap, we present a comprehensive perspective on the foundations, applications, and emerging directions of AI and ML in smart manufacturing. It is structured in three parts. The first highlights the foundations and trends that frame the evolution of AI in smart manufacturing. The second focuses on key topics where AI is already enabling advances, including industrial big data analytics, advanced sensing and perception, autonomous systems, additive and laser-based manufacturing, digital twins, robotics, supply chain and logistics optimization, and sustainable manufacturing. The third section explores non-traditional ML approaches that are opening new frontiers, such as physics-informed AI, generative AI, semantic AI, advanced digital twins, explainable AI, RAMS, data-centric metrology, LLMs, and foundation models for highly connected and complex manufacturing systems. By identifying both opportunities and remaining barriers across these areas, this roadmap outlines the advances needed in methods, integration strategies, and industrial adoption. We hope this roadmap will serve as a guide for researchers, engineers, and practitioners to accelerate innovation, align academic and industrial priorities, and ensure that AI-driven smart manufacturing delivers reliable, sustainable, and scalable impact for the future of manufacturing ecosystems.","author":[{"family":"Lee","given":"Jay"},{"family":"Su","given":"Hanqi"},{"family":"Macchi","given":"Marco"},{"family":"Polenghi","given":"Adalberto"},{"family":"Wu","given":"Wei"},{"family":"Zhao","given":"Zhiheng"},{"family":"Huang","given":"George"},{"family":"Allgood","given":"Kiva"},{"family":"Jain","given":"Devendra"},{"family":"Gieger","given":"Benedikt"},{"family":"Pandhare","given":"Vibhor"},{"family":"Bhattacharjee","given":"Soumyabrata"},{"family":"Mohril","given":"Ram"},{"family":"Kong","given":"Lingbao"},{"family":"Wang","given":"Qiyuan"},{"family":"Tang","given":"Xinlan"},{"family":"Kim","given":"Sungjong"},{"family":"Park","given":"Chan"},{"family":"Youn","given":"Byeng"},{"family":"Goh","given":"Guo"},{"family":"Huang","given":"Xi"},{"family":"Yeong","given":"Wai"},{"family":"Shin","given":"Yung"},{"family":"Zhang","given":"He"},{"family":"Wang","given":"Zitong"},{"family":"Tao","given":"Fei"},{"family":"Srai","given":"Jagjit"},{"family":"Gupta","given":"Satyandra"},{"family":"Joung","given":"Byung"},{"family":"John","given":"AR"},{"family":"Sutherland","given":"John"},{"family":"Lee","given":"Sang"},{"family":"Fink","given":"Olga"},{"family":"Sharma","given":"Vinay"},{"family":"Ahmed","given":"Faez"},{"family":"Chen","given":"Wei"},{"family":"Fuge","given":"Mark"},{"family":"Waaler","given":"Arild"},{"family":"Skjæveland","given":"Martin"},{"family":"Kyritsis","given":"Dimitris"},{"family":"Chen","given":"Wei"},{"family":"Karkaria","given":"Vispinevile"},{"family":"Chen","given":"Yi"},{"family":"Tsai","given":"Ying"},{"family":"Cohen","given":"Joseph"},{"family":"Huan","given":"Xun"},{"family":"Lin","given":"Jing"},{"family":"Zhang","given":"Liangwei"},{"family":"Vogl","given":"Greg"},{"family":"Cornelius","given":"Aaron"},{"family":"Jia","given":"Xiaodong"},{"family":"Ji","given":"Dai"},{"family":"Minami","given":"Takanobu"},{"family":"Wang","given":"Ruoxin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.48550/arxiv.2605.00839","URL":"https://doi.org/10.48550/arxiv.2605.00839","source":"openalex"},{"id":"oa:W4409771013","type":"article-journal","title":"A Comprehensive Survey on Deep Learning-based Predictive Maintenance","abstract":"With the advent of Industrial 4.0 and the push toward Industry 5.0, the data generated by the industries have become surprisingly large. This abundance of data significantly boosts machine and deep learning models for Predictive Maintenance (PdM). The PdM plays a vital role in extending the lifespan of industrial equipment and machines while also helping to reduce the risk of unscheduled downtime. Given its multidisciplinary nature, the field of PdM has been approached from many different angles: this comprehensive survey aims at providing an up-to-date overview focused on all the learning-based industrial PdM strategies, discussing weaknesses and strengths. The survey is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodological flow, allowing a systematic and complete review of the literature. In particular, firstly, we explore the main learning models used for PdM, mainly Convolutional Neural Networks (ConvNets), Autoencoders (AEs), Generative Adversarial Networks (GANs), and Transformers, also giving an overview of the newest models such as diffusion models and foundation models. Then, we discuss the main learning paradigms applied to PdM, i.e., supervised, unsupervised, ensemble, transfer, federated, and reinforcement learning. Furthermore, this work discusses the pipeline of the data-driven PdM and its benefits, practical applications, datasets, and benchmarks. In addition, the evaluation metrics for each PdM stage and the state-of-the-art hardware devices used are discussed. Finally, the challenges and future work are presented.","author":[{"family":"Khan","given":"Uzair"},{"family":"Cheng","given":"Dong"},{"family":"Setti","given":"Francesco"},{"family":"Fummi","given":"Franco"},{"family":"Cristani","given":"Marco"},{"family":"Capogrosso","given":"Luigi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1145/3732287","URL":"https://doi.org/10.1145/3732287","source":"openalex"},{"id":"oa:W7124600441","type":"article-journal","title":"Smart IoT Infrastructure for Workplace Efficiency and Energy Savings","abstract":"The rapid digitization of modern workplaces has led to increased reliance on electrical equipment, automated systems, and digital infrastructure, resulting in higher energy consumption and operational complexity. Conventional workplace infrastructure systems often operate independently, without real time coordination or intelligent control, which leads to energy wastage, inefficient resource utilization, and reduced employee comfort. To address these challenges, this paper proposes a Smart Internet of Things (IoT) based infrastructure aimed at improving workplace efficiency while achieving significant energy savings. The proposed system integrates distributed smart sensors, intelligent controllers, cloud-based data analytics, and automated control mechanisms to continuously monitor environmental conditions, occupancy behavior, and equipment usage in real time. By analyzing collected data, the system dynamically optimizes lighting, heating, ventilation, air conditioning, and power usage based on actual workplace demand. Experimental evaluation and scenario-based analysis indicate that the proposed IoT framework can reduce overall energy consumption by a substantial margin while maintaining optimal indoor comfort levels. Additionally, automation reduces manual intervention and operational overhead, contributing to improved productivity and system reliability. The modular and scalable design of the infrastructure allows it to be deployed across various workplace environments, including offices, industrial facilities, and institutional buildings. The findings of this study demonstrate that smart IoT-enabled infrastructure provides an effective, sustainable, and future-ready solution for intelligent workplace management and energy efficient operations.","author":[{"family":"Mim","given":"Mahrima"},{"family":"Sharif","given":"Murad"},{"family":"Rahman","given":"Florina"},{"family":"Nahar","given":"Shamsun"}],"issued":{"date-parts":[[2026]]},"DOI":"10.30574/wjaets.2026.18.1.0026","URL":"https://doi.org/10.30574/wjaets.2026.18.1.0026","source":"openalex"},{"id":"oa:W4407393708","type":"article-journal","title":"A Comprehensive Review of Load Frequency Control and Solar Energy Integration: Challenges & Opportunities in Indian Context","abstract":"Energy plays a crucial role in driving economic growth, and India’s energy consumption has increased notably due to its growing population and development. At present, fossil fuels such as coal, petroleum, and natural gas fulfill the majority of India’s energy requirements, but their swift depletion and negative environmental effects present significant challenges. India’s abundant solar energy potential—estimated at approximately 5000 trillion kWh annually—positions the nation to harness clean and sustainable power. With steady growth, solar energy has become a key component of India’s power grid. However, integrating renewable energy into the grid presents challenges, such as maintaining frequency and voltage stability. This report analyzes India’s substantial advancements in solar energy, emphasizing the enabling government policies and the problems associated with integrating renewable energy into the grid. The study underscores the crucial need for effective load frequency control (LFC) solutions to mitigate grid stability issues, intensified by the fluctuating and intermittent characteristics of solar energy. It also evaluates policy-driven approaches and technological advancements, providing practical recommendations to overcome integration challenges. This research aims to contribute to the effective deployment of solar energy in India’s energy mix, ensuring long-term grid stability and sustainability, and it underscores that India’s creative strategies can serve as a model for other nations facing analogous issues in renewable energy integration. It emphasizes the necessity of recognizing optimal practices that integrate energy security, economic development, and environmental objectives, thus contributing to global dialogs on energy transitions.","author":[{"family":"Singh","given":"Anjana"},{"family":"Shankar","given":"Ravi"},{"family":"Kumar","given":"Amitesh"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/en18040843","URL":"https://doi.org/10.3390/en18040843","source":"openalex"},{"id":"oa:W7125708765","type":"article-journal","title":"Implementation of Integrated Control Systems Projects in Companies Focused on Industry 4.0: Opportunities and Challenges in Brazil","abstract":"Integrated control systems (Supervisory Control and Data Acquisition–SCADA and Manufacturing Execution Systems—MES) constitute the backbone of Industry 4.0; however, research on their implementation remains scarce. This study analyzes the opportunities and challenges of modernizing these systems within the context of the Brazilian industry. A survey of 101 experts was conducted, with results analyzed via Friedman and Holm–Sidak nonparametric tests to establish a clear hierarchy of factors. Findings reveal that while economic efficiency, productivity gains, and real-time remote access represent the most significant opportunities, they are countered by critical structural challenges: obsolete machinery and inadequate infrastructure. These challenges significantly inflate implementation costs and highlight the reality of technological obsolescence that is typical of emerging economies. By applying the Resource-Based View (RBV), this research frames digital integration as a strategic competitive capability rather than a mere technical upgrade. Practically, the study provides a roadmap for industrial leaders to balance digital agility expectations with pragmatic operational constraints. These insights offer a foundation for successful digital transformation, delivering actionable value for academics, industrial managers, and policymakers.","author":[{"family":"Correia","given":"Auro"},{"family":"Silva","given":"Leandro"},{"family":"Araújo","given":"Josiane"},{"family":"Contador","given":"José"},{"family":"Contador","given":"José"},{"family":"Magalhães","given":"Guilherme"},{"family":"Prado","given":"Rogério"},{"family":"Sátyro","given":"Walter"},{"family":"Spinola","given":"Mauro"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/technologies14020078","URL":"https://doi.org/10.3390/technologies14020078","source":"openalex"},{"id":"oa:W4414184954","type":"article-journal","title":"Bridging the Gap to Industry 5.0","abstract":"Since 2011, the term 'Industry 4.0' (I4.0) has gained significance in industry. After a decade of digital transformation, the European Commission is now advancing towards Industry 5.0 (I5.0). The focus is on using technology to support people, enhance ecological sustainability, and make industry more resilient. This paper examines the transition from I4.0 to I5.0, with a particular focus on the learning factory Smart Production Lab as a model for future-oriented manufacturing companies. The study involves a systematic literature review to identify key technologies and concepts of I4.0 and analyse their evolution in the context of I5.0. A comparative analysis forms the basis for a matrix that facilitates a clear comparison and guides future developments of the Lab. This research identifies the technologies underpinning the goals of I5.0 and their implications for practical applications in manufacturing. It also provides actionable recommendations for companies.","author":[{"family":"Leitenbauer","given":"Lena"},{"family":"Sorko","given":"Sabrina"},{"family":"Lichem-Herzog","given":"Christine"}],"issued":{"date-parts":[[2025]]},"DOI":"10.31803/tg-20240519112501","URL":"https://doi.org/10.31803/tg-20240519112501","source":"openalex"},{"id":"oa:W7134944526","type":"article-journal","title":"Advances in Hydrogen Pipeline Joints: Materials, Sealing Structures, and Intelligent Monitoring for Safe Hydrogen Transport","abstract":"Against the backdrop of the accelerating global energy transition toward clean and low-carbon sources, hydrogen energy is emerging as a vital component of future energy systems due to its zero-carbon emissions, high energy density, and renewable nature. The safe and efficient transportation of hydrogen is a critical link in the hydrogen energy industry chain. As core connecting components in hydrogen transmission systems, the sealing integrity, hydrogen embrittlement resistance, and long-term service reliability of hydrogen pipeline joints directly impact the stable operation of entire hydrogen transmission systems and the feasibility of large-scale application. This study systematically reviews the research literature on hydrogen pipeline joints from 2014 to 2025 using bibliometric and knowledge graph analysis methods based on the Web of Science Core Collection database. It constructs co-occurrence networks and clustering graphs of keywords to identify core research themes in this field, including hydrogen embrittlement failure mechanisms, degradation of sealing material properties, structural design optimization of joints, and intelligent monitoring and fault diagnosis. Furthermore, this study highlights existing research gaps in evaluating joints’ long-term service performance, developing low-cost and efficient manufacturing technologies, and verifying reliability under complex operating conditions. This study provides a systematic bibliometric perspective on hydrogen pipeline joint technology development, aiding in identifying research frontiers and technological evolution pathways. It offers theoretical support and decision-making references for the safe construction and standardized development of hydrogen energy infrastructure.","author":[{"family":"Hong","given":"Siyan"},{"family":"Ma","given":"Xincheng"},{"family":"Zhao","given":"Yapan"},{"family":"Zhang","given":"Miaomiao"},{"family":"Li","given":"Cuiyan"},{"family":"Luo","given":"Jun"},{"family":"Wang","given":"Y"},{"family":"Hong","given":"BS"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19061408","URL":"https://doi.org/10.3390/en19061408","source":"openalex"},{"id":"oa:W7167931497","type":"article-journal","title":"Additive Manufacturing for Sustainable Construction 4.0: Trends, Opportunities, and Future Directions","abstract":"Additive manufacturing (AM) is applied in sustainable architecture and Construction 4.0 because it can support design flexibility, mass customization, material efficiency, and reduced reliance on conventional formwork. Prior reviews often addressed either construction applications or broader digital transformation, leaving the intersection of AM, construction sustainability, digital technologies, and lifecycle performance underexplored. This study conducts a systematic and bibliometric review of literature retrieved from Scopus and Web of Science covering the period from January 2016 to January 2026. The review protocol followed SPAR-4-SLR principles and PRISMA 2020 guidelines, with 58 records retained for analysis. Bibliometric and thematic analyses identified a marked rise in publication activity after 2021 with four major research themes: material development and innovation, digital fabrication and process control, lifecycle assessment and circularity, and digital integration and project implementation. Construction 4.0 technologies, including BIM, digital twins, automation, and robotics, were the most frequently represented digital enablers. The review further identifies future research opportunities and outlines a proposed conceptual pathway toward Construction 5.0. This pathway connects materials, robotics, lifecycle performance, and human-centered priorities as a future research agenda. Overall, this study contributes to a more integrated understanding of how AM can advance sustainable, digitally enabled, and human-centered construction practice.","author":[{"family":"Yasmin","given":"Farhana"},{"family":"Zhu","given":"ZQ"},{"family":"Devkota","given":"Ajit"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/architecture6030110","URL":"https://doi.org/10.3390/architecture6030110","source":"openalex"},{"id":"oa:W4417292791","type":"article-journal","title":"Exploring the Spillover Effect of Supply Chain Digitalisation on Pollution Emissions Through Social Network Analysis","abstract":"ABSTRACT The supply chain consists of interconnected businesses and organisations responsible for the flow of goods and services. As firms increasingly adopt digital technologies, the spillover effects of supply chain digitalisation (SCD) on environmental performance remain underexplored. This study examines how the digitalisation of suppliers and customers influences pollution emissions in midstream manufacturing firms. Using data from Chinese A‐share‐listed firms and social network analysis, we construct a novel indicator to measure SCD. Our findings reveal that digitalisation within the supply chain significantly reduces pollution emissions through three key mechanisms: cost efficiency, improved resource allocation and green technology innovation. The effect is more pronounced in high‐pollution industries, regions with stricter environmental regulations and regions with well‐developed digital infrastructure. These insights highlight the strategic role of digital transformation in driving corporate sustainability and provide valuable implications for firms and policymakers navigating green business strategies.","author":[{"family":"Cao","given":"Zengdong"},{"family":"Williams","given":"Nichola"},{"family":"Ali","given":"Ibrahim"},{"family":"Periola","given":"Ololade"},{"family":"Kayıkçı","given":"Yaşanur"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/bse.70443","URL":"https://doi.org/10.1002/bse.70443","source":"openalex"},{"id":"oa:W4408419967","type":"article-journal","title":"Extending the Welding Seams Detection as Preparation Towards the Digital Twin Technology","abstract":"ABSTRACT Detection and identification of defects in manufactured products, a task related to the basic requirements of quality management systems. By moving to higher levels, under the right conditions, these defects can be avoided, for example, by preventing manufacturing defects from occurring. Quality control and monitoring of welds are closely linked to the requirements of Industry 4.0. In the case of welding processes, quality assurance is a multifaceted area, including not only the analysis of input parameters but also the quality of the weld surface. By superimposing the point clouds of the parts under test, geometric features are generated to the initial manufacturing parameters to help increase manufacturing efficiency. In our work, the information data recorded by the data acquisition framework, which is captured during the welding process, is integrated with the outputs of the point cloud characteristics of the examined by the structured light scanning technology, as well as the value of the seam width magnitude extracted by the image recognition algorithms. This contributes to the possibilities of broadening the seam detection processes.","author":[{"family":"Hegedűskuti","given":"János"},{"family":"Szőlősi","given":"József"},{"family":"Birosz","given":"Márton"},{"family":"Csobán","given":"Attila"},{"family":"Popamüller","given":"Izolda"},{"family":"Andó","given":"Mátyás"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/cim2.70027","URL":"https://doi.org/10.1049/cim2.70027","source":"openalex"},{"id":"oa:W7171977235","type":"article-journal","title":"Designing a digital twin of a crude oil heating system","abstract":"This article is devoted to the design of a digital twin of a crude oil heating system. For the successful functioning of the oil industry, it is very important to control the parameters of ongoing processes and indicators of devices and equipment involved in the production process. Every year, there is an increasing automation of the extraction and transportation processes to detect temperature changes in a timely manner. Lowering the oil temperature to the crystallization temperature of the paraffins in its composition is a favorable factor for the formation of asphalt-resin-paraffin deposits on the inner wall of the pipeline, which may be a factor that first reduces the productivity of the pipeline, and then completely prevents it. Therefore, the issues of the relevance of integrating the technology of digital deposits come to the fore. The aim of the work is to study various techniques and technologies to prevent the appearance and removal of asphalt-resin-paraffin deposits and, as a result, to develop a mathematical model of the temperature field of an oil pipeline and conduct an experiment simulating the oil flow inside the pipeline to measure the temperature of the liquid. In order to solve the tasks set, the article analyzes the state of the oil industry, examines the issues of ensuring industrial safety measures and limiting the harmful effects of the oil production on the environment. The article describes the characteristics and chemical composition of asphalt-resin-paraffin deposits, the causes of their occurrence and the mechanism of formation, methods of combating asphalt-resin-paraffin deposits. As a result, a digital twin model of the crude oil heating system was developed, an experiment was conducted that proved the system operability and confirmed its ability to respond to changes in the temperature field of the oil emulsion inside the pipeline. For citation: Stolbovskaya N.V., Esipova K.I., Pasternak S.N., Turovskaya L.G., Davydov T.G. Designing a digital twin of a crude oil heating system. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 2026, vol. 337, no. 7, pp. 113-124. https://doi.org/10.18799/24131830/2026/7/5027","author":[{"family":"Stolbovskaya","given":"Natalya"},{"family":"Esipova","given":"Ksenia"},{"family":"Pasternak","given":"Svetlana"},{"family":"Turovskaya","given":"Lyudmila"},{"family":"Davydov","given":"Tigran"}],"issued":{"date-parts":[[2026]]},"DOI":"10.18799/24131830/2026/7/5027","URL":"https://doi.org/10.18799/24131830/2026/7/5027","source":"openalex"},{"id":"oa:W7161175396","type":"article-journal","title":"Artificial intelligence in modern pharmacy: Transforming discovery, clinical practice, and manufacturing","abstract":"Artificial Intelligence (AI) has emerged as a disruptive force within the pharmaceutical sector, shifting the industry from traditional batch-based methodologies to a data-driven, precision-oriented model. This review examines the current landscape of AI integration in modern pharmacy as of 2026, focusing on its role in accelerating drug discovery, optimizing clinical pharmacy services, and enabling \"Pharma 4.0\" manufacturing. Key advancements include the use of generative AI for de novo molecule design, predictive analytics for adverse drug event (ADE) prevention, and digital twins for personalized dosing. Despite these breakthroughs, challenges such as algorithmic bias, regulatory \"black box\" dilemmas, and data fragmentation persist. This article concludes that while AI significantly enhances efficiency and patient safety, a robust framework for explainable AI (XAI) and human-in-the-loop mechanisms is essential for full-scale clinical adoption.","author":[{"family":"Kumawat","given":"Pooja"},{"family":"Patel","given":"Rupali"},{"family":"Kumar","given":"Yogendra"},{"family":"Chaturvedi","given":"Mohit"}],"issued":{"date-parts":[[2026]]},"DOI":"10.33545/26646862.2026.v8.i5a.329","URL":"https://doi.org/10.33545/26646862.2026.v8.i5a.329","source":"openalex"},{"id":"oa:W7202091652","type":"article-journal","title":"Physics-guided digital-twin-ready surrogate framework for predictive design of double-bridge compliant mechanisms in advanced manufacturing systems","abstract":"The integration of physics-based modeling and data-driven prediction is creating new opportunities for predictive design, optimization, and the deployment of digital twins in advanced manufacturing systems. In compliant mechanisms, particularly double-bridge configurations used in precision positioning and surface engineering applications, accurate prediction and optimization of amplification ratio remain challenging due to coupled geometric interactions and nonlinear design trade-offs. This study presents a Physics-Guided Digital-Twin-Ready Framework for the predictive design and multi-objective optimization of double-bridge compliant mechanisms. A physics-consistent dataset comprising 8,000 design samples was generated using Latin Hypercube Sampling, analytical compliance modeling, constraint-based filtering, and response-space stratified sampling. The resulting dataset provides balanced coverage of amplification ratios within the range of 5–50, enabling robust learning across diverse design regimes. Machine-learning models, including Random Forest and Extreme Gradient Boosting (XGBoost), were developed to predict amplification ratio from geometric and material parameters. The models achieved excellent predictive performance, with coefficients of determination (R 2 ) exceeding 0.99, mean absolute errors below 0.93, and root mean square errors below 0.65. Uncertainty quantification was incorporated through ensemble variance estimation, yielding prediction intervals with less than 5% relative uncertainty in well-sampled regions. SHAP-based explainability and sensitivity analyses revealed that amplification behavior is primarily governed by geometric parameters, particularly beam lengths and flexure thickness, whereas material stiffness has comparatively lower influence. NSGA-II-based multi-objective optimization identified Pareto-optimal solutions that balance amplification ratio and equivalent stiffness, highlighting the inherent trade-off between displacement amplification and structural rigidity. The developed surrogate models enable rapid design exploration, uncertainty assessment, and optimization, while achieving computational speed-ups of approximately 10 3 –10 7 times compared with finite-element-based evaluation workflows, depending on the evaluation method. The primary contribution of this work is the integration of analytical compliance modeling, physics-consistent dataset generation, uncertainty-aware machine learning, explainable artificial intelligence, and multi-objective optimization within a unified predictive framework. The proposed methodology should be interpreted as a digital-twin-ready surrogate architecture rather than a fully implemented digital twin, as real-time sensing, and online model updating are beyond the scope of the present study. Nevertheless, the framework provides a scalable foundation for future integration with experimental measurements, multi-fidelity datasets, and digital-twin-enabled manufacturing environments.","author":[{"family":"Kolate","given":"Vijay"},{"family":"Darade","given":"Pradipkumar"},{"family":"Deshmukh","given":"Suhas"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fmech.2026.1888696","URL":"https://doi.org/10.3389/fmech.2026.1888696","source":"openalex"},{"id":"oa:W7128808529","type":"article-journal","title":"Mechanism-Driven Green Extraction of Plant Polyphenols: From Molecular Interactions to Process Integration and Intelligent Optimization","abstract":"Plant polyphenols are valuable secondary metabolites with significant bioactivities; however, their efficient extraction faces multiple challenges, including the structural complexity arising from their coexistence in free and bound forms within plant matrices, as well as their sensitivity to oxidation and heat. Although emerging green extraction technologies such as deep eutectic solvents, supercritical fluid extraction, and physical field enhancement show potential, current research largely remains method-oriented, lacking an in-depth understanding of the coupling mechanisms between molecular interactions and mass transfer processes. This review explicitly proposes a \"mechanism-driven, synergistic integration\" framework for the green extraction of plant polyphenols. By systematically analyzing the molecular basis of extractability and the complementarity among emerging technologies, this framework provides theoretical guidance and a practical blueprint for transitioning from empirical optimization to intelligent, synergistic system design. Specifically, it begins by systematically dissecting the structural characteristics of polyphenols and their interactions with cell wall components to clarify the molecular basis of extractability. Next, it critically reviews the mechanisms, advantages, and engineering bottlenecks of representative green technologies, with a focus on how synergistic integration strategies based on complementary mechanisms can overcome the limitations of single technologies to achieve higher extraction efficiency and selectivity. Furthermore, it evaluates the application of response surface methodology and artificial neural networks in process modeling. Finally, it highlights critical challenges such as industrial scale-up, sustainability assessment, and intelligent manufacturing. This review advocates a paradigm shift from optimizing single techniques toward designing intelligent, synergistic systems grounded in mechanistic insights.","author":[{"family":"Yuan","given":"Shiwei"},{"family":"Zhao","given":"Wanru"},{"family":"Wang","given":"Yong"},{"family":"Dong","given":"He"},{"family":"Song","given":"Kai"},{"family":"Shi","given":"Dongfang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/plants15040596","URL":"https://doi.org/10.3390/plants15040596","source":"openalex"},{"id":"oa:W7128476249","type":"article-journal","title":"A Critical Review Exploring the Interplay Between Advanced Technologies and Innovation Ecosystems in Industry 5.0 Scenario","abstract":"ABSTRACT Unlike Industry 4.0, which primarily emphasized automation and efficiency, Industry 5.0 marks a transition toward human‐centricity, sustainability, and resilience. One of the key challenges for Industry 5.0 innovation ecosystems lies in integrating technological progress with social equity, environmental responsibility, and active human involvement. This study aims to explore how digital and advanced technologies contribute to the development of Industry 5.0 within innovation ecosystems. Through a qualitative approach based on a critical literature review, the research identifies three promising areas where such technologies support the core principles of Industry 5.0, connecting them with Innovation Ecosystem Theory. The study's findings contribute to the creation of a conceptual framework intended to guide scholars in future research focused on understanding how advanced technologies can foster inclusive, resilient, and sustainable innovation ecosystems. Although the study follows a rigorous methodology, it also acknowledges some limitations, which could be addressed in future research developments.","author":[{"family":"Barile","given":"Domenica"},{"family":"Lorenzi","given":"Maria"},{"family":"Latino","given":"Maria"},{"family":"Secundo","given":"Giustina"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1002/csr.70430","URL":"https://doi.org/10.1002/csr.70430","source":"openalex"},{"id":"oa:W4410307541","type":"article-journal","title":"Trust by Design: An Ethical Framework for Collaborative Intelligence Systems in Industry 5.0","abstract":"Industry 5.0 highlights human-centricity, sustainability, and resilience. This article presents a novel Trust by Design framework applicable to collaborative intelligence systems within Industry 5.0, addressing the need for collaborative systems to be reliable by design, incorporating ethical principles such as transparency, accountability, fairness, and privacy throughout the entire system lifecycle. The framework is grounded in select ethical philosophies applied to practical design requirements for human-AI collaboration, identifying key ethical challenges that threaten to damage trust and restrict the adoption of collaborative systems. The authors employ a qualitative, literature-driven method, conceptual modeling, and scenario-based case study analysis, synthesizing best practices and ethical policies from the EU AI Act, GDPR, and more. Trust by Design suggests a structured set of principles and implementation measures to embed ethics into every phase of the system’s lifecycle. The applicability and suitability of the framework are demonstrated through representative real-world application scenarios across industries. The results indicate that trust in collaborative intelligence systems is not static but dynamic, context-dependent, and controlled by transparency, fairness, and user experience. The framework includes instruments and methods to measure ethical performance, including trust metrics, override rates, fairness indicators, and incident tracking.","author":[{"family":"Merchán-Cruz","given":"Emmanuel"},{"family":"Gabelaia","given":"Ioseb"},{"family":"Savrasovs","given":"Mihails"},{"family":"Hansen","given":"Mark"},{"family":"Soe","given":"Shwe"},{"family":"Rodríguez-Cañizo","given":"Ricardo"},{"family":"Aragón-Camarasa","given":"Gerardo"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/electronics14101952","URL":"https://doi.org/10.3390/electronics14101952","source":"openalex"},{"id":"oa:W7160038722","type":"article-journal","title":"Sustainable and resilient cyber-physical production systems: A systematic literature review","abstract":"Abstract Cyber-physical production systems (CPPSs) enable intelligent decision-making, self-diagnosis, predictive maintenance, and real-time monitoring, thereby enhancing resilience, sustainability, and operational efficiency, and positioning them as central to the Industry 5.0 vision. However, current CPPS design and assessment approaches often treat resilience and sustainability separately, lacking an integrated framework. To address this gap, this study introduces the concept of sustainable and resilient CPPSs (SR-CPPSs) and systematically reviews 69 studies to synthesize current approaches, frameworks, methods, and parameters for the design and assessment of SR-CPPSs. The findings identify key categories that clarify how resilience and sustainability principles are integrated into the development and evaluation of CPPSs. The review reveals significant advancements in resilience-oriented CPPS research, whereas sustainability-focused approaches remain limited. This paper highlights that sustainability can reinforce resilience by supporting long-term system viability, while resilience contributes to sustainability by mitigating disruption-induced resource losses and operational inefficiencies. However, this relationship is not always synergistic, trade-offs may emerge depending on design configurations and operational contexts, and this study analyses them. Furthermore, this paper proposes a systemic roadmap for CPPS’s sustainability assessment to realize sustainability goals in SR-CPPS research. The review provides insights into current academic and industrial challenges in advancing SR-CPPSs, including human–automation interaction, lifecycle-oriented evaluation, dynamic adaptation under uncertainty, and the management of time-dependent system complexity. Finally, this work outlines a future research agenda for SR-CPPSs to advance manufacturing systems toward resilient, adaptable, and environmentally responsible production ecosystems, thereby supporting the twin green and digital transitions.","author":[{"family":"Barrero-Arciniegas","given":"Humberto"},{"family":"Bataleblu","given":"Ali"},{"family":"Rauch","given":"Erwin"},{"family":"Matt","given":"Dominik"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1093/jcde/qwag043","URL":"https://doi.org/10.1093/jcde/qwag043","source":"openalex"},{"id":"oa:W7128162373","type":"article-journal","title":"Advancing Sustainable Materials Engineering with Natural-Fiber Biocomposites","abstract":"Natural-fiber biocomposites are increasingly viewed as promising materials for sustainable engineering. However, their broader adoption remains constrained by coupled challenges related to interfacial compatibility, moisture sensitivity, environmental durability, processing limitations, and end-of-life trade-offs. Rather than treating fiber selection, matrix chemistry, processing routes, durability, and sustainability as independent considerations, this review emphasizes their interdependence through the fiber–matrix interface, which governs stress transfer, moisture transport, and long-term property evolution. It provides a comprehensive and integrative analysis of natural-fiber–reinforced polymer composites, encompassing plant-, animal-, and emerging bio-derived reinforcements combined with bio-based, biodegradable, and selected synthetic matrices. Comparative analysis across the literature demonstrates that interfacial engineering consistently dominates mechanical performance, moisture resistance, and property retention, while mediating trade-offs among stiffness, toughness, recyclability, and biodegradability. Moisture transport and environmental ageing are examined using thermodynamic and diffusion-controlled frameworks that link fiber chemistry, interfacial energetics, swelling, and debonding to performance degradation. Fire behavior and flame-retardant strategies are reviewed with attention to heat-release control and their implications for durability and circularity. Processing routes, including extrusion, injection molding, compression molding, resin transfer molding, and additive manufacturing, are assessed with respect to fiber dispersion, thermal stability, scalability, and compatibility with bio-based systems. By integrating structure–property relationships, processing science, durability mechanisms, and sustainability considerations, this review clarifies how natural-fiber biocomposites can be designed to achieve balanced performance, environmental stability, and circular life-cycle behavior, thereby providing guidance for the development of systems suitable for near-term engineering applications.","author":[{"family":"Bonyani","given":"Maryam"},{"family":"Marincic","given":"Ian"},{"family":"Krishnan","given":"Sitaraman"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/jcs10020086","URL":"https://doi.org/10.3390/jcs10020086","source":"openalex"},{"id":"oa:W7160291923","type":"article-journal","title":"BIBLIOMETRIC ANALYSIS OF THE INTEGRATION OF RENEWABLE ENERGY IN LEAN MANUFACTURING PRODUCTION SYSTEMS","abstract":"This study presents a bibliometric analysis of the integration of renewable energy into lean manufacturing production systems using Scopus-indexed data from 2022 to 2026. The objective is to map research trends, identify dominant thematic clusters, and examine existing research gaps at the intersection of operational efficiency and energy sustainability. A total of over 1,400 documents were analyzed using VOSviewer to construct keyword co-occurrence networks and thematic maps. The findings reveal four major research clusters: (1) lean manufacturing and sustainable development, (2) Industry 4.0 and digital twins, (3) production control and optimization, and (4) hydrogen production and renewable energy systems. Despite stable publication trends in both lean manufacturing and renewable energy domains, the results indicate weak structural connections between the two fields, suggesting limited integrative research. This study highlights a significant research gap in combining lean operational principles with renewable energy applications, particularly in real-world manufacturing contexts and developing countries. It contributes by providing a comprehensive bibliometric mapping and proposing future research directions that integrate lean efficiency with sustainable energy metrics within interdisciplinary production system frameworks.","author":[{"family":"Lubis","given":"Putri"},{"family":"Najiha","given":"Putri"},{"family":"Bintang"}],"issued":{"date-parts":[[2026]]},"DOI":"10.56190/jree.v4i1.81","URL":"https://doi.org/10.56190/jree.v4i1.81","source":"openalex"},{"id":"oa:W4413247004","type":"article-journal","title":"A Review of Key Factors Shaping the Development of the U.S. Wind Energy Market in the Context of Contemporary Challenges","abstract":"The United States has emerged as a global leader in wind energy deployment, yet the industry faces evolving challenges linked to policy uncertainty, infrastructure constraints, and supply chain disruptions. This review aims to analyze selected aspects of the U.S. wind energy market in light of recent economic, regulatory, and environmental developments. Drawing upon the academic literature, policy documents, and industry reports, the paper outlines key trends in both onshore and offshore wind sectors, evaluates technological and economic progress, and identifies structural barriers that may hinder further growth. Special attention is given to the role of federal incentives, such as the Inflation Reduction Act, and to the regional differentiation in wind capacity expansion. Additionally, the potential of small-scale wind systems for individual- and community-level energy resilience is explored as an underrepresented area in current research. The findings suggest that while the U.S. wind market holds significant untapped potential, strategic improvements in grid modernization, permitting processes, and public engagement are essential. The review highlights the need for more inclusive and regionally sensitive policy approaches to unlock future development pathways in the U.S. wind energy sector.","author":[{"family":"Zupok","given":"Sebastian"},{"family":"Chomać-Pierzecka","given":"Ewa"},{"family":"Dmowski","given":"Artur"},{"family":"Dyrka","given":"Stefan"},{"family":"Hordyj","given":"Andrzej"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/en18164224","URL":"https://doi.org/10.3390/en18164224","source":"openalex"},{"id":"oa:W4409449764","type":"article-journal","title":"Quantitative Phase Imaging with a Meta-Based Interferometric System","abstract":"Optical phase imaging has become a pivotal tool in biomedical research, enabling label-free visualization of transparent specimens. Traditional optical phase imaging techniques, such as Zernike phase contrast and differential interference contrast microscopy, fall short of providing quantitative phase information. Digital holographic microscopy (DHM) addresses this limitation by offering precise phase measurements; however, off-axis configurations, particularly Mach-Zehnder and Michelson-based setups, are often hindered by environmental susceptibility and bulky optical components due to their separate reference and object beam paths. In this work, we have developed a meta-based interferometric quantitative phase imaging system using a common-path off-axis DHM configuration. A meta-biprism, featuring two opposite gradient phases created using GaN nanopillars selected for their low loss and durability, serves as a compact and efficient beam splitter. Our system effectively captures the complex wavefronts of samples, enabling the retrieval of quantitative phase information, which we demonstrate using standard resolution phase targets and human lung cell lines. Additionally, our system exhibits enhanced temporal phase stability compared to conventional off-axis DHM configurations, reducing phase fluctuations over extended measurement periods. These results not only underline the potential of metasurfaces in advancing the capabilities of quantitative phase imaging but also promise significant advancements in biomedical imaging and diagnostics.","author":[{"family":"Chu","given":"Cheng"},{"family":"Tsai","given":"Chen"},{"family":"Yamaguchi","given":"Takeshi"},{"family":"Wang","given":"Yuxiang"},{"family":"Tanaka","given":"Takuo"},{"family":"Chen","given":"Huei‐wen"},{"family":"Luo","given":"Yuan"},{"family":"Tsai","given":"Din"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1021/acsami.5c02901","URL":"https://doi.org/10.1021/acsami.5c02901","source":"openalex"},{"id":"oa:W7119140806","type":"article-journal","title":"Artificial intelligence and robotics in predictive maintenance: a comprehensive review","abstract":"The integration of artificial intelligence (AI) and robotics into predictive maintenance (PdM) systems has brought about a fundamental change in the operations of the industries since it has left behind the previous method of reactive and scheduled maintenance models in favor of proactive and data-driven models. The current systematic review of literature (2015-2025) is aimed at the development of PdM, in which AI techniques, machine learning, sensor technology, and the incorporation of robotics contribute to more efficient systems and address the difficulties in their implementation and implications for the future of industries. The findings show that the support vector machines and neural networks with supervised learning algorithms are very accurate in fault classification and the remaining useful life prediction. On the other hand, the methods of unsupervised learning can be applied in the detection of anomalies in cases where a limited quantity of labelled data exists. Examples of deep learning architectures that are more effective in processing more complex sensor data, as well as time-series patterns, include convolutional neural networks (CNNs) and long short-term memory (LSTM) networks. Moreover, sensor systems that are already linked to the IoT provide the ability to monitor in real time, and this significantly improves fault detection. The AI-based PdM systems in combination are highly rewarded with reduced downtime, longer equipment life, and enhanced maintenance scheduling. There are still, however, concerns about data quality, computation loads, and implementation cost that remain a major barrier to common usage. The future of AI should be on explainable AI, hybrid modelling techniques, and enhanced sensor technology to render AI scalable, interpretable, and more industry-applicable.","author":[{"family":"Azeta","given":"Joseph"},{"family":"Omeche","given":"Theodore"},{"family":"Daniyan","given":"Ilesanmi"},{"family":"Abiola","given":"Johnson"},{"family":"Daniyan","given":"Lanre"},{"family":"Phuluwa","given":"Humbulani"},{"family":"Muvunzi","given":"Rumbidzai"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3389/fmech.2025.1722114","URL":"https://doi.org/10.3389/fmech.2025.1722114","source":"openalex"},{"id":"oa:W4411059115","type":"article-journal","title":"Circular Material Flows, the Twin Transition of Manufacturing, and the Future of Labour","abstract":"In this chapter, we focus on the “twin transition” of manufacturing and the future of labour within the context of the circular economy and ocean plastics. Our point of departure is the sustainability challenges associated with ocean plastics, the fishing industry, and local coastal communities, and we first describe the existing challenges before presenting issues related to sustainability and circularity. We then discuss the related future opportunities for the labour market given that we are beginning to see the re-imagining and re-routing of material from linear to circular flows. We illustrate this through presenting the “microfactory” concept first developed under the Peniche Ocean Watch Initiative in Portugal, where the re-routing and re-purposing of discarded fishing nets is done on-site, in the local context, to be later re-imagined into new forms of use, in this case, recyclable furniture produced through large-scale additive manufacturing. We then return to our overarching discussion – how a turn to nature might also be a turn for the future of labour, and conclude by pinpointing how this turn offers an alternative way forward – one that by staying close to nature is inclusive, sustainable, and circular.","author":[{"family":"Teigland","given":"Robin"},{"family":"Wiberg","given":"Mikael"},{"family":"Borgen","given":"Jon"},{"family":"Freitas","given":"Mafalda"},{"family":"Landberg","given":"Johan"},{"family":"Rouhi","given":"Mohammad"},{"family":"Teigland","given":"Karoline"},{"family":"Wiest","given":"W"}],"issued":{"date-parts":[[2025]]},"DOI":"10.4324/9781003391333-17","URL":"https://doi.org/10.4324/9781003391333-17","source":"openalex"},{"id":"oa:W7128517873","type":"article-journal","title":"Vehicle lightweighting for carbon neutrality: decarbonization mechanisms, key processes and engineering applications","abstract":"Abstract The transport sector is under increasing pressure to contribute to national and global carbon-neutrality targets, and vehicle lightweighting has emerged as a core technical route for reducing energy use and CO₂ emissions. This review examines vehicle lightweighting from a decarbonization and life-cycle perspective, moving beyond traditional mass-reduction thinking toward integrated “lightweight decarbonization process systems”. First, the physical mechanisms by which mass reduction lowers tractive energy demand are analyzed for conventional and electrified powertrains, together with the secondary effects of powertrain downsizing and reduced parasitic losses. The role of life-cycle assessment (LCA) in quantifying trade-offs between higher embodied emissions of lightweight materials and use-phase energy savings is then discussed, including the influence of vehicle duty cycles, energy mixes and recycling rates. The review summarizes major technology routes for lightweighting body-in-white, chassis, powertrain and new energy vehicle subsystems, and highlights high-value opportunities in exhaust aftertreatment and thermal management systems. Key enabling processes—including low-carbon material preparation, advanced forming and casting, multi-material joining, surface engineering and digital design—are analyzed as the foundation of lightweighting-oriented decarbonization. Representative engineering applications and industrial case patterns are used to illustrate typical magnitudes of mass and CO₂ reduction and to extract lessons for integrating lightweight design with recycled and low-carbon materials. Finally, the paper identifies critical scientific questions, process and manufacturing bottlenecks, and cross-scale digitalization needs, and outlines promising directions for future “key technologies and applications” in vehicle lightweight decarbonization, with a particular focus on life-cycle CO₂ performance and real-world demonstrator platforms.","author":[{"family":"Wang","given":"Yi"},{"family":"Ma","given":"Qiang"},{"family":"Wang","given":"Tingyu"},{"family":"Zhang","given":"Bo"},{"family":"Wang","given":"Dongtao"},{"family":"Zhang","given":"Xianglong"},{"family":"博文","given":"長海"},{"family":"Yang","given":"Bowen"},{"family":"Ren","given":"Xu"},{"family":"Huang","given":"Jin"},{"family":"Zhang","given":"Yingjie"},{"family":"Chen","given":"Xiaoping"},{"family":"Xiong","given":"Wenpeng"},{"family":"Wang","given":"Bo"},{"family":"Li","given":"Yuan"},{"family":"Liu","given":"Xincong"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s44438-026-00023-5","URL":"https://doi.org/10.1007/s44438-026-00023-5","source":"openalex"},{"id":"oa:W7171916586","type":"article-journal","title":"A system-of-systems framework for Digital Twin enabled Real-Time Sustainability Reporting","abstract":"The convergence of Industry 5.0 imperatives, sustainability challenges, and compulsory reporting standards necessitate advances in manufacturing analysis. Digital Twins (DTs) enable real-time manufacturing monitoring and optimization, yet remain disconnected from corporate sustainability reporting (SR). This separation restricts leveraging operational data for mandatory disclosures and seeking operational improvements from sustainability reporting insights. DT research has predominantly focused on energy efficiency, with limited attention to broader environmental dimensions. We address this gap by developing a System-of-Systems framework integrating operational DTs with SR requirements. The gap, identified through literature analysis, is confirmed using expert interviews. We identify data mismatches between DT systems with process-level data and SR using periodic, facility-level data. Applying System-of-Systems theory, we develop a four-step framework (Mapping, Matching, Measuring, Modeling) enabling systematic translation between two independent systems. The framework demonstrates how manufacturing systems DTs can both supply and respond to SR outputs. Interview cited examples using a simplified manufacturing system and exemplified SR standard demonstrate applicability. The outcome is a structured approach for integrating DTs to support SR generation, and for SR insights to inform DT-enabled operational scenarios for performance enhancement. The contribution of the DT and SR framework is both to modeling advancement as well as management practice.","author":[{"family":"Luo","given":"Julia"},{"family":"Jorquera","given":"Juan"},{"family":"Ball","given":"Peter"},{"family":"Luo","given":"Yujia"},{"family":"Candia","given":"Juan"},{"family":"Ball","given":"Peter"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/00207543.2026.2703757","URL":"https://doi.org/10.1080/00207543.2026.2703757","source":"openalex"},{"id":"oa:W7131299133","type":"article-journal","title":"Evaluating the suitability of handwritten text recognition for industrial operations: a practical case study on acceptance sampling inspection workflow","abstract":"Abstract Handwritten Text Recognition (HTR) is an Artificial Intelligence (AI) technology designed to interpret and digitize handwritten text, enabling automated data extraction and reducing the reliance on manual processing. While HTR has been extensively developed in theory, leveraging advanced machine learning and pattern recognition models, its practical adoption remains uneven. Documented applications exist in fields such as historical document digitization, banking, and healthcare; however, its use in industrial and manufacturing contexts is still largely unexplored. This practical case study explores the use of HTR in an industrial setting by redesigning the operational execution of acceptance sampling activities in a pharmaceutical manufacturing company, in which handwritten records are traditionally used. The performance of the HTR software, which employs a patented hybrid stroke-based recognition method combining neural and statistical classifiers with structural matching, was tested and evaluated in terms of recognition accuracy and process efficiency to assess its potential to meet industrial standards. Preliminary findings indicate that while HTR can improve efficiency, limitations in recognition accuracy, and the need for human validation restrict full automation. Although promising, further advancements in recognition models and system adaptability are needed to ensure reliable and seamless integration into industrial workflows. Graphical Abstract","author":[{"family":"Martuscelli","given":"Luca"},{"family":"Fantozzi","given":"Italo"},{"family":"Mancusi","given":"Francesco"},{"family":"Schiraldi","given":"Massimiliano"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s12008-026-02513-9","URL":"https://doi.org/10.1007/s12008-026-02513-9","source":"openalex"},{"id":"oa:W4406974798","type":"article-journal","title":"Harnessing technological resources for effective growth hacking: A mixed-method framework using systematic literature review, content analysis, and multi-layer decision-Making","abstract":"The rise of Industry 4.0′s digital transformations has revolutionised organisational practices and significantly influenced analysis methods. One effective strategy affected by smart technologies is growth hacking. Growth hacking equips organisations with skills in product enhancement and customer acquisition tools, drastically enhancing efficiency and effectiveness. It strengthens organisations and accelerates growth through agile processes, enabling them to maintain competitive advantages. This study aims to identify and analyse technological resources and their impacts on growth hacking features to familiarise organisations and adopt agile strategies based on learning and creativity. Using a mixed-method approach, a systematic literature review (SLR) and content analysis (CA) uncover growth hacking and smart technology features. The Bayesian best-worst method (BBWM) assesses their importance, while a set-covering based mathematical model identifies key smart technologies that bolster growth hacking features. Accordingly, the growth hacking approach includes seven features, with innovation and creativity being the most important. Furthermore, it was revealed that Big Data and Artificial Intelligence are among the most important technologies impacting the growth hacking features. Interestingly, artificial intelligence has the potential to promote all features and increase the efficiency and speed of analysis in growth hacking.","author":[{"family":"Mahdiraji","given":"Hannan"},{"family":"Arabi","given":"Hojatallah"},{"family":"Duan","given":"Keru"},{"family":"Vrontis","given":"Demetris"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jbusres.2025.115180","URL":"https://doi.org/10.1016/j.jbusres.2025.115180","source":"openalex"},{"id":"oa:W4414332026","type":"article-journal","title":"3D Bioprinting and Artificial Intelligence for Tumor Microenvironment Modeling: A Scoping Review of Models, Methods, and Integration Pathways","abstract":"Recent advances in cancer research emphasize the development of physiologically relevant models to better understand tumor behavior and therapeutic responses. The tumor microenvironment (TME) plays a pivotal role in tumor progression, metastasis, and treatment resistance. Three-dimensional (3D) bioprinting offers unique capabilities for constructing complex in vitro tumor models that closely replicate the TME heterogeneity and interactions. These biomimetic models surpass the limitations of traditional 2D cultures and reduce the reliance on animal testing. This review aimed to systematically map current research on 3D bioprinting and artificial intelligence (AI) applications in modeling TME across selected cancer types. The review was structured into three thematic domains: 3D bioprinting of TME models for selected cancer types, AI applications in 3D bioprinting regardless of clinical focus, and integration of AI with 3D bioprinting specifically for TME modeling. A comprehensive literature search was conducted in PubMed, covering publications from January 2020 to June 2025. The review was conducted in accordance with PRISMA-ScR guidelines and focused on peer-reviewed original research articles published in English. Included cancer types were colorectal cancer, oral cancer, breast cancer, and glioma. In total, 63 articles were screened for TME-specific 3D bioprinting, with 44 included. For AI applications in 3D bioprinting irrespective of cancer type, 67 records were identified and 14 met the inclusion criteria. Only one study explicitly integrated AI and 3D bioprinting for TME modeling, highlighting a critical research gap. These findings are illustrated in the PRISMA flowcharts for clarity. Despite growing interest in both 3D bioprinting and AI, their combined application for modeling of the tumor microenvironment remains limited. The reviewed literature demonstrates significant progress in bioink development, process optimization, and quality control through AI methods. However, further interdisciplinary research is necessary to realize the potential of AI in enhancing TME modeling for oncology applications.","author":[{"family":"Piotrowska","given":"Urszula"},{"family":"Tsoi","given":"James"},{"family":"Singh","given":"Pradeep"},{"family":"Banerjee","given":"Avijit"},{"family":"Sobczak","given":"Marcin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1021/acs.molpharmaceut.5c01062","URL":"https://doi.org/10.1021/acs.molpharmaceut.5c01062","source":"openalex"},{"id":"oa:W7126029320","type":"article-journal","title":"Multistage Static and Dynamic Optimization Framework for Composite Laminates in Lightweight Urban Rail Vehicle Car Bodies","abstract":"This paper presents a robust multistage optimization framework for the integration of composite laminates into the car body shell of a low-floor light rail vehicle (LRV). While structural design in low-floor vehicles is typically complex, this methodology successfully balances both static and dynamic requirements through a sequential optimization process. Developed in strict accordance with reference European standards, the methodology addresses the structural challenges inherent in low-floor architectures, where complex load paths and redistributed equipment masses require targeted reinforcement. The proposed approach sequentially addresses dynamic and static requirements through a structural optimization process. Two distinct 10-ply laminate configurations, one symmetric and one asymmetric, were investigated. The results demonstrate that the multistage optimization successfully converged to a highly mass-efficient solution, achieving a 66% reduction in laminate thickness compared to the baseline design. This significant result was accomplished while maintaining full regulatory compliance; the failure index increased by approximately 22.5% and 23.3% for the two composite laminate configurations, respectively, effectively maximizing material utilization. A key finding of this study is the preservation of structural dynamic integrity; the fundamental natural frequency was maintained at approximately 16 Hz, with a high correlation across the first ten vibration modes, confirming that the global dynamic behaviour remains unaffected. These observations provide critical insights into the synergy between hybridization and structural constraints, suggesting a systematic pathway for designers to achieve an optimal trade-off between manufacturing costs, weight reduction, and performance in advanced urban transit platforms.","author":[{"family":"Cascino","given":"Alessio"},{"family":"Distaso","given":"Francesco"},{"family":"Meli","given":"Enrico"},{"family":"Rindi","given":"Andrea"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/ma19030531","URL":"https://doi.org/10.3390/ma19030531","source":"openalex"},{"id":"oa:W7115940588","type":"article-journal","title":"Evolution and research trends in virtual reality and augmented reality technologies for the architecture, engineering, and construction (AEC) industry: a systematic review and science mapping approach","abstract":"This systematic review and bibliometric analysis examine the evolution and research trends of Virtual Reality (VR) and Augmented Reality (AR) technologies within the Architecture, Engineering, and Construction (AEC) industry to identify key research themes, application domains, and future directions. A comprehensive literature search was conducted using both Scopus and Web of Science databases covering publications from 2015 to 2025 to ensure robust multi-database validation. After applying engineering subject area filters, the Scopus search yielded 1,301 articles while Web of Science returned 898 articles. The methodology combined quantitative bibliometric analysis using Bibliometrix software with qualitative thematic analysis of the most-cited and relevant studies following PRISMA guidelines. Performance analysis, science mapping, and co-occurrence analysis were employed to identify research clusters and trends across both databases. Cross-database validation confirmed convergent patterns in publication growth, thematic structure, and collaboration networks, with both databases demonstrating exponential growth and similar dominant research themes centered on digital twins, virtual reality applications, and BIM integration. This study provides a comprehensive quantitative mapping of VR/AR research in the AEC industry with multi-database validation, revealing the intellectual structure and research fronts. The integrated approach combining bibliometric analysis with thematic synthesis offers insights for researchers and practitioners to understand current applications, identify research gaps, and guide future technology adoption strategies.","author":[{"family":"Sornoza-Parrales","given":"Diego"},{"family":"Vera","given":"Günther"},{"family":"Poveda","given":"María"},{"family":"Macías-Parrales","given":"Tania"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/frvir.2025.1725875","URL":"https://doi.org/10.3389/frvir.2025.1725875","source":"openalex"},{"id":"oa:W7156079180","type":"article-journal","title":"Quality Assurance in Decentralized Manufacturing: A Review of Validation Frameworks for 3D-Printed Personalized Medicines","abstract":"Background The pharmaceutical industry is in a paradigm shift in which the mass-production model based on one-size-fits-all is being replaced by the patient-centric model that is made possible by three-dimensional printing (3DP) and decentralized manufacturing (DM). Although 3DP enables the personalization of dosage form as never before, the translation of the technology into clinical practice is complicated by the complicated quality assurance (QA) and validation barriers. Purpose: This review critically synthesizes the existing validation frameworks of 3DP personalized medicines with special emphasis on the combination of Process Analytical Technology (PAT), Digital Twins, and the recently implemented UK MHRA 2025 regulatory framework. Methodology: Scopus-indexed literature (20192026) was searched in a PRISMA-compliant systematic search that focused on point-of-care (POC) manufacturing, real-time release testing (RTRT), and data integrity. Core Mechanisms: We consider technical modalities, such as Fused Deposition Modeling (FDM), Semi-Solid Extrusion (SSE), and Selective Laser Sintering (SLS), their respective Critical Process Parameters (CPPs) and Critical Quality Attributes (CQAs). Findings: The review identifies the Hub-and-Spoke model as the most feasible structure of decentralized QA with centralized hubs that address the issue of integrity of the pharma-ink and decentralized spokes that address the issue of process validation. In-line Near-Infrared (NIR) and Raman spectroscopy technologies that enable the real time release of doses are accurate and non-destructive (R 2 = 0.98) and allow real time verification of doses. Moreover, the Digital Twin technology improves three-stage process validation lifecycle, providing predictive maintenance and proactive quality management. Conclusion: To attain sustainable clinical implementation of the 3DP, a radical change toward Quality-by-Design (QbD) and a powerful digital infrastructure is required. In the coming 2026 and beyond, we suggest a roadmap to standardize decentralized validation to achieve the best safety and efficacy of personalized medicines.","author":[{"family":"Bikram","given":"Joardar"},{"family":"Santu","given":"Karmakar"},{"family":"Sucheta","given":"Dalai"},{"family":"Shristi","given":"Kundu"},{"family":"Poulomi","given":"Chatterjee"},{"family":"Ritam","given":"Chatterjee"},{"family":"Sourav","given":"Rudra"},{"family":"Anisha","given":"Gazi"},{"family":"Shirsha","given":"Majumdar"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.19824633","URL":"https://doi.org/10.5281/zenodo.19824633","source":"openalex"},{"id":"oa:W4412907259","type":"article-journal","title":"Additive electronics manufacturing via droplet jetting technologies: materials, methods, applications, and opportunities","abstract":"Droplet jetting technologies offer a versatile, digital platform to fabricate functional devices from nanomaterial building blocks. Inkjet, aerosol jet, and electrohydrodynamic jet printing constitute three distinct technologies for precise patterning of functional materials in an additive, digital, and noncontact manner. While the unique physical mechanism of each technology endows it with specific advantages and disadvantages, commonalities in materials compatibility, patterning capabilities, and application domains motivate a holistic assessment of nanomaterial integration with these methods. This report will highlight progress across ink formulation, process design, and application development from recent years, with an emphasis on emerging materials and practical applications in this evolving field of research. This includes an overview of the three printing technologies, a survey of ink formulation and printing efforts across conductive, insulating, and semiconducting materials, an examination of compelling application demonstrations in electronics, sensing, and energy, as well as discussion of key emerging themes related to artificial intelligence, multimaterial printing, and nonplanar patterning.","author":[{"family":"Secor","given":"Ethan"},{"family":"Yeboah","given":"Daniel"},{"family":"Gamba","given":"Livio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1039/d5nr02110c","URL":"https://doi.org/10.1039/d5nr02110c","source":"openalex"},{"id":"oa:W4407441752","type":"article-journal","title":"Data-driven additive manufacturing with concrete: Enhancing in-line sensory data with domain knowledge, Part I: Geometry","abstract":"First-time-right manufacturing is an important step toward unlocking the full potential of digital fabrication with concrete (DFC), which can be advanced through data-driven approaches. Non-invasive in-line sensors can collect vast amounts of measurements during the manufacturing process. However, knowledge-driven feature engineering (KDFE) strategies are necessary to extract meaningful information, referred to as features, from the raw sensory data. This contribution, part of a two-part study, presents an approach to integrating KDFE with various in-line sensors in a 3D concrete printing (3DCP) facility, focusing on 2D laser scanning techniques to capture the ‘as-printed’ layer geometry during production. The geometric profiles are translated into features that quantify layer dimensions, cross-sectional area, and surface texture, reducing data complexity while enhancing relevancy. Real-world data is utilized to demonstrate the approach. A companion paper extends the methodology to other sensors, including those monitoring moisture and temperature, further advancing process monitoring in 3DCP. • In-line sensors enable autonomous quality assessment in 3DCP systems. • Knowledge-driven feature engineering reduces complexity in high-dimensional data. • Laser scanning techniques allow for detailed layer and surface geometry analysis. • The computation of geometric features is demonstrated using real-world data.","author":[{"family":"Versteege","given":"Jelle"},{"family":"Wolfs","given":"Rob"},{"family":"Salet","given":"TAM"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.autcon.2025.106020","URL":"https://doi.org/10.1016/j.autcon.2025.106020","source":"openalex"},{"id":"oa:W4410531477","type":"article-journal","title":"Performance degradation assessment method for linear motor feed systems driven by digital twins","abstract":"To address the challenges of missing degradation samples and the low accuracy of traditional degradation assessment methods in linear motor feeding systems, and considering the advantages of Digital Twin technology in complex equipment status evaluation and performance prediction, this study introduces Digital Twin into the performance degradation assessment of the linear motor feeding system. To resolve the issue of missing degradation samples, a digital integrated model consisting of the mechanical subsystem, electrical subsystem, and control subsystem is established, based on an analysis of the multi-field coupling mechanisms (mechanical, electrical, and magnetic) of the linear motor feeding system. Normal operating conditions and demagnetization degradation conditions are designed, and the motor output characteristics under multiple conditions are simulated and analyzed. A current simulation dataset for both normal and demagnetization degradation conditions is constructed.In response to the challenges posed by the temporal dependence of operational data and the difficulty of identifying degradation states, and leveraging the superior data transformation capabilities of Gramian Angular Field (GAF), which effectively preserves temporal information, this study proposes a performance degradation assessment model combining GAF encoding with the AlexNet convolutional neural network. The model first converts one-dimensional time-series data into two-dimensional images using GAF encoding, and then utilizes the image recognition capabilities of AlexNet to assess the degradation state of the linear motor feeding system. This approach enables the evaluation of irreversible demagnetization degradation levels, achieving an accuracy of 98.3%.Furthermore, compared to the traditional methods of PNN, GRNN, and LS-SVM, the proposed method shows improvements of 10.3%, 4.9%, and 15.2% in the AUC index, respectively. The average accuracy is improved by 10.5%, 5.3%, and 14.7%, significantly enhancing the evaluation accuracy. This method effectively resolves the issue of insufficient real degradation samples and provides a powerful tool for predictive maintenance and performance monitoring in industrial environments.","author":[{"family":"Yang","given":"Zeqing"},{"family":"Yao","given":"Yiding"},{"family":"Cui","given":"Wei"},{"family":"Chen","given":"Yingshu"},{"family":"Liu","given":"Beibei"},{"family":"Jin","given":"Yi"},{"family":"Zhang","given":"Yanrui"},{"family":"Zhao","given":"Hongwei"},{"family":"Zhang","given":"Guofeng"},{"family":"Yi","given":"Wei"},{"family":"Zhang","given":"Zonghua"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-02347-7","URL":"https://doi.org/10.1038/s41598-025-02347-7","source":"europepmc"},{"id":"oa:W4412675172","type":"article-journal","title":"Measuring digital transformation in high-end equipment manufacturing: an I-P-O model-based approach","abstract":"The digital transformation of high-end equipment manufacturing enterprises serves as a critical driver for upgrading the manufacturing value chain and achieving high-quality development. This paper constructs an evaluation index system for assessing the digital transformation level of high-end equipment manufacturing enterprises based on the Input-Process-Output (I-P-O) theoretical model. It employs the VHSD-EM model to evaluate the digital transformation levels of 124 such enterprises from 2016 to 2021. Additionally, the barrier model is utilized to analyze the primary obstacles affecting their digital transformation. The findings indicate that (1) overall, the digital transformation levels of high-end equipment manufacturing enterprises exhibited an upward trend from 2016 to 2021, though the growth rate was slow, with relatively few enterprises achieving outstanding transformation levels. Notable differences in scores and changes were observed across five key fields. (2) An indicator perspective reveals that the primary obstacles from 2016 to 2021 are concentrated within the top five, with most showing a slight upward trend. Conversely, from a criteria perspective, the challenges primarily involve enterprise awareness of digital transformation and the process itself, demonstrating a slight downward trend.","author":[{"family":"Chen","given":"Yinzhong"},{"family":"Huang","given":"Jingfeng"},{"family":"Li","given":"Yi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41598-025-11398-9","URL":"https://doi.org/10.1038/s41598-025-11398-9","source":"openalex"},{"id":"oa:W4414016570","type":"article-journal","title":"Additive manufacturing of Inconel 718: A review on microstructures and mechanical properties of DED-LB-processed samples","abstract":"Abstract Additive manufacturing (AM) is a process in which parts are manufactured in a layer-by-layer fashion. Several AM methods have been successfully developed to produce complex geometries and process different materials. Regarding metallic alloys with aerospace applications, directed energy deposition (DED) stands out due to its high deposition rate and superior build quality. Inconel 718 (IN718) is a precipitation-hardened nickel-based superalloy renowned for its exceptional mechanical properties and resistance to oxidation and corrosion at elevated temperatures, up to 650 °C. The alloy derives its strength primarily from the precipitation of γ′ (Ni 3 (Al, Ti)) and γ″ (Ni 3 Nb), with additional strengthening from solid solution elements and carbides. Due to its thermal stability, fatigue resistance, and creep performance, IN718 is widely used in aerospace engines, gas turbines, and petrochemical equipment. This work presents a review of IN718-processed via Laser-based DED, exploring recent studies on microstructural evolution, mechanical properties, and post-processing treatments. Graphical abstract","author":[{"family":"Cavalcante","given":"Thiago"},{"family":"Mariani","given":"Fábio"},{"family":"Ávila","given":"Julián"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1557/s43578-025-01663-y","URL":"https://doi.org/10.1557/s43578-025-01663-y","source":"openalex"},{"id":"oa:W7129237350","type":"article-journal","title":"AI-powered open-source infrastructure for accelerating materials discovery and advanced manufacturing","abstract":"Abstract Recent advances in artificial intelligence (AI) offer significant opportunities to drive industrial transformation by addressing growing societal demands for products, techno-economic efficiency, and reduced carbon footprints. This review presents a structured framework for building transparent, scalable, and sustainable AI-driven infrastructures spanning conceptualization to commercialization for materials discovery and advanced manufacturing. The framework traces the evolution of materials development from empirical approaches toward integrated AI-enabled platforms, emphasizing open-source tools that unify data acquisition, modeling, simulation, and deployment to democratize access, foster collaboration, and enhance reproducibility. Key enabling components include self-driving laboratories for real-time optimization, advanced computational approaches for high-fidelity data, and blockchain-based mechanisms for secure data sharing, provenance, and supply-chain traceability. The review further discusses the importance of machine learning for materials property prediction, synthesis and process optimization, together with scalable cloud–edge architectures that improve efficiency and reduce latency. Emphasis is placed on lifecycle-aware design, techno-economic analysis, and ethical AI principles to align industrial development with global sustainability goals.","author":[{"family":"Salas","given":"Mariangeles"},{"family":"Singh","given":"Anand"},{"family":"Pignataro","given":"Carlos"},{"family":"Pal","given":"Lokendra"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s43246-026-01105-0","URL":"https://doi.org/10.1038/s43246-026-01105-0","source":"openalex"},{"id":"oa:W4407590041","type":"article-journal","title":"Remaining useful life prediction methods of equipment components based on deep learning for sustainable manufacturing: a literature review","abstract":"Abstract The operational reliability of large mechanical equipment is typically influenced by the functional effectiveness of key components. Consequently, prompt repair before their failure is necessary to ensure the dependability of mechanical equipment. The prognostic and health management (PHM) technology could track the system’s health state and timely detect faults. Therefore, the remaining useful life (RUL) prediction as one of the key components of PHM is rather important. Accurate RUL prediction results could be the data support for condition-based equipment maintenance plans. Also, it could increase the dependability and safety of mechanical equipment while reducing the loss of human and financial resources and meet the requirements of sustainable manufacturing in the Industry 4.0 era. However, with the widespread use of deep learning in the field of intelligent manufacturing, there is a lack of review on RUL prediction based on deep learning. In this paper, different deep learning-based RUL prediction methods for mechanical components are summarized and classified, along with their pros and cons. Then, the case study on the C-MAPSS dataset is mainly conducted and different methods are compared. And finally, the difficulties and future directions of the RUL prediction in practical scenarios are discussed.","author":[{"family":"Pan","given":"Yuwen"},{"family":"Kang","given":"Shijia"},{"family":"Kong","given":"Linggang"},{"family":"Wu","given":"Jiaju"},{"family":"Yang","given":"Yonghui"},{"family":"Zuo","given":"Hongfu"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1017/s0890060424000271","URL":"https://doi.org/10.1017/s0890060424000271","source":"openalex"},{"id":"oa:W4415740881","type":"article-journal","title":"Application of Artificial Intelligence in Electronics and Semiconductor Industries","abstract":"The global semiconductor industry is expected to reach $650 billion by 2024, spurred by the adoption of 5th Generation (5G), artificial intelligence (AI), and Internet of Things (IoT) technologies, making the electronics and semiconductor sector a key component of technological innovation worldwide. With 13% of the global market for semiconductor assembly, packaging, and testing, Malaysia is a key player. The electrical and electronics (E&E) sector contributes 5.8% of the nation’s GDP and 40% of its exports. By improving fault detection accuracy to over 90% and lowering maintenance costs by up to 25%, the incorporation of AI into semiconductor production has revolutionized processes. The $5.3 billion National Semiconductor Strategy and Malaysia’s Industry 4.0 goals align with AI-powered solutions that maximize productivity, anticipate equipment faults, and encourage sustainable practices. The review focuses on the integration and effectiveness of AI in the electronics and semiconductor industry including the utilization of AI in quality control and inspection, and inventory management. Emphasizing its impact on productivity, innovation, and global competitiveness particularly for fault detection, predictive maintenance, sustainable manufacturing practices, productivity enhancement, and economic contribution of semiconductors. The challenges of high energy consumption associated with AI infrastructure are also discussed. However, it is realized that the application of AI has greatly increased productivity, quality, and efficiency by reducing waste and managing to build robust and adaptable manufacturing ecosystems. Future advancements in AI, including digital twins and robotics, could create strong and flexible manufacturing systems, leading to a more innovative and resilient semiconductor industry.","author":[{"family":"Hafiz","given":"Muhammad"},{"family":"Azmi","given":"Eisrul"},{"family":"Azlie","given":"Muhammad"},{"family":"Zaki","given":"MJ"},{"family":"Mazilan","given":"Muhammad"},{"family":"Mazuki","given":"Muhammad"},{"family":"Nor","given":"Muhammad"},{"family":"Ghani","given":"Jaharah"},{"family":"Rahmat","given":"Mohd"},{"family":"Khamis","given":"Nor"}],"issued":{"date-parts":[[2025]]},"DOI":"10.17576/jkukm-2025-37(7)-11","URL":"https://doi.org/10.17576/jkukm-2025-37(7)-11","source":"openalex"},{"id":"oa:W4411738013","type":"article-journal","title":"Research Progress and Application Scenarios of Wire + Arc Additive Manufacturing: From Process Control to Performance Evaluation","abstract":"In recent years, with the innovation and continuous development of additive manufacturing technology, research on wire arc additive manufacturing technology (WAAM) has become increasingly common and in-depth in the chemical industry, mold manufacturing, and other fields. Therefore, it has attracted the attention of many universities, research institutes, and aerospace industries, conducted in-depth research on WAAM technology, and achieved certain research results. This paper briefly summarizes the current research status of arc additive manufacturing technology and summarizes the application status of WAAM technology in product development, personalized customization, traditional process replacement, \"material-structure-function\" integration, mold repair, etc. WAAM technology has huge development potential and good application prospects. In the future, arc additive manufacturing will develop in the direction of intelligence and high precision.","author":[{"family":"Guo","given":"Chun"},{"family":"Lin","given":"Qingcheng"},{"family":"Hu","given":"Ruizhang"},{"family":"Wu","given":"Suisong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/mi16070749","URL":"https://doi.org/10.3390/mi16070749","source":"openalex"},{"id":"oa:W4409590847","type":"article-journal","title":"Machine vision in manufacturing SMEs: a review","abstract":"Abstract Automating manufacturing tasks, such as quality control, fault detection, part classification, and inventory management with machine vision systems can significantly improve process efficiency, accuracy, and productivity. As a result, the machine vision technology market is expanding, largely driven by its applications in manufacturing across both hardware and software sectors. Nevertheless, small- and medium-sized enterprises (SMEs) face distinct challenges in the implementation of such systems due to their human, technical, and organizational constraints. An overview of the current state of research and practical insights is essential to address these constraints and guide future developments. Although some surveys and interviews have been conducted, no comprehensive review outlines scientific literature on research methods and initiatives related to the characteristics and challenges of adopting machine vision systems in industrial SMEs. Therefore, we present a systematic literature review to identify applications, challenges and proposed approaches for machine vision and its adoption in industrial SMEs, analyzing 770 articles. The review highlights quality control as the prominent application, while primary challenges for SMEs include limited investment capacity, labor and expertise shortages, and high-variety, low-volume production, which often leads to insufficient data for training algorithms. Furthermore, the review identifies approaches involving low-cost hardware, open-source software, and intuitive-to-use systems as potential solutions to these challenges. Although many articles contribute to highly specific problems of SMEs, we identified a lack of broader applicable interdisciplinary approaches to integrate machine vision. This article outlines challenges and initiatives for adopting machine vision across different applications to enhance value generation for industrial SMEs facing specific challenges. Future research can leverage our findings to develop industrial solutions or explore new research directions in this domain.","author":[{"family":"Werheid","given":"Jonas"},{"family":"Behnen","given":"Hannes"},{"family":"Woltersmann","given":"Jan"},{"family":"He","given":"Shengjie"},{"family":"Hamann","given":"Tobias"},{"family":"Abdelrazeq","given":"Anas"},{"family":"Schmitt","given":"Robert"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s42452-025-06923-4","URL":"https://doi.org/10.1007/s42452-025-06923-4","source":"openalex"},{"id":"oa:W4407220306","type":"article-journal","title":"Ontology‐Based Digital Infrastructure for Data‐Driven Glass Development","abstract":"The development of new glasses is often hampered by inefficient trial‐and‐error approaches. The traditional glass manufacturing process is not only time‐consuming, but also difficult to reproduce with inevitable variations in process parameters. These challenges are addressed by implementing an ontology‐based digital infrastructure coupled with a robotic melting system. This system facilitates high‐throughput glass synthesis and ensures the collection of consistent process data. In addition, the digital infrastructure includes machine learning models for predicting glass properties and a tool for extracting patent information. Current glass databases have significant gaps in the relationships between compositions, process parameters, and properties due to inconsistent studies and nonconforming units. In addition, process parameters are often omitted, and even original literature references provide limited information. By continuously expanding the database with consistent, high‐quality data, it is aimed to fill these gaps and accelerate the glass development process.","author":[{"family":"Chen","given":"Ya‐fan"},{"family":"Arendt","given":"Felix"},{"family":"Bornhöft","given":"Hansjörg"},{"family":"Camargo","given":"Andréa"},{"family":"Deubener","given":"Joachim"},{"family":"Diegeler","given":"Andreas"},{"family":"Gogula","given":"Shravya"},{"family":"Jaimes","given":"Altair"},{"family":"Kempf","given":"Sebastian"},{"family":"Kilo","given":"Martin"},{"family":"Limbach","given":"René"},{"family":"Müller","given":"Ralf"},{"family":"Niebergall","given":"Rick"},{"family":"Pan","given":"Zhong"},{"family":"Puppe","given":"Frank"},{"family":"Reinsch","given":"Stefan"},{"family":"Schottner","given":"G"},{"family":"Stier","given":"Simon"},{"family":"Waurischk","given":"Tina"},{"family":"Wondraczek","given":"Lothar"},{"family":"Sierka","given":"Marek"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/adem.202401560","URL":"https://doi.org/10.1002/adem.202401560","source":"openalex"},{"id":"oa:W4407450075","type":"article-journal","title":"Modeling and Digital Twins: Insights and Strategies for Software Engineers","abstract":"Software modeling and digital twins are transforming the way software engineers design, operate, and maintain complex systems. In this column, we highlight cutting-edge research presented at the ACM/IEEE 27th International Conference on Model-Driven Engineering Languages and Systems (MODELS 2024) and the 1st International Conference on Engineering Digital Twins (EDTconf 2024). The selected papers tackle critical challenges in improving system understanding, enhancing stakeholder communication, streamlining design and development processes, optimizing lifecycles, and enabling seamless integration of complex systems.","author":[{"family":"Abrahão","given":"Silvia"},{"family":"Staron","given":"Miroslaw"},{"family":"Michael","given":"Judith"},{"family":"Combemale","given":"Benoît"},{"family":"Chećhik","given":"Marsha"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/ms.2024.3510892","URL":"https://doi.org/10.1109/ms.2024.3510892","source":"openalex"},{"id":"oa:W4411962499","type":"article-journal","title":"Sustainable in-space manufacturing by upcycling metal space debris via a vertically integrated processing paradigm","abstract":"This study presents a novel approach to upcycling metallic space debris into functional components. This is the first work to investigate the feasibility of using additive friction stir deposition (AFSD), a solid-state additive manufacturing (SSAM) technique, for in-space upcycling of space debris made into feedstock using continuous casting. In upcycling applications, AFSD combines the advantages of additive manufacturing of hard-to-weld metals and post-processing to produce near-net shape components. Simulated space debris, composed of AA6061, was fabricated into rods using continuous casting to create feedstock for twin rod AFSD (TR-AFSD). The resulting TR-AFSD deposit showed a reduction of many of the casting defects inherent in the feedstock material and exhibited a microstructure corresponding to improved material properties. These findings highlight the potential of AFSD for upcycling space debris through microstructure refinement and homogenization, enabling in-situ fabrication of high-performance components for sustainable space exploration.","author":[{"family":"Baker","given":"Charlye"},{"family":"Zhu","given":"Ning"},{"family":"Ravindranath","given":"Pruthul"},{"family":"Pawelski","given":"Joseph"},{"family":"Ritter","given":"Cole"},{"family":"Swinney","given":"Rachel"},{"family":"Matthews","given":"Walter"},{"family":"Fleck","given":"Trevor"},{"family":"Jordon","given":"JB"},{"family":"Allison","given":"Paul"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s44334-025-00042-z","URL":"https://doi.org/10.1038/s44334-025-00042-z","source":"openalex"},{"id":"oa:W4414343593","type":"article-journal","title":"Transforming B2B platforms through interconnected digital twins: Enhancing situation awareness for decision-making","abstract":"Business-to-business (B2B) platforms hold transformative potential for manufacturing by enabling firms to collaborate, share data, and coordinate decisions across interconnected cyber-physical networks. However, many firms struggle to fully leverage these platforms due to bounded rationality, as decision-makers face difficulties in processing fragmented, heterogeneous, and real-time data streams. Interconnected Digital Twins (IDTs) offer a promising technological response to this challenge. By integrating data from multiple sources and simulating dynamic manufacturing processes across organizational boundaries, IDTs create shared, real-time representations of operations that support decision-making in complex B2B ecosystems. Grounded in Endsley's Situation Awareness Theory, this study examines how IDTs support perception, comprehension, and projection in cross-organizational decision-making. We conducted an exploratory qualitative case study of a leading automotive manufacturer, drawing on ethnographic access to its IDT implementation. Our findings show that IDTs enhance situation awareness and support cross-organizational decision-making by consolidating fragmented data and reducing cognitive overload through simulation. The study contributes to B2B platform ecosystem research by identifying IDTs as a technological enabler of digital transformation and demonstrating their role in enhancing situation awareness in industrial ecosystems. • IDTs are a key B2B platform innovation for digital transformation in manufacturing. • IDTs enhance situation awareness at a digital scale on B2B platforms. • IDTs reduce cognitive overload across B2B platform ecosystems. • IDTs enable shared situation awareness across organizational boundaries. • IDTs reposition B2B platforms as intelligence-enhancing decision support systems.","author":[{"family":"Schink","given":"Alexander"},{"family":"Gutmann","given":"Tobias"},{"family":"Brenk","given":"Sebastian"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.technovation.2025.103368","URL":"https://doi.org/10.1016/j.technovation.2025.103368","source":"openalex"},{"id":"oa:W4406899125","type":"article-journal","title":"Multi-objective optimization for layout planning of matrix manufacturing system","abstract":"Abstract The automotive industry is experiencing rapid changes due to the rise of the Industry 4.0 manufacturing paradigm, which requires strategic implementation of advanced manufacturing systems to meet diverse customer needs. The Matrix Manufacturing System, characterized by modular facilities and autonomous mobile robots, offers greater flexibility compared to traditional dedicated production systems. This paper conducts a multi-objective optimization of facility layout planning within the matrix manufacturing system to enhance efficiency and responsiveness to market volatility. To solve the optimization problem, three heuristic algorithms—Simulated Annealing, Particle Swarm Optimization, and Non-dominated Sorting Genetic Algorithm-II are employed and their performance is compared. For the comparative analysis, frequency maps are used, visualizing the optimization processes and outcomes between metaheuristic algorithms. The framework with methodologies presented in this report is expected to improve productivity and flexibility of a matrix manufacturing system in the automotive industry.","author":[{"family":"Park","given":"JS"},{"family":"Lee","given":"Chang‐ha"},{"family":"Oh","given":"Seog‐chan"},{"family":"Noh","given":"Sang"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s40684-025-00696-2","URL":"https://doi.org/10.1007/s40684-025-00696-2","source":"openalex"},{"id":"oa:W4414596944","type":"article-journal","title":"Physics-informed machine learning-based real-time long-horizon temperature fields prediction in metallic additive manufacturing","abstract":"Real-time long-horizon temperature prediction in wire arc additive manufacturing is critical for process control and quality assurance. However, finite element methods are computationally expensive, and the existing data-driven models suffer from error accumulation and poor adaptability. Here we propose a physics-informed geometric recurrent neural network that integrates geometric characteristics and physical constraints, captures spatiotemporal characteristics via convolutional long short-term memory cells, and enforces physical consistency through hard-encoding initial/boundary conditions and physics-informed loss function. The model can predict the temperature field for future 1.25 s based on current 1.25 s data, and has also been evaluated for more long-horizon predictions. Transfer learning was used to enhance the model’s efficiency in practical applications. Results demonstrate that the proposed model achieves 4.5−13.9% maximum prediction error in simulations and experimental data. Including geometric characteristics and physical information reduces maximum error by about 1%, while the integrated model lowers it by 4%. Furthermore, transfer learning reduces the training time by approximately 50% while achieving the same loss level. Real-time long-horizon temperature prediction in metal additive manufacturing is critical for process control and quality assurance. Mingxuan Tian and colleagues propose a physics-informed machine learning model to predict temperature field for future 1.25 s.","author":[{"family":"Tian","given":"Mingxuan"},{"family":"Mu","given":"Haochen"},{"family":"Liu","given":"Tao"},{"family":"Li","given":"Mengjiao"},{"family":"Ding","given":"Donghong"},{"family":"Zhao","given":"Jianping"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s44172-025-00501-7","URL":"https://doi.org/10.1038/s44172-025-00501-7","source":"openalex"},{"id":"oa:W4410369686","type":"article-journal","title":"Strategic Framework for Additive Manufacturing with Smart Polymer Composites: A Pathway to Net-Zero Manufacturing","abstract":"Despite manufacturing firms recognizing the potential benefits of polymer-based smart materials (PBSM) in additive manufacturing (AM), their large-scale integration remains limited. As manufacturing firms strive toward net-zero emissions (NZE) and sustainable manufacturing, integrating PBSM into AM could be pivotal for manufacturing firms striving to achieve NZE and more sustainable production. In this regard, this study uses a mixed-method approach: a systematic literature review (SLR) to address the current trends and critical challenges associated with the \"development, processing, and scalability\" of PBSM adoption for AM. Further, the study analyzes 100 responses from Indian manufacturing firms, employing exploratory factor analysis (EFA) to develop a framework. This framework is further validated by determining the priority order of challenges using the Combined Compromise Solution (CoCoSo) through a case study. The outcome highlights that end-of-life management and lack of standardization are the most critical challenges for manufacturing firms, restricting the adoption of PBSM for AM. This research provides valuable insights for industry professionals and academia, guiding a strategic roadmap toward net-zero manufacturing. With this transformation, industries can align with global net-zero targets and contribute to India's net-zero economy (NZE) goal by 2070.","author":[{"family":"Yadav","given":"Alok"},{"family":"Garg","given":"Rajiv"},{"family":"Sachdeva","given":"Anish"},{"family":"Qureshi","given":"Karishma"},{"family":"Qureshi","given":"MN"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/polym17101336","URL":"https://doi.org/10.3390/polym17101336","source":"openalex"},{"id":"oa:W7124850969","type":"article-journal","title":"Advances, challenges and prospective research when geographical information science meets digital twin","abstract":"Digital twins, originating from industrial engineering, demonstrate considerable potential in the field of Geographical Information Science (GIS) in recent years, nevertheless, the absence of a unified research paradigm leads to significant disparities in geographical twinning frameworks, twinning technologies of geographical objects, data models of twinning objects, and visualisation in twin space as well. These discrepancies have hindered the development of geospatial digital twins. To address this issue, this study carries out a comprehensive review of 154 articles related to digital twins and GIS, published between 2019 and 2024, and describes their advances, potential challenges and future directions. The key insights are: 1) Spatiotemporal data models possess limited capacity for managing the virtual–real alignment of all geographical entities; therefore, an integrated and intelligent data model is required to replicate all geographical entities and realise virtual–real interactions within geospatial digital twins; 2) Twinning technologies that fail to consider dynamic behaviours constrain geographical scenario simulations; consequently, a geographical process twinning technology is expected to become a prominent research; 3) A collaborative visualisation scheme offers an optimal solution for addressing multimodal data, multi-user operations, and scenario simulations; 4) An integration strategy combining geospatial twin frameworks with geospatial artificial intelligence (GeoAI) models will become another prospective research. These findings contribute to understand the foundational theories and key technologies of geospatial digital twins, further promote its development.","author":[{"family":"Xue","given":"Cunjin"},{"family":"Li","given":"LC"},{"family":"Liu","given":"Jian"},{"family":"Su","given":"Fenzhen"},{"family":"Wu","given":"Wenzhou"},{"family":"Ma","given":"Ziyue"},{"family":"Xiang","given":"Zheng"},{"family":"Wu","given":"Shiyu"},{"family":"Qin","given":"Qunce"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/27525783.2025.2610851","URL":"https://doi.org/10.1080/27525783.2025.2610851","source":"openalex"},{"id":"oa:W4415502865","type":"article-journal","title":"Industry 5.0 Digital DNA: A Genetic Code of Human-Centric Smart Manufacturing","abstract":"This study proposes and empirically assesses a bio-inspired conceptual framework, termed Digital DNA, for modeling Industry 5.0 transformation as a complementary extension of established Industry 4.0 principles with an explicit focus on human-centricity, sustainability, and resilience. Rather than positing a new industrial revolution, our positioning follows the European Commission’s view that Industry 5.0 complements Industry 4.0 by emphasizing stakeholder value and human-technology symbiosis. We encode organizational capabilities (genotype) into four gene groups, Adaptability, Technology, Governance, and Culture, and link them to five human-centric outcomes (phenotype). Twenty capability genes and ten outcome measures were scored, normalized (0–100 scale), and analyzed using correlations, K-means clustering, and mutation/drift tracking to capture both static maturity levels and dynamic change patterns. Results show that high Industry 5.0 readiness is consistently associated with elevated Governance and Culture scores. Three transformation archetypes were identified: Alpha, representing holistic socio-technical integration; Beta, with strong technical capacity but weaker cultural alignment; and Gamma, with fragmented capabilities and elevated vulnerability. The Digital DNA framework offers a replicable diagnostic tool for linking socio-technical capabilities to human-centric outcomes, enabling readiness assessment and guiding adaptive, ethical manufacturing strategies.","author":[{"family":"Djebbouri","given":"KB"},{"family":"Alofaysan","given":"Hind"},{"family":"Hassan","given":"Fatma"},{"family":"Mohammed","given":"Kamel"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17219450","URL":"https://doi.org/10.3390/su17219450","source":"openalex"},{"id":"oa:W4411972936","type":"article-journal","title":"Recent Trends in Non-Destructive Testing Approaches for Composite Materials: A Review of Successful Implementations","abstract":"Non-destructive testing (NDT) methods are critical for evaluating the structural integrity of and detecting defects in composite materials across industries such as aerospace and renewable energy. This review examines the recent trends and successful implementations of NDT approaches for composite materials, focusing on articles published between 2015 and 2025. A systematic literature review identified 120 relevant articles, highlighting techniques such as ultrasonic testing (UT), acoustic emission testing (AET), thermography (TR), radiographic testing (RT), eddy current testing (ECT), infrared thermography (IRT), X-ray computed tomography (XCT), and digital radiography testing (DRT). These methods effectively detect defects such as debonding, delamination, and voids in fiber-reinforced polymer (FRP) composites. The selection of NDT approaches depends on the material properties, defect types, and testing conditions. Although each technique has advantages and limitations, combining multiple NDT methods enhances the quality assessment of composite materials. This review provides insights into the capabilities and limitations of various NDT techniques and suggests future research directions for combining NDT methods to improve quality control in composite material manufacturing. Future trends include adopting multimodal NDT systems, integrating digital twin and Industry 4.0 technologies, utilizing embedded and wireless structural health monitoring, and applying artificial intelligence for automated defect interpretation. These advancements are promising for transforming NDT into an intelligent, predictive, and integrated quality assurance system.","author":[{"family":"Tai","given":"Jan"},{"family":"Sultan","given":"Mohamed"},{"family":"Łukaszewicz","given":"Andrzej"},{"family":"Jóźwik","given":"Jerzy"},{"family":"Oksiuta","given":"Zbigniew"},{"family":"Shahar","given":"Farah"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/ma18133146","URL":"https://doi.org/10.3390/ma18133146","source":"openalex"},{"id":"oa:W4412635581","type":"article-journal","title":"Embedding Circular Operations in Manufacturing: A Conceptual Model for Operational Sustainability and Resource Efficiency","abstract":"In response to growing environmental pressures and material constraints, circular economy principles are gaining traction across manufacturing sectors. However, most existing frameworks emphasize design and supply chain considerations, with limited focus on how circularity can be operationalized within internal manufacturing systems. This paper proposes a conceptual model that embeds circular operations at the core of production strategy. Grounded in circular economy theory, operations management, and socio-technical systems thinking, the model identifies four key operational pillars: circular input management, looping process and waste valorization, product-life extension, and reverse logistics. These are supported by enabling factors—digital infrastructure, organizational culture, and leadership—and mediated by operational flexibility, which facilitates adaptive, closed-loop performance. The model aims to align internal processes with long-term sustainability outcomes, specifically resource efficiency and operational resilience. Practical implications are outlined for resource-intensive industries such as automotive, electronics, and FMCG, along with a readiness assessment framework for guiding implementation. This study offers a pathway for future empirical research and policy development by integrating circular logic into the structural and behavioral dimensions of operations. The model contributes to advancing the Sustainable Development Goals (SDGs), particularly SDG 9 and SDG 12, by positioning circularity as a regenerative operational strategy rather than a peripheral initiative.","author":[{"family":"Setyadi","given":"Antonius"},{"family":"Pawirosumarto","given":"Suharno"},{"family":"Damaris","given":"Alana"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17156737","URL":"https://doi.org/10.3390/su17156737","source":"openalex"},{"id":"oa:W7120076662","type":"article-journal","title":"Advances in Materials and Manufacturing for Scalable and Decentralized Green Hydrogen Production Systems","abstract":"The expansion of green hydrogen requires technologies that are both manufacturable at a GW-to-TW power scale and adaptable for decentralized, renewable-driven energy systems. Recent advances in proton exchange membrane, alkaline, and solid oxide electrolysis reveal persistent bottlenecks in catalysts, membranes, porous transport layers, bipolar plates, sealing, and high-temperature ceramics. Emerging fabrication strategies, including roll-to-roll coating, spatial atomic layer deposition, digital-twin-based quality assurance, automated stack assembly, and circular material recovery, enable high-yield, low-variance production compatible with multi-GW power plants. At the same time, these developments support decentralized hydrogen systems that demand compact, dynamically operated, and material-efficient electrolyzers integrated with local renewable generation. The analysis underscores the need to jointly optimize material durability, manufacturing precision, and system-level controllability to ensure reliable and cost-effective hydrogen supply. This paper outlines a convergent approach that connects critical-material reduction, high-throughput manufacturing, a digitalized balance of plant, and circularity with distributed energy architectures and large-scale industrial deployment.","author":[{"family":"Szabó","given":"Gabriella"},{"family":"Coteț","given":"Florina"},{"family":"Ferenci","given":"Sàra"},{"family":"Szabó","given":"Loránd"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/jmmp10010028","URL":"https://doi.org/10.3390/jmmp10010028","source":"openalex"},{"id":"oa:W4406890645","type":"article-journal","title":"Lightweight and Robust Key Agreement for Securing IIoT-Driven Flexible Manufacturing Systems","abstract":"The ever-evolving Internet of Things (IoT) has ushered in a new era of intelligent manufacturing across multiple industries. However, the security and privacy of real-time data transmitted over the public channel of the Industrial IoT (IIoT) remain formidable challenges. Existing lightweight protocols often omit one or more critical security features, such as anonymity and untraceability, and are susceptible to threats like desynchronization attacks. Additionally, they struggle to achieve an optimal balance between robust security and performance efficiency. To bridge these gaps, we introduce a new lightweight key agreement security scheme that guarantees secure access to the IIoT-enabled flexible manufacturing system (FMS). The strength of our scheme lies in its utilization of the authenticated encryption with associative data (AEAD) primitive, AEGIS, along with hash functions and physical unclonable functions, which secure the IIoT ecosystem. Additionally, our scheme offers flexibility in the form of the addition of new machines, password updates, and revocation in cases of theft or loss. A comprehensive security analysis demonstrates the efficacy of the proposed scheme in thwarting various attacks. The formal analysis, based on the Real-or-Random (RoR) model, ensures session key indistinguishability, while the informal analysis highlights its resilience against known attacks. The comparative assessment demonstrates that the proposed scheme consistently outperforms the benchmark schemes across multiple dimensions, including security and functionality features, computational and communication overheads, and runtime efficiency. Specifically, the proposed scheme achieves peak performance enhancements of 77.55%, 44.73%, and 69.6% in computational overhead, runtime overhead, and communication overhead, respectively, underscoring its substantial performance advantages.","author":[{"family":"Hammad","given":"Muhammad"},{"family":"Badshah","given":"Akhtar"},{"family":"Almeer","given":"Mohammed"},{"family":"Waqas","given":"Muhammad"},{"family":"Song","given":"Houbing"},{"family":"Chen","given":"Sheng"},{"family":"Han","given":"Zhu"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1109/jiot.2025.3535846","URL":"https://doi.org/10.1109/jiot.2025.3535846","source":"openalex"},{"id":"doi:10.3390/polym17182557","type":"article-journal","title":"Data-Driven Optimization of Discontinuous and Continuous Fiber Composite Processes Using Machine Learning: A Review.","abstract":"This paper surveys the application of machine learning in fiber composite manufacturing, highlighting its role in adaptive process control, defect detection, and real-time quality assurance. First, the need for ML in composite processing is highlighted, followed by a review of data-driven approaches-including predictive modeling, sensor fusion, and adaptive control-that address material heterogeneity and process variability. An in-depth analysis examines six case studies, among which are XPBD-based surrogates for RL-driven robotic draping, hyperspectral imaging (HSI) with U-Net segmentation for adhesion prediction, and CNN-driven surrogate optimization for variable-geometry forming. Building on these insights, a hybrid AI model architecture is proposed for natural-fiber composites, integrating a physics-informed GNN surrogate, a 3D Spectral-UNet for defect segmentation, and a cross-attention controller for closed-loop parameter adjustment. Validation on synthetic data-including visualizations of HSI segmentation, graph topologies, and controller action weights-demonstrates end-to-end operability. The discussion addresses interpretability, domain randomization, and sim-to-real transfer and highlights emerging trends such as physics-informed neural networks and digital twins. This paper concludes by outlining future challenges in small-data regimes and industrial scalability, thereby providing a comprehensive roadmap for ML-enabled composite manufacturing.","author":[{"family":"Malashin","given":"Ivan"},{"family":"Martysyuk","given":"Dmitry"},{"family":"Тынченко","given":"ВС"},{"family":"Gantimurov","given":"Andrei"},{"family":"Nelyub","given":"Vladimir"},{"family":"Бородулин","given":"АС"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/polym17182557","URL":"https://doi.org/10.3390/polym17182557","source":"europepmc"},{"id":"doi:10.1002/bit.70093","type":"article-journal","title":"Self-Driving Development of Perfusion Processes for Monoclonal Antibody Production.","abstract":"The development of autonomous agents in bioprocess development is crucial for advancing biopharma innovation. Time and resources required to develop and transfer a process for clinical material generation can be significantly decreased. While robotics and machine learning have greatly accelerated drug discovery and initial screening, the later stages of development have primarily benefited from experimental automation, lacking advanced computational tools for experimental planning and execution. For example, in the development of new monoclonal antibodies, the search for optimal upstream conditions (such as feeding strategy, pH, temperature, and media composition) is often conducted using sophisticated high-throughput (HT) mini-bioreactor systems, while the integration of machine learning tools for experimental design and operation in these systems have not matured accordingly. In this work, we developed an integrated user-friendly software framework that combines a Bayesian experimental design (BED) algorithm and a cognitive digital twin of the cultivation system. This framework is digitally linked to an advanced 24-parallel mini-bioreactor perfusion platform. This results in an autonomous experimental machine capable of: (1) embedding existing process knowledge, (2) learning during experimentation, (3) utilizing information from similar processes, (4) predicting future events, and (5) autonomously operating the parallel bioreactors to achieve challenging objectives. As proof of concept, we present experimental results from a 27 day-long cultivation including 20-days operated by the autonomous software agent, which successfully achieved challenging goals such as increasing the viable cell volume (VCV) and maximizing the viability throughout the experiment.","author":[{"family":"Gadiyar","given":"Chethana"},{"family":"Müller","given":"Claudio"},{"family":"Vuillemin","given":"Thomas"},{"family":"Bielser","given":"Jean‐marc"},{"family":"Souquet","given":"Jonathan"},{"family":"Fagnani","given":"Alessandro"},{"family":"Sokolov","given":"Michael"},{"family":"Stosch","given":"Moritz"},{"family":"Feidl","given":"Fabian"},{"family":"Butté","given":"Alessandro"},{"family":"Bournazou","given":"Mariano"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/bit.70093","URL":"https://doi.org/10.1002/bit.70093","source":"europepmc"},{"id":"oa:W4411162017","type":"article-journal","title":"Sustainable Transition Pathways for Steel Manufacturing: Low-Carbon Steelmaking Technologies in Enterprises","abstract":"Amid escalating global climate crises and the urgent imperative to meet the Paris Agreement’s carbon neutrality targets, the steel industry—a leading contributor to global greenhouse gas emissions—confronts unprecedented challenges in driving sustainable industrial transformation through innovative low-carbon steelmaking technologies. This paper examines decarbonization technologies across three stages (source, process, and end-of-pipe) for two dominant steel production routes: the long process (BF-BOF) and the short process (EAF). For the BF-BOF route, carbon reduction at the source stage is achieved through high-proportion pellet charging in the blast furnace and high scrap ratio utilization; at the process stage, carbon control is optimized via bottom-blowing O2-CO2-CaO composite injection in the converter; and at the end-of-pipe stage, CO2 recycling and carbon capture are employed to achieve deep decarbonization. In contrast, the EAF route establishes a low-carbon production system by relying on green and efficient electric arc furnaces and hydrogen-based shaft furnaces. At the source stage, energy consumption is reduced through the use of green electricity and advanced equipment; during the process stage, precision smelting is realized through intelligent control systems; and at the end-of-pipe stage, a closed-loop is achieved by combining cascade waste heat recovery and steel slag resource utilization. Across both process routes, hydrogen-based direct reduction and green power-driven EAF technology demonstrate significant emission reduction potential, providing key technical support for the low-carbon transformation of the steel industry. Comparative analysis of industrial applications reveals varying emission reduction efficiencies, economic viability, and implementation challenges across different technical pathways. The study concludes that deep decarbonization of the steel industry requires coordinated policy incentives, technological innovation, and industrial chain collaboration. Accelerating large-scale adoption of low-carbon metallurgical technologies through these synergistic efforts will drive the global steel sector toward sustainable development goals. This study provides a systematic evaluation of current low-carbon steelmaking technologies and outlines practical implementation strategies, contributing to the industry’s decarbonization efforts.","author":[{"family":"Zhang","given":"Jinghua"},{"family":"Guo","given":"Haoyu"},{"family":"Yang","given":"Gai­yan"},{"family":"Wang","given":"Yan"},{"family":"Chen","given":"Wei"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17125329","URL":"https://doi.org/10.3390/su17125329","source":"openalex"},{"id":"oa:W4415548751","type":"article-journal","title":"A focused review on numerical computation in wire arc additive manufacturing for high strength low alloy steels: past insights and potential opportunities","abstract":"Wire Arc Additive Manufacturing (WAAM) has emerged as a transformative technology in Metal Additive Manufacturing (MAM), offering significant advantages for fabricating large, complex metal structures that are often difficult or economically unfeasible to produce using traditional methods. Despite its cost-effectiveness and design flexibility, WAAM continues to rely heavily on trial-and-error attempts to achieve high-quality results, leading to significant time, effort and financial costs, particularly when producing large-scale parts. High Strength Low Alloy (HSLA) steels, known for their superior strength-to-weight ratios, mechanical properties and corrosion resistance, have become essential in industries where high performance is critical, such as aerospace, automotive and construction. The integration of HSLA steels into WAAM presents unique challenges that require precise predictions of material behavior and process dynamics. Recent advancements in numerical computation have significantly enhanced the understanding and optimization of WAAM process and have been disseminated in various publications. However, existing research on dedicated topics is often fragmented and lacks sufficient integration, which limits the potential for comprehensive insights. This review synthesizes the state of the art in research from 2020 to mid-2025, with a particular focus on integrating numerical computation, HSLA and WAAM. Through the application of staggered scaling methods, significant strides have been made in predicting critical outputs such as temperature distribution, residual stresses, part distortion and microstructural evolution at the grain level. Building on past insights, emerging research trends are focusing on more advanced methods to further optimize the WAAM process. One exciting direction is the use of Hybrid Physics-Informed Neural Networks (PINNs), which integrate neural networks, governing physical laws, analytical models and data-driven methods to offer more accurate and efficient process control. Although still in its early stages, this methodology provides an opportunity to address existing gaps in material performance and process optimization. By leveraging past insights and emerging computational methods, future research holds the potential to significantly advance the industrial adoption of HSLA-WAAM, enabling the production of parts with unprecedented design flexibility, customized material performance and enhanced reliability. This could reshape the manufacturing landscape and position manufacturing modelling and MAM as cornerstones of next-generation manufacturing technology.","author":[{"family":"Ghazali","given":"Sarah"},{"family":"Ibrahim","given":"Mohd"},{"family":"Manurung","given":"Yupiter"},{"family":"Adenan","given":"Mohd"},{"family":"Rahman","given":"Asm"},{"family":"Ramlan","given":"Abdul"},{"family":"Harati","given":"Ebrahim"},{"family":"Busari","given":"Yusuf"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s00170-025-16817-9","URL":"https://doi.org/10.1007/s00170-025-16817-9","source":"openalex"},{"id":"oa:W4409167555","type":"article-journal","title":"Agricultural mechanization perspective in Pakistan: present challenges and digital future","abstract":"Agriculture constitutes a critical sector within the economic landscape of Pakistan, engaging 37.4% of the labour force and contributing 22.9% to the Gross Domestic Product (GDP), thus functioning as an essential element of the country's economic architecture and the sustenance of its citizens. The primary agricultural commodities, which encompass wheat, rice, cotton, maize, and sugarcane, occupy extensive tracts of agricultural land, thereby underscoring their paramount importance regarding food security, impacts on territory management and related landscape, as well as income generation through export activities. Despite its crucial role, the advancement of agricultural mechanization in Pakistan is significantly lacking, with the available agricultural power that is a little less than 1.6 kW ha-1, which is below the minimum required farm power of 1.82 kW ha-1. In this study, we seek to investigate the historical evolution, current scenario, and significant obstacles confronting agricultural mechanization in Pakistan, especially right now when innovative trends worldwide are pushing towards a progressive digitisation of the sector. Continuing with the conventional agricultural practices during the period of independence in 1947, the Green Revolution of the 1960s represented a crucial transformation towards mechanization, propelled by the indigenous manufacturing of tractors. Nevertheless, the pace of mechanization has slowed in recent years, primarily due to the prevalence of small farm sizes, economic constraints, and inadequate access to financial resources. While tasks such as land preparation and pesticide application have achieved notable levels of mechanization, fundamental operations including sowing, transplanting, weeding, and harvesting continue to be insufficiently mechanized. Significant initiatives, such as Laser Land Levelling in Punjab, show the considerable impact of focused interventions. To address the mechanization deficit, proposed strategies encompass the enhancement of local machinery manufacturing, the establishment of quality standards, the promotion of advanced imported equipment, an increase in farmer education, and the implementation of comprehensive government support through subsidies, tax benefits, and dedicated research and development efforts. A collaborative approach between governmental bodies and the private sector is imperative for fostering advancements in mechanization, thereby ensuring a more efficient, productive, and sustainable agricultural sector in Pakistan.","author":[{"family":"Mahmood","given":"G"},{"family":"Liberatori","given":"Sandro"},{"family":"Mazzetto","given":"Fabrizio"}],"issued":{"date-parts":[[2025]]},"DOI":"10.4081/jae.2025.1636","URL":"https://doi.org/10.4081/jae.2025.1636","source":"openalex"},{"id":"oa:W4413222323","type":"article-journal","title":"Impact of Digitalization on Carbon Emissions in Guangdong’s Manufacturing Sector: An Input–Output Perspective","abstract":"As global pressure to reduce emissions intensifies, China is increasingly turning to digital technologies to drive sustainable industrial development, aiming to boost production while keeping carbon emissions in check. This study takes a micro-level approach by dividing the industry into 17 sectors and applying an environmentally-extended input–output (EEIO) model combined with structural decomposition analysis (SDA) to quantify the impact of digital transformation on carbon emissions across sectors. This study used input–output data from 2012 and 2017. The results indicate that (1) technological improvements driven by digitalization play a key role in reducing industrial carbon emissions, and (2) while high-carbon sectors show substantial emission reductions due to digital transformation, industries such as textiles—where digital adoption is more challenging—exhibit only limited improvements. These findings underscore the need to further advance technological upgrading and transformation in less digitally integrated sectors.","author":[{"family":"Jingren","given":"Jiao"},{"family":"Yabar","given":"Helmut"},{"family":"Mizunoya","given":"Takeshi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17167234","URL":"https://doi.org/10.3390/su17167234","source":"openalex"},{"id":"oa:W4414181155","type":"article-journal","title":"AI-Based Surrogate Models for the Food and Drink Manufacturing Industry: A Comprehensive Review","abstract":"Surrogate models provide virtual representations that mirror physical objects or processes, serving distinct purposes in simulations and digital transformation. This review article examines how integrating surrogate modelling with artificial intelligence (AI) techniques can facilitate the iterative development of surrogate models and identify instances where additional data acquisition is necessary to enhance the performance of a surrogate model. This demonstrates the potential of combining AI with surrogate modelling in addressing some of the key challenges in the food and drink manufacturing industry. The paper also provides an accessible examination of AI and surrogate modelling in the food and drink manufacturing industry, offering a summary of current applications and advancements within the field. The key areas addressed by this article include the application of AI and ML in process control, prediction, and modelling for food manufacturing, as well as the advantages and limitations of AI-based surrogate modelling (SM), among other issues addressed. Based on the literature reviewed herein, AI-based surrogate models can be employed to optimise production processes and reduce the need for extensive physical prototyping in the food and drink manufacturing industry. This review emphasises AI-based surrogate modelling techniques tailored for complex food processing systems and distinguishes itself by bridging method-specific insights with practical industrial relevance. Additionally, this article reviews challenges and limitations in the food and drink manufacturing industry and the application of surrogate modelling, along with future directions for research in this rapidly evolving field.","author":[{"family":"Lwele","given":"Emmanuel"},{"family":"Shenfield","given":"Alex"},{"family":"Silva","given":"Carlos"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/pr13092929","URL":"https://doi.org/10.3390/pr13092929","source":"openalex"},{"id":"oa:W7128166723","type":"article-journal","title":"AI-Driven Hybrid Deep Learning and Swarm Intelligence for Predictive Maintenance of Smart Manufacturing Robots in Industry 4.0","abstract":"Advancements in Industry 4.0 technologies, which combine big data analytics, robotics, and intelligent decision systems to enable new ways to increase automation in the industrial sector, have undergone significant transformations. In this research, a Hybrid Attention-Gated Recurrent Unit (At-GRU) model, combined with Sand Cat Optimization (SCO), is proposed to enhance fault identification and predictive maintenance capabilities. The model utilized multivariate sensor data from cyber-physical and IoT-enabled robotic platforms to learn operational patterns and predict failures with enhanced reliability. The At-GRU provides deeper temporal feature extraction, thereby improving classification performance. The robustness of the proposed model is validated through analysis of a benchmark dataset for industrial robots, and the results demonstrate that the proposed model exhibits impressive predictive capacity, surpassing other prediction methods and predictive maintenance approaches. Additionally, the performance evaluation indicates a lower computational cost due to the lightweight gating architecture of GRU, combined with attention. The robotic motion is further optimized by the SCO algorithm, which reduces energy usage, execution delay, and trajectory deviations while ensuring smooth operation. Overall, the proposed work offers an intelligent and scalable solution for next-generation industrial automation systems. Furthermore, the proposed model demonstrates the real-world applicability and significant benefits of incorporating hybrid artificial intelligence models into real-time robot control applications for smart manufacturing environments.","author":[{"family":"Kumar","given":"Deepak"},{"family":"Addula","given":"Santosh"},{"family":"Lind","given":"Mary"},{"family":"Brown","given":"Steven"},{"family":"Odion","given":"Segun"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/electronics15030715","URL":"https://doi.org/10.3390/electronics15030715","source":"openalex"},{"id":"oa:W4410056341","type":"article-journal","title":"Strategies for recycling multi-material polymer blends for additive manufacturing","abstract":"The rapid advancement of additive manufacturing (AM) technology, combined with the growing accumulation of plastic waste, has generated significant interest in utilizing materials derived from plastic waste and their composites within the AM industry. This paper examines the methods and approaches currently employed in recycling and blending thermoplastic waste into additive manufacturing feedstocks, aiming to enhance understanding and guide future advancements in this field. A systematic literature review including 82 papers from 2014 to 2024 was performed using the Scopus and Web of Science databases. The review findings indicate that approximately 83 % of the research is concentrated in production of new materials combining various polymer waste with recycled bio-sourced materials, recycled fillers or other additives for property enhancement. The evaluation and characterization of these new materials was carry out mostly using 3D printing, predominantly employing fused filament fabrication technology (63 %). The remaining 17 % focus on the improvement of the printing quality and optimization, development or adaptation of 3D printers for the utilization of new materials, and material reprocessability. This review highlight the need of evaluating the behavior of recycled blends over multiple life cycles, the cost and environmental assessments, and primary end-use applications of these materials, including as well as further development and design of printers.","author":[{"family":"Gonzalez","given":"Catalina"},{"family":"Basdeo","given":"Aditi"},{"family":"Sanchez","given":"Fabio"},{"family":"Nouvel","given":"Cécile"},{"family":"Pearce","given":"Joshua"},{"family":"Boudaoud","given":"Hakim"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.susmat.2025.e01430","URL":"https://doi.org/10.1016/j.susmat.2025.e01430","source":"openalex"},{"id":"oa:W4417180026","type":"article-journal","title":"Global Trends in Procurement and Supply Chain Analytics with Implications for Manufacturing Innovation","abstract":"The rapid digitalization of procurement and supply chain management has transformed how organizations coordinate, evaluate, and innovate within global manufacturing systems. The integration of analytics into procurement processes enables firms to enhance efficiency, transparency, and resilience, while simultaneously supporting the transition toward advanced manufacturing innovation. Recent global shifts including the proliferation of big data, artificial intelligence, blockchain, and Industry 4.0 technologies redefined how procurement is conducted, turning it into a strategic driver of value creation. This paper provides an in-depth literature-based review of global trends in procurement and supply chain analytics with a focus on their implications for manufacturing innovation. By synthesizing secondary research up to 2025, it explores the historical evolution, methodological developments, and emerging debates that define this rapidly changing field. The analysis underscores the growing significance of predictive and prescriptive analytics, the integration of sustainability considerations, the use of advanced digital platforms, and the move toward collaborative, data-sharing ecosystems. Particular attention is given to the implications for manufacturing innovation, including enhanced product design, agile production, risk resilience, and sustainable operations. The findings highlight the opportunities and challenges facing organizations as they adapt to a data-intensive procurement and supply chain landscape. This paper contributes to scholarly discourse and managerial practice by consolidating current knowledge, identifying critical gaps, and outlining directions for future research.","author":[{"family":"Akin-Oluyomi","given":"Olatunde"},{"family":"Okoruwa","given":"Precious"},{"family":"Babatope","given":"Odunayo"},{"family":"Akokodaripon","given":"David"}],"issued":{"date-parts":[[2025]]},"DOI":"10.54660/.ijmrge.2025.6.5.964-974","URL":"https://doi.org/10.54660/.ijmrge.2025.6.5.964-974","source":"openalex"},{"id":"oa:W4411801834","type":"article-journal","title":"Energy Efficiency and Sustainability of Additive Manufacturing as a Mass-Personalized Production Mode in Industry 5.0/6.0","abstract":"This review article examines the role of additive manufacturing (AM) in increasing energy efficiency and sustainability within the evolving framework of Industry 5.0 and 6.0. This review highlights the unique ability of additive manufacturing to deliver mass-customized products while minimizing material waste and reducing energy consumption. The integration of smart technologies such as AI and IoT is explored to optimize AM processes and support decentralized, on-demand manufacturing. Thisarticle discusses different AM techniques and materials from an environmental and life-cycle perspective, identifying key benefits and constraints. This review also examines the potential of AM to support circular economy practices through local repair, remanufacturing, and material recycling. The net energy efficiency of AM depends on the type of process, part complexity, and production scale, but the energy savings per component can be significant if implemented strategically.AM significantly improves energy efficiency in certain manufacturing contexts, often reducing energy consumption by 25–50% compared to traditional subtractive methods. The results emphasize the importance of innovation in both hardware and software to overcome current energy and sustainability challenges. This review highlights AM as a key tool in achieving a human-centric, intelligent, and ecological manufacturing paradigm.","author":[{"family":"Rojek","given":"Izabela"},{"family":"Mikołajewski","given":"Dariusz"},{"family":"Kopowski","given":"Jakub"},{"family":"Bednarek","given":"Tomasz"},{"family":"Tyburek","given":"Krzysztof"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/en18133413","URL":"https://doi.org/10.3390/en18133413","source":"openalex"},{"id":"oa:W4410183502","type":"article-journal","title":"Development of a catalog and a description model for methods and digital tools in Manufacturing Change Management","abstract":"Abstract Today’s manufacturing industry faces numerous complex challenges, requiring companies to continuously adapt to external influences like supply chain disruptions, energy shortages, and skilled-labor deficits. Addressing these challenges often necessitates Manufacturing Changes (MCs), managed systematically through Manufacturing Change Management (MCM). Despite MCM’s growing importance, studies reveal significant gaps in the methodical and digital support for MCM processes, leading to inefficient and ineffective MCs. To address this challenge, this paper focuses on developing a catalog of methods and digital tools (M&DT) for MCM, structured with descriptive attributes to enhance the selection and application of M&DT in response to specific MCs. The catalog was developed through a three-phase approach, with attributes derived from the literature, an online survey, and expert interviews. The catalog and the associated descriptive framework were tested in a first industrial use case. In conclusion, the catalog developed in this contribution aims to guide companies in selecting suitable M&DT for specific use cases based on their individual requirements.","author":[{"family":"Rammo","given":"Jan"},{"family":"Agyekum","given":"Ellen"},{"family":"Perez","given":"Olaya"},{"family":"Zaeh","given":"Michael"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s11740-025-01343-0","URL":"https://doi.org/10.1007/s11740-025-01343-0","source":"openalex"},{"id":"oa:W4407616436","type":"article-journal","title":"To Explore the Relationship Between Sustainability, Digital Technology, and Sustainable Development Goals","abstract":"ABSTRACT In the era of rapid technological advancement and growing global challenges, the interaction between sustainability, digital technology (DT), and sustainable development goals (SDGs) presents a vital opportunity for transformative action. This convergence opens doors to innovative solutions for addressing critical environmental and societal issues while advancing economic progress. Therefore, this study aims to explore the intricate relationship between sustainability, digital technology, and SDGs. A systematic literature review and Preferred Reporting Items for Systematic Review and Meta‐Analyses (PRISMA) protocol have been used to comprehend the impact of DT on promoting SDGs across diverse sectors while enhancing sustainability. By analyzing the 141 articles, it could be concluded that achieving sustainability by adhering to the SDGs requires effective integration of DT and a thorough understanding of the policy reforms and SDG knowledge that support both sustainability goals and digitalization. The findings also indicate that achieving the SDGs in the era of digitalization relies on the collective and collaborative ability to leverage digital technology as a crucial tool and resource for positive transformation while mitigating its adverse impacts. Furthermore, the successful integration of DT with SDGs requires a comprehensive approach that encompasses technological innovation, a supportive governance framework, and capacity building.","author":[{"family":"Saha","given":"Aditi"},{"family":"Raut","given":"Rakesh"},{"family":"Kumar","given":"Mukesh"},{"family":"Ghoshal","given":"Sudishna"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/bsd2.70076","URL":"https://doi.org/10.1002/bsd2.70076","source":"openalex"},{"id":"oa:W7150912933","type":"article-journal","title":"Hybrid agentic AI and multi-agent systems in smart manufacturing","abstract":"The convergence of Agentic Artificial Intelligence (AI) and Multi-Agent Systems (MAS) enables a new paradigm for intelligent decision-making in Smart Manufacturing Systems (SMS). Traditional MAS architectures emphasize distributed coordination and specialized autonomy, while recent advances in agentic AI driven by Large Language Models (LLMs) introduce higher-order reasoning, planning, and tool orchestration capabilities. This paper presents a hybrid agentic AI and multi-agent framework for a Prescriptive Maintenance (RxM) use case, where LLM-based agents provide strategic orchestration and adaptive reasoning, complemented by rule-based and Small Language Models (SLMs) agents performing efficient, domain-specific tasks on the edge. The proposed framework adopts a layered architecture that consists of perception, preprocessing, analytics, and optimization layers, coordinated through an LLM Planner Agent that manages workflow decisions and context retention. Specialized agents autonomously handle schema discovery, intelligent feature analysis, model selection, and prescriptive optimization, while a human-in-the-loop interface ensures transparency and auditability of generated maintenance recommendations. This hybrid approach enables dynamic model adaptation, transparent decision-making, and cost-aware maintenance scheduling based on data-driven insights. An initial proof-of-concept implementation is validated on two industrial manufacturing datasets. The developed framework is modular and extensible, allowing new agents or domain-specific modules to be integrated seamlessly as system capabilities evolve. The results demonstrate the system’s capability to automatically detect schema, adapt preprocessing pipelines, optimize model performance through adaptive intelligence, and generate actionable, prioritized maintenance recommendations. The framework shows promise in achieving improved robustness, scalability, and explainability for RxM in smart manufacturing, bridging the gap between high-level agentic reasoning and low-level autonomous execution. • Hybrid agentic AI and multi-agent framework enables prescriptive maintenance in smart manufacturing. • Layered architecture coordinates perception, preprocessing, analytics, and optimization agents. • LLMs provide strategic reasoning and orchestration, while SLMs support low-latency edge intelligence. • Framework delivers transparent, modular, and cost-aware recommendations with human-in-the-loop oversight. • Validated on manufacturing datasets across classification, regression, and anomaly detection tasks.","author":[{"family":"Farahani","given":"Mojtaba"},{"family":"Khan","given":"Irfan"},{"family":"Wuest","given":"Thorsten"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.jmsy.2026.04.002","URL":"https://doi.org/10.1016/j.jmsy.2026.04.002","source":"openalex"},{"id":"oa:W4407272013","type":"article-journal","title":"Segregation-dislocation self-organized structures ductilize a work-hardened medium entropy alloy","abstract":"Dislocations are the intrinsic origin of crystal plasticity. However, initial high-density dislocations in work-hardened materials are commonly asserted to be detrimental to ductility according to textbook strengthening theory. Inspired by the self-organized critical states of non-equilibrium complex systems in nature, we explored the mechanical response of an additively manufactured medium entropy alloy with segregation-dislocation self-organized structures (SD-SOS). We show here that when initial dislocations are in the form of SD-SOS, the textbook theory that dislocation hardening inevitably sacrifices ductility can be overturned. Our results reveal that the SD-SOS, in addition to providing dislocation sources by emitting dislocations and stacking faults, also dynamically interacts with gliding dislocations to generate sustainable Lomer-Cottrell locks and jogs for dislocation storage. The effective dislocation multiplication and storage capabilities lead to the continuous refinement of planar slip bands, resulting in high ductility in the work-hardened alloy produced by additive manufacturing. These findings set a precedent for optimizing the mechanical behavior of alloys via tuning dislocation configurations.","author":[{"family":"Guo","given":"Bojing"},{"family":"Cui","given":"Dingcong"},{"family":"Wu","given":"Qingfeng"},{"family":"Ma","given":"Yuemin"},{"family":"Wei","given":"Daixiu"},{"family":"Kumara","given":"LSR"},{"family":"Zhang","given":"Yashan"},{"family":"Xu","given":"Chenbo"},{"family":"Wang","given":"Zhijun"},{"family":"Li","given":"Junjie"},{"family":"Lin","given":"Xin"},{"family":"Wang","given":"Jincheng"},{"family":"Wang","given":"Xun‐li"},{"family":"He","given":"Feng"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41467-025-56710-3","URL":"https://doi.org/10.1038/s41467-025-56710-3","source":"openalex"},{"id":"oa:W4414097645","type":"article-journal","title":"Assessment of Smart Manufacturing Readiness for Small and Medium Enterprises in the Indian Automotive Sector","abstract":"This study evaluates the degree to which small and medium sized enterprises (SMEs) are prepared to adopt smart manufacturing in contrast to large enterprises, a transition that depends on the effective use of the Internet of Things, artificial intelligence (AI), and advanced analytics. While many large multinational companies have already integrated such technologies, smaller firms still struggle because of tight budgets, limited technical expertise, and difficulties in scaling new systems. To capture these realities, the investigation refines the Initiative Mittelstand-Digital für Produktionsunternehmen und Logistik-Systeme (IMPULS) Industry 4.0 readiness model, which was initially developed to help German SMEs, so that it aligns with the circumstances faced by smaller manufacturers. A thorough review of published work first surveys existing readiness and maturity frameworks, highlights their limitations, and guides the selection of new, SME-specific indicators. The framework gauges readiness across six dimensions: strategic planning and organizational design, smart factory infrastructure, lean operations, digital products, data-driven services, and workforce capability. Each dimension is operationalized through a questionnaire that offers clear benchmarks and actionable targets suited to the current resources of each enterprise. Weaving strategic vision, skill growth, and cooperative support, the approach offers managers a direct path to sharper competitiveness and lasting innovation within a changing industrial landscape. Additionally, a separate Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis is provided for each dimension based on survey data offering decision-makers concise guidance for future investment. The proposed adaptation of the IMPULS framework, validated through empirical data from 31 SMEs, introduces a novel readiness index, diagnostic gap metrics, and actionable cluster profiles tailored to developing-country industrial ecosystems.","author":[{"family":"Dwivedy","given":"Maheshwar"},{"family":"Pandit","given":"Deepak"},{"family":"Khatter","given":"Kiran"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17188096","URL":"https://doi.org/10.3390/su17188096","source":"openalex"},{"id":"oa:W4409271233","type":"article-journal","title":"Knowledge flows in industry 4.0 research: a longitudinal and dynamic analysis","abstract":"Abstract Industry 4.0 represents a significant shift in industrial practices, presenting unique opportunities to improve manufacturing via advanced digital technologies and sustainable processes. The rapid growth of Industry 4.0 research has uncovered a significant knowledge gap and emphasized the need for studies adopting dynamic and longitudinal perspectives to understand this field’s evolution comprehensively. This study meticulously analyzes 10,176 articles to investigate the thematic evolution and knowledge transfer mechanisms within Industry 4.0. The examination reveals four distinct sub-periods, each characterized by thematic transitions, starting with foundational themes such as simulation and cyber-physical systems, progressing to later focuses on cloud computing, convolutional neural networks, and digital twin technologies. As research progresses, themes like production facilities, monitoring, and security highlight the shift towards automation, real-time monitoring, and strong data security measures. Five primary thematic domains are identified: (1) core enablers of sustainable smart manufacturing, (2) innovation and strategic transformation, (3) smart and secure manufacturing systems, (4) advanced data-driven manufacturing technologies, and (5) AI-driven real-time monitoring and production. These domains illustrate a transition from fundamental enablers like the Internet of Things (IoT) to more intricate AI-based applications. The main path analysis indicates a shift in emphasis, moving from essential digital integration towards sustainability, digital transformation, and resource efficiency applications. The findings reveal significant implications and highlight Industry 4.0 as a driving force for sustainable and resilient industrial ecosystems.","author":[{"family":"Rejeb","given":"Abderahman"},{"family":"Rejeb","given":"Karim"},{"family":"Süle","given":"Edit"},{"family":"Hassoun","given":"Abdo"},{"family":"Keogh","given":"John"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s42488-025-00146-3","URL":"https://doi.org/10.1007/s42488-025-00146-3","source":"openalex"},{"id":"oa:W4412087679","type":"article-journal","title":"Additive Manufacturing of Biodegradable Metallic Implants by Selective Laser Melting: Current Research Status and Application Perspectives","abstract":"Biodegradable metallic implants represent a paradigm shift in implantology, eliminating secondary removal surgeries through predictable controlled degradation. This review systematizes current achievements in selective laser melting (SLM) of biodegradable metals (Mg, Fe, Zn), analyzing how processing parameters influence microstructure, mechanical properties, and degradation kinetics. Key findings demonstrate that SLM-produced Mg alloys achieve bone-matching modulus (40–45 GPa) with moderate degradation (1–3 mm/year); Fe-based systems provide superior strength (400–600 MPa) but slower degradation (0.1–0.5 mm/year); while Zn alloys offer intermediate properties. Design strategies for porous/lattice structures enhancing osseointegration and enabling property gradients are discussed. Major challenges include controlling degradation kinetics, optimizing SLM parameters for reactive metals, standardizing testing methodologies, and regulatory harmonization. This comprehensive analysis provides systematic guidelines for material selection and process optimization, establishing a foundation for developing next-generation personalized biodegradable implants.","author":[{"family":"Gracheva","given":"Anna"},{"family":"Polozov","given":"Igor"},{"family":"Popovich","given":"Anatoly"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/met15070754","URL":"https://doi.org/10.3390/met15070754","source":"openalex"},{"id":"oa:W7117152735","type":"article-journal","title":"Hybrid AI Systems for Tool Wear Monitoring in Manufacturing: A Systematic Review","abstract":"Tool wear is critical to quality, productivity, and sustainability in manufacturing processes. Therefore, accurately monitoring and predicting wear is one of the primary goals of smart manufacturing systems. While AI-based approaches have achieved significant success in this area in recent years, issues such as physical inconsistency, limited generalizability, and low interpretability associated with solely data-driven methods have necessitated the development of hybrid approaches. This study systematically examines the literature published between 2020 and 2025 and comprehensively analyzes hybrid AI systems used in tool wear monitoring. Hybrid systems are categorized into four main groups: physics-based hybrids, knowledge-driven hybrids, transfer learning-based hybrids, and heterogeneous model hybrids. This classification holistically evaluates the synergistic effects and performance gains achieved by combining different methods. The findings demonstrate that the combined use of physical models, expert knowledge, and data-driven learning approaches provides significant advantages in terms of both accuracy and explainability. However, challenges such as data shortage, model complexity, and computational cost remain limitations to widespread industrial use of hybrid systems. The study demonstrates that hybrid AI systems represent a new research direction enabling the development of more reliable, transparent, and efficient solutions in smart manufacturing.","author":[{"family":"Saatçı","given":"Büşra"},{"family":"Ulaş","given":"Mustafa"},{"family":"Gürgenç","given":"Turan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app16010208","URL":"https://doi.org/10.3390/app16010208","source":"openalex"},{"id":"oa:W4411119947","type":"article-journal","title":"Melt-based additive manufacturing of refractory metals and alloys: Experiments and modeling","abstract":"Refractory metals and alloys possess unique properties, such as high melting points and excellent mechanical stability at elevated temperatures, making them attractive for aerospace, nuclear, and other demanding industries. However, fabrication of these materials using traditional manufacturing techniques is challenging due to their high melting points and intrinsic brittleness. Additive manufacturing (AM) techniques provide an approach to mitigate some of these challenges, but systematic insights into their process parameters, microstructure control, and mechanical performance remain fragmented in the literature. This paper provides an overview of the challenges and future prospects associated with melt-based AM of refractory metals and alloys from the perspectives of experiments, physics-based models, and machine learning approaches. Our review concludes by summarizing the frontiers in the field and highlighting the future developments necessary to enable efficient AM fabrication of refractory metals and alloys.","author":[{"family":"Araghi","given":"Mohammad"},{"family":"Dashti","given":"Ali"},{"family":"Fani","given":"Mahshad"},{"family":"Ghamarian","given":"Iman"},{"family":"Ruiz","given":"César"},{"family":"Xu","given":"Shuozhi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jmrt.2025.05.207","URL":"https://doi.org/10.1016/j.jmrt.2025.05.207","source":"openalex"},{"id":"oa:W4416861929","type":"article-journal","title":"Experimental Validation and Dynamic Analysis of Additive Manufacturing Burner for Gas Turbine Applications","abstract":"In the context of a rapidly evolving energy sector, the development of hydrogen-ready gas turbines, a key milestone in the energy transition toward decarbonization, requires advanced gas injectors capable of operating with both natural gas and hydrogen. Additive manufacturing (AM) significantly accelerates the iterative design process, enabling the production of single-piece, fully three-dimensional components and supporting rapid prototyping with optimized process parameters. Early assessment of component durability, particularly structural damping, is crucial to predicting dynamic response and high-cycle fatigue life, reducing costly design modifications in later stages. In this work, a methodology is proposed for structural damping characterization at the early prototypal stage, combining ping test measurements with a numerical approach based on the Half-Power Bandwidth Method (HBM) enhanced by an iterative procedure. This approach enables the accurate estimation of representative damping values for low-mass, high-stiffness components, overcoming the limited accuracy of standard Rayleigh damping models at this stage. The methodology was applied to a gas turbine burner manufactured via additive manufacturing, demonstrating that even with partial experimental data, it is possible to obtain reliable damping estimates, support rapid design iteration, and ensure convergence toward optimal mechanical performance.","author":[{"family":"Cascino","given":"Alessio"},{"family":"Meli","given":"Enrico"},{"family":"Rindi","given":"Andrea"},{"family":"Pucci","given":"Egidio"},{"family":"Matoni","given":"Emanuele"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/machines13121111","URL":"https://doi.org/10.3390/machines13121111","source":"openalex"},{"id":"oa:W4412077941","type":"article-journal","title":"Leveraging Digital Intelligence Technologies for Green Shipping: Organization Information Processing and Contingency Perspective","abstract":"ABSTRACT This study investigates how digital intelligence technology applications (DITAs) enhance green shipping management performance (GSMP) by improving organizational capabilities in the face of environmental uncertainty. Drawing on organizational information processing theory and contingency theory, we develop a framework that examines the mediating roles of data analytics capability and business process reengineering and the moderating effects of green supply chain integration. A two‐wave survey was conducted in China and Korea, with 205 responses collected from shipping organizations between May and August 2023. Structural equation modeling and multigroup analysis were employed. The results show that DITA significantly improves data analytics capability and business process reengineering. Meanwhile, green internal integration strengthens the effects of both data analytics capability and business process reengineering on GSMP, whereas green supplier and customer integration only enhance the impact of business process reengineering. These results offer new insights into how improvements in information processing capabilities, supported by digital and integrative mechanisms, can promote sustainable practices in the shipping industry. Practical implications are provided for managers seeking to build adaptive, digitally enabled, and environmentally aligned shipping strategies.","author":[{"family":"Pang","given":"Qiwei"},{"family":"Liu","given":"Xin"},{"family":"Su","given":"Miao"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/bse.70056","URL":"https://doi.org/10.1002/bse.70056","source":"openalex"},{"id":"oa:W7128530370","type":"article-journal","title":"Implementing an Operational Digital Twin for Optimizing Water Motor Operations in Resource-Constrained Environments","abstract":"Small centrifugal pumps critical for rural and peri-urban water supply often lack advanced monitoring. This study develops a low-cost operational Digital Twin (DT) for a 3.7 kW induction motor pump at IIIT-Hyderabad (IIIT-H), optimised for resource-constrained settings with limited bandwidth and power. Using an ESP32 gateway, temperature, current, and vibration data are streamed to ThingSpeak, stored in MongoDB, and synchronised with a Simulink model via Eclipse Ditto. The system continuously compares simulated and actual pump data and raises alerts when abnormal behaviour is detected using a Root Mean Square Error (RMSE)-based anomaly detector. A dashboard was developed to enable remote motor operation and automated shutdown during unsafe conditions. The twin operates in a partially closed-loop mode: sensor streams continuously update the virtual model and generate alerts, while relay-based actuation allows automated start/stop motor operation. From August to November 2024, 160,000 minutely-sampled records demonstrated an≈8-second end-to-end latency, which is characterised as near real-time and adequate for supervisory pump monitoring. This meets the SCADA real-time standards, with 5% modelling error. The system enabled anomaly detection, detecting faults hours early without labelled data, and achieved rapid operator adoption with minimal training. This open-source solution bridges a research gap for 3-5 HP pumps, offering a scalable blueprint for small utilities and supporting future enhancements like fully closed-loop control.","author":[{"family":"Kriti","given":"Ankit"},{"family":"Tomar","given":"Kratika"},{"family":"Narasimha","given":"Vadla"},{"family":"Chouhan","given":"Shailesh"},{"family":"Chaudhari","given":"Sachin"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1109/access.2026.3663445","URL":"https://doi.org/10.1109/access.2026.3663445","source":"openalex"},{"id":"oa:W7117658103","type":"article-journal","title":"Design of a Digital Twin System for Deepwater Installation Systems","abstract":"ABSTRACT With the rapid advancement of deepwater oil and gas exploration, subsea operations are facing increasingly complex environments and technical challenges. As water depth increases, the difficulty of installation, operational risks and uncertainties grow significantly, resulting in shorter weather windows, limited real‐time response and higher safety requirements. To address these challenges and enhance operational efficiency and safety, this paper proposes a digital twin‐based support system for deepwater subsea installation. The system integrates heterogeneous data sources to establish dynamic mappings between physical assets and their digital counterparts, enabling real‐time monitoring, predictive analysis and intelligent decision‐making across the entire installation lifecycle. By incorporating environmental sensing, dynamic simulation and virtual‐reality interaction, the digital twin system supports task planning, risk forecasting and remote operations in complex subsea conditions. A case study is presented to demonstrate the system's effectiveness in improving decision efficiency and reducing operational risk. The research provides a theoretical foundation and technical pathway for the intelligent and digital transformation of deepwater offshore engineering.","author":[{"family":"Chen","given":"Song"},{"family":"Wang","given":"Z"},{"family":"Wang","given":"Shuo"},{"family":"Duan","given":"Lizhi"},{"family":"Wu","given":"Jianhang"},{"family":"Wu","given":"Renhui"},{"family":"Qu","given":"Yan"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1049/dgt2.70020","URL":"https://doi.org/10.1049/dgt2.70020","source":"openalex"},{"id":"oa:W4411352410","type":"article-journal","title":"Explainable AI for reinforcement learning based dynamic scheduling solutions in semiconductor manufacturing","abstract":"Abstract The scheduling of complex job shop manufacturing environments is a difficult and NP-hard optimization problem. It is tackled increasingly with AI-based methods, often by reinforcement learning approaches. So far, this is mostly an academic endeavor as the trust in such systems is limited. The neural networks representing the policy are often seen as a black box by domain experts. By proposing a holistic approach to make such policies more interpretable and explainable, we hope to bridge the gap between academia and industry. With increasing trust in the solution, it becomes closer to being deployed in a real manufacturing environment. We propose a combination of different statistical and well-established ML-based methodologies to analyze single state-action explanations as well as the overall strategy and apply them to pretrained agents on open-source benchmark simulation models. This allows us to deliver humanly understandable explanations for the policies of the analyzed agents.","author":[{"family":"Immordino","given":"Alessandro"},{"family":"Stöckermann","given":"Patrick"},{"family":"Hayen","given":"Niels"},{"family":"Altenmüller","given":"Thomas"},{"family":"Susto","given":"Gian"},{"family":"Gebser","given":"Martin"},{"family":"Schekotihin","given":"Konstantin"},{"family":"Seidel","given":"Georg"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s10845-025-02631-3","URL":"https://doi.org/10.1007/s10845-025-02631-3","source":"openalex"},{"id":"oa:W4414664059","type":"article-journal","title":"Technological Innovations in Sustainable Civil Engineering: Advanced Materials, Resilient Design, and Digital Tools","abstract":"Civil engineering today faces the challenge of responding to climate change, rapid urbanization, and the need to reduce environmental impacts. These factors drive the search for more sustainable approaches and the adoption of digital technologies. This article addresses three principal dimensions: advanced low-impact materials, resilient structural designs, and digital tools applied throughout the infrastructure life cycle. To this end, a systematic search was conducted considering studies published between 2020 and 2025, including both experimental and review works. The results show that materials such as geopolymers, biopolymers, natural fibers, and nanocomposites can significantly reduce the carbon footprint; however, they still face regulatory, cost, and adoption barriers. Likewise, modular, adaptable, and performance-based design proposals enhance infrastructure resilience against extreme climate events. Finally, digital tools such as Building Information Modeling, digital twins, artificial intelligence, the Internet of Things, and 3D printing provide improvements in planning, construction, and maintenance, though with limitations related to interoperability, investment, and training. In conclusion, the integration of materials, design, and digitalization presents a promising pathway toward safer, more resilient, and sustainable infrastructure, aligning with the Sustainable Development Goals and the concept of smart cities.","author":[{"family":"Ligarda-Samanez","given":"Carlos"},{"family":"Carrión","given":"Mary"},{"family":"Moscoso","given":"Domingo"},{"family":"Sáenz","given":"Doris"},{"family":"Hernández","given":"Jaime"},{"family":"Espinoza","given":"Antonina"},{"family":"Huamaní","given":"Dante"},{"family":"Carrasco","given":"Carlos"},{"family":"Pino-Cordero","given":"Darwin"},{"family":"León","given":"Reynaldo"},{"family":"Durán","given":"Yolanda"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17198741","URL":"https://doi.org/10.3390/su17198741","source":"openalex"},{"id":"oa:W4413945761","type":"article-journal","title":"Exploring the Future of Manufacturing: An Analysis of Industry 5.0’s Priorities and Perspectives","abstract":"The present study explores the enablers for the integration of Industry 5.0 principles within the automotive industry, emphasizing the transition towards human-centric, sustainable, and resilient manufacturing. This research utilized a three-round Delphi method involving a panel of experts to identify, evaluate, and prioritize key enablers associated with the adoption of Industry 5.0. In order to enhance the analytical depth, consensus trajectory mapping was employed to track opinion convergence across rounds. Fuzzy ranking was applied to provide a more nuanced evaluation of item prioritization. The results indicate a substantial degree of consensus on subjects such as collaborative robotics, cognitive automation, and circular manufacturing. The present study offers theoretical and practical implications, providing a roadmap for researchers and automotive stakeholders seeking to operationalize Industry 5.0 values.","author":[{"family":"Ionescu","given":"Ana"},{"family":"Ionescu","given":"Ana"},{"family":"Ionescu","given":"Alexandru"},{"family":"Ionescu","given":"Alexandru"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17177842","URL":"https://doi.org/10.3390/su17177842","source":"openalex"},{"id":"oa:W4414618102","type":"article-journal","title":"The Impact of Technological Innovations on Digital Supply Chain Management: The Mediating Role of Artificial Intelligence: An Empirical Study","abstract":"Background: This study examines the impact of technological innovations on digital supply chain management, with a focus on the mediating role of artificial intelligence. With global supply chains increasingly relying on digital platforms, the integration of advanced technologies has become essential for achieving efficiency and competitiveness. Methods: The research employs a mixed-methods approach, combining survey data and expert interviews with professionals from Jordan’s industrial sector. It investigates how emerging digital innovations influence supply chain performance and examines the extent to which artificial intelligence contributes to automation, predictive analytics, and data-driven decision-making. Results: The findings reveal that artificial intelligence plays a pivotal role in enhancing the effectiveness of technological innovations within digital supply chain systems. Specifically, AI improves adaptability to market fluctuations, increases operational efficiency, and strengthens strategic flexibility. These outcomes suggest that organizations adopting AI-enabled innovations are better equipped to respond to uncertainty and achieve superior supply chain performance. Conclusions: The study concludes that technological innovations significantly advance digital supply chain management when supported by artificial intelligence as a mediating factor. The integration of AI not only magnifies the value of digital innovations but also enables sustainable performance improvements and reinforces competitiveness in dynamic industrial environments.","author":[{"family":"Dalain","given":"Ali"},{"family":"Alnadi","given":"Mohammad"},{"family":"Allahham","given":"Mahmoud"},{"family":"Yamin","given":"Bohari"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/logistics9040138","URL":"https://doi.org/10.3390/logistics9040138","source":"openalex"},{"id":"oa:W4415054331","type":"manuscript","title":"Toward Trustworthy Digital Twinning: Taxonomy, Analysis, and Open Challenges","abstract":"The proliferation of Digital Twins (DTs) across industries like manufacturing, healthcare, and logistics is leading to the formation of complex ecosystems where heterogeneous DTs must cooperate. In such environments, establishing trust becomes paramount. However, trust in DTs remains an under-investigated problem, with current research predominantly focused on security and privacy, which are prerequisites but not sole constituents of trust. This paper presents a comprehensive framework for analyzing and enhancing the trustworthiness of Digital Twins. First, we propose a novel 5-layer symmetrical reference architecture (Asset, Synchronization, Data, Application, Integration) that models physical and digital twins as peers, improving reusability and maintainability. Using this architecture as a foundation, we then develop a multi-dimensional taxonomy to categorize DT trust issues from three critical perspectives: (1) an architectural perspective, which identifies and maps trust issues (e.g., model accuracy, data latency, application usability) to specific layers and behavioral attributes like conformance and dependability; (2) a massive twinning perspective, which explores emergent challenges in ecosystems of cooperating DTs, such as relationship complexity and data management; and (3) a stakeholder perspective, which addresses the need for both qualitative and quantitative trust assurances. Our analysis reveals that trust is a composite property requiring a holistic approach beyond conventional security. The paper concludes by synthesizing these perspectives into a unified view of DT trust and outlining critical open challenges and future research directions, providing a foundational roadmap for developing truly trustworthy DT systems.","author":[{"family":"Azzedin","given":"Farag"},{"family":"Alhazmi","given":"Turki"},{"family":"Rahman","given":"Md"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202510.0700.v1","URL":"https://doi.org/10.20944/preprints202510.0700.v1","source":"openalex"},{"id":"oa:W7130662072","type":"article-journal","title":"Digital twin enabled robot collision detection using time series forecasting","abstract":"Abstract The advent of Industry 4.0 has reshaped modern manufacturing, driven by breakthroughs in cutting-edge technologies. A key example is the widespread deployment of sensors, which capture and transmit large volumes of operational data. This data surge has fueled the development of advanced Artificial Intelligence (AI) applications, enhancing manufacturing intelligence and efficiency. A key enabler of such intelligence is Time-Series Forecasting (TSF), which leverages historical data to predict future trends and events, thereby providing actionable insights for proactive decision-making. In parallel, Digital Twin (DT) technology has gained significant prominence due to its capacity for bidirectional communication with physical manufacturing systems, enabling unprecedented levels of real-time monitoring, control, and optimization. Despite their benefits, the combined adoption of TSF and DT technologies presents considerable challenges, particularly in developing integrated, closed-loop systems. This study addresses this gap by proposing a novel framework that unifies TSF with DTs for the early detection of potential collisions between manufacturing assets. The framework is demonstrated using a robotic assembly line, with a detailed account of the training and deployment process of a TSF–DT pipeline. The proposed proof-of-concept is designed to be generalizable, offering applicability across diverse manufacturing systems.","author":[{"family":"Kalach","given":"Fadi"},{"family":"Farahani","given":"Mojtaba"},{"family":"Samaha","given":"Philip"},{"family":"Wuest","given":"Thorsten"},{"family":"Harik","given":"Ramy"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s10845-026-02803-9","URL":"https://doi.org/10.1007/s10845-026-02803-9","source":"openalex"},{"id":"oa:W4411492617","type":"article-journal","title":"Digital Transformation of Healthcare Enterprises in the Era of Disruptions—A Structured Literature Review","abstract":"Digital transformation is the process of using digital technologies for creating or modifying existing business processes and customer experience, leveraging cutting-edge technology to meet changing market needs. Disruptions like the COVID-19 pandemic, regional wars, and climate-driven natural disasters create consequential scenarios, e.g., global supply chain disruption creating further demand–supply mismatch for healthcare enterprises. According to KPMG’s 2021 Healthcare CEO Future Pulse, 97% of healthcare leaders reported that COVID-19 significantly accelerated the digital transformation agenda. Successful digital transformation initiatives, for example, digital twins for supply chains, augmented reality, the IoT, and cybersecurity technology initiatives implemented significantly enhanced resiliency in supply chain and manufacturing operations. However, according to another study conducted by Mckinsey & Company, 70% of digital transformation efforts for healthcare enterprises fail to meet their goals. Healthcare enterprises face unique challenges, such as complex regulatory environments, cultural resistance, workforce IT skills, and the need for data interoperability, which make digital transformation a challenging project. Therefore, this study explored potential barriers, enablers, disruption scenarios, and digital transformation use cases for healthcare enterprises. A structured literature review (SLR), followed by thematic content analysis, was conducted to inform the research objectives. A sample of sixty (n = 60) peer-reviewed journal articles were analyzed using research screening criteria and keywords aligned with research objectives. The key themes for digital transformation use cases identified in this study included information processing capability, workforce enablement, operational efficiency, and supply chain resilience. Collaborative leadership as a change agent, collaboration between information technology (IT) and operational technology (OT), and effective change management were identified as the key enablers for digital transformation of healthcare enterprises. This study will inform digital transformation leaders, researchers, and healthcare enterprises in the development of enterprise-level proactive strategies, business use cases, and roadmaps for digital transformation.","author":[{"family":"Hundal","given":"Gaganpreet"},{"family":"Rhodes","given":"Donna"},{"family":"Laux","given":"Chad"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/su17135690","URL":"https://doi.org/10.3390/su17135690","source":"openalex"},{"id":"oa:W4409572172","type":"article-journal","title":"Transfer learning assessment of small datasets relating manufacturing parameters with electrochemical energy cell component properties","abstract":"The performance of electrochemical cells for energy storage and conversion can be improved by optimizing their manufacturing processes. This can be time-consuming and costly with the traditional trial-and-error approaches. Machine Learning (ML) models can help to overcome these obstacles. In academic research laboratories, manufacturing dataset sizes can be small, while ML models typically require large amounts of data. In this work, we propose a simple but still novel application of a Transfer Learning (TL) approach to address these manufacturing problems with a small amount of data. We have tested this approach with pre-existing experimental and stochastically generated datasets. These datasets consisted of component properties (e.g., electrode density) related to different manufacturing parameters (e.g., solid content, comma gap, coating speed). We have demonstrated the robustness of our TL approach for manufacturing problems by achieving excellent prediction performance for electrodes in lithium-ion batteries and gas diffusion layers in fuel cells.","author":[{"family":"Fernándeznavarro","given":"Francisco"},{"family":"Saravanan","given":"Soorya"},{"family":"Omongos","given":"Rashen"},{"family":"Troncoso","given":"Javier"},{"family":"Galvezaranda","given":"Diego"},{"family":"Franco","given":"Alejandro"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s44334-025-00024-1","URL":"https://doi.org/10.1038/s44334-025-00024-1","source":"openalex"},{"id":"oa:W4414611822","type":"article-journal","title":"Statistical Learning-Assisted Evolutionary Algorithm for Digital Twin-Driven Job Shop Scheduling with Discrete Operation Sequence Flexibility","abstract":"With the rapid development of Industry 5.0, smart manufacturing has become a key focus in production systems. Hence, achieving efficient planning and scheduling on the shop floor is important, especially in job shop environments, which are widely encountered in manufacturing. However, traditional job shop scheduling problems (JSP) assume fixed operation sequences, whereas in modern production, some operations exhibit sequence flexibility, referred to as sequence-free operations. To mitigate this gap, this paper studies the JSP with discrete operation sequence flexibility (JSPDS), aiming to minimize the makespan. To effectively solve the JSPDS, a mixed-integer linear programming model is formulated to solve small-scale instances, verifying multiple optimal solutions. To enhance solution quality for larger instances, a digital twin (DT)–enhanced initialization method is proposed, which captures expert knowledge from a high-fidelity virtual workshop to generate high-quality initial population. In addition, a statistical learning-assisted local search method is developed, employing six tailored search operators and Thompson sampling to adaptively select promising operators during the evolutionary algorithm (EA) process. Extensive experiments demonstrate that the proposed DT-statistical learning EA (DT-SLEA) significantly improves scheduling performance compared with state-of-the-art algorithms, highlighting the effectiveness of integrating digital twin and statistical learning techniques for shop scheduling problems. Specifically, in the Wilcoxon test, pairwise comparisons with the other algorithms show that DT-SLEA has p-values below 0.05. Meanwhile, the proposed framework provides guidance on utilizing symmetry to improve optimization in complex manufacturing systems.","author":[{"family":"Jia","given":"Yan"},{"family":"Cheng","given":"Weiyao"},{"family":"Meng","given":"Leilei"},{"family":"Zhang","given":"Chaoyong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/sym17101614","URL":"https://doi.org/10.3390/sym17101614","source":"openalex"},{"id":"oa:W4415172590","type":"article-journal","title":"Cloud–edge–device collaborative computing in smart agriculture: architectures, applications, and future perspectives","abstract":"Smart agriculture is rapidly evolving in response to growing global demands for food security and sustainable resource management. Cloud-edge-device collaborative computing has emerged as a transformative paradigm, addressing the limitations of traditional centralized architectures by enabling distributed intelligence, real-time processing, and adaptive decision-making. This review provides a comprehensive overview of the architectures, technical characteristics, and application scenarios of cloud-edge-device collaboration in agriculture. Key domains covered include environmental monitoring, intelligent irrigation, UAV-machinery coordination, livestock health management, and pest and disease control. Major challenges such as device heterogeneity, data consistency, resource constraints, and privacy concerns are identified and discussed. Furthermore, six critical research directions are outlined, including intelligent scheduling algorithms, lightweight edge AI, hierarchical data fusion, federated learning, interoperability frameworks, and digital twin technologies. This review aims to serve as a practical reference and theoretical foundation for advancing the design and implementation of next-generation smart agriculture systems.","author":[{"family":"Yu","given":"Pengpeng"},{"family":"Teng","given":"Fei"},{"family":"Zhu","given":"Wenhui"},{"family":"Shen","given":"Chaoping"},{"family":"Chen","given":"Zhenping"},{"family":"Song","given":"Jinxiu"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3389/fpls.2025.1668545","URL":"https://doi.org/10.3389/fpls.2025.1668545","source":"openalex"},{"id":"oa:W4412916538","type":"article-journal","title":"Digital Twins in Industrial Maintenance: Integrating Virtual and Augmented Reality for Innovation","abstract":"The optimization of processes, cost reduction, and increased efficiency stand as primary objectives within the textile industry. With the advancement of technologies, the digital twin concept – a digital representation model of the processes and physical objects within the manufacturing environment – has been extensively employed. This article aims to examine and investigate how it is possible to integrate the use of augmented and virtual reality technologies with a digital twin model, in order to enhance equipment maintenance within this industry. In addition to a review of the current state of the art in this field, several articles related to the topic were studied, complemented by the results of a small-scale experiment. These findings indicate that the utilization of these technologies is indeed advantageous in supporting equipment maintenance and managing the flow of data generated by real physical objects and processes.","author":[{"family":"Miranda","given":"João"},{"family":"Costa","given":"André"},{"family":"Romero","given":"Luís"},{"family":"Faria","given":"Pedro"}],"issued":{"date-parts":[[2025]]},"DOI":"10.17013/wjis.v2i2.35","URL":"https://doi.org/10.17013/wjis.v2i2.35","source":"openalex"},{"id":"oa:W4410827513","type":"article-journal","title":"Driving Sustainability Performance in Hotels Through Green Digital Leadership and Circular Economy: The Moderating Role of Hotel Green Efficacy","abstract":"This study examines the role of green digital transformational leadership (GDTL) in enhancing sustainability performance in the hotel industry through the mediating mechanism of circular economy (CE) practices and the moderating effects of otel green efficacy (HGE). Grounded in the dynamic capabilities theory, natural resource-based view (NRBV) theory, and social exchange theory, a novel conceptual model that bridges digital innovation, ecological stewardship, and organizational psychology was proposed. The study adopted a quantitative approach and used a self-administered questionnaire survey to collect data from 402 employees across green-certified hotels in Sharm El-Sheikh, Egypt. Participants were recruited using a stratified sampling method to ensure sectoral representation. Data analysis techniques included performing partial least squares structural equation modeling (PLS-SEM) using Smart PLS 3.0. Key findings reveal that GDTL directly influences the three key aspects of sustainability performance in hotels, including environmental, economic, and social aspects. Likewise, CE practices significantly mediate the linkage between GDTL and hotel sustainability performance. Notably, HGE strengthens the GDTL-CE relationship, underscoring the critical role of employee empowerment in translating leadership vision into regenerative practices. These results add to the growing literature on sustainable leadership by revealing how digital tools like AI, blockchain, and closed-loop systems can synergize to support economic growth and conserve natural resources.","author":[{"family":"Elshaer","given":"Ibrahim"},{"family":"Azazz","given":"Alaa"},{"family":"Alyahya","given":"Mansour"},{"family":"Fayyad","given":"Sameh"},{"family":"Taleb","given":"Mohamed"},{"family":"Mohammad","given":"Abuelkassem"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/systems13060415","URL":"https://doi.org/10.3390/systems13060415","source":"openalex"},{"id":"oa:W4411353547","type":"article-journal","title":"MetalMind: A knowledge graph-driven human-centric knowledge system for metal additive manufacturing","abstract":"Abstract In the Industry 5.0 era, increasing manufacturing complexity and fragmented knowledge pose challenges for decision-making and workforce development. To tackle this, we present a human-centric knowledge system that integrates explicit knowledge from formal sources and implicit knowledge from expert insights. The system features three core innovations: (1) an automated KG construction pipeline leveraging large language models (LLMs) with collaborative verification to enhance knowledge extraction accuracy and minimize hallucinations; (2) a hybrid retrieval framework that combines vector-based, graph-based, and hybrid retrieval strategies for comprehensive knowledge access, achieving a 336.61% improvement over vector-based retrieval and a 68.04% improvement over graph-based retrieval in global understanding; and (3) an MR-enhanced interface that supports immersive, real-time interaction and continuous knowledge capture. Demonstrated through a metal additive manufacturing (AM) case study, this approach enriches domain expertise, improves knowledge representation and retrieval, and fosters enhanced human-machine collaboration, ultimately supporting adaptive upskilling in smart manufacturing.","author":[{"family":"Fan","given":"Haolin"},{"family":"Fan","given":"Zhen"},{"family":"Liu","given":"Chenshu"},{"family":"Zhu","given":"Jianhao"},{"family":"Gibbs","given":"Tom"},{"family":"Fuh","given":"Jerry"},{"family":"Lu","given":"Wen"},{"family":"Li","given":"Bingbing"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s44334-025-00038-9","URL":"https://doi.org/10.1038/s44334-025-00038-9","source":"openalex"},{"id":"oa:W7131638452","type":"article-journal","title":"Digital product passports","abstract":"Abstract Digital product passports (DPPs) will become mandatory in the European Union (EU) for a wide range of product categories under the Ecodesign for Sustainable Products Regulation (ESPR). DPPs are digital artifacts that capture and share essential product data across organizational boundaries. They have the potential to enhance transparency across value chains and ecosystems, thereby supporting data-driven decision-making throughout the entire product lifecycle and unlocking new opportunities for sustainable value creation. Despite growing momentum, the design, implementation, and management of DPPs are still evolving, resulting in a vast space of design options and ambiguity. This fundamentals paper reports on a multivocal literature review to advance our understanding of this emerging phenomenon from an information systems perspective. We position the DPP against adjacent concepts, define it, develop a conceptual framework, and present a demonstrative scenario that instantiates the conceptual framework’s elements. The findings have implications for DPP research and practice and lay the groundwork for achieving both regulatory compliance and enabling additional sustainable pathways.","author":[{"family":"Petrik","given":"Dimitri"},{"family":"Strobel","given":"Gero"},{"family":"Schoormann","given":"Thorsten"},{"family":"Möller","given":"Frederik"},{"family":"Hoppe-Ludwig","given":"Christoph"},{"family":"Springer","given":"Virginia"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s12525-026-00877-0","URL":"https://doi.org/10.1007/s12525-026-00877-0","source":"openalex"},{"id":"oa:W4412598296","type":"article-journal","title":"Temperature Monitoring in Metal Additive Manufacturing in the Era of Industry 4.0","abstract":"The field of metal additive manufacturing has witnessed significant growth in recent years, with technology offering the ability to produce complex geometries that are challenging to manufacture using the traditional methods. In situ monitoring and control of the manufacturing process are crucial for increasing the production capacity and improving the quality of manufactured parts. This article provides a comparative analysis of computational, indirect, and direct methods for in situ temperature monitoring during additive manufacturing of metal alloy components. Furthermore, it discusses the current status, recent improvements, and perspectives for in situ temperature measurements. The basic principles of thermal imaging, two-color pyrometry, and millimeter-wave radiometry are explored, highlighting their limitations for addressing challenges related to material emissivity and rapid changes in building material composition. Overcoming the challenges related to the inaccessibility of the chamber where the parts are formed, direct temperature measurements would allow for the integration of collected information into big data systems. Within the framework of Industry 4.0, this approach offers a viable alternative to the conventional metal shaping processes, improving the production capacity and part quality. This research aims to contribute to ongoing advancements in metal additive manufacturing and its potential to completely replace traditional metal casting practices in the Industry 4.0 era.","author":[{"family":"Mitrašinović","given":"Aleksandar"},{"family":"Đurđević","given":"Teodora"},{"family":"Nešković","given":"Jasmina"},{"family":"Radosavljević","given":"Milinko"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/technologies13080317","URL":"https://doi.org/10.3390/technologies13080317","source":"openalex"},{"id":"oa:W4410778893","type":"article-journal","title":"Digital Technologies as Enablers of the Circular Economy: An Empirical Perspective on the Role of Companies in Driving Customer Behaviour Change","abstract":"ABSTRACT The circular economy concept has gained significant attention in the academic and industrial discourse. Yet, the widespread adoption of circular business models is still outstanding, with a lack of customer acceptance representing a critical barrier. Recently, there has been a growing interest in the potential of digital technologies to expedite the circular economy's broader implementation. This study investigates the role of digital technologies in enhancing customer acceptance of circular business models in consumer‐facing industries. To extract insights from practice, we conducted 41 semi‐structured interviews with experts from companies that have implemented circular economy principles, management consulting firms, and academia. As a result, we provide thematical structures of (1) 35 factors affecting customer acceptance of circular business models, (2) 36 practices that organizations can deploy to address these factors and enhance customer acceptance, and (3) 19 digital technologies to facilitate such practices. Our findings combine and extend insights from the distinct research streams of behavioral science and theory of digital technology management by adding a technology dimension to the behavior change wheel, highlighting the interplay between sources of behavior (factors), intervention functions (practices), and technological enablers (digital technologies). This extended framework will support researchers investigating the role of digital technologies and inform companies about the use of digital technologies in circular business model innovation as an enabler of customer acceptance.","author":[{"family":"Bücker","given":"Christian"},{"family":"Pantel","given":"Julia"},{"family":"Geissdoerfer","given":"Martin"},{"family":"Bhattacharjya","given":"Jyotirmoyee"},{"family":"Kumar","given":"Mukesh"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1111/radm.12762","URL":"https://doi.org/10.1111/radm.12762","source":"openalex"},{"id":"oa:W4406324336","type":"article-journal","title":"Advancing Digital Transformation in Material Science: The Role of Workflows Within the MaterialDigital Initiative","abstract":"The MaterialDigital initiative represents a major driver toward the digitalization of material science. Next to providing a prototypical infrastructure required for building a shared data space and working on semantic interoperability of data, a core focus area of the Platform MaterialDigital (PMD) is the utilization of workflows to encapsulate data processing and simulation steps in accordance with findable, accessible, interoperable, and reusable principles. In collaboration with the funded projects of the initiative, the workflow working group strives to establish shared standards, enhancing the interoperability and reusability of scientific data processing steps. Central to this effort is the Workflow Store, a pivotal tool for disseminating workflows with the community, facilitating the exchange and replication of scientific methodologies. This article discusses the inherent challenges of adapting workflow concepts, providing the perspective on developing and using workflows in the respective domain of the various funded projects. Additionally, it introduces the Workflow Store's role within the initiative and outlines a future roadmap for the PMD workflow group, aiming to further refine and expand the role of scientific workflows as a means to advance digital transformation and foster collaborative research within material science.","author":[{"family":"Bekemeier","given":"Simon"},{"family":"Rêgo","given":"Celso"},{"family":"Mai","given":"Han"},{"family":"Saikia","given":"Ujjal"},{"family":"Waseda","given":"Osamu"},{"family":"Apel","given":"Markus"},{"family":"Arendt","given":"Felix"},{"family":"Aschemann","given":"Alexander"},{"family":"Bayerlein","given":"Bernd"},{"family":"Courant","given":"Robert"},{"family":"Dziwis","given":"Gordian"},{"family":"Fuchs","given":"Florian"},{"family":"Giese","given":"Ulrich"},{"family":"Junghanns","given":"Kurt"},{"family":"Kamal","given":"Mohamed"},{"family":"Koschmieder","given":"Lukas"},{"family":"Leineweber","given":"Sebastian"},{"family":"Luger","given":"Marc"},{"family":"Lukas","given":"Marco"},{"family":"Maas","given":"Jürgen"},{"family":"Mertens","given":"Jana"},{"family":"Mieller","given":"Björn"},{"family":"Overmeyer","given":"Ludger"},{"family":"Pirch","given":"Norbert"},{"family":"Reimann","given":"Jan"},{"family":"Schröck","given":"Sebastian"},{"family":"Schulze","given":"Philipp"},{"family":"Schuster","given":"Jörg"},{"family":"Seidel","given":"Alexander"},{"family":"Shchyglo","given":"Oleg"},{"family":"Sierka","given":"Marek"},{"family":"Silze","given":"Frank"},{"family":"Stier","given":"Simon"},{"family":"Tegeler","given":"Marvin"},{"family":"Unger","given":"Jörg"},{"family":"Weber","given":"Matthias"},{"family":"Hickel","given":"Tilmann"},{"family":"Schaarschmidt","given":"Jörg"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1002/adem.202402149","URL":"https://doi.org/10.1002/adem.202402149","source":"openalex"},{"id":"oa:W7127312444","type":"article-journal","title":"Conceiving Socio-technical Information Systems from the Perspective of Digital Twins","abstract":"Digital twins (DT) present benefits, challenges, and opportunities well aligned to socio-technical information systems.The challenge for information systems engineering is the development of organization excellence solutions through virtual factory replication, as cited by Grieves in the manufacturing industry [Grieves, 2014].The empirically defined information systems framework development using DT with interacting organizational sub-systems that align peoples' capabilities with their goals, related to processes operating within a physical infrastructure, and share cultural assumptions and norms is not a trivial task.The information systems community might embrace this challenge for the following ten years to conceive successful socio-technical information systems..","author":[{"family":"Ralha","given":"Célia"},{"family":"Claro","given":"Daniela"},{"family":"Maciel","given":"Rita"}],"issued":{"date-parts":[[2025]]},"DOI":"10.5753/sbc.rt.2025.181.13","URL":"https://doi.org/10.5753/sbc.rt.2025.181.13","source":"openalex"},{"id":"oa:W4416424431","type":"article-journal","title":"Towards enhanced cybersecurity in industrial control systems: a systematic review of context-based modeling, digital twins, and machine learning approaches","abstract":"Abstract The increasing integration of Industrial Control Systems (ICS) and Cyber-Physical Systems (CPS) with the Internet of Things (IoT) has significantly enhanced their operational efficiency but also exposed them to advanced cyber threats. Traditional cybersecurity approaches, often tailored for IT systems, must address the unique complexities of ICS and CPS environments. This paper systematically reviews the integration of three critical areas: context-based modeling, digital twins, and machine learning (ML), to enhance cybersecurity for ICS and CPS. Context-based modeling provides dynamic, situational awareness; digital twins offer real-time system replicas for monitoring and simulation; and ML delivers predictive and adaptive threat detection and response capabilities. The review synthesizes findings from recent literature to answer four research questions focusing on methodologies in context-based modeling, applications of digital twins and ML in attack detection, and integrating these approaches for improved cyber resilience. The results demonstrate the synergistic potential of combining these technologies, enabling real-time anomaly detection, predictive threat analysis, and adaptive response mechanisms. Challenges such as data limitations, scalability, and verification complexities are vital areas requiring further research. This integrated framework offers a robust pathway for securing critical infrastructure and advancing cybersecurity practices in increasingly interconnected ICS and CPS environments.","author":[{"family":"Abraham","given":"Doney"},{"family":"Erceylan","given":"Gizem"},{"family":"Gkioulos","given":"Vasileios"},{"family":"Houmb","given":"Siv"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1007/s10207-025-01158-1","URL":"https://doi.org/10.1007/s10207-025-01158-1","source":"openalex"},{"id":"oa:W4412676542","type":"article-journal","title":"Modeling Human Tasks and Motion in 360-Degree Videos for Real-Time Digital Twin Application","abstract":"This research presents a framework for real-time task detection and digital twin modeling based on human posture estimation from 360° videos. The system integrates markerless human posture estimation with task classification and digital twin visualization. Posture estimation using MediaPipe provided accurate skeletal tracking, while kinematic feature extraction enabled detailed motion analysis. Gaussian Mixture Models effectively segmented task transitions, distinguishing between different phases of ladder use. Gaussian Splatting helped realistic and adaptive visualizations, for a digital twin that accurately represented human-environment interactions. Using these techniques, the framework achieves a non-intrusive and scalable approach to task detection and digital twin modeling. The system captured human movements from 360° videos and classified them into task-specific segments. The results demonstrated that task detection based on posture estimation could improve workplace safety by identifying inefficient or hazardous postures. The digital twin representation can be analyzed for movement patterns and ergonomic risk assessment.","author":[{"family":"Iyer","given":"Hari"},{"family":"Eiris","given":"Ricardo"},{"family":"Jeong","given":"Heejin"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1177/10711813251358789","URL":"https://doi.org/10.1177/10711813251358789","source":"openalex"},{"id":"oa:W4406290456","type":"article-journal","title":"Challenges and opportunities for high-quality battery production at scale","abstract":"As the world electrifies, global battery production is expected to surge. However, batteries are both difficult to produce at the gigawatt-hour scale and sensitive to minor manufacturing variation. As a result, the battery industry has already experienced both highly-visible safety incidents and under-the-radar reliability issues-a trend that will only worsen if left unaddressed. Here we highlight both the challenges and opportunities to enable battery quality at scale. We first describe the interplay between various battery failure modes and their numerous root causes. We then discuss how to manage and improve battery quality during production. We hope our perspective brings greater visibility to the battery quality challenge to enable safe global electrification.","author":[{"family":"Attia","given":"Peter"},{"family":"Moch","given":"Eric"},{"family":"Herring","given":"Patrick"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1038/s41467-025-55861-7","URL":"https://doi.org/10.1038/s41467-025-55861-7","source":"openalex"},{"id":"oa:W4412447404","type":"article-journal","title":"Green buildings and digital technologies: A pathway to sustainable development","abstract":"Digital technologies have the potential to enhance the performance of green buildings to address climate change impacts. Therefore, this study explores the nexus between green buildings and digital technologies, which is a crucial point that has the potential to reshape the field of sustainable development. This examination is done with the utilization of bibliometric analysis and qualitative systematic approach. This review aims to conduct a thorough analysis of green buildings and digital technologies for a sustainable future, with a focus on the integration of digital technologies, associated challenges and solutions, key research techniques, knowledge gaps, and future research directions within the realm of green buildings. To do this, a bibliometric analysis was initially conducted after retrieving 135 articles from the Scopus database. Next, a qualitative systematic approach was conducted. In addition, five challenges and technological solutions were identified; (i) high initial costs, (ii) limited availability of sustainable materials, (iii) energy inefficiency and performance variability, (iv) regulatory compliance and certification requirements, and (v) waste management and recycling. Key research techniques were identified (i) simulation and modeling, (ii) decision-making techniques and (iii) surveys and interviews (qualitative and quantitative techniques). This review study offers both theoretical and practical contributions to the current research on green buildings and digital technologies, with the aim of improving sustainability. Theoretically, this review study strengthens the body of knowledge by integrating sustainable practices with advanced digital technologies, hence improving energy efficiency and sustainability. It provides practical insights for researchers, practitioners, and policymakers to implement digital technologies in construction projects, promoting sustainable designs. These insights can assist researchers in refining technology-driven sustainability models, guide practitioners in implementing these solutions more effectively, and enable policymakers to craft regulations that promote innovation and environmental stewardship in the sector.","author":[{"family":"Manzoor","given":"Bilal"},{"family":"Antwiafari","given":"Maxwell"},{"family":"Alotaibi","given":"Khalid"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.grets.2025.100243","URL":"https://doi.org/10.1016/j.grets.2025.100243","source":"openalex"},{"id":"oa:W7129096244","type":"article-journal","title":"Comparative Evaluation of Voxel and Mesh Representations for Digital Defect Detection in Construction-Scale Additive Manufacturing","abstract":"Additive manufacturing is increasingly used in construction, yet reliable quality assurance for three-dimensional-printed concrete elements remains a major challenge. Existing digital defect-detection methods, particularly voxel-based and mesh-based approaches, are often evaluated separately, which limits understanding of their relative capabilities for construction-scale inspection. This study establishes a controlled comparison of the two representations using identical scan-to-design data, consistent preprocessing, and unified defect thresholding. A voxel pipeline employing signed distance fields and a three-dimensional convolutional neural network, and a mesh pipeline using triangular surface reconstruction, geometric surface descriptors, and MeshCNN, were applied to structured-light scans of printed clay wall segments containing intentional voids, material buildup, and layer-height inconsistencies. Across common performance metrics, the voxel-based method achieved a recall of 95% for spatially coherent, volumetric-consistent void-related anomalies inferred from surface geometry, reflecting improved aggregation of distributed deviations, while the mesh-based method attained a mean surface defect localization error of 0.32 mm with a substantially lower computational cost in runtime and memory. These results clarify representation-dependent trade-offs and provide guidance for selecting appropriate inspection pipelines in extrusion-based construction. The findings establish a controlled, construction-oriented comparative framework for digital defect detection and support more efficient, reliable, and scalable quality-assurance workflows for sustainable additive manufacturing.","author":[{"family":"Mirmotalebi","given":"Seyedali"},{"family":"Moon","given":"Hyosoo"},{"family":"Tesiero","given":"Raymond"},{"family":"Noor","given":"Sadia"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/buildings16040805","URL":"https://doi.org/10.3390/buildings16040805","source":"openalex"},{"id":"oa:W7108342056","type":"article-journal","title":"An Industry 4.0 Framework for the Smart Production Management of Renewable Energy and Water Systems: An Application of AI, IoT, and Digital Twin Technologies","abstract":"This study develops an integrated Industry 4.0 framework for smart production management in renewable energy systems applied to water processes. The framework combines artificial intelligence, the Internet of Things, and digital twin technologies to improve production planning, system reliability, and environmental performance. A neural network model was implemented for predictive analytics and achieved high accuracy (MAE = 0.82, R² = 0.92), enabling precise forecasting for energy generation and operational scheduling. Optimization algorithms, including genetic algorithms and particle swarm optimization, increased energy utilization efficiency from 65% to 85% and reduced operational costs by 15%. The IoT utilization enhanced real-time monitoring and reduced fault detection time from 120 minutes to 15 minutes, significantly improving maintenance response. Digital twin simulations allowed process optimization and predictive maintenance, further increasing production efficiency to 92% and system uptime to 99.5%. The approaches also led to a 20% reduction in CO₂ emissions, demonstrating both economic and environmental benefits. Overall, this framework offers a practical and data-driven solution for improving the efficiency and sustainability of renewable energy systems in water applications and contributes to the advancement of smart manufacturing in industrial engineering.","author":[{"family":"Mukhitdinov","given":"Otabek"},{"family":"Jumanazarov","given":"Doniyor"},{"family":"Khudoynazarov","given":"Egambergan"},{"family":"Safarova","given":"Lola"},{"family":"Sakhabayeva","given":"Saira"},{"family":"Alsayah","given":"Ahmed"}],"issued":{"date-parts":[[2025]]},"DOI":"10.24867/ijiem-397","URL":"https://doi.org/10.24867/ijiem-397","source":"openalex"},{"id":"oa:W4411624691","type":"article-journal","title":"Advances in the Additive Manufacturing of Superalloys","abstract":"This study presents a bibliometric analysis of the evolution and research trends in the additive manufacturing (AM) of superalloys over the last decade (2015–2025). The review follows a structured methodology based on the PRISMA 2020 protocol, utilizing data from the Scopus and Web of Science (WoS) databases. Particular attention is devoted to the intricate process–structure–property relationships and the specific behavioral trends associated with different superalloy families, namely Ni-based, Co-based, and Fe–Ni-based systems. The findings reveal a substantial growth in scientific output, with the United States and China leading contributions and an increasing trend in international collaboration. Key research areas include process optimization, microstructural evolution and control, mechanical property assessment, and defect minimization. The study highlights the pivotal role of technologies such as laser powder bed fusion, electron beam melting, and directed energy deposition in the fabrication of high-performance components. Additionally, emerging trends point to the integration of machine learning and artificial intelligence for real-time quality monitoring and manufacturing parameter optimization. Despite these advancements, challenges such as anisotropic properties, porosity issues, and process sustainability remain critical for both industrial applications and future academic research in superalloys.","author":[{"family":"Bosque","given":"Antonio"},{"family":"Fernándezarias","given":"Pablo"},{"family":"Vergara","given":"Diego"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/jmmp9070215","URL":"https://doi.org/10.3390/jmmp9070215","source":"openalex"},{"id":"oa:W4409310425","type":"article-journal","title":"A risk analysis method for implementation of additive manufacturing","abstract":"The evolution of additive manufacturing (AM) over the past few decades has significantly shifted its application from prototyping to the production of final products. Despite this progress, the industrial uptake of AM remains limited due to the complex integration challenges within existing manufacturing value chains. This paper addresses the gap by presenting a prescriptive approach for assessing risks associated with incorporating AM into established workflows. Utilising two case studies from the ‘Demonstration of Infrastructure for Digitalization enabling industrialisation of AM (DiDAM)’ project, which involves several Swedish manufacturing companies, this study develops a methodology for risk assessment. The proposed method involves mapping workflows into multi-domain matrices, establishing dependencies with uncertainty values, and performing risk analysis to determine potential impacts. Results indicate that this quantitative risk assessment approach provides valuable insights into hidden issues that could affect the implementation of AM. By offering a decision-support tool for managers, this methodology enhances the likelihood of successful integration of AM and supports digitalisation efforts in traditional manufacturing settings. The practical applications of this approach are demonstrated through a detailed analysis of the two industrial cases.","author":[{"family":"Brahma","given":"Arindam"},{"family":"Hajali","given":"Tina"},{"family":"Mallalieu","given":"Adam"},{"family":"Isaksson","given":"Ola"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1080/09544828.2025.2489641","URL":"https://doi.org/10.1080/09544828.2025.2489641","source":"openalex"},{"id":"oa:W4410004311","type":"article-journal","title":"Digital innovation, human capital allocation, and labour share: Empirical evidence from listed companies in China","abstract":"Digital technology is increasingly blurring the lines between humans and machines, significantly influencing the distribution of income among workers. The question of how businesses can capitalise on the benefits of digital advancement by optimising internal human capital allocation during the digital innovation process has become a critical concern. This study utilises the Sentence-BERT(SBERT) model to identify digital innovation and examines its effects on the labour share within firms, alongside the underlying mechanisms from the viewpoint of human capital allocation. The research findings are as follows: First, digital innovation has a positive and significant impact on the labour share, a conclusion that remains robust after conducting various sensitivity tests and addressing endogeneity issues. Second, the mechanism analysis reveals that changes in human capital allocation serve as a crucial mediating factor between digital innovation and labour share. Further exploration indicates that skills training, as an element of human capital allocation, demonstrates varying levels of influence across various company sizes and industry characteristics. Third, the positive impact of digital innovation on labour share is more pronounced in regions with supportive business environments, high-tech sectors and firms with superior corporate governance . Lastly, for ordinary employees, digital innovation enhances their labour share. Conversely, for management, while digital innovation reduces their labour share, it increases their equity incentive, suggesting that digital innovation aids in bridging the digital divide within firms and fosters a more equitable distribution of benefits. This study not only enriches the theoretical understanding of the effects of digital innovation on labour income but also encourages the practical application of digital innovation in reducing the wealth gap and achieving shared prosperity.","author":[{"family":"Ling","given":"Hongcheng"},{"family":"Ding","given":"Xuebin"},{"family":"Tao","given":"Changqi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1016/j.jik.2025.100705","URL":"https://doi.org/10.1016/j.jik.2025.100705","source":"openalex"},{"id":"oa:W4415240062","type":"manuscript","title":"Towards AI-based Sustainable and XR-based human-centric manufacturing: Implementation of ISO 23247 for digital twins of production systems","abstract":"Since the introduction of Industry 4.0, digital twin technology has significantly evolved, laying the groundwork for a transition toward Industry 5.0 principles centered on human-centricity, sustainability, and resilience. Through digital twins, real-time connected production systems are anticipated to be more efficient, resilient, and sustainable, facilitating communication and connectivity between digital and physical systems. However, environmental performance and integration with virtual reality (VR) and artificial intelligence (AI) of such systems remain challenging. Further exploration of digital twin technologies is needed to validate the real-world impact and benefits. This paper investigates these challenges by implementing a real-time digital twin based on the ISO 23247 standard, connecting the physical factory and simulation software with VR capabilities. This digital twin system provides cognitive assistance and a user-friendly interface for operators, thereby improving cognitive ergonomics. The connection of the Internet of Things (IoT) platform allows the digital twin to have real-time bidirectional communication, collaboration, monitoring, and assistance. A lab-scale drone factory was used as the digital twin application to test and evaluate the ISO 23247 standard and its potential benefits. Additionally, AI integration and environmental performance Key Performance Indicators (KPIs) have been considered as the next stages in improving VR-integrated digital twins. With a solid theoretical foundation and a demonstration of the VR-integrated digital twins, this paper addresses integration issues between various technologies and advances the framework of digital twins based on ISO 23247.","author":[{"family":"Cao","given":"Huizhong"},{"family":"Söderlund","given":"Henrik"},{"family":"Fang","given":"Qi"},{"family":"Chen","given":"Siyuan"},{"family":"Erdal","given":"Lejla"},{"family":"Gubartalla","given":"Ammar"},{"family":"Lopes","given":"Paulo"},{"family":"Shao","given":"Guodong"},{"family":"Lonnehed","given":"Per"},{"family":"Putto","given":"Henri"},{"family":"Ahmed","given":"Abbe"},{"family":"Ekered","given":"Sven"},{"family":"Johansson","given":"Björn"}],"issued":{"date-parts":[[2025]]},"DOI":"10.48550/arxiv.2508.14580","URL":"https://doi.org/10.48550/arxiv.2508.14580","source":"openalex"},{"id":"oa:W7166703752","type":"article-journal","title":"The Impact of IoT and Digital Twin Adoption on Waste Reduction in the Textile Industry in Bandung","abstract":"The textile industry is one of the most important manufacturing sectors in Indonesia; however, it faces significant challenges related to production waste and resource inefficiency. The adoption of Industry 4.0 technologies, particularly the Internet of Things (IoT) and Digital Twin, has emerged as a promising solution for improving operational efficiency and supporting sustainable manufacturing practices. This study aims to analyze the impact of IoT implementation and Digital Twin implementation on waste reduction in the textile industry in Bandung. A quantitative research approach was employed using a survey method involving 75 respondents from textile manufacturing companies. Data were collected through a structured questionnaire measured using a five-point Likert scale and analyzed using SPSS version 25. The analytical techniques included validity and reliability tests, classical assumption tests, multiple linear regression analysis, coefficient of determination analysis, and hypothesis testing. The results indicate that IoT implementation has a positive and significant effect on waste reduction. Similarly, Digital Twin implementation positively and significantly affects waste reduction. Furthermore, the simultaneous test demonstrates that IoT and Digital Twin implementation jointly influence waste reduction. The coefficient of determination (R² = 0.697) indicates that 69.7% of the variation in waste reduction can be explained by the two independent variables. These findings suggest that the integration of IoT and Digital Twin technologies enhances operational visibility, predictive decision-making, and process optimization, thereby reducing production waste in textile manufacturing. The study contributes to the growing literature on Industry 4.0 and provides practical insights for textile companies seeking to improve sustainability and operational efficiency through digital transformation.","author":[{"family":"Nurhasanah","given":"Dila"},{"family":"Susilo","given":"Anton"},{"family":"Muhtadi","given":"Muhamad"}],"issued":{"date-parts":[[2026]]},"DOI":"10.58812/wsshs.v4i06.2946","URL":"https://doi.org/10.58812/wsshs.v4i06.2946","source":"openalex"},{"id":"oa:W4415842840","type":"manuscript","title":"From Silicon to Serum: The Critical Path of Validating Computational Predictions in Modern Vaccinology","abstract":"Vaccinology has undergone a profound paradigm shift—from traditional empirical discovery to a rational, engineering-based discipline. This transformation is driven by the synergistic and iterative cycle between computational (in silico) prediction and rigorous experimental validation, now the cornerstone of modern, accelerated vaccine development. This review delineates the architecture of this integrated pipeline. We first survey the expanding computational toolbox for vaccine design, spanning immunoinformatics and reverse vaccinology for antigen discovery, AI-driven structure-based engineering of stabilized immunogens, and systems vaccinology for modeling immune dynamics. We then outline the “experimental gauntlet”: a hierarchy of biochemical, cellular, and in vivo preclinical assays that verify computational hypotheses—confirming molecular structures, binding kinetics, immunogenicity, and protective efficacy. The power of this fusion is exemplified by landmark case studies: the structure-guided triumph against Respiratory Syncytial Virus (RSV), the rapid development of COVID-19 mRNA vaccines, the iterative germline-targeting design of HIV immunogens, and the frontier of personalized neoantigen cancer vaccines. Together, these advances demonstrate that the union of predictive computation and empirical validation has moved from promise to proven paradigm. Looking ahead, emerging technologies such as generative AI and immune digital twins are poised to further accelerate this virtuous cycle, transforming vaccinology into a more precise, predictable, and rapid science capable of meeting future global health challenges.","author":[{"family":"Zhang","given":"Yu"},{"family":"Pei","given":"Yusheng"},{"family":"Tan","given":"Dejiang"},{"family":"Du","given":"Yingxun"},{"family":"Cai","given":"Tong"},{"family":"Zhang","given":"Yuan"},{"family":"He","given":"Qing"}],"issued":{"date-parts":[[2025]]},"DOI":"10.20944/preprints202511.0078.v1","URL":"https://doi.org/10.20944/preprints202511.0078.v1","source":"openalex"},{"id":"oa:W4411012562","type":"article-journal","title":"DEVELOPMENT OF A FOG COMPUTING-BASED REAL-TIME FLOOD PREDICTION AND EARLY WARNING SYSTEM USING MACHINE LEARNING AND REMOTE SENSING DATA","abstract":"This study introduces a novel, fog computing-based real-time flood prediction and early warning system that integrates advanced machine learning algorithms with remote sensing technologies to address the limitations of traditional flood monitoring infrastructures. Existing systems often struggle with latency, over-reliance on centralized cloud computing, and fragmented data integration, which collectively hinder their effectiveness during critical flood events. To overcome these challenges, this research employed a mixed methods research design, combining quantitative experimentation with qualitative inquiry to comprehensively evaluate the system’s predictive performance, operational resilience, and stakeholder usability. The quantitative component involved the deployment of an optimized wireless sensor network, designed using Low Energy Adaptive Clustering Hierarchy (LEACH) and Particle Swarm Optimization (PSO), to collect real-time hydrological data including rainfall, river levels, and soil moisture. These data streams were fused with high-resolution remote sensing imagery from Sentinel-1 SAR and Sentinel-2 MSI, and processed using advanced machine learning models such as Long Short-Term Memory (LSTM) networks and Random Forest classifiers. The LSTM model achieved high predictive accuracy with an RMSE of 0.38 and NSE of 0.84, while fog computing nodes reduced latency by over 60%, enabling localized, real-time alert dissemination even during internet outages. The qualitative component involved 23 semi-structured interviews with disaster management authorities, field technicians, and community representatives to assess the system’s usability, trustworthiness, and practical challenges. The triangulation of findings confirmed the technical validity, operational reliability, and end-user relevance of the system. By integrating decentralized processing, intelligent forecasting, and human-centered design, this research contributes a scalable, adaptive, and field-tested framework for intelligent flood early warning systems. It holds significant potential for deployment in climate-vulnerable, infrastructure-constrained regions globally, advancing both technological innovation and disaster resilience in the face of increasing hydrometeorological extremes.","author":[{"family":"Khan","given":"Marufa"},{"family":"Rouf","given":"Md"},{"family":"Sultana","given":"Niger"},{"family":"Akter","given":"Mst"}],"issued":{"date-parts":[[2025]]},"DOI":"10.63125/6y0qwr92","URL":"https://doi.org/10.63125/6y0qwr92","source":"openalex"},{"id":"oa:W7147349870","type":"article-journal","title":"THE IMPACT OF MODERN TECHNOLOGICAL INNOVATIONS ON FOOD SECURITY IN NIGERIA: A CUTTING-EDGE TECHNOLOGY FROM AN AGROPRENEURSHIP PERSPECTIVE","abstract":"This study empirically examines how modern technological innovations affect food security in Nigerian technology-based farming organizations.The goal of this study is to ascertain the nature of connections between modern technological innovation and food security.It's also aimed at identifying modern technological innovations that guarantee food security and determining their effectiveness and profitability for the food security business.This study used a cross-sectional survey research design to examine a few technology-based and digital-farming organizations in Delta State that were reachable by the study population.From the managers who were the study objects, 60 of the remaining managerial personnel were reported.To assess the data from the respondents, Spearman's rank-order correlation coefficient was used.The findings demonstrated a strong positive connection between food security and modern technological innovations.The study identified the modern technological innovations that guarantees food security such as nanotechnology in agriculture, Artificial Intelligence (AI) in Quality Control, Robotics in Food Processing, The Blockchain Technology and Supply chain management, The Use of Drones in Agriculture, Internet of Things (IoT) in Food Safety, Climate-Resilient Crops, Automated Harvesting using Robot and Post-Harvest Technologies, digital farming, responsible innovation, Vertical Farming, Precision Agriculture, micro-innovation.This study concludes that all the identified modern technological innovations are effective and profitable for the food security business.The study recommends that farmers adopt modern technological innovations to ensure food security and, to a greater extent, sustain the economy.","author":[{"family":"Chukwuka","given":"Ernest"},{"family":"Moemeke","given":"Clara"},{"family":"Onyemaechi","given":"Ugboh"},{"family":"Nneka","given":"Nwaka"},{"family":"Ejaita","given":"Okpako"},{"family":"Chukwuka","given":"Glory"},{"family":"Nkechi","given":"And"}],"issued":{"date-parts":[[2026]]},"DOI":"10.47278/journal.abr/2026.014","URL":"https://doi.org/10.47278/journal.abr/2026.014","source":"openalex"},{"id":"oa:W7156023002","type":"article-journal","title":"Quality Assurance in Decentralized Manufacturing: A Review of Validation Frameworks for 3D-Printed Personalized Medicines","abstract":"Background The pharmaceutical industry is in a paradigm shift in which the mass-production model based on one-size-fits-all is being replaced by the patient-centric model that is made possible by three-dimensional printing (3DP) and decentralized manufacturing (DM). Although 3DP enables the personalization of dosage form as never before, the translation of the technology into clinical practice is complicated by the complicated quality assurance (QA) and validation barriers. Purpose: This review critically synthesizes the existing validation frameworks of 3DP personalized medicines with special emphasis on the combination of Process Analytical Technology (PAT), Digital Twins, and the recently implemented UK MHRA 2025 regulatory framework. Methodology: Scopus-indexed literature (20192026) was searched in a PRISMA-compliant systematic search that focused on point-of-care (POC) manufacturing, real-time release testing (RTRT), and data integrity. Core Mechanisms: We consider technical modalities, such as Fused Deposition Modeling (FDM), Semi-Solid Extrusion (SSE), and Selective Laser Sintering (SLS), their respective Critical Process Parameters (CPPs) and Critical Quality Attributes (CQAs). Findings: The review identifies the Hub-and-Spoke model as the most feasible structure of decentralized QA with centralized hubs that address the issue of integrity of the pharma-ink and decentralized spokes that address the issue of process validation. In-line Near-Infrared (NIR) and Raman spectroscopy technologies that enable the real time release of doses are accurate and non-destructive (R 2 = 0.98) and allow real time verification of doses. Moreover, the Digital Twin technology improves three-stage process validation lifecycle, providing predictive maintenance and proactive quality management. Conclusion: To attain sustainable clinical implementation of the 3DP, a radical change toward Quality-by-Design (QbD) and a powerful digital infrastructure is required. In the coming 2026 and beyond, we suggest a roadmap to standardize decentralized validation to achieve the best safety and efficacy of personalized medicines.","author":[{"family":"Bikram","given":"Joardar"},{"family":"Santu","given":"Karmakar"},{"family":"Sucheta","given":"Dalai"},{"family":"Shristi","given":"Kundu"},{"family":"Poulomi","given":"Chatterjee"},{"family":"Ritam","given":"Chatterjee"},{"family":"Sourav","given":"Rudra"},{"family":"Anisha","given":"Gazi"},{"family":"Shirsha","given":"Majumdar"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5281/zenodo.19824634","URL":"https://doi.org/10.5281/zenodo.19824634","source":"openalex"},{"id":"oa:W7160867598","type":"article-journal","title":"Digital Twins in Agriculture: A Comprehensive Bibliometric Exploration of Applications and Future Trends","abstract":"This bibliometric study was conducted between September and December, 2025 using data retrieved from the Scopus database, focusing on global research publications related to Digital Twin applications in agriculture. Digital Twin technology has become a key component of Agriculture 4.0, enabling real-time simulation, prediction, and optimization of farming systems through virtual representations of physical environments. As agriculture faces rising food demand, climate variability, labour shortages, and resource constraints, Digital Twins offer significant potential to improve productivity, sustainability, and decision-making. However, research in this area remains fragmented across domains such as IoT, AI, robotics, precision agriculture, and climate-smart practices. Using a structured search strategy and PRISMA screening, 95 eligible articles published between 2019 and 2026 were identified. Bibliometric analysis was performed using the Bibliometrix R package and Biblioshiny interface, covering descriptive indicators, co-authorship and co-citation networks, keyword co-occurrence, and thematic evolution. Results show a fluctuating yet overall increasing publication trend, with a notable rise in 2025. Major publication sources include IEEE Access, Applied Sciences, Sensors, and Smart Agricultural Technology. China, the Netherlands, and the USA are leading contributors, with the Netherlands demonstrating the highest citation impact. Keyword analysis highlights strong emphasis on Digital Twins, IoT, machine learning, embedded systems, and agricultural robotics. Thematic mapping identifies core motor themes and emerging areas such as smart agriculture and climate resilience. Overall, the study consolidates fragmented knowledge, identifies research gaps, and outlines future directions to advance Digital Twin applications for sustainable, data-driven agriculture.","author":[{"family":"Dhivya","given":"C"},{"family":"Arunkumar","given":"R"},{"family":"Thirumal","given":"A"},{"family":"Jayashree","given":"V"},{"family":"Kamali","given":"SP"}],"issued":{"date-parts":[[2026]]},"DOI":"10.23910/2/2026.6916","URL":"https://doi.org/10.23910/2/2026.6916","source":"openalex"},{"id":"oa:W7127132316","type":"article-journal","title":"Dynamic plastic deformation delocalization in FCC solid solution metals","abstract":"Metallic materials undergo irreversible deformation under mechanical loading, leading to intense local plastic localization that reduces their mechanical performance. We identify a mechanism of plastic deformation that dynamically promotes the homogenization of plasticity in face-centered cubic solid solution-strengthened metallic alloys. We observe that this mechanism occurs within a narrow range of stacking fault energies and involves competing deformation between nanoscale twinning and slip. This phenomenon is attributed to a new mechanism referred to as dynamic plastic deformation delocalization, which opens a new design space for enhancing the mechanical performance of metallic materials. We demonstrate that the activation of this mechanism has a significant impact on fatigue properties, greatly enhancing fatigue strength when it occurs.","author":[{"family":"Anjaria","given":"Dhruv"},{"family":"Heczko","given":"Milan"},{"family":"You","given":"Daegun"},{"family":"Calvat","given":"Mathieu"},{"family":"Sanandiya","given":"Shuchi"},{"family":"Rajkowski","given":"Maik"},{"family":"Tirunilai","given":"Aditya"},{"family":"Sehitoglu","given":"Hüseyin"},{"family":"Laplanche","given":"Guillaume"},{"family":"Stinville","given":"JC"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1038/s41467-026-69046-3","URL":"https://doi.org/10.1038/s41467-026-69046-3","source":"openalex"},{"id":"oa:W7163319225","type":"article-journal","title":"Physics-Informed machine learning for turbulent combustion in aerospace propulsion: bridging physical rigour and data intelligence","abstract":"Turbulent combustion dictates efficiency, stability, and emissions in gas turbines, scramjets, and rocket engines; however, its multiscale turbulence-chemistry interactions remain difficult to forecast with conventional Reynolds-averaged and large-eddy simulation (LES) frameworks under realistic operational conditions. Although data-driven models offer computational efficiency, their limited physical consistency and inadequate extrapolation capabilities limit their applicability in safety-critical propulsion applications. Physics-informed machine learning (PIML) has emerged as a promising paradigm by embedding governing equations, physical constraints, and conservation laws directly into learning architectures, thereby enabling greater accuracy with reduced data dependence. This review systematically scrutinizes recent advancements in PIML for turbulent reacting flows, encompassing physics-informed neural networks, neural operators, and hybrid physics-data models integrated with Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) solvers. Emphasis is placed on their proficiency to address stiffness, turbulence-chemistry coupling, and multi-fidelity data integration under propulsion-relevant conditions. Key challenges related to data scarcity, scalability, uncertainty quantification, and model interpretability are critically discussed. The review concludes with a forward-looking roadmap accentuating constraint-aware learning, adaptive modelling, and digital twin integration as indispensable for reliable, real-time combustion prediction. These advancements directly bolster sustainable propulsion technologies aligned with UN Sustainable Development Goals 7 and 9, advocating for cleaner energy conversion and innovation-driven aerospace systems.HighlightsPIML bridges physics-based modelling with data-driven intelligence in combustion.Hybrid neural operators improve prediction in turbulent reacting flows.Constraint-preserving learning enhances physical fidelity and scalability.Adaptive sampling accelerates convergence under sparse data conditions.Roadmap proposed for uncertainty-aware, digital-twin-ready PIML frameworks.PIML transforms real-time combustion simulation for next-gen propulsion.","author":[{"family":"Selvam","given":"DC"},{"family":"Devarajan","given":"Yuvarajan"},{"family":"Raja","given":"T"},{"family":"Tiwari","given":"Alok"},{"family":"Kumar","given":"MS"},{"family":"Sharma","given":"Kunal"},{"family":"Agrawal","given":"Anant"},{"family":"Khandual","given":"Ansuman"},{"family":"Mehar","given":"Kulmani"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1080/19942060.2026.2678066","URL":"https://doi.org/10.1080/19942060.2026.2678066","source":"openalex"},{"id":"oa:W4406336888","type":"article-journal","title":"Prussian Blue and Its Analogues for Commercializing Fast-Charging Sodium/Potassium-Ion Batteries","abstract":"Fast-charging technology, which reduces charging time and enhances convenience, is attracting attention. Sodium-ion batteries (SIBs) and potassium-ion batteries (PIBs) are emerging as viable alternatives to lithium-ion batteries (LIBs) due to their abundant resources and low cost. However, during fast charging and discharging, the crystal structures of cathode materials in SIBs/PIBs can be damaged, negatively impacting their performance, lifespan, and capacity. To address this, there is a need to explore electrode materials with ultrahigh rate capabilities. Prussian Blue and its analogues (PB and PBAs) have shown great potential as cathode materials for both SIBs and PIBs due to their unique structures and excellent electrochemical properties. This Review examines the use of PBAs in SIBs and PIBs, focusing on the fast-charging (rate) performance and commercialization potential. Through systematic analysis and discussion, we hope to provide practical guidance for developing fast-charging SIBs and PIBs, contributing to the advancement and widespread adoption of green energy technologies.","author":[{"family":"Hong","given":"Ping"},{"family":"Xu","given":"Changfan"},{"family":"Yan","given":"Chengzhan"},{"family":"Dong","given":"Yulian"},{"family":"Zhao","given":"Huaping"},{"family":"Lei","given":"Yong"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1021/acsenergylett.4c02915","URL":"https://doi.org/10.1021/acsenergylett.4c02915","source":"openalex"},{"id":"oa:W7134194100","type":"article-journal","title":"Development of a Digital Twin for Robotic Inspection Using Computer Vision and Machine Learning","abstract":"This article reveals the creation and execution of a digital twin (DT) for the robotic inspection system of mechanical parts, applying the machine vision method. The examination is carried out on the KUKA iiwa robot that has a camera for the purpose of identifying and sorting the parts that are positioned on the work area. A vision system based on a YOLO convolutional neural network (CNN) was utilized for the tasks of object detection and classification. The dataset was automatically created via the use of 3D CAD models along with domain randomization to mitigate the risk of overfitting. The simulation environment was set up in IsaacSim, and the vision system was interfaced through ROS Noetic with hand-eye calibration also included. The performance of the YOLO network evidenced an overall precision of 94.8% and recall of 87.7% in the test dataset indicating the parts' effective detection and classification. The research underlines the convergence of simulation, deep learning, robotics, and the potential for automated inspections in manufacturing sectors.","author":[{"family":"Pramila","given":"PV"},{"family":"Jothilakshmi","given":"R"},{"family":"Kumar","given":"KRS"},{"family":"Revathi","given":"B"},{"family":"Kistan","given":"A"},{"family":"Lingampalli","given":"Bhavya"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1051/epjconf/202635403005/pdf","URL":"https://doi.org/10.1051/epjconf/202635403005/pdf","source":"openalex"},{"id":"oa:W7125561893","type":"article-journal","title":"Advanced Fault Detection and Diagnosis Exploiting Machine Learning and Artificial Intelligence for Engineering Applications","abstract":"Modern engineering systems require reliable and timely Fault Detection and Diagnosis (FDD) to ensure operational safety and resilience. Traditional model-based and rule-based approaches, although interpretable, exhibit limited scalability and adaptability in complex, data-intensive environments. This survey provides a systematic overview of recent studies exploring Machine Learning (ML) and Artificial Intelligence (AI) techniques for FDD across industrial, energy, Cyber-Physical Systems (CPS)/Internet of Things (IoT), and cybersecurity domains. Deep architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformers, and Graph Neural Networks (GNNs) are compared with unsupervised, hybrid, and physics-informed frameworks, emphasizing their respective strengths in adaptability, robustness, and interpretability. Quantitative synthesis and radar-based assessments suggest that AI-driven FDD approaches offer increased adaptability, scalability, and early fault detection capabilities compared to classical methods, while also introducing new challenges related to interpretability, robustness, and deployment. Emerging research directions include the development of foundation and multimodal models, federated learning (FL), and privacy-preserving learning, as well as physics-guided trustworthy AI. These trends indicate a paradigm shift toward self-adaptive, interpretable, and collaborative FDD systems capable of sustaining reliability, transparency, and autonomy across critical infrastructures.","author":[{"family":"Paolini","given":"Davide"},{"family":"Dini","given":"Pierpaolo"},{"family":"Elhanashi","given":"Abdussalam"},{"family":"Saponara","given":"Sergio"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/electronics15020476","URL":"https://doi.org/10.3390/electronics15020476","source":"openalex"},{"id":"oa:W7133198849","type":"article-journal","title":"Development of a Digital Twin for Robotic Inspection Using Computer Vision and Machine Learning","abstract":"This article reveals the creation and execution of a digital twin (DT) for the robotic inspection system of mechanical parts, applying the machine vision method. The examination is carried out on the KUKA iiwa robot that has a camera for the purpose of identifying and sorting the parts that are positioned on the work area. A vision system based on a YOLO convolutional neural network (CNN) was utilized for the tasks of object detection and classification. The dataset was automatically created via the use of 3D CAD models along with domain randomization to mitigate the risk of overfitting. The simulation environment was set up in IsaacSim, and the vision system was interfaced through ROS Noetic with hand-eye calibration also included. The performance of the YOLO network evidenced an overall precision of 94.8% and recall of 87.7% in the test dataset indicating the parts' effective detection and classification. The research underlines the convergence of simulation, deep learning, robotics, and the potential for automated inspections in manufacturing sectors.","author":[{"family":"Pramila","given":"PV"},{"family":"Jothilakshmi","given":"R"},{"family":"Kumar","given":"KRS"},{"family":"Revathi","given":"B"},{"family":"Kistan","given":"A"},{"family":"Lingampalli","given":"Bhavya"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1051/epjconf/202635403005","URL":"https://doi.org/10.1051/epjconf/202635403005","source":"openalex"},{"id":"oa:W7114918762","type":"article-journal","title":"Artificial intelligence driven platforms in the construction industry: implications for companies’ business models","abstract":"Purpose This research paper aims to understand the development and impact of artificial intelligence (AI)-driven digital platform business models within the construction industry, addressing their strengths, weaknesses and changes from previous models. Design/methodology/approach The research uses a three-phase qualitative multiple-case study approach, analyzing three companies developing AI-driven digital platforms. Data was gathered from multiple sources within cases, including interviews, group meetings, workshops and company documentation. The analysis used thematic interpretation of qualitative data and the application of business model canvases for within-case structuring and cross-case synthesis. Findings Results reveal that AI-driven platforms have potential to enhance collaboration, efficiency and scalability through data-driven, personalized services. Platforms drive new business models and leverage benefits for ecosystem stakeholders. However, adoption faces barriers including high implementation costs, integration complexities, data risks, resistance to change and gaps in stakeholders’ maturity. Overcoming the barriers will require strategic planning, training, data governance frameworks,\\ and tailored stakeholder engagement. Research limitations/implications The study acknowledges limitations related to participant bias, partly virtual data collection and regional focus. Future research should expand the sample size and conduct longitudinal studies. Practical implications The research provides guidance for companies, emphasizing the importance of operational redesign, cultural alignment and training, data governance, collaborative development and fostering ecosystem partnerships. Originality/value This study contributes to the limited body of empirical research on AI-driven digital platforms in construction, offering insights for companies seeking to leverage platform-based business models in their business.","author":[{"family":"Nyqvist","given":"Roope"},{"family":"Peltokorpi","given":"Antti"},{"family":"Lavikka","given":"Rita"},{"family":"Ainamo","given":"Antti"}],"issued":{"date-parts":[[2025]]},"DOI":"10.1108/ci-09-2024-0291","URL":"https://doi.org/10.1108/ci-09-2024-0291","source":"openalex"},{"id":"oa:W7130653093","type":"article-journal","title":"A Data-Driven Framework for the Development of Reliability-Aware Business Process Digital Twins","abstract":"Digital Twin (DT) technologies are increasingly adopted as valuable methods to support the analysis and optimization of Business Processes (BPs). The use of simulation-based techniques in the BPM context is not new. Nonetheless, existing approaches for BP simulation primarily focus on performance-related aspects. In this respect, this paper introduces a data-driven framework for the automated generation of reliability-aware DTs derived from event and state logs. The proposed method integrates process mining techniques, resource reliability modeling, and model-driven transformations to produce executable DT simulations capable of predicting the failure behavior of process resources. The proposed framework has been applied to the predictive maintenance domain, where DT-based simulations are used to estimate resource availability, identify possible failure scenarios, and support the timely scheduling of preventive maintenance interventions. A manufacturing case study shows that the proposed approach can enhance process operability and reduce downtime compared to conventional BP execution without DT-based reliability insights.","author":[{"family":"Bocciarelli","given":"Paolo"},{"family":"Fiorelli","given":"Manuel"},{"family":"Dambrogio","given":"Andrea"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/technologies14020136","URL":"https://doi.org/10.3390/technologies14020136","source":"openalex"},{"id":"oa:W7129641033","type":"article-journal","title":"A comprehensive framework for data challenges and intelligent resource optimization for offshore wind energy","abstract":"Offshore wind parks are central to the global energy transition, yet efficiently utilizing resources remains challenging. This review synthesizes data-driven approaches for improving offshore wind system performance, covering natural resources (e.g., wind and meteorological conditions) and artificial resources (e.g., turbines and supporting infrastructure). Three recurring data challenges—data imbalance, distribution shift, and data sparsity—are identified as key constraints in wind power forecasting, turbine layout optimization, and maintenance planning. For natural resource management, machine learning and deep learning models enhance wind and power forecasting under highly variable offshore conditions, while surrogate modeling and spatial optimization reduce wake losses and layout costs. Across representative studies, hourly and daily capacity-factor prediction errors are typically reduced by around 10% and 15–20%, respectively. For artificial resources, data-driven lifecycle management and preventive maintenance increasingly rely on SCADA data, sensor networks, and digital twins to assess equipment health and mitigate operational risks, although limited failure data remains a major bottleneck. Existing evidence suggests maintenance cost reductions of approximately 20–30%. Beyond operational efficiency, this review examines the integration of sustainability and circular-economy principles into offshore wind development, including material recycling, component lifetime extension, and wind-to-hydrogen integration. Overall, effective data-driven optimization depends on advanced algorithms, high-quality data, and system integration. By linking data challenges with circular-economy objectives, this study proposes a unifying framework to support intelligent and sustainable offshore wind systems.","author":[{"family":"Lyu","given":"Yucheng"},{"family":"Chen","given":"Hao"},{"family":"Yazan","given":"Devrim"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.seta.2026.104888","URL":"https://doi.org/10.1016/j.seta.2026.104888","source":"openalex"},{"id":"oa:W7154722021","type":"article-journal","title":"INFORMATION-CONTROLLED MECHATRONIC SYSTEMS OF POWER SUPPLY AND AUTOMATION OF TECHNOLOGICAL PROCESSES IN THE AGRO-INDUSTRIAL COMPLEX","abstract":"The paper examines modern approaches to the development, research, and implementation of mechatronic systems for adaptive control of technological processes in the agro-industrial complex. Particular attention is paid to the integration of electrical, information, sensor, and control subsystems into a unified intelligent structure capable of self-adjustment, environmental analysis, and energy optimization. It is shown that under conditions of rapid digitalization, climate change, and the need for rational use of resources, such systems ensure flexibility, stability, and efficiency of production processes. The study determines that effective mechatronic systems should be based on a modular structure including sensor, executive, analytical, and communication levels. The sensor level collects process data, the executive level performs control actions, the analytical level applies adaptive and optimization algorithms, and the communication level ensures integration through industrial digital networks. It is established that adaptive mechatronic systems increase energy efficiency, reduce raw material losses, improve product quality, and maintain stable operating parameters under unstable external conditions. Special attention is given to mathematical modeling, simulation, and the use of frequency-controlled electric drives with digital control systems, which improve positioning accuracy, speed regulation, and overall energy performance. The paper identifies key directions for further development, including autonomous robotic systems, wireless sensor networks, digital twins, intelligent energy management, and adaptive control under changing climatic conditions. The obtained results are of scientific and practical significance for precision agriculture, livestock production, smart greenhouses, and automated processing systems.","author":[{"family":"Stadnik","given":"Mykola"},{"family":"Shtuts","given":"Andrii"},{"family":"Kolisnyk","given":"Mykola"},{"family":"Kohut","given":"Vasyl"}],"issued":{"date-parts":[[2026]]},"DOI":"10.37128/2520-6168-2026-1-10","URL":"https://doi.org/10.37128/2520-6168-2026-1-10","source":"openalex"},{"id":"oa:W7128428963","type":"article-journal","title":"A Review of Federated Large Language Models for Industry 4.0","abstract":"Industry 4.0 envisions a highly interconnected, autonomous manufacturing ecosystem enabled by the Industrial Internet of Things, Cyber-Physical Systems, and Artificial Intelligence. The emergence of large language models introduces new capabilities for semantic-aware decision-making, cross-domain knowledge integration, and intelligent automation. However, privacy, security, and regulatory constraints often isolate industrial data, impeding the scalability of LLMs in manufacturing. Federated learning addresses this by enabling decentralized LLM optimization without exposing raw data. This paper presents a comprehensive review of recent federated large language model research with a focus on industrial feasibility, comparing enabling techniques, system designs, and deployment strategies. Based on existing studies, forward-looking analyses are provided to highlight potential challenges and trade-offs in practical adoption, including computation and communication overheads, synchronization in large-scale federations, and system robustness. By bridging foundational methods with emerging industrial scenarios, we finally discuss the significant challenges associated with deploying federated large language models in complex industrial environments and outline a future research agenda.","author":[{"family":"Feng","given":"Jing"},{"family":"Zhang","given":"Yujing"},{"family":"Mt","given":"Gao"},{"family":"Zhang","given":"Xiongtao"},{"family":"Zhou","given":"Huaizhe"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/s26041116","URL":"https://doi.org/10.3390/s26041116","source":"openalex"},{"id":"oa:W7128718699","type":"article-journal","title":"Frontier Research and Application Advances in Energy-Saving Technologies for Aluminum Electrolysis","abstract":"The Hall–Héroult aluminum electrolysis process remains highly energy-intensive, making energy efficiency improvement crucial for sustainable aluminum production. Recent progress has focused on four key areas: electrolyzer structure optimization, advanced electrode materials, intelligent process control, and waste heat recovery. Structural innovations such as reducing the anode to cathode distance (ACD) and improving magnetohydrodynamic stability have lowered operating voltage and thermal losses. Novel carbon-based and conductive electrode materials have improved current efficiency and extended service life. Intelligent control methods, including model predictive control, adaptive dynamic programming, and Kalman filtering, have optimized alumina feeding, stabilized operations, and reduced perfluorocarbon emissions. Moreover, recovering waste heat from anode gases and electrolyzer sidewalls has created new opportunities for energy reuse. The integration of these strategies is advancing aluminum electrolysis toward higher efficiency, lower carbon emissions, and intelligent operation. Future directions include digital twin modeling, artificial-intelligence-driven control, ultra-low ACD designs, and efficient heat recovery systems to promote sustainable industrial transformation.","author":[{"family":"Zhou","given":"Yu"},{"family":"Zhao","given":"Chaoxian"},{"family":"Xiao","given":"Jin"},{"family":"Zhou","given":"Liuzhou"},{"family":"Wang","given":"Mengdi"},{"family":"Huang","given":"Sen"},{"family":"Yang","given":"Jie"},{"family":"Mao","given":"Qiuyun"},{"family":"You","given":"Zihan"},{"family":"Zhong","given":"Qifan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/en19040959","URL":"https://doi.org/10.3390/en19040959","source":"openalex"},{"id":"oa:W7155399098","type":"article-journal","title":"Future research directions and applications of artificial intelligence in tribology","abstract":"Artificial intelligence (AI) is transforming tribology by enabling the prediction and understanding of friction, wear, and lubrication at a higher level than conventional methods. This is important because 20–23% of global energy is wasted due to friction and wear, and 30–40% of machine failures are due to these issues. This review analyzes recent developments, existing problems, uses, and prospective research on AI in tribology. It also holds tribo-informatics that is a combination of tribology and data science. The review deals with multiple scales of tribology, including small particles up to large components and long-term wear experiments, as well as existing machine-learning methods. These methods include physics-informed machine learning, which uses major equations, such as lubrication and wear equations. Studies have shown that traditional machine learning (ML) can predict friction and wear with 90–95% accuracy, whereas deep learning improves wear prediction by 20–40%. CNN-based methods can identify wear states with 95–98% accuracy, and hybrid methods predict the remaining life of parts with less than 5–10% error. Challenges include limited data, complex interactions, hard-to-understand models, high resource needs, and privacy issues, making most industrial data unavailable. Despite this, AI improves production efficiency by 15–30%, reduces unexpected failures by 20–40%, and cuts maintenance costs by 10–25%. These have enormous effects on aerospace, renewable energy and manufacturing industries. Others are that it needs open databases, legal explainable AI to show why it made its decisions and digital twins and autonomous labs to improve diagnostics, lubricant design, and energy-saving systems.","author":[{"family":"Mehta","given":"Amrinder"},{"family":"Vasudev","given":"Hitesh"},{"family":"Sabareshwaran","given":"S"},{"family":"Suma","given":"BV"},{"family":"Singh","given":"Jashanpreet"},{"family":"Prasad","given":"Brijesh"},{"family":"Singh","given":"Saravjeet"},{"family":"Katelo","given":"Oda"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s44245-026-00249-0","URL":"https://doi.org/10.1007/s44245-026-00249-0","source":"openalex"},{"id":"oa:W7204459263","type":"article-journal","title":"An Intelligent Multi‐Criteria Framework for Digital Twin Adoption Assessment in Smart Manufacturing via Circular q‐Rung Orthopair Fuzzy CoCoFISO Dynamics","abstract":"ABSTRACT Digital twin technologies are gaining importance in modern intelligent manufacturing to facilitate increased efficiency, smartness in manufacturing, and sustainability. Nevertheless, the choice of a suitable digital twin solution is a complicated long‐term decision because of the high rate of technological development, integration issues, and financial limitations. To solve these problems, this research proposes a multi‐criteria decision‐making model based on the circular q‐rung orthopair fuzzy compromise of ideal solution (CqROF‐CoCoFISO). The proposed model uses circular q‐rung orthopair fuzzy sets, which is an effective model for capturing the uncertainty, hesitation and ambiguity that exists in smart manufacturing environments. The most important assessment criteria will be the technological flexibility, compatibility with the system, the cost of implementation, functionality of the system, intellectual property protection, adherence to security and sustainability. The CoCoFISO mechanism will allow ranking competing digital twin alternatives reliably based on conflicting criteria, which will improve the strength and stability of decision‐making results. The usefulness of the proposed framework can be proved through a comparative analysis. The findings offer useful information to manufacturing engineers, decision‐makers and policymakers aiming at informed and credible digital twin adoption policies in changing industrial conditions.","author":[{"family":"Farhad","given":"Asma"},{"family":"Ullah","given":"Kifayat"},{"family":"Ali","given":"Zeeshan"},{"family":"Shang","given":"Yilun"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1049/cim2.70076","URL":"https://doi.org/10.1049/cim2.70076","source":"openalex"},{"id":"oa:W7163807763","type":"article-journal","title":"Planning-Based Decision Space Exploration for Digital Twins in Immature Production Processes","abstract":"Highly variant and immature production processes frequently occur during the ramp-up of new manufacturing technologies, where process parameters, resource configurations, and operating strategies must be established under incomplete process knowledge. The resulting combinatorial configuration spaces make systematic planning and evaluation of alternative process setups difficult. This paper proposes a planning-based digital twin architecture that enables structured exploration and reduction of such decision spaces while integrating simulation-based feasibility assessment. The approach combines formal modeling of discrete process parameter variants with automated planning and physics-based simulation using PyBullet. Symbolic planning operates on an abstract representation of process steps, resources, and parameter variants to generate consistent process paths under cost and quality objectives. These process paths are subsequently instantiated as executable simulation scenarios, allowing verification of their physical feasibility and operational behavior. The architecture integrates decision generation, execution, and evaluation within a unified and modular pipeline. A virtual thermoforming demonstrator is used to verify the functional feasibility of the approach and to illustrate systematic decision space reduction through constraint-based planning. The results demonstrate that planning-based digital twin architectures provide a scalable foundation for supporting decision-making during ramp-up and configuration of highly variant production processes.","author":[{"family":"Bott","given":"Alexander"},{"family":"Salihi","given":"Suliot"},{"family":"Puchta","given":"Alexander"},{"family":"Fleischer","given":"Jürgen"}],"issued":{"date-parts":[[2026]]},"DOI":"10.36897/jme/222460","URL":"https://doi.org/10.36897/jme/222460","source":"openalex"},{"id":"oa:W7140142264","type":"article-journal","title":"EdTech and the Environment: A Research Program","abstract":"Abstract The global EdTech market, valued at nearly USD 250 billion, generates not only revenue but substantial ecological and planetary costs that the EdTech scholarly community has insufficiently examined. This article argues that those working in and around EdTech bear a moral responsibility to move beyond (non)performative engagement with sustainable development goals toward serious, structural inquiry into the environmental impacts of EdTech. Drawing on a postdigital transdisciplinary framework, we identify key scholarly fields and approaches—Critical EdTech Studies, AI and education research, postdigital-biodigital approaches, Education for Sustainable Development, degrowth theory, ecopedagogy, and studies of unequal planetary conditions—and examine their respective contributions to understanding relationships between EdTech and the environment. We outline an open research program grounded in ontological, epistemological, ethical, political, pedagogical, positional, and community commitments that resist technological solutionism and growth-dependent development models. Rather than offering definitive answers, this paper extends an invitation to transdisciplinary collaboration, recognising that planetary challenges require planetary responses from a coalition of scholars willing to work across—and beyond—disciplinary boundaries.","author":[{"family":"Jandrić","given":"Petar"},{"family":"Knox","given":"Jeremy"},{"family":"Rapanta","given":"Chrysi"},{"family":"Hayes","given":"Sarah"},{"family":"Kostakis","given":"Vasilis"},{"family":"Tolbert","given":"Sara"},{"family":"Misiaszek","given":"Greg"},{"family":"Lee","given":"Kyungmee"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s42438-026-00635-7","URL":"https://doi.org/10.1007/s42438-026-00635-7","source":"openalex"},{"id":"oa:W7204438517","type":"article-journal","title":"Industry 5.0 and digital transformation for sustainable textile and manufacturing systems","abstract":"The rapid evolution of digital technologies has significantly transformed modern manufacturing systems, creating new opportunities for improving productivity, sustainability, and industrial resilience. In this context, Industry 5.0 has emerged as a new industrial paradigm that extends the technological achievements of Industry 4.0 by emphasizing human-centric manufacturing, sustainable production, and resilient industrial systems. Simultaneously, digital transformation has become a key enabler for integrating intelligent technologies into both textile and manufacturing industries, supporting resource-efficient production, process optimization, and environmentally responsible manufacturing practices. This paper presents a comprehensive review of the relationship between Industry 5.0, digital transformation, and sustainable textile and manufacturing systems. The study examines the fundamental principles of Industry 5.0 and discusses the role of enabling technologies, including Artificial Intelligence (AI), the Internet of Things (IoT), Digital Twins, Big Data analytics, Cloud Computing, and Cyber-Physical Systems (CPS), in supporting intelligent manufacturing environments. Particular attention is devoted to the application of these technologies in textile manufacturing, where digitalization contributes to automated quality control, smart textile production, resource efficiency, digital product traceability, and circular production strategies. Based on the findings of the literature review, the authors propose a conceptual model of Industry 5.0-driven digital transformation that integrates three complementary dimensions: Digital Technologies, Human-Centred Manufacturing, and Sustainable Manufacturing. The proposed model illustrates how the interaction among these dimensions contributes to improved manufacturing performance through enhanced productivity, flexibility, product quality, environmental responsibility, and industrial resilience. Furthermore, the model demonstrates the importance of integrating technological innovation with human expertise and sustainability principles to support the future development of both textile and manufacturing systems. The proposed conceptual model may serve as a foundation for future research focused on intelligent manufacturing, smart textile production, Artificial Intelligence, Digital Twins, sustainable industrial development, and Industry 5.0 implementation strategies.","author":[{"family":"Srebrenkoska","given":"Sara"},{"family":"Krstev","given":"Dejan"},{"family":"Dimitrov","given":"Sasko"},{"family":"Nikolova","given":"Simona"}],"issued":{"date-parts":[[2026]]},"DOI":"10.5937/ct_iti26476s","URL":"https://doi.org/10.5937/ct_iti26476s","source":"openalex"},{"id":"oa:W7203719530","type":"article-journal","title":"A proactive digital twin framework for dynamic pull scheduling in modular construction factories","abstract":"Achieving continuous flow in modular construction is challenging due to high-mix variability, where traditional static methods often fail, leading to excess Work-in-Process (WIP) and flow stagnation.This study proposes a Digital Twin framework utilizing a novel \"Offline Learning, Online Control\" architecture.The methodology employs Simulation-Based Optimization to derive optimal control policies offline, which are synthesized into a lightweight surrogate model.This model drives an autonomous Scheduler Agent that acts as a virtual pacemaker, regulating real-time flow to shift production from a 'push' to a dynamic 'pull' strategy.Specifically, the agent monitors the cumulative count of finished units at critical downstream constraints, throttling upstream releases until the cumulative count of finished units from the current project surpasses a dynamically calculated threshold.To validate this approach, a case study was conducted on a wall panel assembly line in Edmonton, Canada.For this specific implementation, a Genetic Algorithm was used to train a linear regression surrogate policy against stochastic demand scenarios.Experimental results demonstrate a 38.5% reduction in average Cycle Time (Lead Time) compared to the facility's baseline practice.These findings confirm that integrating simulation-based learning with real-time surrogate control successfully stabilizes flow efficiency, minimizes WIP accumulation, and prevents gridlock in constrained manufacturing environments.","author":[{"family":"Moghimi","given":"Nima"},{"family":"Shamaee","given":"Sahar"},{"family":"Mei","given":"Qipei"},{"family":"González","given":"Vicente"},{"family":"Hamzeh","given":"Farook"}],"issued":{"date-parts":[[2026]]},"DOI":"10.24928/2026/0246","URL":"https://doi.org/10.24928/2026/0246","source":"openalex"},{"id":"oa:W4406617430","type":"article-journal","title":"Innovative Driver Monitoring Systems and On-Board-Vehicle Devices in a Smart-Road Scenario Based on the Internet of Vehicle Paradigm: A Literature and Commercial Solutions Overview","abstract":"In recent years, the growing number of vehicles on the road have exacerbated issues related to safety and traffic congestion. However, the advent of the Internet of Vehicles (IoV) holds the potential to transform mobility, enhance traffic management and safety, and create smarter, more interconnected road networks. This paper addresses key road safety concerns, focusing on driver condition detection, vehicle monitoring, and traffic and road management. Specifically, various models proposed in the literature for monitoring the driver's health and detecting anomalies, drowsiness, and impairment due to alcohol consumption are illustrated. The paper describes vehicle condition monitoring architectures, including diagnostic solutions for identifying anomalies, malfunctions, and instability while driving on slippery or wet roads. It also covers systems for classifying driving style, as well as tire and emissions monitoring. Moreover, the paper provides a detailed overview of the proposed traffic monitoring and management solutions, along with systems for monitoring road and environmental conditions, including the sensors used and the Machine Learning (ML) algorithms implemented. Finally, this review also presents an overview of innovative commercial solutions, illustrating advanced devices for driver monitoring, vehicle condition assessment, and traffic and road management.","author":[{"family":"Visconti","given":"Paolo"},{"family":"Rausa","given":"Giuseppe"},{"family":"Del-Valle-Soto","given":"Carolina"},{"family":"Velázquez","given":"Ramiro"},{"family":"Cafagna","given":"Donato"},{"family":"Fazio","given":"Roberto"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/s25020562","URL":"https://doi.org/10.3390/s25020562","source":"openalex"},{"id":"oa:W7166690582","type":"article-journal","title":"The Integration of Digital Twin Technology and the Industrial Internet of Things (IIoT) for Enhanced Predictive Maintenance in Smart Manufacturing: A Hybrid Framework with Realistic Field Projections","abstract":"The contemporary industrial landscape is undergoing a transformative paradigm shift driven by the Fourth Industrial Revolution (Industry 4.0), characterized by the convergence of digital technologies with physical manufacturing processes. Central to this transformation is the evolution from reactive and preventive maintenance strategies toward data-driven Predictive Maintenance (PdM), which promises to revolutionize asset management practices across manufacturing sectors. This comprehensive research paper investigates the structural integration of Digital Twin (DT) technology and the Industrial Internet of Things (IIoT) to optimize operational efficiency, reliability, and service life extension of complex industrial machinery. By establishing a continuous, bidirectional cyber-physical feedback loop, the proposed framework enables real-time anomaly detection, high-fidelity fault isolation, and precise Remaining Useful Life (RUL) estimations. The study proposes a hybrid architecture combining physics-based models (Extended Kalman Filtering) with data-driven algorithms (LSTM networks and Physics-Informed Neural Networks) within a distributed edge-cloud computing environment. Under optimal simulated conditions, the framework indicates a potential reduction in unscheduled downtime of up to 93.4% and a 90.4% improvement in RUL estimation precision compared to traditional methods. However, these figures are presented as theoretical upper bounds derived from controlled simulation environments using the NASA C-MAPSS dataset. Recognizing the inherent gap between simulation and physical deployment—commonly referred to as the \"simulation-to-reality gap\" or \"generalization gap\"—the study provides conservative field-performance projections. These projections estimate a realistic field reduction of approximately 60.8% (with a sensitivity range of 55–61%), accounting for unavoidable stochastic failures, sensor drift, electromagnetic interference, and domain adaptation challenges when transitioning from aerospace turbine data to multi-axis manufacturing centers. The paper rigorously validates the framework using the NASA C-MAPSS dataset and extended custom simulation environments, while also presenting a phased 12-month implementation roadmap, a tri-scenario economic feasibility analysis (optimistic, realistic, pessimistic), and a robust ethical governance framework aligned with UNESCO AI Ethics principles. This research offers a mature, actionable blueprint for resilient, next-generation industrial asset management, with explicit acknowledgment of current limitations and prioritized directions for future field validation.","author":[{"family":"Aghlelib","given":"Suad"},{"family":"Arjiah","given":"Asma"},{"family":"Abdulhamid","given":"Maryam"}],"issued":{"date-parts":[[2026]]},"DOI":"10.65405/827x7841","URL":"https://doi.org/10.65405/827x7841","source":"openalex"},{"id":"oa:W7125689455","type":"article-journal","title":"The Evolution of Mechatronics Engineering and Its Relationship with Industry 3.0, 4.0, and 5.0","abstract":"Mechatronics developed under the influence of the Third Industrial Revolution and was a discipline that provided methods and tools for the development of industrial robots, advanced machine tools, mobile phones, and automobiles, among other sophisticated products. With the emergence of Industry 4.0 in 2011, mechatronics has become indispensable, as traditional production systems are being transformed into cyber-physical systems (CPS), some of which are composed of sophisticated technologies such as Digital Twins (DT) and sophisticated robots, among others. In 2020, the Fifth Industrial Revolution began, giving rise to so-called Human Cyber-Physical Systems (HCPS) and promoting the use of Cobots in industries. Because today’s industrial world is influenced by three active industrial revolutions and two transitions, it is possible to find machines and production systems that were designed with different principles and for different purposes, making it necessary to propose a classification that allows each system to be located according to the premises of its respective industrial revolution. This article analyzes the evolution of mechatronics and proposes a classification of machines and production systems based on the premises of each industrial revolution. The objective is to determine the influence of mechatronics on the different types of machines that exist today and analyze its implications.","author":[{"family":"López","given":"Eusebio"},{"family":"Palomares","given":"Juan"},{"family":"Chávez","given":"Omar"},{"family":"Muñoz","given":"Flavio"},{"family":"Velásquez","given":"Luis"},{"family":"Lugo","given":"José"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/technologies14020081","URL":"https://doi.org/10.3390/technologies14020081","source":"openalex"},{"id":"oa:W7166518362","type":"article-journal","title":"A review of sensor-based cutting force measurement in machining: from microcontroller systems to smart manufacturing","abstract":"Cutting force is a key indicator that reflects the mechanical interaction between the cutting tool and the workpiece during machining. It directly influences energy consumption, tool wear, process stability, and machined surface quality. As modern manufacturing increasingly demands efficient, flexible, and sustainable production systems, the development of adaptive, real-time, and cost-effective cutting force measurement technologies has become essential. Previous review studies have primarily focused on cutting force modelling and commercial dynamometer systems, while limited attention has been given to the integration of low-cost sensors, microcontrollers, Internet of Things (IoT) technologies, and smart manufacturing applications. This review aims to evaluate recent developments in sensor- and microcontroller-based cutting force measurement systems and their potential integration within Industry 4.0 environments. The review synthesizes more than 230 references, primarily published between 2020 and 2026, together with selected earlier studies that provide important theoretical and technological foundations. Four main aspects are discussed: (1) theoretical foundations of cutting force, (2) sensor technologies and measurement system architectures, (3) modelling and data analysis methods, and (4) challenges and future development trends. The findings indicate that load cell and strain gauge sensors provide economical and practical solutions for long-term monitoring, whereas piezoelectric sensors remain the preferred option for high-frequency dynamic measurements due to their superior sensitivity and bandwidth. Furthermore, the integration of microcontrollers, IoT connectivity, machine learning, and digital twin technologies is accelerating the development of intelligent machining systems for smart and sustainable manufacturing.","author":[{"family":"Ginting","given":"Yogie"},{"family":"Ginting","given":"Selvia"},{"family":"Sutono","given":"Sutono"},{"family":"Romy","given":"Romy"},{"family":"Aulia","given":"Mega"}],"issued":{"date-parts":[[2026]]},"DOI":"10.31258/jamt.8.1.21-40","URL":"https://doi.org/10.31258/jamt.8.1.21-40","source":"openalex"},{"id":"oa:W7135015176","type":"article-journal","title":"Cybersecurity Digital Twins for Industrial Systems: From Literature Synthesis to Framework Design","abstract":"Digital Twins (DTs) are increasingly recognized as a strategic technology for enhancing cybersecurity in industrial environments, particularly in the face of rising threats targeting Operational Technology (OT). After comparatively examining closely related DT–cybersecurity frameworks to position the contribution within the existing research landscape, this paper presents a systematic literature review and comparative analysis of 19 recent DT-based cybersecurity studies, focusing on their relevance to incident detection and response in sectors such as Industrial Internet of Things (IIoT), manufacturing, and energy. The analysis evaluates each study across multiple dimensions, including attack types, detection and response mechanisms, DT integration, and technology stacks. From this review, we derive a consolidated set of requirements, categorized as functional, non-functional, security-specific, and domain-specific. These requirements serve as the foundation for a novel, cybersecurity-focused, ISO 23247-based framework. The proposed architecture formalizes a DT-enabled incident detection and response lifecycle aligned with ISO 23247. It is explicitly mapped to the derived requirements and detailed with practical implementation considerations. This work contributes a structured, evidence-based approach to DT-based security engineering and offers a reference design for researchers and practitioners aiming to build resilient, adaptive cybersecurity solutions in industrial settings.","author":[{"family":"Kampourakis","given":"Konstantinos"},{"family":"Gkioulos","given":"Vasileios"},{"family":"Katsikas","given":"Sokratis"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/info17030286","URL":"https://doi.org/10.3390/info17030286","source":"openalex"},{"id":"oa:W4411096276","type":"article-journal","title":"Global Research Trends in AI and Blockchain for Smart Grids: A Bibliometric Analysis with a Focus on Morocco (2014–2024)","abstract":"As Information and Communication Technologies (ICTs) are increasingly incorporated into energy systems, smart grids are becoming essential parts of modern energy infrastructures. However, this integration exposes them to significant cybersecurity risks, highlighting the need for effective prevention and mitigation strategies to enhance resilience. Due to their promising implications, blockchain and artificial intelligence (AI) have emerged as key technologies to strengthen security, improve data analysis, and optimize processes in smart grids. This bibliometric study investigates key trends, opportunities, and evolving dynamics within the field, analyzing a dataset of 9611 articles from the Scopus database, covering the period 2014–2024. To evaluate the research, we utilized a range of bibliometric tools, including Bibliometrix R, VOSviewer, and Python. We used these tools to identify impactful articles. We also analyzed country and institutional productivity, assessed prolific authors, and uncovered emerging trends. The findings highlight a shift towards advanced smart grids incorporating AI and blockchain, with significant progress in Morocco’s research since 2016. Morocco ranks 36th globally and 3rd in Africa, contributing to the National Digital Morocco 2030 Strategy, which promotes digital transition and innovation, particularly in smart grids, to bolster the country’s energy system.","author":[{"family":"Betouil","given":"Anass"},{"family":"Haddouti","given":"Samia"},{"family":"Chaoui","given":"Habiba"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/electronics14122314","URL":"https://doi.org/10.3390/electronics14122314","source":"openalex"},{"id":"oa:W7124600317","type":"article-journal","title":"Cloud Native Fintech Analytics Platform for IoT Enabled Retail Networks","abstract":"The rapid digital transformation of retail ecosystems has accelerated the adoption of Internet of Things (IoT) technologies alongside fintech driven payment and financial management systems. Smart point-of-sale terminals, connected inventory systems, and sensor enabled retail environments continuously generate large volumes of heterogeneous, high velocity data. However, traditional on premise analytics infrastructures face significant limitations in handling the scale, real time processing requirements, and integration complexity associated with these data streams. As a result, retailers often experience delayed financial insights, limited fraud detection capabilities, and inefficient operational decision-making. To address these challenges, this paper proposes a cloud native fintech analytics platform specifically designed for IoT-enabled retail networks. The proposed architecture integrates real time data ingestion pipelines, scalable cloud-based analytics services, and intelligent financial insight generation within a unified framework. By leveraging cloud-native design principles such as microservices, container orchestration, and event driven processing, the platform enables elastic scalability, high availability, and fault tolerance while reducing infrastructure and maintenance overhead. The system supports real time transaction monitoring, contextual fraud detection through IoT data correlation, and advanced business intelligence for retail operations. Experimental evaluation using simulated retail workloads demonstrates significant improvements in transaction processing latency, anomaly detection accuracy, and system resilience when compared with conventional monolithic retail analytics systems. The results highlight the effectiveness of cloud-native approaches in supporting data intensive fintech applications and confirm their suitability for next-generation smart retail environments that demand agility, scalability, and real-time financial intelligence.","author":[{"family":"Sharan","given":"SMMI"},{"family":"Fahim","given":"Md"},{"family":"Farooq","given":"Hamza"}],"issued":{"date-parts":[[2026]]},"DOI":"10.30574/wjaets.2026.18.1.1582","URL":"https://doi.org/10.30574/wjaets.2026.18.1.1582","source":"openalex"},{"id":"oa:W4415284130","type":"article-journal","title":"Performance-Based Maintenance and Operation of Multi-Campus Critical Infrastructure Facilities Using Supply Chain Multi-Choice Goal Programming","abstract":"Building maintenance is a critical component of ensuring long-term performance, safety, and cost-efficiency in both conventional and critical infrastructures. While traditional contracting approaches have often led to inefficiencies and rigid procurement systems, recent developments in performance-based maintenance, digital technologies, and multi-objective optimization provide opportunities to enhance both operational reliability and energy performance. From a resilience perspective, the ability to sustain functionality, adapt maintenance intensity, and recover performance under resource or operational stress is essential for ensuring infrastructure continuity and resilience. This study develops and validates an optimization model for the operation and maintenance of large campus infrastructures, addressing the persistent imbalance between over-maintenance, where costs exceed optimal levels by up to 300%, and under-maintenance, which compromises performance continuity and weakens resilience over time. The model integrates maintenance efficiency indicators, building performance indices, and energy-efficiency retrofits, particularly LED-based lighting upgrades, within a multi-choice goal programming framework. Using datasets from 15 campuses comprising over 2000 buildings, the model was tested through case studies, sensitivity analyses, and simulations under varying facility life cycle expectancies. The facilities were analyzed for alternative life cycles of 25, 50, 75, and 90 years, and the design life cycle was set for 50 years. The results show that the optimized approach can reduce maintenance costs by an average of 34%, with savings ranging from 1% to 55% across campuses. Additionally, energy retrofit strategies such as LED replacement yielded significant economic and environmental benefits, with payback periods of approximately 2–2.5 years. The findings demonstrate that integrated maintenance and energy-efficiency planning can simultaneously enhance building performance, reduce costs, and support sustainability objectives, offering a practical decision-support tool for managing large-scale campus infrastructures.","author":[{"family":"Shohet","given":"Igal"},{"family":"Levi","given":"SN"},{"family":"Zeibak-Shini","given":"Reem"},{"family":"Shahin","given":"Fadi"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/app152011161","URL":"https://doi.org/10.3390/app152011161","source":"openalex"},{"id":"oa:W7155503288","type":"article-journal","title":"Achieving Sustainable Manufacturing Through Digital Leadership","abstract":"This study investigates the organizational drivers of sustainability performance in the manufacturing sector and proposes and tests an integrated model grounded in dynamic capability theory. Using structural equation modeling on empirical data, it examines the role of digital leadership as a catalyst for sustainable practices, mediated by digital knowledge management and organizational resilience. The findings confirm that digital leadership exerts a significant total effect on sustainability outcomes. Crucially, this influence is primarily channeled through two parallel mediating pathways: by building organizational resilience and by establishing systematic digital knowledge management. The model demonstrates high explanatory power, revealing that sustainability performance is a systemic achievement, dependent on the synergistic interaction of strategic leadership, institutionalized learning, and adaptive capacity.","author":[{"family":"Ge","given":"Zhihong"},{"family":"Linghe","given":"He"},{"family":"Khan","given":"Mohammed"},{"family":"Alam","given":"Shahid"},{"family":"Ghardallou","given":"Wafa"},{"family":"Vveinhardt","given":"Jolita"}],"issued":{"date-parts":[[2026]]},"DOI":"10.4018/joeuc.408168","URL":"https://doi.org/10.4018/joeuc.408168","source":"openalex"},{"id":"oa:W7165387419","type":"article-journal","title":"Twin transition in manufacturing firms: The role of supply chain orchestration and supply chain business model innovation","abstract":"Twin transition, the concurrent development of digitalization practices and circular practices, are believed to be the key to firm performance. However, empirical evidence is currently scarce regarding the effect of twin transition on firm performance and the complementary practices that enable and realize it. This study draws on a survey of 188 Swedish manufacturing firms and employs PLS structural equation modelling to test the hypothesis. The results indicate that firm performance can be improved through digitalization practices but with circular practices as a mediator. Moreover, our results show a significant and positive moderation effect of supply chain orchestration and supply chain business model innovation as complementary mechanisms for enabling and realizing the process. This implies time sequencing between the two twin transition dimensions. These results carry theoretical implications for twin transition research and circular economy literatures. The results also provide novel managerial insights by showing that digital investments must be coupled with early orchestration of supply chain partners and aligned business model innovation to effectively scale circular practices and realize performance benefits.","author":[{"family":"Panda","given":"Debadrita"},{"family":"Parida","given":"Vinit"},{"family":"Frishammar","given":"Johan"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.technovation.2026.103626","URL":"https://doi.org/10.1016/j.technovation.2026.103626","source":"openalex"},{"id":"oa:W7119518951","type":"article-journal","title":"Computational Design Strategies and Software for Lattice Structures and Functionally Graded Materials","abstract":"This study presents a comparative analysis of software platforms and computational methods used in the design of three-dimensional lattice structures and functionally graded materials (FGMs). Through systematic evaluation of 31 computational platforms across seven critical criteria (lattice type support, parametric control, conformal generation, multi-material capabilities, ease of use, FEA integration, and AM compatibility), this review identifies that specialized platforms significantly outperform general-purpose CAD tools, with scores exceeding 30/35 points compared to 15–20/35 for conventional systems. The analysis reveals that implicit and voxel-based representations dominate high-performance applications, while traditional boundary-representation methods approach fundamental limitations for complex lattice generation. Emerging machine learning-driven frameworks demonstrate 82% reduction in optimization iterations through Bayesian optimization and achieve property prediction speedups of nearly 100× compared to computational homogenization, enabling rapid inverse design workflows previously computationally infeasible. These insights provide researchers with evidence-based guidance for selecting computational approaches aligned with specific manufacturing capabilities and design objectives.","author":[{"family":"Prisecaru","given":"Delia"},{"family":"Ulerich","given":"Oliver"},{"family":"Călin","given":"Andrei"},{"family":"Paduraru","given":"Georgiana"}],"issued":{"date-parts":[[2026]]},"DOI":"10.3390/jcs10010032","URL":"https://doi.org/10.3390/jcs10010032","source":"openalex"},{"id":"oa:W7172496761","type":"article-journal","title":"Operator-in-the-Loop Digital Twin Enabled Augmented Reality for Assembly Quality Assurance","abstract":"Ensuring dimensional and geometric quality during manual and semi-automated assembly remains challenging in low-volume, high-complexity manufacturing systems. Operator variability, incomplete process standardization, and part-level geometric deviations frequently lead to tolerance non-conformities, rework, and installation delays. While digital twins offer strong potential for process monitoring and optimization, their integration with human operators during assembly execution remains limited. This paper proposes an operator-in-the-loop digital twin (OIL-DT) framework for tolerance-driven assembly quality assurance, in which augmented reality (AR) serves as a real-time interaction layer between digital and physical domains. The framework integrates CAD-based geometric models, assembly process plans, and tolerancing intent within a cyber–physical architecture, enabling spatially registered guidance and real-time alignment verification during assembly execution. Unlike instruction-centric AR systems, the proposed framework embeds executable tolerance constraints directly into assembly execution. A Design for Six Sigma (DMADV) logic is adopted to ensure traceable links between quality requirements, tolerancing specifications, and AR-based enforcement mechanisms. The framework is experimentally validated on the assembly of a hybrid renewable energy generation unit. Compared with conventional procedures, the AR-enabled approach reduced installation time and eliminated recurring tolerance-related interruptions previously causing extended delays. The results demonstrate that embedding tolerance enforcement and execution traceability within an OIL-DT can significantly improve assembly robustness and consistency without reducing operator autonomy.","author":[{"family":"Karganroudi","given":"Sasan"},{"family":"Aminzadeh","given":"Ahmad"},{"family":"Moghaddam","given":"Milad"},{"family":"Tahan","given":"Souheil"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1016/j.procir.2026.03.136","URL":"https://doi.org/10.1016/j.procir.2026.03.136","source":"openalex"},{"id":"oa:W7204226074","type":"article-journal","title":"Artificial intelligence for quality control and monitoring in directed energy deposition metal additive manufacturing: applications, challenges, and opportunities","abstract":"Directed energy deposition (DED) is a versatile metal additive manufacturing (MAM) technique that enables the fabrication and repair of high-value components across diverse industries. However, ensuring consistent quality in DED remains a persistent challenge due to the complex interplay of thermal gradients, material behavior, and process parameters. In recent years, artificial intelligence (AI) methodologies, particularly machine learning (ML) and deep learning (DL), have shown significant promise in enhancing quality control and real-time monitoring in DED processes. This study presents a systematic literature review of AI-enabled quality control and monitoring in DED, with emphasis on defect detection, process-state monitoring, physics-informed modeling, digital twins, industrial readiness, and the comparison between AI-based and conventional inspection approaches. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, 145 peer-reviewed articles published between 2015 and 2026 were analyzed. Quality issues in DED are classified into geometrical, morphological, and microstructural categories, and the use of AI is analyzed for each category. The review shows that convolutional neural networks (CNNs), random forests, autoencoders, and related ML/DL models have been widely applied for melt-pool monitoring, thermal and visual signal interpretation, defect classification, geometric prediction, and process-condition assessment. The comparative analysis indicates that conventional methods remain essential for direct measurement, validation, and qualification, whereas AI-based methods are mainly positioned for in-process prediction, early warning, screening, and potential closed-loop control. Emerging physics-informed ML and digital twin frameworks further extend AI capabilities by linking process data with thermal, geometric, and defect-related quality states. Despite these advances, key challenges remain in data acquisition, sensor reliability, the interpretability of AI models, and generalization across geometries and materials. This review identifies future research needs in data-efficient learning, physics-integrated sensor fusion, robust and interpretable modeling, standardized quality metrics, and industrially deployable closed-loop control. By synthesizing current research, the study provides a consolidated foundation for advancing AI-enabled DED quality assurance from research purpose demonstrations toward scalable, traceable, and qualification-ready manufacturing systems.","author":[{"family":"Debnath","given":"Binoy"},{"family":"Zihan","given":"Tasbirul"},{"family":"Ruiz","given":"Cesar"},{"family":"Allen","given":"Janet"},{"family":"Raman","given":"Shivakumar"}],"issued":{"date-parts":[[2026]]},"DOI":"10.1007/s10845-026-02931-2","URL":"https://doi.org/10.1007/s10845-026-02931-2","source":"openalex"},{"id":"oa:W4416730494","type":"article-journal","title":"Review of Recent Advances in Lithium-Ion Batteries: Sources, Extraction Methods, and Industrial Uses","abstract":"Lithium-ion batteries (LIBs) have become the leading energy storage technology because of their high specific energy, excellent efficiency, and longer lifespan. This review offers a comprehensive overview of the lithium battery industry, covering lithium materials and the global supply chain, as well as examining traditional and sustainable extraction methods. The discussion includes the technical and environmental challenges of each extraction method, with particular emphasis on feedstock selection, which greatly influences lithium recovery efficiency, yield, and ecological impact, and capital and operating expenditures. It also investigates the growth of the global battery recycling industry and provides an outlook on innovations in this area. These innovations include recycling systems, a case study on Biomass Energy Systems Inc., and the battery chemistries needed to support a circular economy. The review highlights industrial applications of LIBs in sectors such as automotive, consumer electronics, and aerospace. Finally, it addresses supply chain and recycling challenges related to LIBs, positioning cost, environmental footprint, and regulatory compliance as central considerations for the future of the battery industry.","author":[{"family":"Fatoki","given":"Olukayode"},{"family":"Mohammed","given":"Habeeb"},{"family":"Parupelli","given":"Santosh"},{"family":"Mathew","given":"Alex"},{"family":"Kaur","given":"Manpreet"},{"family":"Rehmat","given":"Amir"},{"family":"Muhammed","given":"Suhaimi"},{"family":"Bastakoti","given":"Bishnu"},{"family":"Desai","given":"Salil"}],"issued":{"date-parts":[[2025]]},"DOI":"10.3390/batteries11120433","URL":"https://doi.org/10.3390/batteries11120433","source":"openalex"},{"id":"oa:W4401179667","type":"article-journal","title":"A comprehensive overview of industrial demand response status in Europe","abstract":"Industrial demand response (IDR) will play a crucial role in shaping future electricity systems, as it is a key element of a just energy transition and industrial development. The aim of this work is to provide an overview of the current status of IDR in a holistic perspective. First, the main benefits and potential of IDR are reviewed, together with the motivations and challenges for the industrial sector. Most recent advances in European markets and regulations with specific focus on IDR applications are explored. Then, the different resources which are currently available to help industries participate and implement IDR programmes are reviewed. In particular: 1) the (possible) tools for defining energy-aware scheduling and planning of the manufacturing systems are analysed; 2) The role of aggregators (i.e. intermediaries between industries and power markets) for facilitating explicit IDR is examined; 3) the importance of digitalisation to provide better IDR services from the manufacturing industry is highlighted, pointing out that digital twins, cyber-physical systems, Internet of Things sensors, robots, edge computing, artificial intelligence, and big data are promising technologies; and 4) most recent related research projects are reviewed. Finally, it is analysed and discussed how each of those resources can address the different challenges that are still preventing industries to apply IDR programmes.","author":[{"family":"Ranaboldo","given":"Matteo"},{"family":"Aragüéspeñalba","given":"Mònica"},{"family":"Arica","given":"Emrah"},{"family":"Bade","given":"A"},{"family":"Bullichmassagué","given":"Eduard"},{"family":"Burgio","given":"Alessandro"},{"family":"Caccamo","given":"Chiara"},{"family":"Caprara","given":"Adriano"},{"family":"Cimmino","given":"Domenico"},{"family":"Domenech","given":"Bruno"},{"family":"Donoso","given":"I"},{"family":"Fragapane","given":"Giuseppe"},{"family":"González-Fontderubinat","given":"Paula"},{"family":"Jahnke","given":"E"},{"family":"Juanpera","given":"Marc"},{"family":"Manafi","given":"Ehsan"},{"family":"Rövekamp","given":"Jessica"},{"family":"Tani","given":"R"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.rser.2024.114797","URL":"https://doi.org/10.1016/j.rser.2024.114797","source":"openalex"},{"id":"oa:W4400646805","type":"article-journal","title":"Digital Footprints of Obesity Treatment: GLP-1 Receptor Agonists and the Health Equity Divide","abstract":"Our research investigates the societal implications of access to glucagon-like peptide-1 (GLP-1) agonists, particularly in light of recent clinical trials demonstrating the efficacy of semaglutide in reducing cardiovascular mortality. A decade-long analysis of Google Trends indicates a significant increase in searches for GLP-1 agonists, primarily in North America. This trend contrasts with the global prevalence of obesity. Given the high cost of GLP-1 agonists, a critical question arises: Will this disparity in medication accessibility exacerbate the global health equity gap in obesity treatment? This viewpoint explores strategies to address the health equity gap exacerbated by this emerging medication. Because GLP-1 agonists hold the potential to become a cornerstone in obesity treatment, ensuring equitable access is a pressing public health concern.","author":[{"family":"Azizi","given":"Zahra"},{"family":"Rodríguez","given":"Fátima"},{"family":"Assimes","given":"Themistocles"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1161/circulationaha.124.069680","URL":"https://doi.org/10.1161/circulationaha.124.069680","source":"openalex"},{"id":"oa:W4383265533","type":"article-journal","title":"Devising a method for detecting “evil twin” attacks on IEEE 802.11 networks (Wi-Fi) with KNN classification model","abstract":"The object of research is IEEE 802.11 (Wi-Fi) networks, which are often the targets of a group of attacks called \"evil twin\". Research into this area is extremely important because Wi-Fi technology is a very common method of connecting to a network and is usually the first target of cybercriminals when they attack businesses. With the help of a systematic analysis of the literature focused on countering attacks of the \"evil twin\" type, this work identifies the main advantages of using artificial intelligence systems in the analysis of network data and identification of intrusions in Wi-Fi networks. To evaluate the effectiveness of intrusion detection and cybercrime analysis, a number of experiments as close as possible to real attacks on Wi-Fi networks were conducted. As part of the research reported in this paper, a method is proposed for detecting cybercrimes in IEEE 802.11 (Wi-Fi) wireless networks using artificial intelligence, namely a model built on the basis of the k-nearest neighbors method. This method is based on the classification of previously collected data, namely the signal strength from the access point, and then continuous comparison of the newly collected data with the trained model. A compact and energy-efficient prototype of a hardware and software system has been designed for the implementation of monitoring, analysis of ethernet network packets and data storage based on time series. In order to reduce the load on the computer network and taking into account the limited computing power of the system, a method of data aggregation was proposed, which ensures fast transfer of information. The results, namely 100 % of test cases (more than 7 thousand), were classified correctly, which indicates that the chosen method of data analysis will significantly increase the security of information and communication systems at the state and private levels","author":[{"family":"Банах","given":"Роман"},{"family":"Piskozub","given":"Andrian"},{"family":"Оpirskyy","given":"Іvan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.15587/1729-4061.2023.282131","URL":"https://doi.org/10.15587/1729-4061.2023.282131","source":"openalex"},{"id":"oa:W4389428089","type":"article-journal","title":"A comprehensive literature review of the applications of AI techniques through the lifecycle of industrial equipment","abstract":"Abstract Driven by the ongoing migration towards Industry 4.0, the increasing adoption of artificial intelligence (AI) has empowered smart manufacturing and digital transformation. AI enhances the migration towards industry 4.0 through AI-based decision-making by analyzing real-time data to optimize different processes such as production planning, predictive maintenance, quality control etc., thus guaranteeing reduced costs, high precision, efficiency and accuracy. This paper explores AI-driven smart manufacturing, revolutionizing traditional approaches and unlocking new possibilities throughout the major phases of the industrial equipment lifecycle. Through a comprehensive review, we delve into a wide range of AI techniques employed to tackle challenges such as optimizing process control, machining parameters, facilitating decision-making, and elevating maintenance strategies within the major phases of an industrial equipment lifecycle. These phases encompass design, manufacturing, maintenance, and recycling/retrofitting. As reported in the 2022 McKinsey Global Survey ( https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review ), the adoption of AI has witnessed more than a two-fold increase since 2017. This has contributed to an increase in AI research within the last six years. Therefore, from a meticulous search of relevant electronic databases, we carefully selected and synthesized 42 articles spanning from 01 January 2017 to 20 May 2023 to highlight and review the most recent research, adhering to specific inclusion and exclusion criteria, and shedding light on the latest trends and popular AI techniques adopted by researchers. This includes AI techniques such as Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Bayesian Networks, Support Vector Machines (SVM) etc., which are extensively discussed in this paper. Additionally, we provide insights into the advantages (e.g., enhanced decision making) and challenges (e.g., AI integration with legacy systems due to technical complexities and compatibilities) of integrating AI across the major stages of industrial equipment operations. Strategically implementing AI techniques in each phase enables industries to achieve enhanced productivity, improved product quality, cost-effectiveness, and sustainability. This exploration of the potential of AI in smart manufacturing fosters agile and resilient processes, keeping industries at the forefront of technological advancements and harnessing the full potential of AI-driven solutions to improve manufacturing processes and products.","author":[{"family":"Elahi","given":"Mahboob"},{"family":"Afolaranmi","given":"Samuel"},{"family":"Lastra","given":"José"},{"family":"García","given":"José"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1007/s44163-023-00089-x","URL":"https://doi.org/10.1007/s44163-023-00089-x","source":"openalex"},{"id":"oa:W4393023577","type":"manuscript","title":"Mixed-Reality Digital Twins: Leveraging the Physical and Virtual Worlds for Hybrid Sim2Real Transition of Multi-Agent Reinforcement Learning Policies","abstract":"Multi-agent reinforcement learning (MARL) for cyber-physical vehicle systems usually requires a significantly long training time due to their inherent complexity. Furthermore, deploying the trained policies in the real world demands a feature-rich environment along with multiple physical embodied agents, which may not be feasible due to monetary, physical, energy, or safety constraints. This work seeks to address these pain points by presenting a mixed-reality (MR) digital twin (DT) framework capable of: (i) boosting training speeds by selectively scaling parallelized simulation workloads on-demand, and (ii) immersing the MARL policies across hybrid simulation-to-reality (sim2real) experiments. The viability and performance of the proposed framework are highlighted through two representative use cases, which cover cooperative as well as competitive classes of MARL problems. We study the effect of: (i) agent and environment parallelization on training time, and (ii) systematic domain randomization on zero-shot sim2real transfer, across both case studies. Results indicate up to 76.3% reduction in training time with the proposed parallelization scheme and sim2real gap as low as 2.9% using the proposed deployment method.","author":[{"family":"Samak","given":"Chinmay"},{"family":"Samak","given":"Tanmay"},{"family":"Krovi","given":"Venkat"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2403.10996","URL":"https://doi.org/10.48550/arxiv.2403.10996","source":"openalex"},{"id":"oa:W4360994956","type":"article-journal","title":"Data-driven soft sensors in blast furnace ironmaking: a survey","abstract":"The blast furnace is a highly energy-intensive, highly polluting, and extremely complex reactor in the ironmaking process. Soft sensors are a key technology for predicting molten iron quality indices reflecting blast furnace energy consumption and operation stability, and play an important role in saving energy, reducing emissions, improving product quality, and producing economic benefits. With the advancement of the Internet of Things, big data, and artificial intelligence, data-driven soft sensors in blast furnace ironmaking processes have attracted increasing attention from researchers, but there has been no systematic review of the data-driven soft sensors in the blast furnace ironmaking process. This review covers the state-of-the-art studies of data-driven soft sensors technologies in the blast furnace ironmaking process. Specifically, we first conduct a comprehensive overview of various data-driven soft sensor modeling methods (multiscale methods, adaptive methods, deep learning, etc.) used in blast furnace ironmaking. Second, the important applications of data-driven soft sensors in blast furnace ironmaking (silicon content, molten iron temperature, gas utilization rate, etc.) are classified. Finally, the potential challenges and future development trends of data-driven soft sensors in blast furnace ironmaking applications are discussed, including digital twin, multi-source data fusion, and carbon peaking and carbon neutrality.","author":[{"family":"Luo","given":"Yueyang"},{"family":"Zhang","given":"Xinmin"},{"family":"Kano","given":"Manabu"},{"family":"Deng","given":"Long"},{"family":"Yang","given":"Chunjie"},{"family":"Song","given":"Zhihuan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1631/fitee.2200366","URL":"https://doi.org/10.1631/fitee.2200366","source":"openalex"},{"id":"oa:W4381996201","type":"article-journal","title":"IMMERSIVE APPIAN WAY HEALTH INFRASTRUCTURE: HUMAN CENTRIC DIGITAL TWIN (THE PAAA ARCHEOLOGICAL PARK OF THE APPIAN WAY 12KM STATE-OWN SECTION, UNESCO CANDIDATURE)","abstract":"Abstract. From Rome to Benevento, the Appian Way (Via Appia Antica) was born as a military road, 'Regina Viarum'. In 312 b.C., consul Appio Claudio extended the infrastructure for 132 miles to Capua. Many transformations and integration occurred across the centuries, resulting in a unique multi-stratified world heritage (landscape, architecture, archaeological remains and tombs along the military way). In the 19th century, Luigi Canina conceived the Appian Way as an outdoor museum, realizing a first state-own section along the 12km here surveyed and described. This year, the Ministry of Culture (MIC) has launched the UNESCO nomination for the road. The article discusses aspects of the mass digitization undertaken by the Parco Archeologico dell'Appia Antica (PAAA, the Archaeological Park of the Appian Way). The aim is to build a Digital Twin of the infrastructure supporting knowledge enhancement, preservation, design, communication and fruition. A virtual space where digital technologies and eXtended Reality are the digital arms of the contemporary Vitruvian humanistic mission and vision of the PAAA Appian Way as a source of wealth and healthiness for all the users and visitors.","author":[{"family":"Brumana","given":"Raffaella"},{"family":"Quilici","given":"S"},{"family":"Oliva","given":"L"},{"family":"Previtali","given":"M"},{"family":"Attico","given":"Dario"},{"family":"Roncoroni","given":"Fabio"},{"family":"Stanga","given":"C"}],"issued":{"date-parts":[[2023]]},"DOI":"10.5194/isprs-archives-xlviii-m-2-2023-311-2023","URL":"https://doi.org/10.5194/isprs-archives-xlviii-m-2-2023-311-2023","source":"openalex"},{"id":"oa:W4402096635","type":"article-journal","title":"DIGITAL TECHNOLOGIES IN THE FINANCIAL SECTOR OF THE ECONOMY","abstract":"The article is devoted to the study of the main trends in the development of digital technologies in the financial sector of the economy, namely, the topic is relevant in the context of rapid globalization, digitalization and transition to digital ecosystems. The modern financial sector of the economy at different stages of its life cycle cannot function without the use of digital technologies. In addition, online activity, browsing social networks, and web pages, and using various applications are essential for civil society. The purpose of this paper is to study the changing impact of advanced technologies on digital security, as well as to substantiate the trends in the development of digital technologies in the financial sector of the economy.The article characterizes the risks arising from the digitalization of the economy - the results of the analysis show that the effective use of these factors can stimulate the competitiveness of financial institutions. The level of threat in data management is investigated, which should be taken into account when forecasting potential threats of digitalization in the financial sector of the economy, which allows the management of institutions to optimize: financial, human and technological resources for risk management and take measures to offset possible losses from cyber threats and restore the stable development of economic systems.The article identifies trends in the development of digital technologies in the financial sector of the economy that require detailed study and provide for the transition to a modern digital financial platform. This transition will not only strengthen the country's domestic market, increasing the level of independence from the import of foreign technologies but will also contribute to improving the global importance of the economy. Therefore, the use of digital technologies in the financial sector of the economy is of key importance, and effective financing in the new economic reality largely ensures the success of the country's socio-economic development.","author":[{"family":"Biliavskyi","given":"Valentyn"},{"family":"Biliavska","given":"Yuliia"},{"family":"Umantsiv","given":"Yurii"},{"family":"Shestack","given":"Yaroslav"},{"family":"Журба","given":"Олександр"},{"family":"Хаванов","given":"Артем"}],"issued":{"date-parts":[[2024]]},"DOI":"10.55643/fcaptp.4.57.2024.4444","URL":"https://doi.org/10.55643/fcaptp.4.57.2024.4444","source":"openalex"},{"id":"oa:W4390049501","type":"article-journal","title":"A Model-Based Approach Towards the Conceptualization of Digital Twins: The Case of the EU-Project COGITO","abstract":"In agile business ecosystems, digitalization is a key enabler for agility and flexibility. However, digital transformation is often challenging for instance due to unclear definitions and a lack of problem understanding. In this work this complexity is addressed with a model-based approach for conceptualizing digitalization and related meta modelling activities to enable the conceptual integration of diverse concepts. Existing modelling approaches – BPMN and ArchiMate – are leveraged with domain specific considerations that are relevant for the digitalization. The construction use case from the European project COGITO serves as a foundation for ideation and first requirements engineering. Physical experiments in the OMiLAB Innovation Environment are used as an experimental method towards identifying relevant digital twinning concepts, while modelling methods can be seen as an integration platform for physical and digital elements. Key digitalization aspects towards digital twinning are discussed and conceptualized in a meta model.","author":[{"family":"Sumereder","given":"Anna"},{"family":"Burzynski","given":"Patrik"},{"family":"Karagiannis","given":"Dimitris"},{"family":"Woitsch","given":"Robert"}],"issued":{"date-parts":[[2023]]},"DOI":"10.62036/isd.2023.5","URL":"https://doi.org/10.62036/isd.2023.5","source":"openalex"},{"id":"oa:W4327696245","type":"article-journal","title":"News Reporting in Drone Internet of Things Digital Journalism","abstract":"The current study investigated several innovations for drone technology adoption in journalistic expeditions for intelligence and news gathering purposes. The necessity to leverage technologies to improve the direct involvement of eyewitnesses especially in violence-prone areas where physical and direct human involvement would be impossible or with high risk of survivability expectations is the motivating factor that directed the current research. The paper surveys the adoption of autonomous sensing drone systems in internet of things journalism and amalgamated the theoretic ingredients from the academic standpoint with realistic technological advancements from the global perspective and eventually expanded the propositions for conceivable adoption in the credible societal applications. The paper envisioned the future journalism and mass media practices and how drone innovation can revolutionize the journalism profession for the purpose of news and intelligence gathering with practical and technical realism with reduction of journalistic casualties.","author":[{"family":"Nwanakwaugwu","given":"Andrew"},{"family":"Matthew","given":"Ugochukwu"},{"family":"Okey","given":"Ogobuchi"},{"family":"Kazaure","given":"Jazuli"},{"family":"Nwamouh","given":"Ubochi"}],"issued":{"date-parts":[[2023]]},"DOI":"10.4018/ijicst.320181","URL":"https://doi.org/10.4018/ijicst.320181","source":"openalex"},{"id":"oa:W4405722475","type":"article-journal","title":"Energy in Smart Cities: Technological Trends and Prospects","abstract":"Energy management in smart cities has gained particular significance in the context of climate change and the evolving geopolitical landscape. It has become a key element of sustainable urban development. In this context, energy management plays a central role in facilitating the growth of smart and sustainable cities. The aim of this article is to analyse existing scientific research related to energy in smart cities, identify technological trends, and highlight prospective directions for future studies in this field. The research involves a literature review based on the analysis of articles from the Scopus and Web of Science databases to identify and evaluate studies concerning energy in smart cities. The findings suggest that future research should focus on the development of smart energy grids, energy storage, the integration of renewable energy sources, as well as innovative technologies (e.g., Internet of Things, 5G/6G, artificial intelligence, blockchain, digital twins). This article emphasises the significance of technologies that can enhance energy efficiency in cities, contributing to their sustainable development. The recommended practical and policy directions highlight the development of smart grids as a cornerstone for adaptive energy management and the integration of renewable energy sources, underpinned by regulations encouraging collaboration between operators and consumers. Municipal policies should prioritise the adoption of advanced technologies, such as the IoT, AI, blockchain, digital twins, and energy storage systems, to improve forecasting and resource efficiency. Investments in zero-emission buildings, renewable-powered public transport, and green infrastructure are essential for enhancing energy efficiency and reducing emissions. Furthermore, community engagement and awareness campaigns should form an integral part of promoting sustainable energy practices aligned with broader development objectives.","author":[{"family":"Szpilko","given":"Danuta"},{"family":"Fernando","given":"Xavier"},{"family":"Nica","given":"Elvira"},{"family":"Budna","given":"Klaudia"},{"family":"Rzepka","given":"Agnieszka"},{"family":"Lăzăroiu","given":"George"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/en17246439","URL":"https://doi.org/10.3390/en17246439","source":"openalex"},{"id":"oa:W4399176611","type":"article-journal","title":"Digital Twinning‐Based Autonomous Take‐Off, Landing, and Cruising for Unmanned Aerial Vehicles","abstract":"Drones, or unmanned aerial vehicles (UAVs), have altered many sectors, most notably the security, transportation, and maintenance sectors. Autonomy in UAV operations remains a major research challenge, especially in high-stake flying phases like take-off, landing, and cruising. This research investigates the feasibility of using digital twin-based methods to improve UAV autonomy during certain flight stages. The study aims to learn more about digital twinning, how it works, what problems it solves, how it may be implemented, and what advantages and disadvantages it has over existing systems. The study begins by explaining digital twins and how they might be used in crewless aerial vehicles. It focuses on how digital twinning uses real-time data capture, sensor fusion, and environmental analysis to realize UAV autonomy. Next, we look at the difficulties and restrictions of today's techniques for autonomous take-off, landing, and flight. Digital twinning-based systems are discussed regarding the gaps they intend to fill, such as the over-reliance on pre-programmed flight paths and the restricted flexibility they now offer. An architecture is provided for implementing digital twin technology in UAVs. The framework specifies the hardware, software, algorithms, and data for fully autonomous flights. It highlights the importance of having a physical UAV and its digital twin that sync regarding sensor technology, compute capacity, and synchronization. Possible advantages of methods based on digital twins are mentioned, such as increased flexibility, quicker reaction times, and greater protection. Sensor optimization, processing needs, and data security are also discussed as examples of feasibility issues. By looking ahead, we can fully realize the benefits of digital twinning-based autonomous operations for UAVs, ushering in a new era of highly effective, highly flexible, and highly secure UAV missions.","author":[{"family":"Singh","given":"Kiran"},{"family":"Singh","given":"Prabhdeep"},{"family":"Angurala","given":"Mohit"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/9781394257003.ch7","URL":"https://doi.org/10.1002/9781394257003.ch7","source":"openalex"},{"id":"oa:W4360616589","type":"article-journal","title":"Comprehensive Review of Recent Advancements in Battery Technology, Propulsion, Power Interfaces, and Vehicle Network Systems for Intelligent Autonomous and Connected Electric Vehicles","abstract":"Numerous recent innovations have been achieved with the goal of enhancing electric vehicles and the parts that go into them, particularly in the areas of managing energy, battery design and optimization, and autonomous driving. This promotes a more effective and sustainable eco-system and helps to build the next generation of electric car technology. This study offers insights into the most recent research and advancements in electric vehicles (EVs), as well as new, innovative, and promising technologies based on scientific data and facts associated with e-mobility from a technological standpoint, which may be achievable by 2030. Appropriate modeling and design strategies, including digital twins with connected Internet of Things (IoT), are discussed in this study. Vehicles with autonomous features have the potential to increase safety on roads, increase driving economy, and provide drivers more time to focus on other duties thanks to the Internet of Things idea. The enabling technology that entails a car moving out of a parking spot, traveling along a long highway, and then parking at the destination is also covered in this article. The development of autonomous vehicles depends on the data obtained for deployment in actual road conditions. There are also research gaps and proposals for autonomous, intelligent vehicles. One of the many social concerns that are described is the cause of an accident with an autonomous car. A smart device that can spot strange driving behavior and prevent accidents is briefly discussed. In addition, all EV-related fields are covered, including the likely technical challenges and knowledge gaps in each one, from in-depth battery material sciences through power electronics and powertrain engineering to market assessments and environmental assessments.","author":[{"family":"Abro","given":"Ghulam"},{"family":"Zulkifli","given":"Saiful"},{"family":"Kumar","given":"Kundan"},{"family":"Ouanjli","given":"Najib"},{"family":"Asirvadam","given":"Vijanth"},{"family":"Mossa","given":"Mahmoud"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/en16062925","URL":"https://doi.org/10.3390/en16062925","source":"openalex"},{"id":"oa:W4376955598","type":"article-journal","title":"Towards a seamless data cycle for space components: considerations from the growing European future digital ecosystem Gaia-X","abstract":"Abstract ESA’s Design 2 produces cross-cutting initiative includes digitalisation, process automation, interoperability, and harnessing smart embedded sensors to achieve a seamless data cycle (SDC). The SDC in digital engineering covers requirements and design, production, assembly, integration, and testing as well as in-flight operations including recycling. Nevertheless, central data and legal challenges lie in the joint research addressed Europe-wide (geo-return) and the partner network constraints covering agency, large system integrator (LSI), research and development (R&D), and high-tech SME interests. Either way, a legal enabler for digitization of the European space business can be seen in ESA's strict compliance policy with regard to the acceptance of their general terms and conditions. In fact, it is reasonable to assume that ESA declares data to be a common deliverable in the future and that the contractors accept this too. However, there are technical challenges like portability, interoperability, interconnectivity, and the need for a federated infrastructure, while all these aspects have to be solved across company and national borders. The European Gaia-X project tackles the aforementioned challenges while targeting an open, transparent, and secure digital ecosystem in which data are stored, processed, and used while retaining data sovereignty. This paper deepens these framework conditions, addresses them from the perspective of real space applications, and presents key opportunities and challenges at the implementation level. Moreover, it shows how the seamless data cycle contributes to increase freedom of design, improve overall performance, and reduce cost and lead time from concept to manufacturing while creating new high-performance space products.","author":[{"family":"Seidel","given":"André"},{"family":"Wenzel","given":"Ken"},{"family":"Hänel","given":"Albrecht"},{"family":"Teicher","given":"Uwe"},{"family":"Weiß","given":"Annette"},{"family":"Schäfer","given":"U"},{"family":"Ihlenfeldt","given":"Steffen"},{"family":"Eisenmann","given":"H"},{"family":"Ernst","given":"Holger"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1007/s12567-023-00500-4","URL":"https://doi.org/10.1007/s12567-023-00500-4","source":"openalex"},{"id":"oa:W4404977987","type":"article-journal","title":"An immersive interface for remote collaboration with multiple telepresence robots through digital twin spaces","abstract":"A human-robot collaboration system “Telecobot” is proposed, in which a remote user allocates tasks to multiple telepresence robots via digital twin spaces. The digital twin spaces of local sites where robots work is used as a medium to observe the real spaces from a remote site and to give instructions to the smart robots on the local site. Telecobot supports a remote user understanding the real-time status of local sites distributed geographically and allocating tasks to each of the robots. We assume that the robots are smart enough to execute the series of tasks assigned by the remote user. This division of roles is a major characteristic of Telecobot, where a remote user is responsible for judging the situation and building a series of tasks via the digital twin space, while multiple robots working in each of the local sites executes the individual tasks following the information built by the remote user in the digital twins of the local sites. An experiment assuming telecollaboration with smart robots working at nursing care sites demonstrated the division of roles for the care works and showed the potential of increasing the productivity of the work by using the Telecobot interface.","author":[{"family":"Yoshioka","given":"Sawa"},{"family":"Fukushige","given":"Shinichi"},{"family":"Seki","given":"Kohta"},{"family":"Kawakami","given":"Mizuki"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1145/3681756.3697940","URL":"https://doi.org/10.1145/3681756.3697940","source":"openalex"},{"id":"oa:W4385873883","type":"article-journal","title":"Fuel and Energy Complex of Kazakhstan: Geological and Economic Assessment of Enterprises in the Context of Digital Transformation","abstract":"The relevance of the study is dictated by the growing role of the fuel and energy complex of developing countries in the decarbonization of the economy. The article discusses the digital transformation of mining enterprises in Kazakhstan, taking into account the transition to CRIRSCO international standards and growing competition in the global mineral market. The purpose of the study is to assess the current level of digitalization of the mining industry in Kazakhstan and to deepen the methodological apparatus of the geological and economic assessment of the enterprise based on the factual base of deposits. The role of the transformation of the mining sector in achieving the sustainability of the poorly diversified economy of Kazakhstan is shown. The importance of digitalization of the industry to complete the transition to CRIRSCO international standards and improve the assessment of the digital provision of enterprises in order to optimize their financial and economic policies is argued. It has been established that, at present, most of the enterprises in the investment-attractive mining sector have a low potential for the transition to a new technological paradigm. A methodological approach to the geological and economic assessment of these enterprises has been developed. To maintain high standards of management transparency through the digitalization of key business processes, along with well-known practices of economic analysis, the IDEF1 methodology was used. In order to expand the software ecosystem, the formats of electronic geological and economic databases are integrated into the digital infrastructure of the enterprise. It is substantiated that the introduction of high technologies in the mining industry requires institutional changes and coordinated interaction between the state, business, and universities as equal partners.","author":[{"family":"Issatayeva","given":"Farida"},{"family":"Аубакирова","given":"ГМ"},{"family":"Maussymbayeva","given":"Aliya"},{"family":"Togaibayeva","given":"Lyussiya"},{"family":"Biryukov","given":"Valery"},{"family":"Vechkinzova","given":"Elena"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/en16166002","URL":"https://doi.org/10.3390/en16166002","source":"openalex"},{"id":"doi:10.1109/bmsb62888.2024.10608284","type":"article-journal","title":"Federated Digital Twin Implementation Methodology to Build a Large-Scale Digital Twin System","abstract":"This paper considers an implementation methodology for large-scale digital twin system. In our research, federated digital twin implementation methodology is proposed to build the large-scale digital twin system. In the proposed methodology, multiple single digital twin system can be connected and the output data of the multiple digital twin systems is federated. Typically, a single digital twin system is developed to digitally mimic a single physical object, system, or single process. Therefore, in the proposed methodology, the large-scale digital twin can be implemented based on federation of multiple single digital twin systems. To federate the multiple single digital twin systems, single digital twin management, validation and federation techniques are required. Therefore, proposed methodology suggests the architecture and functions of the digital twin federation system.","author":[{"family":"Baek","given":"Myung"},{"family":"Jung","given":"Euisuk"},{"family":"Park","given":"Young"},{"family":"Lee","given":"Yong"},{"family":"Jung","given":"Eui‐suk"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/bmsb62888.2024.10608284","URL":"https://doi.org/10.1109/bmsb62888.2024.10608284","source":"openalex"},{"id":"oa:W4385327150","type":"article-journal","title":"Digital twin deployment for smart agriculture in Cloud-Fog-Edge infrastructure","abstract":"The rapid adoption of Cloud, Fog, and Edge computing paradigms, along with Digital Twin (DT) technology, is being observed across numerous domains.Smart Agriculture is one such domain, where diverse requirements exist for applications that range from Augmented Reality, Satellite, and auto harvesters to a multitude of agricultural devices and sensors.While the integration of Cloud, Fog, and Edge computing can address various challenges, it can also pose some difficulties, including resource allocation, resource scheduling, and task scheduling.To address these challenges and enhance the productivity and sustainability of Smart Agriculture, this paper presents a novel architecture based on Cloud, Fog, Edge computing, and Multi-Agent Systems (MAS), incorporating the concept of Digital Twin.This proposed architecture is implemented in Smart Agricultural farms and fields, opening up new contemporary applications in the Agriculture domain.","author":[{"family":"Kalyani","given":"Yogeswaranathan"},{"family":"Bermeo","given":"Nestor"},{"family":"Collier","given":"Rem"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1080/17445760.2023.2235653","URL":"https://doi.org/10.1080/17445760.2023.2235653","source":"openalex"},{"id":"oa:W4324116351","type":"article-journal","title":"Incipient Interturn Short-Circuit Fault Diagnosis of Permanent Magnet Synchronous Motors Based on the Data-Driven Digital Twin Model","abstract":"As the most common fault of permanent magnet synchronous motor (PMSM), interturn short-circuit fault (ISCF) has great harm and develops rapidly. Once it is not diagnosed in time, it will bring secondary damage to the motor system. In the process of early fault diagnosis, the harmonic of the motor often increases the difficulty of fault feature extraction. In order to improve the reliability of the system, a method for early interturn short-circuit diagnosis of PMSMs based on data-driven digital twin models is proposed in this article. First, the three-phase current residuals of the PMSM under ISCF are analyzed theoretically. Second, the digital twin model of the target motor in healthy states is established through nonlinear auto-regressive model with exogenous inputs (NARX) network. Finally, the early short-circuit diagnosis is completed through the analysis of the three-phase current residual. The method proposed in this article does not need fault data and can complete the diagnosis of minor faults under the condition of large harmonic and certain inherent asymmetry. It has high sensitivity and obvious fault characteristics. Theoretical derivation and experiments verify the effectiveness of the proposed method.","author":[{"family":"Chen","given":"Zhichao"},{"family":"Liang","given":"Deliang"},{"family":"Jia","given":"Shaofeng"},{"family":"Yang","given":"Lin"},{"family":"Yang","given":"Shuzhou"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/jestpe.2023.3255249","URL":"https://doi.org/10.1109/jestpe.2023.3255249","source":"openalex"},{"id":"oa:W4400683926","type":"article-journal","title":"Digital twins: a new paradigm in oncology in the era of big data","abstract":"Recent advancements in health care digitalization opened the collection and availability of big data, whose analysis requires artificial intelligence-based technologies to facilitate the development of predictive tools supporting decision making in clinical practice. In this context, the idea of constructing ‘digital worlds' to evaluate the performance of such novel tools becomes more attractive. Digital twins (DTs) are ‘digital objects' characterized by a bi-directional interaction with their ‘real-world counterparts'. DTs aim to enhance predictions further by leveraging both the predictive capabilities of digital simulations and the continuous updating of real-life data—ideally incorporating clinical records, multiomics data, and patient-reported outcomes. DTs can potentially integrate these diverse data into virtual models applicable across pre-clinical to clinical studies. Running simulations in silico on cancer cells or cancer patients' DTs can provide valuable insights into cancer biology, clinical practice, and health care education, with the added value of reducing costs and overcoming many common limitations of current studies (limited number of variables, challenges in recruiting patients with rare tumors, lack of real-life feedback). Despite their significant potential, DTs are still in their infancy, facing numerous unsolved technical and ethical challenges that hinder their application in clinical practice.","author":[{"family":"Mollica","given":"Luigina"},{"family":"Leli","given":"Claudia"},{"family":"Sottotetti","given":"Federico"},{"family":"Quaglini","given":"Silvana"},{"family":"Locati","given":"Laura"},{"family":"Marceglia","given":"Sara"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.esmorw.2024.100056","URL":"https://doi.org/10.1016/j.esmorw.2024.100056","source":"openalex"},{"id":"oa:W4367611274","type":"article-journal","title":"Digital Twins of the Ocean can foster a sustainable blue economy in a protected marine environment","abstract":"While the field of hydrography is crucial for maritime navigation and other maritime applications, oceanography is the field that provides the relevant data and knowledge for predicting climate change, monitoring marine resources, and exploring marine life. Digital ocean twins combine these two exciting fields and combine ocean observations and ocean models to establish virtual representations of a real world system, in this case the ocean or an ocean area, as well as assets in the ocean and processes within ocean industries or the natural environment. They have the potential to play a critical role in optimising and supporting sustainable ocean development. Digital Twins are synchronised with their real-world counterparts at a specific frequency and fidelity. They can provide valuable insights into the ocean's state and its evolution over time, which can be used to support decision-making in ocean governance and various ocean-related industries. Digital ocean twins can transform human ocean interactions by accelerating holistic understanding, optimal decision-making, and effective interventions. Digital twins of the ocean use ocean observations, historical and forecast data to represent the past and present and simulate possible future scenarios. They are motivated by outcomes, tailored to use cases, powered by integration, built on data, guided by domain knowledge, and implemented in IT systems. In this article, we explore the benefits of digital twins for the ocean, the challenges in developing them, and the current state of the art in ocean digital twin technology. One of the main benefits of digital ocean twins is their ability to provide accurate predictions of ocean conditions under expected interventions. Their information can be used to support decision- making in various applications including ocean-related industries, such as fishing, shipping, and offshore energy production. Additionally, digital twins can help to improve our understanding of the ocean's complex processes and their interactions with human activities, such as climate change, pollution, resource extraction and overfishing. Researchers and IT companies are combining various technologies and data sources, such as the Internet of Things for ocean observations, state of the art data science, artificial intelligence and machine learning, data spaces and vocabularies into digital ocean twins to contextualise data, improve the accuracy of ocean models and make ocean knowledge more accessible to a wide range of users.","author":[{"family":"Brönner","given":"Ute"},{"family":"Sonnewald","given":"Maike"},{"family":"Visbeck","given":"Martin"}],"issued":{"date-parts":[[2023]]},"DOI":"10.58440/ihr-29-a04","URL":"https://doi.org/10.58440/ihr-29-a04","source":"openalex"},{"id":"oa:W4324017666","type":"article-journal","title":"Systems‐based digital twins to help characterize clinical dose–response and propose predictive biomarkers in a Phase I study of bispecific antibody, mosunetuzumab, in NHL","abstract":"Phase I oncology clinical trials often comprise a limited number of patients representing different disease subtypes who are divided into cohorts receiving treatment(s) at different dosing levels and schedules. Here, we leverage a previously developed quantitative systems pharmacology model of the anti-CD20/CD3 T-cell engaging bispecific antibody, mosunetuzumab, to account for different dosing regimens and patient heterogeneity in the phase I study to inform clinical dose/exposure-response relationships and to identify biological determinants of clinical response. We developed a novel workflow to generate digital twins for each patient, which together form a virtual population (VPOP) that represented variability in biological, pharmacological, and tumor-related parameters from the phase I trial. Simulations based on the VPOP predict that an increase in mosunetuzumab exposure increases the proportion of digital twins with at least a 50% reduction in tumor size by day 42. Simulations also predict a left-shift of the exposure-response in patients diagnosed with indolent compared to aggressive non-Hodgkin's lymphoma (NHL) subtype; this increased sensitivity in indolent NHL was attributed to the lower inferred values of tumor proliferation rate and baseline T-cell infiltration in the corresponding digital twins. Notably, the inferred digital twin parameters from clinical responders and nonresponders show that the potential biological difference that can influence response include tumor parameters (tumor size, proliferation rate, and baseline T-cell infiltration) and parameters defining the effect of mosunetuzumab on T-cell activation and B-cell killing. Finally, the model simulations suggest intratumor expansion of pre-existing T-cells, rather than an influx of systemically expanded T-cells, underlies the antitumor activity of mosunetuzumab.","author":[{"family":"Susilo","given":"Monica"},{"family":"Li","given":"Chi‐chung"},{"family":"Gadkar","given":"Kapil"},{"family":"Hernandez","given":"Genevive"},{"family":"Huw","given":"Ling‐yuh"},{"family":"Jin","given":"Jin"},{"family":"Yin","given":"Shen"},{"family":"Wei","given":"Michael"},{"family":"Ramanujan","given":"Saroja"},{"family":"Hosseini","given":"Iraj"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1111/cts.13501","URL":"https://doi.org/10.1111/cts.13501","source":"openalex"},{"id":"oa:W4391384282","type":"article-journal","title":"Battery State-of-Health Estimation: A Step towards Battery Digital Twins","abstract":"For a lithium-ion (Li-ion) battery to operate safely and reliably, an accurate state of health (SOH) estimation is crucial. Data-driven models with manual feature extraction are commonly used for battery SOH estimation, requiring extensive expert knowledge to extract features. In this regard, a novel data pre-processing model is proposed in this paper to extract health-related features automatically from battery-discharging data for SOH estimation. In the proposed method, one-dimensional (1D) voltage data are converted to two-dimensional (2D) data, and a new data set is created using a 2D sliding window. Then, features are automatically extracted in the machine learning (ML) training process. Finally, the estimation of the SOH is achieved by forecasting the battery voltage in the subsequent cycle. The performance of the proposed technique is evaluated on the NASA public data set for a Li-ion battery degradation analysis in four different scenarios. The simulation results show a considerable reduction in the RMSE of battery SOH estimation. The proposed method eliminates the need for the manual extraction and evaluation of features, which is an important step toward automating the SOH estimation process and developing battery digital twins.","author":[{"family":"Safavi","given":"Vahid"},{"family":"Bazmohammadi","given":"Najmeh"},{"family":"Vásquez","given":"Juan"},{"family":"Guerrero","given":"Josep"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/electronics13030587","URL":"https://doi.org/10.3390/electronics13030587","source":"openalex"},{"id":"oa:W4404511772","type":"article-journal","title":"A conceptual digital twin framework for supply chain recovery and resilience","abstract":"Amidst escalating global supply system risks and interruptions, the imperative for fortified supply networks is evident. Organizations striving for competitiveness and resilience must adeptly recognize, comprehend, and address disruptions. This study presents a three-phase digital supply chain twin framework, leveraging discrete event simulation and neural networks to anticipate floods—a typical natural catastrophe and disruptive event—and predict recovery indicators. This aids supply chain (SC) managers in making informed decisions. In the first phase, machine learning algorithms, including logistic regression and Long Short-Term Memory (LSTM), were trained on Kerala India's precipitation data to predict floods. LSTM outperforms logistic regression, achieving flood prediction with 73 % recall, 75 % accuracy, and 84 % Area Under Curve-Receiver Operating Characteristics score. In the second phase, simulations replicate value chain breakdowns. A process flow logic-driven discrete event simulation within a real-world SC network emulates operational disruptions. FlexSim is employed to model service-level failures, influencing SC model performance based on the distribution center service level. The third phase employs simulated case scenario data to train a multilayer neural perceptron network (MLPNN) for predicting production network recovery post-disruptions. The MLPNN monitors the mean squared error (MSE) and disruptive inputs throughout training and validation, revealing consistent MSE reduction over recovery periods. The number of epochs needed to achieve a minimum MSE is used as a recovery indicator to predict service restoration time. Consequently, this study introduces a conceptual digital twin framework for catastrophic operations chain breakdowns and recovery prediction. The framework's output assists SC planners in shaping robust strategies by foreseeing disruptions and facilitating recovery.","author":[{"family":"Ogunsoto","given":"Oluwagbenga"},{"family":"Olivares-Aguila","given":"Jessica"},{"family":"Elmaraghy","given":"Waguih"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.sca.2024.100091","URL":"https://doi.org/10.1016/j.sca.2024.100091","source":"openalex"},{"id":"oa:W4390748783","type":"article-journal","title":"Online distortion simulation using generative machine learning models: A step toward digital twin of metallic additive manufacturing","abstract":"In the era of Industry 4.0 and smart manufacturing, Wire Arc Additive Manufacturing (WAAM) stands at the forefront, driving a paradigm shift towards automated, digitalized production. However, online simulation remains a technical barrier toward building a Digital Twin (DT) for metallic AM due to the prolonged computing time of numerical simulations and limitations in accuracy of current data-driven models. This study addresses these issues by introducing an adaptive online simulation model for predicting distortion fields, utilizing a diffusion model architecture for distortion process modelling with a Vector Quantized Variational AutoEncoder coupled with Generative Adversarial Network (VQVAE-GAN) backbone for spatial feature extraction, complemented by a Recurrent Neural Network (RNN) for time-scale result fusion. Pretrained offline with Finite Element Method (FEM) simulated distortion fields, the model successfully predicts distortion fields online using laser-scanned point clouds during the deposition process. Experimental validation on seven thin-wall structures demonstrated its superior performance, achieving a Root Mean Square Error (RMSE) below 0.9 m, outperforming FEM by 143% and Artificial Neural Networks (ANN) based methods by 151%, marking a significant stride towards realizing an AM-DT.","author":[{"family":"Mu","given":"Haochen"},{"family":"He","given":"Fengyang"},{"family":"Yuan","given":"Lei"},{"family":"Hatamian","given":"Houman"},{"family":"Commins","given":"Philip"},{"family":"Pan","given":"Zengxi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.jii.2024.100563","URL":"https://doi.org/10.1016/j.jii.2024.100563","source":"openalex"},{"id":"oa:W4318999657","type":"article-journal","title":"Metamodelling of Manufacturing Processes and Automation Workflows towards Designing and Operating Digital Twins","abstract":"The automation of workflows for the optimization of manufacturing processes through digital twins seems to be achievable nowadays. The enabling technologies of Industry 4.0 have matured, while the plethora of available sensors and data processing methods can be used to address functionalities related to manufacturing processes, such as process monitoring and control, quality assessment and process modelling. However, technologies succeeding Computer-Integrated Manufacturing and several promising techniques, such as metamodelling languages, have not been exploited enough. To this end, a framework is presented, utilizing an automation workflow knowledge database, a classification of technologies and a metamodelling language. This approach will be highly useful for creating digital twins for both the design and operation of manufacturing processes, while keeping humans in the loop. Two process control paradigms are used to illustrate the applicability of such an approach, under the framework of certifiable human-in-the-loop process optimization.","author":[{"family":"Stavropoulos","given":"Panagiotis"},{"family":"Papacharalampopoulos","given":"Alexios"},{"family":"Sabatakakis","given":"Kyriakos"},{"family":"Mourtzis","given":"Dimitris"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/app13031945","URL":"https://doi.org/10.3390/app13031945","source":"openalex"},{"id":"oa:W4320085791","type":"article-journal","title":"Digital twin-enabled automated anomaly detection and bottleneck identification in complex manufacturing systems using a multi-agent approach","abstract":"Digital twin (DT) models are increasingly being used to improve the performance of complex manufacturing systems. In this context, DTs automatically enabling anomaly detection, such as increase in orders, and bottleneck identification, such as shortage of products, can significantly enhance decision-making to mitigate the consequences of the identified bottlenecks. The existing literature has mainly focused on implementing top-down approaches for analysing the bottlenecks without considering the emergent behaviour of micro-level agents, including inventory levels and human resources, and their impact on the macro-level system’s performance. In order to handle the aforementioned challenges, this paper extends the current literature by proposing a novel DT integrated in a multi-agent cyber physical system (CPS) for detecting anomalies in sensor data, while identifying and removing bottlenecks that emerge during the operation of complex manufacturing systems. An extended 5 C CPS architecture, using multi-agent approach, is implemented to allow DT integration. The agent-based simulation technique enables capturing the probabilistic variability, and aggregate parallelism and dynamism of parallel dynamic interactions within the DT-CPS. A new single agent at the exo-level of the multi-level agent-based modelling structure, called the ‘monitoring agent’, is introduced in this research. The agent detects anomalies and identify bottlenecks through communicating with other agents in different levels automatically. The DT-CPS provides feedback automatically to the physical space to remove and mitigate the identified bottlenecks. The proposed DT based multi-agent CPS has been tested successfully on a real case study in a cryogenic warehouse shop-floor from the cell and gene therapy industry. The performance of the studied cryogenic warehouse is continuously measured using real-time sensor data. The analyses of the results show that the proposed DT-CPS improves the utilisation rates of human resources, on average, by 30% supporting decision making and control in complex manufacturing systems.","author":[{"family":"Latsou","given":"Christina"},{"family":"Farsi","given":"Maryam"},{"family":"Erkoyuncu","given":"John"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.jmsy.2023.02.008","URL":"https://doi.org/10.1016/j.jmsy.2023.02.008","source":"openalex"},{"id":"oa:W4317888229","type":"article-journal","title":"Relationship between digital twin and building information modeling: a systematic review and future directions","abstract":"Purpose Digital twin (DT) and building information modeling (BIM) are interconnected in some ways. However, there has been some misconception about how DT differs from BIM. As a result, industry professionals reject DT even in BIM-based construction projects due to reluctance to innovate. Furthermore, researchers have repeatedly developed tools and techniques with the same goals using DT and BIM to assist practitioners in construction projects. Therefore, this study aims to assist industry professionals and researchers in understanding the relationship between DT and BIM and synthesize existing works on DT and BIM. Design/methodology/approach A systematic review was conducted on published articles related to DT and BIM. A total record of 54 journal articles were identified and analyzed. Findings The analysis of the selected journal articles revealed four types of relationships between DT and BIM: BIM is a subset of DT, DT is a subset of BIM, BIM is DT, and no relationship between BIM and DT. The existing research on DT and BIM in construction projects targets improvements in five areas: planning, design, construction, operations and maintenance, and decommissioning. In addition, several areas have emerged, such as developing geo-referencing approaches for infrastructure projects, applying the proposed methodology to other construction geometries and creating 3D visualization using color schemes. Originality/value This study contributed to the existing body of knowledge by overviewing existing research related to DT and BIM in construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research.","author":[{"family":"Radzi","given":"Afiqah"},{"family":"Azmi","given":"Nur"},{"family":"Kamaruzzaman","given":"Syahrul"},{"family":"Rahman","given":"Rahimi"},{"family":"Papadonikolaki","given":"Eleni"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1108/ci-07-2022-0183","URL":"https://doi.org/10.1108/ci-07-2022-0183","source":"openalex"},{"id":"oa:W4328053330","type":"article-journal","title":"Maneuvering between skepticism and optimism about hyped technologies: Building trust in digital twins","abstract":"IT vendors’ promises are likely to meet sound skepticism from prospective clients. If a particular technology is in vogue and seen as a “hype,” clients are under pressure to buy the technology while, at the same time, skepticism about its claimed benefits might be reinforced. Finding a balance between optimism and skepticism is essential. In this qualitative case study, we examine how an oil and gas supplier company in Norway deals with different pressures when adopting and subsequently implementing digital twin (DT) technologies. DTs offer the promise of creating a digital representation of the physical assets that can keep production facilities operating efficiently and optimally and, as such, have been heralded as enabling the next frontier of productivity improvements. Our results reveal a set of different pressures promoting the decision to adopt the hyped technology. Yet, when descended to the local context, the hype status of DTs evokes multilevel perception segmentation that hype interpreters maneuver by building trust. Based on this analysis, we propose a framework of trust-building mechanisms that contribute to a more nuanced understanding of adoption of hyped technologies and enable practitioners to deal with hype-induced perception obstacles.","author":[{"family":"Korotkova","given":"Nataliia"},{"family":"Benders","given":"Jos"},{"family":"Mikalef","given":"Patrick"},{"family":"Cameron","given":"David"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.im.2023.103787","URL":"https://doi.org/10.1016/j.im.2023.103787","source":"openalex"},{"id":"oa:W4400826970","type":"article-journal","title":"Digital twin technology for renewable energy microgrids","abstract":"Digital Twin Technology (DTT) is an emerging innovation poised to revolutionize the management and optimization of renewable energy microgrids. A digital twin is a virtual replica of a physical system, integrating real-time data, simulations, and machine learning to provide a dynamic, interactive model of the actual environment. In the context of renewable energy microgrids, DTT offers significant benefits in efficiency, reliability, and sustainability. Renewable energy microgrids, which include solar panels, wind turbines, and energy storage systems, are complex networks that require precise management to balance supply and demand, maximize energy efficiency, and ensure stability. By creating a digital twin of these microgrids, operators can monitor real-time performance, predict potential failures, and optimize operations. This virtual model enables predictive maintenance, reducing downtime and extending the lifespan of equipment by identifying issues before they lead to critical failures. Furthermore, DTT facilitates advanced energy management strategies. Through simulations, it can evaluate various scenarios, such as fluctuating energy demands, changing weather conditions, and equipment performance variations. These simulations help in designing robust control strategies and improving the integration of renewable energy sources, leading to better energy storage utilization and reduced reliance on fossil fuels. Another critical advantage is the enhancement of grid resilience. Digital twins can simulate the impact of extreme weather events and other disruptions, allowing operators to develop and test contingency plans in a risk-free environment. This capability is vital for ensuring continuous energy supply and mitigating the effects of unexpected outages. Digital Twin Technology offers a transformative approach to managing renewable energy microgrids. By providing a comprehensive, real-time virtual model, DTT enhances operational efficiency, predictive maintenance, energy management, and grid resilience. As the renewable energy sector continues to grow, the integration of digital twins will be instrumental in optimizing the performance and sustainability of microgrid systems. Keywords: Digital Twin, Renewable, Energy, Microgrids.","author":[{"family":"Bassey","given":"Kelvin"},{"family":"Opoku-Boateng","given":"Jesse"},{"family":"Antwi","given":"Bernard"},{"family":"Ntiakoh","given":"Afari"},{"family":"Juliet","given":"Ayanwunmi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.51594/estj.v5i7.1319","URL":"https://doi.org/10.51594/estj.v5i7.1319","source":"openalex"},{"id":"oa:W4392378120","type":"article-journal","title":"A Review on Digital Twins and Its Application in the Modeling of Photovoltaic Installations","abstract":"Industry 4.0 is in continuous technological growth that benefits all sectors of industry and society in general. This article reviews the Digital Twin (DT) concept and the interest of its application in photovoltaic installations. It compares how other authors use the DT approach in photovoltaic installations to improve the efficiency of the renewable energy generated and consumed, energy prediction and the reduction of the operation and maintenance costs of the photovoltaic installation. It reviews how, by providing real-time data and analysis, DTs enable more informed decision-making in the solar energy sector. The objectives of the review are to study digital twin technology and to analyse its application and implementation in PV systems.","author":[{"family":"Angelova","given":"Dorotea"},{"family":"Carmona-Fernández","given":"Diego"},{"family":"Calderón","given":"Manuel"},{"family":"Moreno","given":"Juan"},{"family":"González","given":"Juan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/en17051227","URL":"https://doi.org/10.3390/en17051227","source":"openalex"},{"id":"oa:W4362638802","type":"article-journal","title":"Live semantic data from building digital twins for robot navigation: Overview of data transfer methods","abstract":"Increasing reliance on automation and robotization presents great opportunities to improve the management of construction sites as well as existing buildings. Crucial in the use of robots in a built environment is their capacity to locate themselves and navigate as autonomously as possible. Robots often rely on planar and 3D laser scanners for that purpose, and building information models (BIM) are seldom used, for a number of reasons, namely their unreliability, unavailability, and mismatch with localization algorithms used in robots. However, while BIM models are becoming increasingly reliable and more commonly available in more standard data formats (JSON, XML, RDF), they become more promising and reliable resources for localization and indoor navigation, in particular in the more static types of existing infrastructure (existing buildings). In this article, we specifically investigate to what extent and how such building data can be used for such robot navigation. Data flows are built from BIM model to local repository and further to the robot, making use of graph data models (RDF) and JSON data formats. The local repository can hereby be considered to be a digital twin of the real-world building. Navigation on the basis of a BIM model is tested in a real world environment (university building) using a standard robot navigation technology stack. We conclude that it is possible to rely on BIM data and we outline different data flows from BIM model to digital twin and to robot. Future work can focus on (1) making building data models more reliable and standard (modelling guidelines and robot world model), (2) improving the ways in which building features in the digital building model can be recognized in 3D point clouds observed by the robots, and (3) investigating possibilities to update the BIM model based on robot feedback.","author":[{"family":"Pauwels","given":"Pieter"},{"family":"Koning","given":"Rens"},{"family":"Hendrikx","given":"Bob"},{"family":"Torta","given":"Elena"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.aei.2023.101959","URL":"https://doi.org/10.1016/j.aei.2023.101959","source":"openalex"},{"id":"oa:W4399127402","type":"article-journal","title":"Verification and validation of digital twins: a systematic literature review for manufacturing applications","abstract":"Digital Twin (DT) is a concept of growing interest, driven by the technological advancements related to Industry 4.0. DT combines innovative technologies to create a virtual model replicating the physical system and allowing bi-directional data flow. However, to use DTs in support of decision-making, it is essential to have trust in the model and all components of the DT throughout its development. Verification and Validation (V&V) have traditionally been employed to assess models’ credibility, providing a venue for the development of trust. Therefore, V&V are essential foundations for developing DTs that can support decisions in real-world environments. Through a systematic literature review, this research investigated whether and how researchers are employing V&V in DTs for manufacturing applications. It was concluded that very little research was reported to have performed both verification and validation of the developed DTs. The study also examined the most commonly used V&V techniques and explored their relationship with DT capability level and application areas. It was concluded that there is a lack of standard procedures to conduct V&V and a lack of agreement on the V&V objectives. This research uncovers the main challenges to verifying and validating DTs and future research directions to develop trusted DTs.","author":[{"family":"Bitencourt","given":"Julia"},{"family":"Wooley","given":"Ana"},{"family":"Harris","given":"Gregory"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1080/00207543.2024.2357741","URL":"https://doi.org/10.1080/00207543.2024.2357741","source":"openalex"},{"id":"oa:W4395008450","type":"article-journal","title":"Enhancing Reliability in Floating Offshore Wind Turbines through Digital Twin Technology: A Comprehensive Review","abstract":"This comprehensive review explores the application and impact of digital twin (DT) technology in bolstering the reliability of Floating Offshore Wind Turbines (FOWTs) and their supporting platforms. Within the burgeoning domain of offshore wind energy, this study contextualises the need for heightened reliability measures in FOWTs and elucidates how DT technology serves as a transformative tool to address these concerns. Analysing the existing scholarly literature, the review encompasses insights into the historical reliability landscape, DT deployment methodologies, and their influence on FOWT structures. Findings underscore the pivotal role of DT technology in enhancing FOWT reliability through real-time monitoring and predictive maintenance strategies, resulting in improved operational efficiency and reduced downtime. Highlighting the significance of DT technology as a potent mechanism for fortifying FOWT reliability, the review emphasises its potential to foster a robust operational framework while acknowledging the necessity for continued research to address technical intricacies and regulatory considerations in its integration within offshore wind energy systems. Challenges and opportunities related to the integration of DT technology in FOWTs are thoroughly analysed, providing valuable insights into the role of DTs in optimising FOWT reliability and performance, thereby offering a foundation for future research and industry implementation.","author":[{"family":"Chen","given":"Bai"},{"family":"Liu","given":"Kun"},{"family":"Yu","given":"Tongqiang"},{"family":"Li","given":"Ruoxuan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/en17081964","URL":"https://doi.org/10.3390/en17081964","source":"openalex"},{"id":"oa:W4386260714","type":"article-journal","title":"Digital Twin-Enabled Service Satisfaction Enhancement in Edge Computing","abstract":"The emerging digital twin technique enhances the network management efficiency and provides comprehensive insights, through mapping physical objects to their digital twins. The user satisfaction on digital twin-enabled query services relies on the freshness of digital twin data, which is measured by the Age of Information (AoI). Because the remote cloud faces challenges in providing data for users due to long service delays, Mobile Edge Computing (MEC), as a promising technology, offers real-time data communication between physical objects and their digital twins at the edge of the core network. However, the mobility of physical objects and dynamic query arrivals make efficient service provisioning in MEC become challenging. In this paper, we investigate the dynamic digital twin placement for improving user service satisfaction in MEC environments. We focus on two user service satisfaction augmentation problems under both static and dynamic digital twin placement schemes: the static and dynamic utility maximization problems. We first formulate an Integer Linear Programming (ILP) solution to the static utility maximization problem when the problem size is small; otherwise, we propose a performance- guaranteed approximation algorithm for it. We then devise an online algorithm for the dynamic utility maximization problem with a provable competitive ratio. Finally, we evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms outperform the comparison baseline algorithms, and the performance improvement is no less than 11.6%, compared with the baseline algorithms.","author":[{"family":"Li","given":"Jing"},{"family":"Wang","given":"Jianping"},{"family":"Chen","given":"Quan"},{"family":"Li","given":"Yuchen"},{"family":"Zomaya","given":"Albert"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/infocom53939.2023.10228893","URL":"https://doi.org/10.1109/infocom53939.2023.10228893","source":"openalex"},{"id":"oa:W4394927136","type":"article-journal","title":"Current trends in digital twin development, maintenance, and operation: an interview study","abstract":"Abstract Digital twins (DTs) are often defined as a pairing of a physical entity and a corresponding virtual entity (VE), mimicking certain aspects of the former depending on the use-case. In recent years, this concept has facilitated numerous use-cases ranging from design to validation and predictive maintenance of large and small high-tech systems. Various heterogeneous cross-domain models are essential for such systems, and model-driven engineering plays a pivotal role in the design, development, and maintenance of these models. We believe models and model-driven engineering play a similarly crucial role in the context of a VE of a DT. Due to the rapidly growing popularity of DTs and their use in diverse domains and use-cases, the methodologies, tools, and practices for designing, developing, and maintaining the corresponding VEs differ vastly. To better understand these differences and similarities, we performed a semi-structured interview research with 19 professionals from industry and academia who are closely associated with different lifecycle stages of digital twins. In this paper, we present our analysis and findings from this study, which is based on seven research questions. In general, we identified an overall lack of uniformity in terms of the understanding of digital twins and used tools, techniques, and methodologies for the development and maintenance of the corresponding VEs. Furthermore, considering that digital twins are software intensive systems, we recognize a significant growth potential for adopting more software engineering practices, processes, and expertise in various stages of a digital twin’s lifecycle.","author":[{"family":"Muctadir","given":"Hossain"},{"family":"Negrin","given":"David"},{"family":"Gunasekaran","given":"Raghavendran"},{"family":"Cleophas","given":"Loek"},{"family":"Brand","given":"Mark"},{"family":"Haverkort","given":"Boudewijn"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/s10270-024-01167-z","URL":"https://doi.org/10.1007/s10270-024-01167-z","source":"openalex"},{"id":"oa:W4315785694","type":"article-journal","title":"Health assessment framework of marine engines enabled by digital twins","abstract":"The advancements in digital twins when combined with the use of the machine learning tools can facilitate the effective health assessment and diagnostics of safety critical systems. This study aims at developing a framework to address the health assessment of marine engines utilising digital twins based on first-principles. This framework follows four distinct stages, with the former two including the marine engine digital-twin set up by customising the required thermodynamic models, as well as its calibration using tests trials data representing the engine healthy conditions. In the third stage, measurements from actual operating conditions are corrected and subsequently employed to develop the digital twin representing the prevailing conditions. The fourth stage deals with the engine health assessment by assessing health metrics derived from the developed digital twins. This framework is demonstrated in a case study of a large marine four-stroke nine-cylinder propulsion engine. The results demonstrate that three cylinders are identified to be underperforming leading to an average increase of the engine Brake Specific Fuel Consumption (BSFC) by 2.1%, whereas an average decreases of 6.8% in Indicated Mean Effective Pressure (IMEP) and 6.1% in the Exhaust Gas Temperature (EGT) are exhibited for the underperforming cylinders across the entire operating envelope. The developed digital twins facilitate the effective mapping of the engine performance for the entire operating envelope under several health conditions, providing enhanced insights for the current engine health status. The advantages of the proposed framework include the use of easily obtained data, and its application to several engine types including two and four-stroke engines for both propulsion and auxiliary use.","author":[{"family":"Tsitsilonis","given":"Konstantinos"},{"family":"Θεοτοκάτος","given":"Γεράσιμος"},{"family":"Patil","given":"Chaitanya"},{"family":"Coraddu","given":"Andrea"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1177/14680874221146835","URL":"https://doi.org/10.1177/14680874221146835","source":"openalex"},{"id":"oa:W4385772316","type":"article-journal","title":"A state-of-the-art digital factory integrating digital twin for laser additive and subtractive manufacturing processes","abstract":"Purpose This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations. Design/methodology/approach This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques. Findings A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions. Originality/value Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.","author":[{"family":"Tariq","given":"Usman"},{"family":"Joy","given":"Ranjit"},{"family":"Wu","given":"Sung"},{"family":"Mahmood","given":"Muhammad"},{"family":"Malik","given":"Asad"},{"family":"Liou","given":"Frank"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1108/rpj-03-2023-0113","URL":"https://doi.org/10.1108/rpj-03-2023-0113","source":"openalex"},{"id":"oa:W4383648046","type":"article-journal","title":"Sustainable product lifecycle management with Digital Twins: A systematic literature review","abstract":"A Digital Twin (DT) is a virtual replica of a product or product-service system, which can be used to provide transparency of a product's sustainability and to positively influence the ecological impact throughout its lifecycle by means of intelligent data analytics. This paper identifies current sustainability-focused application scenarios of DTs in the manufacturing industry and outlines the results of a systematic literature review (SLR). The identification of the state-of-the-art and the assessment of current DT concepts with regard to the addressed product lifecycle phases, technological maturity and sustainability scope point towards key directions to guide future research.","author":[{"family":"Seegrün","given":"Anne"},{"family":"Kruschke","given":"Thomas"},{"family":"Mügge","given":"Janine"},{"family":"Hardinghaus","given":"Louis"},{"family":"Knauf","given":"Tobias"},{"family":"Riedelsheimer","given":"Theresa"},{"family":"Lindow","given":"Kai"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.procir.2023.03.124","URL":"https://doi.org/10.1016/j.procir.2023.03.124","source":"openalex"},{"id":"oa:W4391221432","type":"article-journal","title":"Improved generalization with deep neural operators for engineering systems: Path towards digital twin","abstract":"Neural Operator Networks (ONets) represent a novel advancement in machine learning algorithms, offering a robust and generalizable alternative for approximating partial differential equations (PDEs) solutions. Unlike traditional Neural Networks (NN), which directly approximate functions, ONets specialize in approximating mathematical operators, enhancing their efficacy in addressing complex PDEs.In this work, we evaluate the capabilities of Deep Operator Networks (DeepONets), an ONets implementation using a branch–trunk architecture. Three test cases are studied: a system of ODEs, a general diffusion system, and the convection–diffusion Burgers’ equation. It is demonstrated that DeepONets can accurately learn the solution operators, achieving prediction accuracy (R2) scores above 0.96 for the ODE and diffusion problems over the observed domain while achieving zero-shot (without retraining) capability. More importantly, when evaluated on unseen scenarios (zero-shot feature), the trained models exhibit excellent generalization ability. This underscores ONets’ vital niche for surrogate modeling and digital twin development across physical systems. While convection–diffusion poses a greater challenge, the results confirm the promise of ONets and motivate further enhancements to the DeepONet algorithm. This work represents an important step towards unlocking the potential of digital twins through robust and generalizable surrogates.","author":[{"family":"Kobayashi","given":"Kazuma"},{"family":"Daniell","given":"James"},{"family":"Alam","given":"Syed"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.engappai.2024.107844","URL":"https://doi.org/10.1016/j.engappai.2024.107844","source":"openalex"},{"id":"oa:W4382599780","type":"article-journal","title":"Exploiting Digitalization of Solar PV Plants Using Machine Learning: Digital Twin Concept for Operation","abstract":"The rapid development of digital technologies and solutions is disrupting the energy sector. In this regard, digitalization is a facilitator and enabler for integrating renewable energies, management and operation. Among these, advanced monitoring techniques and artificial intelligence may be applied in solar PV plants to improve their operation and efficiency and detect potential malfunctions at an early stage. This paper proposes a Digital Twin DT concept, mainly focused on O&M, to obtain more information about the system by using several artificial intelligence boxes. Furthermore, it includes the development of several machine learning (ML) algorithms capable of reproducing the expected behavior of the solar PV plant and detecting the malfunctioning of different components. In this regard, this allows for reducing downtime and optimizing asset management. In this paper, different ML techniques are used and compared to optimize the selected methods for enhanced response. The paper presents all stages of the developed Digital Twin, including ML model development with an accuracy of 98.3% of the whole DT, and finally, a communication and visualization platform. The different responses and comparisons have been made using a model based on MATLAB/Simulink using different cases and system conditions.","author":[{"family":"Yalçin","given":"Tolga"},{"family":"Paradell","given":"Pol"},{"family":"Stefanidou-Voziki","given":"Paschalia"},{"family":"Domínguezgarcía","given":"José"},{"family":"Demirdelen","given":"Tuğçe"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/en16135044","URL":"https://doi.org/10.3390/en16135044","source":"openalex"},{"id":"oa:W4392916642","type":"article-journal","title":"Application Scenarios of Digital Twins for Smart Crop Farming through Cloud–Fog–Edge Infrastructure","abstract":"In the last decade, digital twin (DT) technology has received considerable attention across various domains, such as manufacturing, smart healthcare, and smart cities. The digital twin represents a digital representation of a physical entity, object, system, or process. Although it is relatively new in the agricultural domain, it has gained increasing attention recently. Recent reviews of DTs show that this technology has the potential to revolutionise agriculture management and activities. It can also provide numerous benefits to all agricultural stakeholders, including farmers, agronomists, researchers, and others, in terms of making decisions on various agricultural processes. In smart crop farming, DTs help simulate various farming tasks like irrigation, fertilisation, nutrient management, and pest control, as well as access real-time data and guide farmers through ‘what-if’ scenarios. By utilising the latest technologies, such as cloud–fog–edge computing, multi-agent systems, and the semantic web, farmers can access real-time data and analytics. This enables them to make accurate decisions about optimising their processes and improving efficiency. This paper presents a proposed architectural framework for DTs, exploring various potential application scenarios that integrate this architecture. It also analyses the benefits and challenges of implementing this technology in agricultural environments. Additionally, we investigate how cloud–fog–edge computing contributes to developing decentralised, real-time systems essential for effective management and monitoring in agriculture.","author":[{"family":"Kalyani","given":"Yogeswaranathan"},{"family":"Vorster","given":"LMD"},{"family":"Whetton","given":"Rebecca"},{"family":"Collier","given":"Rem"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/fi16030100","URL":"https://doi.org/10.3390/fi16030100","source":"openalex"},{"id":"oa:W4380366179","type":"article-journal","title":"Towards AI-assisted digital twins for smart railways: preliminary guideline and reference architecture","abstract":"Abstract In the last years, there has been a growing interest in the emerging concept of digital twins (DTs) among software engineers and researchers. DTs not only represent a promising paradigm to improve product quality and optimize production processes, but they also may help enhance the predictability and resilience of cyber-physical systems operating in critical contexts. In this work, we investigate the adoption of DTs in the railway sector, focusing in particular on the role of artificial intelligence (AI) technologies as key enablers for building added-value services and applications related to smart decision-making. In this paper, in particular, we address predictive maintenance which represents one of the most promising services benefiting from the combination of DT and AI. To cope with the lack of mature DT development methodologies and standardized frameworks, we detail a workflow for DT design and development specifically tailored to a predictive maintenance scenario and propose a high-level architecture for AI-enabled DTs supporting such workflow.","author":[{"family":"Donato","given":"Lorenzo"},{"family":"Dirnfeld","given":"Ruth"},{"family":"Somma","given":"Alessandra"},{"family":"Benedictis","given":"Alessandra"},{"family":"Flammini","given":"Francesco"},{"family":"Marrone","given":"Stefano"},{"family":"Azari","given":"Mehdi"},{"family":"Vittorini","given":"Valeria"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1007/s40860-023-00208-6","URL":"https://doi.org/10.1007/s40860-023-00208-6","source":"openalex"},{"id":"oa:W4383648124","type":"article-journal","title":"Integration of Industry 5.0 requirements in digital twin-supported manufacturing process selection: a framework","abstract":"Process selection has been an integral part of manufacturing design and operation, with a close link to manufacturing process modeling. Throughout the years, it has been enriched with many criteria, such as energy efficiency, emissions, resources, and sustainability in general, increasing its complexity in terms of modeling and optimization. Herein, process selection is coupled with (a) the capabilities of the digital twins, (b) the criteria introduced by Industry 5.0 (I5.0) in terms of sustainability and human inclusion, and (c) the opportunities offered by key enabling technologies. A framework is presented capable to implement automated process selection and potentially scheduling through a specific set of integrated technologies, utilizing the concept of the microfactory as a basis in terms of implementation. A case study for the evaluation of two parts, using Additive Manufacturing and laser welding, in different scenarios is presented. It was concluded that the inclusion of the I5.0 criteria not only increases the well-being of the workers but also the energy and time efficiency of the production line, increasing the profit margin.","author":[{"family":"Papacharalampopoulos","given":"Alexios"},{"family":"Foteinopoulos","given":"Panagis"},{"family":"Stavropoulos","given":"Panagiotis"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.procir.2023.06.197","URL":"https://doi.org/10.1016/j.procir.2023.06.197","source":"openalex"},{"id":"oa:W4360979157","type":"article-journal","title":"When the digital twin meets the preventive conservation of movable wooden artifacts","abstract":"Abstract To achieve sustainable heritage conservation, preventive conservation has gradually taken precedence over curative conservation, because it can inhibit the damage caused by various environmental factors and maximizes the preservation life of the artifacts. Due to susceptibility to environmental factors, preventive conservation has been used in the conservation of movable wooden artifacts to further protect them. Recently, digital twin technology, as a concept that transcends reality, can be mapped in virtual space to reflect the full lifecycle process of the corresponding entity, which is a superior characteristic that makes it valued and researched for health monitoring and health management of heritages. This paper proposes a health management method mainly for preventive conservation of movable wooden artifacts, integrating digital twin technology into the health management process. Using the Quanzhou Ship as a typical representative, several important components of health management are specifically analyzed, such as the five-dimensional model of the digital twin, the data interaction process of the digital twin, and the identification and assessment of risks. In particular, the process of preventive conservation of the stern based on the digital twin is presented in detail. This method provides a basis for future preventive conservation of movable wooden artifacts and has implications for the use of digital twin technology in the field of heritage conservation, especially for movable wooden artifacts.","author":[{"family":"Wang","given":"Puxiang"},{"family":"Ma","given":"Xueyi"},{"family":"Fei","given":"Lihua"},{"family":"Zhang","given":"Hongye"},{"family":"Zhao","given":"Dong"},{"family":"Zhao","given":"Jian"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1186/s40494-023-00894-8","URL":"https://doi.org/10.1186/s40494-023-00894-8","source":"openalex"},{"id":"oa:W4401068470","type":"article-journal","title":"Digital Twin Stakeholder Communication: Characteristics, Challenges, and Best Practices","abstract":"Digital Twins (DT) encompass virtual models interconnected with a physical system through data links. Although DTs hold significant potential for positive organisational impact, their successful adoption in industrial practice remains limited. Whereas existing research predominantly focuses on technical challenges, more recent studies underscore the importance of addressing organisational and human factors to overcome implementation barriers. One central aspect in this context is stakeholder communication, especially given the ambiguous nature of the term DT in academic and industrial discussions. To expand the limited understanding of the factors causing challenging DT stakeholder communications, this article presents findings from an extensive exploratory study. It involves 27 in-depth interviews and two focus groups with highly experienced DT professionals. By employing grounded theory and the Gioia methodology, a grounded model for DT stakeholder communication challenges is derived. This model reveals the complex communication dynamics within DT projects, emphasising the emergence of novel stakeholder communication patterns that heavily rely on multidisciplinary collaboration. In total, 28 communication challenges were identified, grouped into eight theoretical themes and categorised into two aggregate dimensions: human- and organisation-centric challenges. Additionally, the study identified 15 practices, e.g., defining clear objectives, and starting small and building gradually, that organisations are following to mitigate these challenges. As a result, this article provides the theoretical groundwork for a comprehensive understanding of DT stakeholder communication and its associated challenges by revealing distinctive features and offering practical guidance to overcome critical challenges in DT projects.","author":[{"family":"Kober","given":"Christian"},{"family":"Medina","given":"Francisco"},{"family":"Benfer","given":"Martin"},{"family":"Wulfsberg","given":"Jens"},{"family":"Martínez","given":"Verónica"},{"family":"Lanza","given":"Gisela"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.compind.2024.104135","URL":"https://doi.org/10.1016/j.compind.2024.104135","source":"openalex"},{"id":"oa:W4386098643","type":"article-journal","title":"The Concept of Creating Digital Twins of Bridges Using Load Tests","abstract":"The paper sheds light on the process of creating and validating the digital twin of bridges, emphasizing the crucial role of load testing, BIM models, and FEM models. At first, the paper presents a comprehensive definition of the digital twin concept, outlining its core principles and features. Then, the framework for implementing the digital twin concept in bridge facilities is discussed, highlighting its potential applications and benefits. One of the crucial components highlighted is the role of load testing in the validation and updating of the FEM model for further use in the digital twin framework. Load testing is emphasized as a key step in ensuring the accuracy and reliability of the digital twin, as it allows the validation and refinement of its models. To illustrate the practical application and issues during tuning and validating the FEM model, the paper provides an example of a real bridge. It shows how a BIM model is utilized to generate a computational FEM model. The results of the load tests carried out on the bridge are discussed, demonstrating the importance of the data obtained from these tests in calibrating the FEM model, which forms a critical part of the digital twin framework.","author":[{"family":"Jasiński","given":"Marcin"},{"family":"Łaziński","given":"Piotr"},{"family":"Piotrowski","given":"Dawid"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/s23177349","URL":"https://doi.org/10.3390/s23177349","source":"openalex"},{"id":"oa:W4386078225","type":"article-journal","title":"A Digital-Twin-Based Health Status Monitoring Method for Single-Phase PWM Rectifiers","abstract":"A digital simulation and health monitoring method for single-phase two-level pulsewidth modulation (PWM) rectifiers based on digital twin technology is proposed in this article. First, the closed-loop control and the main circuit are discretized to develop the digital model of the PWM rectifier. Then, the external characteristics of the digital model are compared with the data sampled from the actual physical circuit, and the particle swarm optimization algorithm is used to iteratively optimize the key parameters. Ultimately, the offline digital twin model is developed, which can realize the health status monitoring of insulated-gate-bipolar-transistor power devices, the ac-side inductor, and the dc-link capacitor in the rectifier. Finally, an experimental prototype is built to test the proposed digital twin model and health monitoring method under different load conditions. A comprehensive statistical comparison of the digital twin model and experiment results has verified that the proposed method can achieve health monitoring within the acceptable range, even if under different initial values of parameters. Thus, this article provides a feasible and noninvasive solution for the digital simulation modeling and health monitoring of single-phase PWM rectifiers, without additional sensors and hardware circuits.","author":[{"family":"Zhang","given":"Sihui"},{"family":"Song","given":"Wensheng"},{"family":"Cao","given":"Hu"},{"family":"Tang","given":"Tao"},{"family":"Zou","given":"Yuchao"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/tpel.2023.3307415","URL":"https://doi.org/10.1109/tpel.2023.3307415","source":"openalex"},{"id":"oa:W4389352625","type":"article-journal","title":"Distributed Digital Twins as Proxies-Unlocking Composability and Flexibility for Purpose-Oriented Digital Twins","abstract":"In the realm of Industrial Internet of Things (IoT) and Industrial Cyber-Physical Systems (ICPS), Digital Twins (DTs) have revolutionized the management of physical entities. However, existing implementations often face constraints due to hardware-centric approaches and limited flexibility. This article introduces a transformative paradigm that harnesses the potential of distributed Digital Twins as proxies, enabling software-centricity and unlocking composability and flexibility for purpose-oriented digital twin development and deployment. The proposed microservices-based architecture, rooted in service-oriented architecture (SOA) and microservices principles, emphasizes reusability, modularity, and scalability. Leveraging the Lean Digital Twin Methodology and packaged business capabilities expedites digital twin creation and deployment, facilitating dynamic responses to evolving industrial demands. This architecture segments the industrial realm into physical and virtual spaces, where core components are responsible for digital twin management, deployment, and secure interactions. By abstracting and virtualizing physical entities into individual digital twins, this approach establishes the groundwork for purpose-oriented composite digital twin creation. Our key contributions involve a comprehensive exposition of the architecture, a practical proof-of-concept (PoC) implementation, and the application of the architecture in a use-case scenario. Additionally, we provide an analysis, including a quantitative evaluation of the proxy aspect and a qualitative comparison with traditional approaches. This assessment emphasizes key properties such as reusability, modularity, abstraction, discoverability, and security, transcending the limitations of contemporary industrial systems and enabling agile, adaptable digital proxies to meet modern industrial demands.","author":[{"family":"Aziz","given":"Abdullah"},{"family":"Chouhan","given":"Shailesh"},{"family":"Schelén","given":"Olov"},{"family":"Bodin","given":"Ulf"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/access.2023.3340132","URL":"https://doi.org/10.1109/access.2023.3340132","source":"openalex"},{"id":"oa:W4315783140","type":"article-journal","title":"Digital Twin – A Tool for Project Management in Manufacturing","abstract":"The Digital Twin concept has the potential to be a useful tool in project management and in Lean manufacturing. The common goal of risk management by project managers and mitigating unpredictable behavior using the Digital Twin can improve the development of manufacturing systems. Digital Twins would also aid project managers in managing resources and communication between stakeholders. The researcher is working with a manufacturing SME in the engineering sector in the application of digitalisation tools to optimize production operations. A Digital Twin is being developed, and this will be used to investigate aspects of risk and resource management as well as the benefits of communication using visualization. Are there aspects of process development that can now be measured using Digital Twins that we were not capable of previously? The Digital Twin as a central point of reference for information about a manufacturing process and its associated equipment could add efficiencies to maintenance and process improvements over the lifecycle of a system.","author":[{"family":"Hickey","given":"Brian"},{"family":"Gachon","given":"Dr"},{"family":"Cosgrove","given":"Dr"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.procs.2022.12.268","URL":"https://doi.org/10.1016/j.procs.2022.12.268","source":"openalex"},{"id":"oa:W4403668433","type":"article-journal","title":"Digital twins in bridge engineering for streamlined maintenance and enhanced sustainability","abstract":"Digital twins are evolving to oversee the entire construction life cycle, with a strong emphasis on sustainability across environmental, financial, regulatory, and administrative dimensions. This paper introduces a methodology for managing existing bridges through an adaptable digital twin. The aim of this research is to develop a framework for constructing digital twins that, by enabling structural analysis and “what-if” scenario simulations, supports more reliable maintenance decision-making. Such type of digital twin ensure safety, extend lifespan, and provide a precise database for managing end-of-life processes within a circular “cradle to cradle” framework. This methodology also addresses obsolescence issues related to software evolution and the longer lifespan of a bridge compared to its creator. A case study demonstrates the methodology's effectiveness, showing that digital twins can be flexible, cost-effective tools for managing all types of bridges, including small and existing ones. • A bridge management methodology is introduced using an interoperable digital twin. • Two case studies illustrate the methodology for managing small and large bridges. • Cost-effective technology and optimization methods yield benefits for small bridges. • Interoperable formats enable degradation prediction and hazard scenario creation.","author":[{"family":"Franciosi","given":"M"},{"family":"Kasser","given":"Michel"},{"family":"Viviani","given":"M"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.autcon.2024.105834","URL":"https://doi.org/10.1016/j.autcon.2024.105834","source":"openalex"},{"id":"oa:W4319320344","type":"article-journal","title":"Interaction with Industrial Digital Twin Using Neuro-Symbolic Reasoning","abstract":"Digital twins have revolutionized manufacturing and maintenance, allowing us to interact with virtual yet realistic representations of the physical world in simulations to identify potential problems or opportunities for improvement. However, traditional digital twins do not have the ability to communicate with humans using natural language, which limits their potential usefulness. Although conventional natural language processing methods have proven to be effective in solving certain tasks, neuro-symbolic AI offers a new approach that leads to more robust and versatile solutions. In this paper, we propose neuro-symbolic reasoning (NSR)-a fundamental method for interacting with 3D digital twins using natural language. The method understands user requests and contexts to manipulate 3D components of digital twins and is able to read maintenance manuals and implement installations and removal procedures autonomously. A practical neuro-symbolic dataset of machine-understandable manuals, 3D models, and user queries is collected to train the neuro-symbolic reasoning interaction mechanism. The evaluation demonstrates that NSR can execute user commands accurately, achieving 96.2% accuracy on test data. The proposed method has industrial importance since it provides the technology to perform maintenance procedures, request information from manuals, and serve as a tool to interact with complex virtual machinery using natural language.","author":[{"family":"Siyaev","given":"Aziz"},{"family":"Valiev","given":"Dilmurod"},{"family":"Jo","given":"Geun‐sik"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/s23031729","URL":"https://doi.org/10.3390/s23031729","source":"openalex"},{"id":"oa:W4394874381","type":"article-journal","title":"Digital Twin for Sustainable Industrial Development","abstract":"This book chapter delves into the transformative potential of Digital Twins in fostering sustainable industrial development. As industries face increasing pressure to reduce their environmental footprint and embrace eco-friendly practices, the concept of Digital Twins emerges as a promising solution. This chapter explores the key aspects of Digital Twins, including predictive maintenance, resource optimization, process enhancement, and supply chain management. It highlights the significance of leveraging real-time data and advanced analytics to drive energy efficiency, minimize waste, and mitigate emissions. The chapter also addresses the challenges associated with implementing Digital Twins, such as data privacy, cybersecurity, and integration hurdles. By examining the latest innovations and case studies, this chapter offers valuable insights into how Digital Twins can revolutionize the industrial landscape, propelling it toward a more sustainable and responsible future. Additionally, digital twins can be used to monitor the performance of a process in real time and make adjustments as needed. Digital twins are also beneficial in the context of Industry 4.0, which emphasizes the integration of advanced technologies such as Internet of Things, big data, and machine learning in industrial processes. Digital twins can be integrated with these technologies to provide real-time data, enabling companies to make data-driven decisions and improve overall performance.","author":[{"family":"Whig","given":"Pawan"},{"family":"Yathiraju","given":"Nikhitha"},{"family":"Modhugu","given":"Venugopal"},{"family":"Bhatia","given":"Ashima"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1201/9781003395416-13","URL":"https://doi.org/10.1201/9781003395416-13","source":"openalex"},{"id":"oa:W4393279137","type":"article-journal","title":"Digital Twin-Enabled Internet of Vehicles Applications","abstract":"The digital twin (DT) paradigm represents a groundbreaking shift in the Internet of Vehicles (IoV) landscape, acting as an instantaneous digital replica of physical entities. This synthesis not only refines vehicular design but also substantially augments driver support systems and streamlines traffic governance. Diverging from the prevalent research which predominantly examines DT’s technical assimilation within IoV infrastructures, this review focuses on the specific deployments and goals of DT within the IoV sphere. Through an extensive review of scholarly works from the past 5 years, this paper provides a fresh and detailed perspective on the significance of DT in the realm of IoV. The applications are methodically categorized across four pivotal sectors: industrial manufacturing, driver assistance technology, intelligent transportation networks, and resource administration. This classification sheds light on DT’s diverse capabilities to confront and adapt to the intricate challenges in contemporary vehicular networks. The intent of this comprehensive overview is to catalyze innovation within IoV by providing an essential reference for researchers who aspire to swiftly grasp the complex dynamics of this evolving domain.","author":[{"family":"Gao","given":"Junting"},{"family":"Peng","given":"Chunrong"},{"family":"Yoshinaga","given":"Tsutomu"},{"family":"Han","given":"Guorong"},{"family":"Guleng","given":"Siri"},{"family":"Wu","given":"Celimuge"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/electronics13071263","URL":"https://doi.org/10.3390/electronics13071263","source":"openalex"},{"id":"oa:W4391992499","type":"article-journal","title":"Smart Mobility Digital Twin Based Automated Vehicle Navigation System: A Proof of Concept","abstract":"Digital twins (DTs) have driven major advancements across various industrial domains over the past two decades. With the rapid advancements in autonomous driving and vehicle-to-everything (V2X) technologies, integrating DTs into vehicular platforms is anticipated to further revolutionize smart mobility systems. In this paper, a new smart mobility DT (SMDT) platform is proposed for the control of connected and automated vehicles (CAVs) over next-generation wireless networks. In particular, the proposed platform enables cloud services to leverage the abilities of DTs to promote the autonomous driving experience. To enhance traffic efficiency and road safety measures, a novel navigation system that exploits available DT information is designed. The SMDT platform and navigation system are implemented with state-of-the-art products, e.g., CAVs and roadside units (RSUs), and emerging technologies, e.g., cloud and cellular V2X (C-V2X). In addition, proof-of-concept (PoC) experiments are conducted to validate system performance. The performance of SMDT is evaluated from two standpoints:(i)the rewards of the proposed navigation system on traffic efficiency and safety and,(ii)the latency and reliability of the SMDT platform. Our experimental results using SUMO-based large-scale traffic simulations show that the proposed SMDT can reduce the average travel time and the blocking probability due to unexpected traffic incidents. Furthermore, the results record a peak overall latency for DT modeling and route planning services to be 155.15 ms and 810.59 ms, respectively, which validates that our proposed design aligns with the 3GPP requirements for emerging V2X use cases and fulfills the targets of the proposed design. Our demonstration video can be found athttps://youtu.be/3waQwlaHQkk.","author":[{"family":"Wang","given":"KC"},{"family":"Li","given":"Zongdian"},{"family":"Nonomura","given":"Kazuma"},{"family":"Yu","given":"Tao"},{"family":"Sakaguchi","given":"Kei"},{"family":"Hashash","given":"Omar"},{"family":"Saad","given":"Walid"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/tiv.2024.3368109","URL":"https://doi.org/10.1109/tiv.2024.3368109","source":"openalex"},{"id":"oa:W4322629912","type":"article-journal","title":"A tool-based system architecture for a digital twin: a case study in a healthcare facility","abstract":"Changes in the local and global markets are forcing A/E/C/FM (Architecture, Engineering, Construction, and Facility Management) organizations to deliver more robust and innovative operational BIMs (Building Information Models). It is hypothesized that BIMs will transform from a static 3D model to a Digital Twin providing a truly digital representation of the physical asset or the building it represents. This transformation to a dynamic Digital Twin will allow the A/E/C/FM industry to visualize, monitor, and optimize operational assets and processes to support better inspection and analysis for a more efficient facility operations and maintenance. To support the adoption and implementation of Digital Twin in A/E/C/FM, the authors have defined two clear objectives. First, we discuss requirements for a functionality-based canonical architecture to create a digital twin followed by proposing two tool-based system architecture options for its implementation. Second, we use a case study approach to develop a proof-of-concept Digital Twin of an operating room in a healthcare facility using Power BI Desktop and Azure Services. The prototype aims to monitor room air quality as per INAIL (National Institute for Insurance against Accidents at Work) and ISO (International Organization for Standards) standards. Multiple sensors connected to a Raspberry Pi 4 are used to capture real-time data for various air quality parameters including temperature, humidity, airflow, particulate contamination, and Nitrous Oxide (N2O) gas. Multiple dashboards are also created to visualize, monitor, and analyze the data harnessed from the OR sensors. The implementation addresses critical issues including security, data storage, visualization, processing, data streaming, collection, and analysis. As an initial validation, the Digital Twin prototype was presented and discussed with a healthcare BIM manager. Initial feedback from the industry expert indicated that the prototype could decrease the required time to respond to facility maintenance issues such as decreased air flow due to possible obstructions.","author":[{"family":"Harode","given":"Ashit"},{"family":"Thabet","given":"Walid"},{"family":"Dongre","given":"Poorvesh"}],"issued":{"date-parts":[[2023]]},"DOI":"10.36680/j.itcon.2023.006","URL":"https://doi.org/10.36680/j.itcon.2023.006","source":"openalex"},{"id":"oa:W4319300573","type":"article-journal","title":"Digital Twin-Based Automated Fault Diagnosis in Industrial IoT Applications","abstract":"In recent years, Digital Twin (DT) has gained significant interest from academia and industry due to the advanced in information technology, communication systems, Artificial Intelligence (AI), Cloud Computing (CC), and Industrial Internet of Things (IIoT). The main concept of the DT is to provide a comprehensive tangible, and operational explanation of any element, asset, or system. However, it is an extremely dynamic taxonomy developing in complexity during the life cycle that produces a massive amount of engendered data and information. Likewise, with the development of AI, digital twins can be redefined and could be a crucial approach to aid the Internet of Things (IoT)-based DT applications for transferring the data and value onto the Internet with better decision-making. Therefore, this paper introduces an efficient DT-based fault diagnosis model based on machine learning (ML) tools. In this framework, the DT model of the machine is constructed by creating the simulation model. In the proposed framework, the Genetic algorithm (GA) is used for the optimization task to improve the classification accuracy. Furthermore, we evaluate the proposed fault diagnosis framework using performance metrics such as precision, accuracy, F-measure, and recall. The proposed framework is comprehensively examined using the triplex pump fault diagnosis. The experimental results demonstrated that the hybrid GA-ML method gives outstanding results compared to ML methods like Logistic Regression (LR), Naïve Bayes (NB), and Support Vector Machine (SVM). The suggested framework achieves the highest accuracy of 95% for the employed hybrid GA-SVM. The proposed framework will effectively help industrial operators make an appropriate decision concerning the fault analysis for IIoT applications in the context of Industry 4.0.","author":[{"family":"Alshathri","given":"Samah"},{"family":"Hemdan","given":"Ezz"},{"family":"Elshafai","given":"Walid"},{"family":"Sayed","given":"Amged"}],"issued":{"date-parts":[[2023]]},"DOI":"10.32604/cmc.2023.034048","URL":"https://doi.org/10.32604/cmc.2023.034048","source":"openalex"},{"id":"oa:W4400111243","type":"article-journal","title":"Generative AI-Driven Digital Twin for Mobile Networks","abstract":"The sixth generation mobile network (6G) is evolving to provide ubiquitous connections, multidimensional perception, native intelligence, global coverage, etc., which poses intense demands for network design to tackle the highly dynamic context and diverse service requirements. Digital Twin (DT) is envisioned as an efficient method for designing 6G that migrates the behaviors of physical nodes to the virtual space. However, in the high-dynamic 6G network, there still exist challenges in achieving accuracy and flexibility when constructing DT. In this article, we propose a Generative Artificial Intelligence (GAI)-driven mobile network digital twin paradigm, where the GAI is utilized as a key enabler to generate DT data. Specifically, GAI is capable of implicitly learning the complex distribution of network data, allowing it to sample from the distribution and obtain high-fidelity data. In addition, the construction of DT is closely related to various types of data, such as environmental, user, and service data. GAI can utilize these data as conditions to control the generation process under different scenarios, thereby enhancing flexibility. In practice, we develop a network digital twin prototype system to accurately model the behaviors of mobile network elements ($i.e$., mobile users, base stations, and wireless environments) and to evaluate network performance. Evaluation results demonstrate that the proposed prototype system can generate high-fidelity DT data and provide practical network optimization solutions.","author":[{"family":"Chai","given":"Haoye"},{"family":"Wang","given":"Huandong"},{"family":"Li","given":"Tong"},{"family":"Wang","given":"Zhaocheng"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/mnet.2024.3420702","URL":"https://doi.org/10.1109/mnet.2024.3420702","source":"openalex"},{"id":"oa:W4384780698","type":"article-journal","title":"The Wind and Photovoltaic Power Forecasting Method Based on Digital Twins","abstract":"Wind and photovoltaic (PV) power forecasting are crucial for improving the operational efficiency of power systems and building smart power systems. However, the uncertainty and instability of factors affecting renewable power generation pose challenges to power system operations. To address this, this paper proposes a digital twin-based method for predicting wind and PV power. By utilizing digital twin technology, this approach provides a highly realistic simulation environment that enables accurate monitoring, optimal control, and decision support for power system operations. Furthermore, a digital twin platform for the AI (Artificial Intelligence) Grid is established, allowing real-time monitoring, and ensuring the safe, reliable, and stable operation of the grid. Additionally, a deep learning-based model WPNet is developed to predict wind and PV power at specific future time points. Four datasets are constructed based on weather conditions and historical wind and PV power data from the Flanders and Wallonia regions. The prediction models presented in this paper demonstrate excellent performance on these datasets, achieving mean square error (MSE) values of 0.001399, 0.001833, 0.000704, and 0.002708; mean absolute error (MAE) values of 0.025164, 0.027854, 0.018592, and 0.033501; and root mean square error (RMSE) values of 0.037409, 0.042808, 0.026541, and 0.052042, respectively.","author":[{"family":"Wang","given":"Yonggui"},{"family":"Qi","given":"Yong"},{"family":"Li","given":"Jian"},{"family":"Huan","given":"Le"},{"family":"Li","given":"Yusen"},{"family":"Xie","given":"Bitao"},{"family":"Wang","given":"Yongshan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/app13148374","URL":"https://doi.org/10.3390/app13148374","source":"openalex"},{"id":"oa:W4398208634","type":"article-journal","title":"Digital Twins for Enhancing Efficiency and Assuring Safety in Renewable Energy Systems: A Systematic Literature Review","abstract":"As the demand for sustainable energy solutions grows, there is a critical requirement for continuous innovation to optimize the performance and safety of renewable energy systems (RESs). Closed-loop digital twins (CLDTs)—synchronized virtual replicas embedded with real-time data and control loops to mirror the behavior of physical systems—have emerged as a promising tool for achieving this goal. This paper presents a systematic literature review on the application of digital twin (DT) technology in the context of RESs with an emphasis on the impact of DTs on the efficiency, performance, and safety assurance of RESs. It explores the concept of CLDTs, highlighting their key functionalities and potential benefits for various renewable energy technologies. However, their effective implementation requires a structured approach to integrate observation, orientation, decision, and action (OODA) processes. This study presents a novel OODA framework specifically designed for CLDTs to systematically identify and manage their key components. These components include real-time monitoring, decision-making, and actuation. The comparison is carried out against the capabilities of DT utilizing the OODA framework. By analyzing the current literature, this review explores how DT empowers RESs with enhanced efficiency, reduced risks, and improved safety assurance.","author":[{"family":"Hashmi","given":"Razeen"},{"family":"Liu","given":"Huai"},{"family":"Yavari","given":"Ali"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/en17112456","URL":"https://doi.org/10.3390/en17112456","source":"openalex"},{"id":"oa:W4315782919","type":"article-journal","title":"Sustainability in the agri-food supply chain: a combined digital twin and simulation approach for farmers","abstract":"The paper seeks to provide a research and practical study to strengthen the resilience of smallholders to unexpected crises like COVID-19. Farmers are usually not assisted by the current technological capabilities while uncertainty is greater than ever. In comparison, with existing static assessments, digital twins use cases in the agricultural sector are still in conceptual and prototype levels. In this regard, the paper aims to provide a framework with the potentials for sustainability for farmers derived from five pillars and their modelling on a digital twin model with simulation capabilities. The goal is to develop an approach and a tool that would enhance the capabilities of smallholders to face any disruption by supporting them in all their management and control activities. Thus, the model aims to analyze the effects of risks as well as the policies that can prevent them, act to reduce their impacts, or react against any internal or external risks in three levels: farmer´s organization, supply chain, and the related environment based on the Corporate Social Sustainability. The purpose is to increase the resilience of smallholders through the improvement and optimization of the agro-food supply chain and related environment of any smallholder organization considering all related stakeholders. As a result, the final goal of the model is the development of recommendations for enhancing future capabilities to secure viability in the long-term.","author":[{"family":"Gallego-García","given":"Sergio"},{"family":"Gallego-García","given":"Diego"},{"family":"García-García","given":"Manuel"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.procs.2022.12.326","URL":"https://doi.org/10.1016/j.procs.2022.12.326","source":"openalex"},{"id":"oa:W4403749687","type":"article-journal","title":"A Retrieval-Augmented Generation Approach for Data-Driven Energy Infrastructure Digital Twins","abstract":"Digital-twin platforms are increasingly adopted in energy infrastructure management for smart grids. Novel opportunities arise from emerging artificial intelligence technologies to increase user trust by enhancing predictive and prescriptive analytics capabilities and by improving user interaction paradigms. This paper presents a novel data-driven and knowledge-based energy digital-twin framework and architecture. Data integration and mining based on machine learning are integrated into a knowledge graph annotating asset status data, prediction outcomes, and background domain knowledge in order to support a retrieval-augmented generation approach, which enhances a conversational virtual assistant based on a large language model to provide user decision support in asset management and maintenance. Components of the proposed architecture have been mapped to commercial-off-the-shelf tools to implement a prototype framework, exploited in a case study on the management of a section of the high-voltage energy infrastructure in central Italy.","author":[{"family":"Ieva","given":"Saverio"},{"family":"Loconte","given":"Davide"},{"family":"Loseto","given":"Giuseppe"},{"family":"Ruta","given":"Michèle"},{"family":"Scioscia","given":"Floriano"},{"family":"Marche","given":"Davide"},{"family":"Notarnicola","given":"Marianna"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/smartcities7060121","URL":"https://doi.org/10.3390/smartcities7060121","source":"openalex"},{"id":"oa:W4401015171","type":"article-journal","title":"Digital twin-enabled synchronized construction management: A roadmap from construction 4.0 towards future prospect","abstract":"Information and automation technologies play a pivotal role in achieving cyber-physical integration within Construction 4.0. In this transformed landscape, the evolution of the construction management paradigm carefully considers the enhancement of business models and organizational structures to prioritize stakeholders’ well-being, environmental sustainability, and heightened resilience. A significant challenge lies in effectively managing and coordinating a myriad of multi-source and heterogeneous entities using information and automation technologies. The key obstacle is synchronizing these elements based on cyber-physical interoperation to optimize multiple objectives seamlessly. Hence synchronization emerges as a crucial factor for orchestrating and sustaining harmonious relationships among multiple entities or activities within a delimited spatial-temporal framework. This ensures seamless and aligned coordination throughout dynamic processes. Therefore, this paper presents a strategic roadmap for the synchronized construction management, derived from a thorough analysis of fundamental elements in Construction 4.0, aimed at advancing the current construction management practices. Moreover, to articulate this synchronization approach systematically, an Orthogonally Synchronized Digital Twin (SDT) model with regular expression is formulated, built upon the proposed roadmap for reshaped construction management. This study provides valuable insights for stakeholders in the construction industry, including architects, engineers, project managers, and policymakers. The findings guide decision-making on digital twin adoption in construction, supporting practitioners to enhance efficiency and improve outcomes, offering a roadmap for industry advancement towards human-centrality, sustainability, and resilience. Future research should focus on validating the proposed roadmap and SDT model in real-world scenarios, exploring synergies between AI and digital twins, and investigating advanced technologies for holistic smart cities management.","author":[{"family":"Jiang","given":"Yishuo"},{"family":"Su","given":"Shuaiming"},{"family":"Zhao","given":"Shuxuan"},{"family":"Zhong","given":"Ray"},{"family":"Qiu","given":"Waishan"},{"family":"Skibniewski","given":"Mirosław"},{"family":"Brilakis","given":"Ioannis"},{"family":"Huang","given":"George"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.dibe.2024.100512","URL":"https://doi.org/10.1016/j.dibe.2024.100512","source":"openalex"},{"id":"oa:W4400138071","type":"article-journal","title":"Optimization Method of CNC Machining Parameters Based on Digital Twin","abstract":"This article mainly discusses the optimization methods of machining parameters for CNC machine tools. Firstly, based on the functional requirements and application scenarios of CNC machining, three-dimensional modeling and motion simulation of twin machine tools are achieved, and a data-driven cutting process model is constructed. Then, in the actual production process, in addition to ensuring the normal processing of physical equipment such as CNC machine tools, the design of data perception schemes and the layout of data acquisition equipment during the processing were also completed, providing data support for information exchange between digital twins and real equipment. In terms of data transmission, the operation data of the entire CNC machine tool processing process is collected through the data perception layer equipment, and all perception data is then uploaded to the virtual space through the communication network of the transmission layer to drive the twin model for subsequent simulation, optimization, and prediction. Finally, based on the results of data collection, an objective function that needs to be optimized was established in the optimization process of CNC machining parameters. The objective function takes the total processing time and processing cost as optimization objectives, and an improved bee colony algorithm is used to solve the objective function. Through experimental simulation, it has been found that the use of CNC machine tool processing parameters can improve both time and processing costs, and the optimization results meet the design expectations.","author":[{"family":"Lu","given":"Hao"},{"family":"Lu","given":"Yan"},{"family":"Lu","given":"Hui"},{"family":"Li","given":"J"},{"family":"Zhang","given":"Haiying"},{"family":"Wang","given":"Shu"},{"family":"Wang","given":"Dong"},{"family":"Lu","given":"Ying"}],"issued":{"date-parts":[[2024]]},"DOI":"10.53106/199115992024063503021","URL":"https://doi.org/10.53106/199115992024063503021","source":"openalex"},{"id":"oa:W4398221321","type":"article-journal","title":"Behavioral Modeling and Digital Predistortion for Power Amplifier Based on the Sparse Smooth Twin Support Vector Regression Method","abstract":"In this paper, a sparse smooth twin support vector regression (Sparse‐STSVR) model for power amplifier (PA) behavioral modeling is obtained by pruning the kernel matrix based on Cholesky decomposition. Based on the primal smooth twin support vector regression (STSVR) model, the Nystrom approximate matrix of the kernel matrix is found to replace the original kernel matrix, thus simplifying the Newton iterative parameter extraction process of the primal STSVR model and accelerating the convergence of the algorithm. In addition, the new rank approximation kernel matrix has the characteristic of sparse parameters, which further reduces the computational complexity of the feedforward link of the digital predistorter. The 100 MHz 5G New Radio (NR) signal is used for verify the effect of PA modeling and digital predistortion (DPD) experiment. The results show that the proposed method can improve the normalized mean square error (NMSE) by about 2 ~ 3 dB with fewer coefficients compared with the previously proposed machine learning model, and the predistortion linearization effect improves by nearly 3 dB on the adjacent channel power ratio (ACPR), which achieves a good trade‐off between model performance and computational complexity. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","author":[{"family":"Xu","given":"Changzhi"},{"family":"Su","given":"Min"},{"family":"Jia","given":"Songlin"},{"family":"Wang","given":"Xiaoyu"},{"family":"Ning","given":"Jinzhi"},{"family":"Li","given":"Mingyu"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/tee.24095","URL":"https://doi.org/10.1002/tee.24095","source":"openalex"},{"id":"oa:W4402962692","type":"manuscript","title":"An Overview of Digital Transformation and Environmental Sustainability: Threats, Opportunities and Solutions","abstract":"Digital transformation, powered by technologies like AI, IoT, and big data, is reshaping industries and societies at an unprecedented pace. While these innovations promise smarter energy management, precision agriculture, and efficient resource utilization, they also introduce serious environmental challenges. This paper examines the dual impact of digital technologies, highlighting key threats such as rising energy consumption, growing e-waste, and increased extraction of raw materials. For instance, global e-waste reached 62 million metric tons in 2022, and data centers alone accounted for nearly 1% of the world's electricity demand in 2019. The review synthesizes findings from studies on topics like the energy use of blockchain technologies and the environmental costs of raw material extraction in the smartphone industry. Moreover, it identifies critical research gaps, particularly in understanding the environmental impact of digital usage at individual and household levels. Practical strategies such as integrating circular economy principles, promoting renewable energy, and green computing are proposed to balance technological advancement with sustainability goals. This study highlights the need for a holistic approach, suggesting future research directions to minimize digital transformation’s environmental footprint while maximizing its sustainability benefits.","author":[{"family":"Goel","given":"Apurva"},{"family":"Masurkar","given":"Snehal"},{"family":"Pathade","given":"GR"}],"issued":{"date-parts":[[2024]]},"DOI":"10.20944/preprints202409.2340.v1","URL":"https://doi.org/10.20944/preprints202409.2340.v1","source":"openalex"},{"id":"oa:W4392358741","type":"article-journal","title":"Does Urban Digital Construction Promote Economic Growth? Evidence from China","abstract":"In order to explore the causal relationship between the level of urban digital construction and urban economic growth, this paper takes 280 cities in China as the research object and constructs a comprehensive indicator evaluation system covering digital infrastructure, overall economic level, innovation development level, digital industry development status, and ecological environment conditions. Using the entropy method to weigh various indicators, this paper has obtained the evaluation results of the digital construction level of each city from 2011 to 2021. Furthermore, a panel data regression model is used to empirically analyze the impact of urban digital construction level on urban economic growth. The results show that for every 1% increase in the level of urban digital construction, the GDP will increase by 0.974. Through the above research, we hope to further enrich the theoretical and empirical research in the field of the digital economy, provide a scientific and reasonable method for quantitatively evaluating the level of urban digital construction, and provide decision-making references for improving the level of urban digital construction and promoting sustainable urban development.","author":[{"family":"Yang","given":"Weixin"},{"family":"Zhu","given":"Chen"},{"family":"Yang","given":"Yunpeng"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/economies12030059","URL":"https://doi.org/10.3390/economies12030059","source":"openalex"},{"id":"oa:W4404789563","type":"article-journal","title":"Towards Reconfigurable Cyber-Physical-Human Systems: Leveraging Mixed Reality and Digital Twins to integrate Human Operations","abstract":"The agility to swiftly and efficiently reconfigure manufacturing systems is crucial in today’s rapidly evolving market demands. Traditional recon-figuration operations often fall short, presenting non-intuitive and error-prone tasks for human operators, without the aid of systematic approaches or supportive technologies. This gap not only complicates the reconfiguration process but also significantly increases the risk of errors. In response, we introduce a novel approach that integrates Mixed Reality and Digital Twins within Cyber-Physical Systems to address these challenges. This enhances the human element in manufacturing reconfigurations by facilitating intuitive trajectory planning for robot (re)programming and comprehensive documentation of physical processes, including human operations. The design and implementation of the approach aim to significantly enhance manufacturing reconfigurations by reducing downtime, complexity, and human error. Further, the paper outlines directions for future work, including comprehensive system validation within a Cyber-Physical-Human manufacturing system, emphasizing the critical role of human operators in the reconfiguration process and the potential for technology to address traditional shortcomings.","author":[{"family":"Mayer","given":"Anjela"},{"family":"Kastner","given":"Kevin"},{"family":"Mühlbeier","given":"Edgar"},{"family":"Chardonnet","given":"Jean"},{"family":"Reichwald","given":"Julian"},{"family":"Puchta","given":"Alexander"},{"family":"Fleischer","given":"Jürgen"},{"family":"Ovtcharova","given":"Jivka"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.procir.2024.10.124","URL":"https://doi.org/10.1016/j.procir.2024.10.124","source":"openalex"},{"id":"oa:W4399597323","type":"manuscript","title":"Natural Language Interaction with a Household Electricity Knowledge-based Digital Twin","abstract":"Domain specific digital twins, representing a digital replica of various segments of the smart grid, are foreseen as able to model, simulate, and control the respective segments. At the same time, knowledge-based digital twins, coupled with AI, may also empower humans to understand aspects of the system through natural language interaction in view of planning and policy making. This paper is the first to assess and report on the potential of Retrieval Augmented Generation (RAG) question answers related to household electrical energy measurement aspects leveraging a knowledge-based energy digital twin. Relying on the recently published electricity consumption knowledge graph that actually represents a knowledge-based digital twin, we study the capabilities of ChatGPT, Gemini and Llama in answering electricity related questions. Furthermore, we compare the answers with the ones generated through a RAG techniques that leverages an existing electricity knowledge-based digital twin. Our findings illustrate that the RAG approach not only reduces the incidence of incorrect information typically generated by LLMs but also significantly improves the quality of the output by grounding responses in verifiable data. This paper details our methodology, presents a comparative analysis of responses with and without RAG, and discusses the implications of our findings for future applications of AI in specialized sectors like energy data analysis.","author":[{"family":"Fortuna","given":"Carolina"},{"family":"Hanžel","given":"Vid"},{"family":"Bertalanič","given":"Blaž"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2406.06566","URL":"https://doi.org/10.48550/arxiv.2406.06566","source":"openalex"},{"id":"oa:W4400687378","type":"manuscript","title":"Digital Twin Technology in Built Environment: A Review of Applications, Capabilities and Challenges","abstract":"Digital Twin (DT) technology is a pivotal innovation within the built environment industry, facilitating digital transformation through advanced data integration and analytics. DTs have demonstrated significant benefits in building design, construction, and asset management, including optimizing lifecycle energy use, enhancing operational efficiency, enabling predictive maintenance, and improving user adaptability. By integrating real-time data from IoT sensors with advanced analytics, DTs provide dynamic and actionable insights for better decision-making and resource management. Despite these promising benefits, several challenges impede the widespread adoption of DT technology, such as technological integration, data consistency, organisational adaptation, and cybersecurity concerns. Addressing these challenges requires inter-disciplinary collaboration, standardization of data formats, and the development of universal design and development platforms for DTs. This paper provides a comprehensive review of DT definitions, applications, capabilities, and challenges within the Architecture, Engineering, and Construction (AEC) industries. This paper provides important insights for researchers and professionals, helping them gain a more comprehensive and detailed view of DT. The findings also demonstrate the significant impact that DTs can have on this sector, contributing to advancing DT implementations and promoting sustainable and efficient building management practices. Ultimately, DT technology is set to revolutionize the AEC industries by enabling autonomous, data-driven decision-making and optimizing building operations for enhanced productivity and performance.","author":[{"family":"Mousavi","given":"Yalda"},{"family":"Gharineiat","given":"Zahra"},{"family":"Aghakarimi","given":"Armin"},{"family":"Mcdougall","given":"Kevin"},{"family":"Rossi","given":"Adriana"},{"family":"Barsanti","given":"Sara"}],"issued":{"date-parts":[[2024]]},"DOI":"10.20944/preprints202407.1004.v1","URL":"https://doi.org/10.20944/preprints202407.1004.v1","source":"preprints"},{"id":"oa:W4408324726","type":"article-journal","title":"Goal-oriented Semantic Communication for Robotic Arm Reconstruction in Digital Twin","abstract":"As one of the most promising technologies in industry, the Digital Twin (DT) facilitates real-time monitoring and predictive analysis for real-world systems by precisely reconstructing virtual replicas of physical entities. However, this reconstruction faces unprecedented challenges due to the ever-increasing communication overhead, especially for digital robotic arm reconstruction. To this end, we propose a novel goal-oriented semantic communication (GSC) design to extract GSC information for the robotic arm reconstruction task in the DT, with the aim of minimising the communication load without sacrificing the reconstruction accuracy. Specifically, rather than transmitting a message that contains complete robotic arm states for reconstruction, we design a Wireless Feature Selection (WFS) algorithm that first segments the motion of the physical robot into several phases, and then extracts and transmits GSC information from this message according to the current phase. Our proposed design is validated through both Pybullet simulations and real-world experiments using the Franka Research 3 robotic arm, where their communication loads are reduced by 44.1% and 35%, respectively, while maintaining the reconstruction error in the same level. The accompanying demo is available online at: https://youtu.be/IAZjoTcbaFA.","author":[{"family":"Chen","given":"Shutong"},{"family":"Spyrakos-Papastavridis","given":"Emmanouil"},{"family":"Jin","given":"Yichao"},{"family":"Deng","given":"Yansha"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/globecom52923.2024.10901815","URL":"https://doi.org/10.1109/globecom52923.2024.10901815","source":"openalex"},{"id":"oa:W4403400457","type":"article-journal","title":"Data Mining Approach for Evil Twin Attack Identification in Wi-Fi Networks","abstract":"Recent cyber security solutions for wireless networks during internet open access have become critically important for personal data security. The newest WPA3 network security protocol has been used to maximize this protection; however, attackers can use an Evil Twin attack to replace a legitimate access point. The article is devoted to solving the problem of intrusion detection at the OSI model’s physical layers. To solve this, a hardware–software complex has been developed to collect information about the signal strength from Wi-Fi access points using wireless sensor networks. The collected data were supplemented with a generative algorithm considering all possible combinations of signal strength. The k-nearest neighbor model was trained on the obtained data to distinguish the signal strength of legitimate from illegitimate access points. To verify the authenticity of the data, an Evil Twin attack was physically simulated, and a machine learning model analyzed the data from the sensors. As a result, the Evil Twin attack was successfully identified based on the signal strength in the radio spectrum. The proposed model can be used in open access points as well as in large corporate and home Wi-Fi networks to detect intrusions aimed at substituting devices in the radio spectrum where IEEE 802.11 networking equipment operates.","author":[{"family":"Банах","given":"Роман"},{"family":"Nyemkova","given":"Elena"},{"family":"Justice","given":"Connie"},{"family":"Piskozub","given":"Andrian"},{"family":"Lakh","given":"Yuriy"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/data9100119","URL":"https://doi.org/10.3390/data9100119","source":"openalex"},{"id":"oa:W4403730007","type":"article-journal","title":"Mitigating Thermal Side-Channel Vulnerabilities in FPGA-Based SiP Systems Through Advanced Thermal Management and Security Integration Using Thermal Digital Twin (TDT) Technology","abstract":"Side-channel attacks (SCAs) are powerful techniques used to recover keys from electronic devices by exploiting various physical leakages, such as power, timing, and heat. Although heat is one of the less frequently analyzed channels due to the high noise associated with thermal traces, it poses a significant and growing threat to the security of very large-scale integrated (VLSI) microsystems, particularly system in package (SiP) technologies. Thermal side-channel attacks (TSCAs) exploit temperature variations, risking not only hardware damage from excessive heat dissipation but also enabling the extraction of sensitive data, like cryptographic keys, by observing thermal patterns. This dual threat underscores the need for a synergistic approach to thermal management and security in designing integrated microsystems. In response, this paper presents a novel approach that improves the early detection of abnormal thermal fluctuations in SiP designs, preventing cybercriminals from exploiting such anomalies to extract sensitive information for malicious purposes. Our approach employs a new concept called Thermal Digital Twin (TDT), which integrates two previously separate methods and techniques, resulting in successful outcomes. It combines the gradient direction sensor scan (GDSSCAN) to capture thermal data from the physical field programmable gate array (FPGA), which guarantees rapid thermal scan with a measurement period that could be close to 10 μs, a resolution of 0.5 ∘C, and a temperature range from −40 ∘C to 140 ∘C; once the data are transmitted in real time to a Digital Twin created in COMSOL Multiphysics® 6.0 for simulation using the Finite Element Method (FEM), the real time required by the CPU to perform all the necessary calculations can extend to several seconds or minutes. This integration allows for a detailed analysis of thermal transfer within the SiP model of our FPGA. Implementation and simulations demonstrate that the Thermal Digital Twin (TDT) approach could reduce the risks associated with TSCA by a significant percentage, thereby enhancing the security of FPGA systems against thermal threats.","author":[{"family":"Benelhaouare","given":"Amrou"},{"family":"Mellal","given":"Idir"},{"family":"Oumlaz","given":"Maroua"},{"family":"Lakhssassi","given":"Ahmed"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/electronics13214176","URL":"https://doi.org/10.3390/electronics13214176","source":"openalex"},{"id":"oa:W4400876624","type":"article-journal","title":"Monitoring Daily Sleep, Mood, and Affect Using Digital Technologies and Wearables: A Systematic Review","abstract":"Background: Sleep and affective states are closely intertwined. Nevertheless, previous methods to evaluate sleep-affect associations have been limited by poor ecological validity, with a few studies examining temporal or dynamic interactions in naturalistic settings. Objectives: First, to update and integrate evidence from studies investigating the reciprocal relationship between daily sleep and affective phenomena (mood, affect, and emotions) through ambulatory and prospective monitoring. Second, to evaluate differential patterns based on age, affective disorder diagnosis (bipolar, depression, and anxiety), and shift work patterns on day-to-day sleep-emotion dyads. Third, to summarise the use of wearables, actigraphy, and digital tools in assessing longitudinal sleep-affect associations. Method: A comprehensive PRISMA-compliant systematic review was conducted through the EMBASE, Ovid MEDLINE(R), PsycINFO, and Scopus databases. Results: Of the 3024 records screened, 121 studies were included. Bidirectionality of sleep-affect associations was found (in general) across affective disorders (bipolar, depression, and anxiety), shift workers, and healthy participants representing a range of age groups. However, findings were influenced by the sleep indices and affective dimensions operationalised, sampling resolution, time of day effects, and diagnostic status. Conclusions: Sleep disturbances, especially poorer sleep quality and truncated sleep duration, were consistently found to influence positive and negative affective experiences. Sleep was more often a stronger predictor of subsequent daytime affect than vice versa. The strength and magnitude of sleep-affect associations were more robust for subjective (self-reported) sleep parameters compared to objective (actigraphic) sleep parameters.","author":[{"family":"Hickman","given":"Robert"},{"family":"Doliveira","given":"Teresa"},{"family":"Davies","given":"A"},{"family":"Shergill","given":"Sukhwinder"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/s24144701","URL":"https://doi.org/10.3390/s24144701","source":"openalex"},{"id":"oa:W4403588879","type":"article-journal","title":"The Fuse Platform: Integrating data from IoT and other Sensors into an Industrial Spatial Digital Twin","abstract":"Abstract. Digital Twins as virtual representations of industrial assets are being used to assimilate varied sources of data for improved awareness and decision making in operations and process optimisation. This paper explores the integration of IoT sensors into a spatial digital twin called Fuse that Woodside Energy has been building for the assets it operates. We describe the Fuse platform and its knowledge graph data core that is used to organise and inter-relate data for presentation within 3D visualisations, domain-specific contexts and immersive augmented reality presentations. The key contribution here is the use of a knowledge graph to link diverse data sources so as to contextualise sensor data for actionable insights. One area of significant innovation has been the development and use of new Internet of Things (IoT) devices which have been enabled by advances in sensor technology, connectivity, and cloud computing. These new tailored data sources are complimenting existing plant and resource planning data for improved asset monitoring, predictive maintenance and process automation.","author":[{"family":"Biegel","given":"G"},{"family":"Bower","given":"Nicholas"},{"family":"Castelnau","given":"Will"}],"issued":{"date-parts":[[2024]]},"DOI":"10.5194/isprs-archives-xlviii-4-2024-79-2024","URL":"https://doi.org/10.5194/isprs-archives-xlviii-4-2024-79-2024","source":"openalex"},{"id":"oa:W4390948185","type":"article-journal","title":"An Integrated Data-Driven System for Digital Bridge Management","abstract":"Relational databases are established and widespread tools for storing and managing information. The efficient collection of information in a database appears to be a promising solution for bridge management (BM), thus facilitating the digital transition. The Italian regulatory framework on infrastructure operation and maintenance (O&M) is complex and is constantly being updated. The current plan for implementing its guidelines envisages that infrastructure managers, also on a regional scale, equip themselves with their own digital database for BM. Within this context, this research proposes an integrated methodology that collects information derived from project documentation, in situ inspections, digital surveys, and monitoring and field tests in a queryable database for digitalising, georeferencing, and creating models of many bridges. Structured query language (SQL) statements are used to efficiently export specific shared information, enabling network cross-analysis. Furthermore, the database represents the source of a geographic information system (GIS) catalogue and the basis for deriving models for building information modelling (BIM). The methodology focuses on the infrastructural context of the Lazio region, Italy, the first beneficiary of the research.","author":[{"family":"Pallante","given":"Luigi"},{"family":"Meriggi","given":"Pietro"},{"family":"Damico","given":"Fabrizio"},{"family":"Gagliardi","given":"Valerio"},{"family":"Napolitano","given":"Antonio"},{"family":"Paolacci","given":"Fabrizio"},{"family":"Quinci","given":"Gianluca"},{"family":"Lorello","given":"Mario"},{"family":"Felice","given":"Gianmarco"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/buildings14010253","URL":"https://doi.org/10.3390/buildings14010253","source":"openalex"},{"id":"oa:W4400580387","type":"article-journal","title":"Simulation Methods and Digital Strategies for Supply Chains Facing Disruptions: Insights from a Systematic Literature Review","abstract":"Supply chain disruptions pose significant economic stability and growth challenges, impacting industries globally. This study aims to systematically review the literature on the use of simulation tools in managing supply chain disruptions, focusing on the historical evolution, prevalent simulation methods, specific challenges addressed, and research gaps. A systematic literature review was conducted using the PRISMA method. An initial pool of 236 articles was identified, from which 213 publications were rigorously reviewed. This study analyzed these articles to map the academic landscape, identify key clusters, and explore the integration of digital advancements in enhancing supply chain resilience. The review identified the chronological development of research in this field, highlighting significant contributions and influential authors. It was found that various simulation methods, including discrete-event simulation, agent-based modeling, and system dynamics, are employed to address different aspects of supply chain disruptions. Two primary research frontiers emerged from the analysis: the strategic reconfiguration of supply chain networks to mitigate ripple effects and the swift implementation of countermeasures to contain disruptions. The findings suggest a need for future research focusing on dynamic analysis and control theory applications to understand and manage supply chain disruptions better. This study also notes the increasing interest and need to use digital technologies (digital twins, artificial intelligence, etc.) in future research. It underscores the necessity for continued research to develop resilient and sustainable supply chain infrastructures aligned with the United Nations’ Sustainable Development Goals. The identified research gaps offer a roadmap for future scholarly exploration and practical implementation.","author":[{"family":"Korder","given":"Benjamin"},{"family":"Maheut","given":"Julien"},{"family":"Konle","given":"Matthias"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/su16145957","URL":"https://doi.org/10.3390/su16145957","source":"openalex"},{"id":"oa:W4399374482","type":"article-journal","title":"The role of leadership in managing digital transformation: A systematic literature review","abstract":"Digital transformation should not be seen as a time-bound project, but rather as a process that needs to be continuously improved and managed over time. In the absence of leadership, digital transformation will occur spontaneously in an organisation, but it is necessary to monitor and manage the process itself to achieve the goal and establish a digital organisation. A person who leads the digital transformation must possess the appropriate competencies. Leadership competencies, especially the combination of digital and human skills, are crucial to the development and success of the digital transformation process. The authors of this article identify a vaguely described process of digital transformation as the main research problem, highlighting the need for the systematisation of leadership competencies necessary for effective digital transformation management. In this regard, the research objectives are to define and describe the process of digital transformation and identify the leadership competencies necessary for successful management of the digital transformation process. In order to achieve the objectives of the paper, a systematic literature review was conducted for the period 2001–2022 and 90 papers were identified based on the criteria outlined by the Web of Science and Scopus index databases. The identified papers were then analysed from the aspect of defining digital transformation, the activities of the digital transformation process, and the characteristics of digital leadership. Following a thorough analysis of the selected literature, the paper provides a comprehensive definition of digital transformation, proposes a framework for its management, and analyses the key competencies of digital transformation leaders (digital leaders), which together make up the paper’s main contribution. The paper can be used not only as a starting point for future research in this area, but also as initial guidelines for the implementation and management of the digital transformation process. The systematic literature review conducted has certain limitations. Only two, albeit the largest, citation databases were searched, and only papers in English were identified. The established framework should be verified and expanded through empirical research.","author":[{"family":"Raković","given":"Lazar"},{"family":"Marić","given":"Slobodan"},{"family":"Milutinović","given":"Lena"},{"family":"Vuković","given":"Vuk"},{"family":"Bjekić","given":"Radmila"}],"issued":{"date-parts":[[2024]]},"DOI":"10.15240/tul/001/2024-2-006","URL":"https://doi.org/10.15240/tul/001/2024-2-006","source":"openalex"},{"id":"oa:W4402536066","type":"article-journal","title":"AI-enabled smart manufacturing boosts ecosystem value capture: The importance of servitization pathways within digital-intensive industries","abstract":"Understanding successful pathways for manufacturers to capture value within the service ecosystem framework is a recent and still nascent area of research that requires further investigation and growth. Within industrial settings, artificial intelligence (AI) constitutes an enabling technology that can be integrated across a network of products and systems, driving the transformation of these service ecosystems. From this perspective, this study proposes that the symbiotic convergence between AI-enabled smart manufacturing, which facilitates process and product enhancements, and servitization, which enables product availability and customization, contributes to a higher level of ecosystem value capture. To address this issue, a research model employing Smart Partial Least Squares was developed to examine the interplay between these constructs. By using survey data from a purposively selected sample of servitized manufacturing firms, the findings reveal the synergistic effects of integrating AI-enabled smart manufacturing and servitization. Furthermore, the results indicate variances across industrial sectors, and highlight that in digitally-intensive industries, service business models have undergone more substantial transformations, fostering accelerated ecosystem development streamlined by customization. Conversely, in digitally-augmented industries, where inputs are digital but products are predominantly analog, digital capabilities are primarily confined to production processes.","author":[{"family":"Bustinza","given":"Óscar"},{"family":"Fernández","given":"Luis"},{"family":"Vendrell-Herrero","given":"Ferrán"},{"family":"Opazobasáez","given":"Marco"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.ijpe.2024.109411","URL":"https://doi.org/10.1016/j.ijpe.2024.109411","source":"openalex"},{"id":"oa:W4403534921","type":"article-journal","title":"Design, Development and Maintenance of a Digital Twin of vitrification process: a methodological contribution","abstract":"This paper explores the concept of the digital twin introduced by Industry 4.0. Classically considered, a digital twin serves as a virtual replica or a physical asset, enabling various usages such as real-time monitoring, predictive maintenance management, or optimization. The application case is a continuous vitrification process developed in France for the treatment of final nuclear waste here supported by various physical prototypes. Using both normative references and concepts and principles from Model Based Systems and Software Engineering (MBSSE), the contribution introduces a methodological approach for the design, implementation and maintenance of a so-called digital twin system. Through case studies and analysis, the paper intents to demonstrate the potential of this approach in improving vitrification process for nuclear waste.","author":[{"family":"Galand","given":"G"},{"family":"Rabah","given":"Souad"},{"family":"Chapurlat","given":"Vincent"},{"family":"Chabal","given":"Caroline"},{"family":"Ledoux","given":"Alain"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/codit62066.2024.10708207","URL":"https://doi.org/10.1109/codit62066.2024.10708207","source":"openalex"},{"id":"oa:W4391786327","type":"article-journal","title":"Twin vocal folds as a novel evolutionary adaptation for vocal communications in lemurs","abstract":"Primates have varied vocal repertoires to communicate with conspecifics and sometimes other species. The larynx has a central role in vocal source generation, where a pair of vocal folds vibrates to modify the air flow. Here, we show that Madagascan lemurs have a unique additional pair of folds in the vestibular region, parallel to the vocal folds. The additional fold has a rigid body of a vocal muscle branch and it is covered by a stratified squamous epithelium, equal to those of the vocal fold. Such anatomical features support the hypothesis that it also vibrates in a manner like the vibrations that occur in the vocal folds. To examine the acoustic function of the two pairs of folds, we made a silicone compound model to demonstrate that they can simultaneously vibrate to lower the fundamental frequency and increase vocal efficiency. Similar acoustic effects are achieved using different features of the larynx for the other primates, e.g., by vibrating multiple sets of ventricular folds in several species and further by an evolutionary modification of enlarged larynx in howler monkeys. Our multidisciplinary approaches found that these functions were acquired through a unique evolutionary adaptation of the twin vocal folds in Madagascan lemurs.","author":[{"family":"Nakamura","given":"Kanta"},{"family":"Kanaya","given":"Mayuka"},{"family":"Matsushima","given":"Daisuke"},{"family":"Dunn","given":"Jacob"},{"family":"Hirabayashi","given":"Hideki"},{"family":"Sato","given":"Kiminori"},{"family":"Tokuda","given":"Isao"},{"family":"Nishimura","given":"Takeshi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1038/s41598-024-54172-z","URL":"https://doi.org/10.1038/s41598-024-54172-z","source":"openalex"},{"id":"oa:W4402287447","type":"manuscript","title":"Research on Electric Vehicle Power Systems Based on Digital Twin Technology","abstract":"As a critical component of electric vehicles, the powertrain has a significant impact on the overall performance of the vehicle. In addressing the challenge of lengthy testing cycles, this study develops a para model of the powertrain utilizing digital twin (DT) technology, thereby establishing a framework for simulation testing of multi-controller intermodulation. The research conducts functional definition coverage testing through the design of specific functional requirement use cases, and it validates the failure mechanism via fault injection use cases. The results indicate that the DT testing platform can effectively simulate the operational interactions among various controllers within the powertrain system. In comparison to traditional field testing, the digital twin-based testing methodology offers enhanced operational efficiency and allows for the examination of testing conditions that are impractical to implement in real vehicles, particularly in the context of fault injection testing, thus facilitating the early detection of potential safety risks within the system. The advancement of this technical solution holds significant practical implications for the future mass production and development of electric vehicles.","author":[{"family":"Li","given":"Chong"},{"family":"Lei","given":"Mei"},{"family":"Yang","given":"Liangyi"},{"family":"Xu","given":"Wei"},{"family":"You","given":"Yong"}],"issued":{"date-parts":[[2024]]},"DOI":"10.20944/preprints202409.0360.v1","URL":"https://doi.org/10.20944/preprints202409.0360.v1","source":"preprints"},{"id":"oa:W4402261802","type":"article-journal","title":"AI4WATER: A Digital Twin for Irrigated Agriculture","abstract":"This study presents a Digital Twin (DT) that is being created to optimize the use of the available hydric resources, and mitigate the effects of the increasing water shortage in irrigated agriculture in fields in the Urgell channel region (Lleida). A DT is \"a virtual representation of an object or system that spans its lifecycle, it is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making.\" It will model the water fluxes using the knowledge of the amounts of water taken in, used, and returned to the environment, and other parameters that impact the water budget, such as atmospheric variables (temperature, water vapor deficit, relative humidity, solar radiance…), surface soil moisture, and evapotranspiration maps, etc. Satellite Earth Observation (EO) data, collocated with in-situ data from a network of 20 soil moisture probes and 2 meteo stations will be used to train the DT. Additionally, a rover-based ground penetrating radar will be used for cross-calibration.","author":[{"family":"Camps","given":"Adriano"},{"family":"López-Martínez","given":"Carlos"},{"family":"Gonga","given":"A"},{"family":"Gracia","given":"G"},{"family":"Pérez-Portero","given":"Adrián"},{"family":"Alonso-González","given":"Alberto"},{"family":"Vallllossera","given":"M"},{"family":"Park","given":"Hyuk"},{"family":"Pérez","given":"V"},{"family":"Caselles","given":"O"},{"family":"Domenech","given":"C"},{"family":"Català","given":"Pau"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/igarss53475.2024.10641740","URL":"https://doi.org/10.1109/igarss53475.2024.10641740","source":"openalex"},{"id":"oa:W4393968657","type":"manuscript","title":"On future power system digital twins: A vision towards a standard architecture","abstract":"The energy sector's digital transformation brings mutually dependent communication and energy infrastructure, tightening the relationship between the physical and the digital world. Digital twins (DT) are the key concept for this. This paper initially discusses the evolution of the DT concept across various engineering applications before narrowing its focus to the power systems domain. By reviewing different definitions and applications, the authors present a new definition of DTs specifically tailored to power systems. Based on the proposed definition and extensive deliberations and consultations with distribution system operators, energy traders, and municipalities, the authors introduce a vision of a standard DT ecosystem architecture that offers services beyond real-time updates and can seamlessly integrate with existing transmission and distribution system operators' processes while reconciling with concepts such as microgrids and local energy communities based on a system-of-systems view. The authors also discuss their vision related to the integration of power system DTs into various phases of the system's life cycle, such as long-term planning, emphasising challenges that remain to be addressed, such as managing measurement and model errors, and uncertainty propagation. Finally, the authors present their vision of how artificial intelligence and machine learning can enhance several power systems DT modules established in the proposed architecture.","author":[{"family":"Zomerdijk","given":"Wouter"},{"family":"Pálenský","given":"Peter"},{"family":"Alskaif","given":"Tarek"},{"family":"Vergara","given":"Pedro"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2404.02568","URL":"https://doi.org/10.48550/arxiv.2404.02568","source":"openalex"},{"id":"oa:W4406223934","type":"article-journal","title":"A digital twin technique using external observational data to reduce sample sizes in clinical trials on Alzheimer’s disease","abstract":"Abstract Background Randomized placebo‐controlled trials (RCTs) are the gold standard to evaluate efficacy of new drug treatments for Alzheimer’s disease. For example, the United States FDA approved the brain amyloid‐targeting drug lecanemab following CLARITY AD, Biogen and Eisai’s Phase 3 RCT. However, recruiting enough participants for a high‐powered and demographically representative trial is difficult and expensive. Fortunately, historical patient data from existing external observational studies of a disease can help populate RCTs [Thorlund et al. (2020). https://doi.org/10.2147/CLEP.S242097 ]. We propose a new trial framework that uses an external study to source “digital twins” for each trial participant. Using computer‐simulated trials mimicking CLARITY AD’s demographics and 18‐month duration, we show that our digital twin trial (DTT) has increased power compared to a conventional RCT. Method A continuous time linear mixed model tracked CDRSB change‐from‐baseline (CDRSBΔbl) trajectories in 670 ADNI participants satisfying CLARITY AD inclusion criteria [clinicaltrials.gov/study/NCT03887455]. To simulate an RCT, we resampled and added noise to participants’ data, generating a desired sample size of “recruited” participants who we randomized 1:1 to “drug” and “placebo” groups. We calculated participants’ CDRSBΔbl scores at 18 months and simulated the drug effect as a 25% reduction in CDRSBΔbl. For each participant in our DTT, we used Gower’s distance on demographic and clinical baseline variables to identify 20 most‐similar real ADNI participants (the digital twins) from our original 670. Each original ADNI participant’s 18‐month CDRSBΔbl was calculated using the model. A z‐score was then calculated for each DTT participant’s 18‐month CDRSBΔbl relative to their digital twins. T‐tests were used to evaluate DTT drug vs. placebo group difference in mean z‐score and, separately, RCT group difference in mean 18‐month CDRSBΔbl. We simulated each trial 1,000 times. Power is the proportion of simulations with a statistically significant treatment group difference. Result Figure 1 shows that 90% power is reached with approximately 500 fewer recruited participants in simulated DTTs (∼1,600 participants) compared to RCTs (∼2,100 participants). Conclusion DTTs might require substantially fewer recruited participants to achieve the same power as conventional RCTs. This sample size reduction could facilitate recruitment for trials on Alzheimer’s and in rare diseases with low patient numbers.","author":[{"family":"Andrews","given":"Daniel"},{"family":"Collins","given":"DL"},{"family":"Initiative","given":"The"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/alz.086975","URL":"https://doi.org/10.1002/alz.086975","source":"openalex"},{"id":"oa:W4405750668","type":"article-journal","title":"Technological Drivers and Barriers for Digital Twin Adoption in the Malaysian Construction Industry","abstract":"Digital twin (DT) technology can potentially boost project performance and decision-making across various industries, including construction. However, the Malaysian construction sector encounters various barriers to its implementation. This paper aims to explore the barriers and drivers associated with the adoption of digital twin technology in Malaysia’s construction industry. Specifically, it aims to identify obstacles to adoption and propose technological drivers that could facilitate its integration into construction practices. A total of 23 journal articles were meticulously reviewed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. In addition, data from 97 responses collected from G7 construction professionals were analysed using the Statistical Package for Social Sciences (SPSS). The study uncovers various barriers hindering the adoption of digital twin technology in the Malaysian construction industry. These barriers include financial uncertainties, technological complexity, lack of standardisation, cyber security concerns and issues related to intellectual property rights. Furthermore, barriers arise from the novelty of the technology, the diversity of source systems, and interoperability issues. Moreover, the study categorizes the identified drivers into distinct categories and sub-themes, focusing on principles, production, operational performance and preservation. The findings indicate that overcoming these barriers and utilising the identified factors could accelerate the implementation of digital twin technology in the Malaysian construction industry. This study adds to the existing knowledge base and provides insights to encourage the spread of digital twin technology in Malaysia.","author":[{"family":"Esa","given":"Muneera"},{"family":"Munianday","given":"Praveena"},{"family":"Asim","given":"Jahanzeb"}],"issued":{"date-parts":[[2024]]},"DOI":"10.37934/araset.54.1.331350","URL":"https://doi.org/10.37934/araset.54.1.331350","source":"openalex"},{"id":"oa:W4365134817","type":"article-journal","title":"Patient‐centered digital biomarkers for allergic respiratory diseases and asthma: The ARIA‐EAACI approach – ARIA‐EAACI Task Force Report","abstract":"Biomarkers for the diagnosis, treatment and follow-up of patients with rhinitis and/or asthma are urgently needed. Although some biologic biomarkers exist in specialist care for asthma, they cannot be largely used in primary care. There are no validated biomarkers in rhinitis or allergen immunotherapy (AIT) that can be used in clinical practice. The digital transformation of health and health care (including mHealth) places the patient at the center of the health system and is likely to optimize the practice of allergy. Allergic Rhinitis and its Impact on Asthma (ARIA) and EAACI (European Academy of Allergy and Clinical Immunology) developed a Task Force aimed at proposing patient-reported outcome measures (PROMs) as digital biomarkers that can be easily used for different purposes in rhinitis and asthma. It first defined control digital biomarkers that should make a bridge between clinical practice, randomized controlled trials, observational real-life studies and allergen challenges. Using the MASK-air app as a model, a daily electronic combined symptom-medication score for allergic diseases (CSMS) or for asthma (e-DASTHMA), combined with a monthly control questionnaire, was embedded in a strategy similar to the diabetes approach for disease control. To mimic real-life, it secondly proposed quality-of-life digital biomarkers including daily EQ-5D visual analogue scales and the bi-weekly RhinAsthma Patient Perspective (RAAP). The potential implications for the management of allergic respiratory diseases were proposed.","author":[{"family":"Bousquet","given":"Jean"},{"family":"Shamji","given":"Mohamed"},{"family":"Antó","given":"Josep"},{"family":"Schünemann","given":"Holger"},{"family":"Canonica","given":"Giorgio"},{"family":"Jutel","given":"Marek"},{"family":"Giacco","given":"Stefano"},{"family":"Zuberbier","given":"Torsten"},{"family":"Pfaar","given":"Oliver"},{"family":"Fonseca","given":"João"},{"family":"Sousapinto","given":"Bernardo"},{"family":"Klimek","given":"Ludger"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1111/all.15740","URL":"https://doi.org/10.1111/all.15740","source":"openalex"},{"id":"oa:W4396645954","type":"manuscript","title":"An Advanced Framework for Ultra-Realistic Simulation and Digital Twinning for Autonomous Vehicles","abstract":"Simulation is a fundamental tool in developing autonomous vehicles, enabling rigorous testing without the logistical and safety challenges associated with real-world trials. As autonomous vehicle technologies evolve and public safety demands increase, advanced, realistic simulation frameworks are critical. Current testing paradigms employ a mix of general-purpose and specialized simulators, such as CARLA and IVRESS, to achieve high-fidelity results. However, these tools often struggle with compatibility due to differing platform, hardware, and software requirements, severely hampering their combined effectiveness. This paper introduces BlueICE, an advanced framework for ultra-realistic simulation and digital twinning, to address these challenges. BlueICE's innovative architecture allows for the decoupling of computing platforms, hardware, and software dependencies while offering researchers customizable testing environments to meet diverse fidelity needs. Key features include containerization to ensure compatibility across different systems, a unified communication bridge for seamless integration of various simulation tools, and synchronized orchestration of input and output across simulators. This framework facilitates the development of sophisticated digital twins for autonomous vehicle testing and sets a new standard in simulation accuracy and flexibility. The paper further explores the application of BlueICE in two distinct case studies: the ICAT indoor testbed and the STAR campus outdoor testbed at the University of Delaware. These case studies demonstrate BlueICE's capability to create sophisticated digital twins for autonomous vehicle testing and underline its potential as a standardized testbed for future autonomous driving technologies.","author":[{"family":"He","given":"Yuankai"},{"family":"Chen","given":"Hanlin"},{"family":"Shi","given":"Weisong"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2405.01328","URL":"https://doi.org/10.48550/arxiv.2405.01328","source":"openalex"},{"id":"oa:W4406906095","type":"article-journal","title":"The use of digital twin systems in the construction of socio-cyber-physical systems","abstract":"The modern stage of technology development allows us to create anthropogenic systems that feature a fundamentally new level of complexity compared to existing systems, which for the most part are multilevel heterogeneous distributed systems, which include anthropogenic physical entities, virtual entities, natural objects, living beings, people and human collectives. Such systems can be defined as socio-cyber-physical systems. The article analyzes the current state of technology for building socio-cyber-physical systems, and considers the possibility of using digital twins in their construction. The possible aspects of using digital twin in the construction of this class of systems are considered. This article discusses one of the possible approaches to the construction of socio-cyber-physical systems based on the use of runtime digital twin systems built using a polymodel approach. The proposed approach can be considered as a convergence of several well-known approaches to the construction of sociocyber-physical systems. A reference architecture of the run-time digital twin is proposed, the basis of which is not a monolithic model, but a system of models. Typical models that can be used in the construction of socio-cyber-physical systems are analyzed. One of the key problems facing the developers of socio-cyber-physical systems is the construction of a human model.","author":[{"family":"Vodyaho","given":"Alexander"},{"family":"Zhukova","given":"Nataly"},{"family":"Ananeva","given":"VY"}],"issued":{"date-parts":[[2024]]},"DOI":"10.21638/spbu10.2024.403","URL":"https://doi.org/10.21638/spbu10.2024.403","source":"openalex"},{"id":"oa:W4393150681","type":"manuscript","title":"Towards A Distributed Digital Twin Framework for Predictive Maintenance in Manufacturing Systems","abstract":"This study uses a wind turbine case study to showcase an architecture for implementing a distributed digital twin in which all important aspects of a predictive maintenance solution in a DT use a fog computing paradigm, and the typical predictive maintenance DT is improved to offer better asset utilization and management through real time condition monitoring, predictive analytics, and health management of selected components of Wind turbines in a wind farm.. Digital twin (DT) is a technology that sits at the intersection of Internet of Things, Cloud Computing and Software Engineering to provide a suitable tool for replicating physical objects in the digital space. This can facilitate the implementation of asset management in manufacturing systems through predictive maintenance solutions leveraged by Machine Learning (ML). With DTs, a solution architecture can easily use data and software to implement asset management solutions such as Condition Monitoring and Predictive Maintenance using acquired sensor data from physical objects and computing capabilities in the digital space. While DT offers a good solution, it is an emerging technology that could be improved with better standards, architectural framework, and implementation methodologies. Researchers in both academia and industry have showcased DT implementations with different levels of success. However, DTs remain limited in standards and architectures that offer efficient predictive maintenance solutions with real time sensor data, and intelligent DT capabilities. An appropriate feedback mechanism is also needed to improve asset management operations.","author":[{"family":"Abdullahi","given":"Ibrahim"},{"family":"Longo","given":"Stefano"},{"family":"Samie","given":"Mohammad"}],"issued":{"date-parts":[[2024]]},"DOI":"10.20944/preprints202403.1357.v1","URL":"https://doi.org/10.20944/preprints202403.1357.v1","source":"preprints"},{"id":"oa:W4404835058","type":"article-journal","title":"Enhancing the energy efficiency in district heating networks through digital twins","abstract":"Europe prioritizes energy efficiency for sustainable development and climate action, with buildings consuming 40% of the EU’s energy and contributing over 30% of CO 2 emissions. To address this, the EU implements policies targeting energy efficiency across sectors like industry, transportation, and district heating. The Energy Efficiency Directive mandates reductions in energy consumption, promoting measures such as energy audits and performance standards. Initiatives like the European Green Deal and Renovation Wave Strategy underscore the importance of energy efficiency in achieving carbon neutrality. District heating systems play a vital role in this strategy, offering Efficient heating solutions for urban areas, and optimizing their operation is a key focus of research. Techniques include mathematical modeling, advanced control strategies, and integration of renewable energy sources. This work focuses on the application of a digital twin to model the district heating network combined with prediction tools to enhance system efficiency. A procedure to integrate physics (white-box) and data-driven (black-box) approaches to foster better-informed decisions in the optimal energy resources management is presented.","author":[{"family":"Hernández","given":"José"},{"family":"Miguel","given":"Ignacio"},{"family":"Vélez","given":"Fredy"},{"family":"Marcos","given":"Pablo"},{"family":"Martínbroto","given":"Javier"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.procs.2024.09.277","URL":"https://doi.org/10.1016/j.procs.2024.09.277","source":"openalex"},{"id":"oa:W4394813098","type":"article-journal","title":"Brazilian Twin Studies: A Scoping Review","abstract":"The current study was motivated by an interest in deepening understanding of Brazilian twin research, which is underrepresented internationally, in an effort to rectify this situation. Our aim was threefold: (1) to carry out a comprehensive investigation of Brazilian research on twins according to the area of knowledge; (2) to evaluate the representation of research in the field of psychology in comparison with other areas; (3) to evaluate characteristics of the research that may have contributed to its exclusion from the comprehensive meta-analysis of 50 years of twin research. A scoping review was performed according to PRISMA guidelines. Titles and abstracts were searched up to 2022 in six databases: CAPES, BDLTD, PePSIC, PubMed, Google Scholar, and SciELO, using selected keywords both in Portuguese and in English (e.g., 'twins' and 'Brazil'; 'twinning' and 'Brazil'; 'gemelaridade' [twinning], and 'gêmeos' [twins]). Three hundred and forty publications were included in the review. Approximately half (53.8‰) used the classic twin design to investigate the heritability of several traits, and the other half (46.2%) used other research designs. The scoping review showed that the number of publications doubled approximately every 10 years. Most publications were from the health area, with medicine accounting for approximately half of the studies, followed by psychology, odontology, and biology. We found that the interest in studying twins among Brazilian scientists is increasing over the years and there are reasons to be enthusiastic about the potential impact of this trend in the global scenario.","author":[{"family":"Fernandes","given":"Eloísa"},{"family":"Ferreira","given":"Isabella"},{"family":"Felipe","given":"Renata"},{"family":"Segal","given":"Nancy"},{"family":"Otta","given":"Emma"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1017/thg.2024.17","URL":"https://doi.org/10.1017/thg.2024.17","source":"openalex"},{"id":"oa:W4403304547","type":"article-journal","title":"Digitally gamified co-creation: enhancing community engagement in urban design through a participant-centric framework","abstract":"Abstract Urban co-creation is an approach to urban design that actively involves stakeholders and end-users in the design process. As designers increasingly use digital tools to manage design information, stakeholders and residents may find it difficult to participate, resulting in a lack of engagement. The emergence of metaverse technologies offers a crucial opportunity to employ user-friendly and collaborative tools, enabling more effective participation. In the study presented in this article, a custom-designed digital game with virtual reality environment was used to facilitate a series of co-creation workshops. The study focused on changes in participants’ experience by comparing baseline and endline survey results against the design outputs. It employed a holistic framework considering four dimensions: game design, participatory experience, learning outcomes and co-creation results. The findings indicate that the digitally gamified approach helped enhance participation and knowledge sharing, and even though game design ratings varied, the use of video games motivated engagement, particularly in an intergenerational context. The co-creation workshop design documented in this article offers new methods to enhance community engagement in urban design. Especially during digital transformation, it opens renewed discussions on balancing traditional output-driven approaches with more participant-centric methods and design objectives.","author":[{"family":"Ng","given":"Provides"},{"family":"Zhu","given":"Shutong"},{"family":"Li","given":"Yuechun"},{"family":"Ameijde","given":"Jeroen"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1017/dsj.2024.17","URL":"https://doi.org/10.1017/dsj.2024.17","source":"openalex"},{"id":"oa:W4402459449","type":"article-journal","title":"Impacts of Digital Entrepreneurial Ecosystems on Sustainable Development: Insights from Latin America","abstract":"Digital Entrepreneurial Ecosystems (DEEs) are transforming the economic landscape through their integration of digital technologies, offering new opportunities for innovation and growth. This study explores the impact of DEEs on sustainable development, focusing specifically on Latin America. As DEEs continue to evolve, understanding their influence on economic, environmental, and social sustainability becomes crucial, particularly in a region characterized by significant developmental challenges. Utilizing a data panel from two different periods of analysis, from 2013 to 2017 and from 2018 to 2022, within the adapted DEE framework provided by the Global Entrepreneurship Development Institute (GEDI), we employ Principal Component Regression (PCR), Partial Least Squares Regression (PLSR), and fuzzy-set Qualitative Comparative Analysis (fsQCA 3.0) to analyze DEE components across 14 Latin American countries. These countries may not have the full spectrum of digital capabilities, yet they are still able to harness the digital elements they do possess effectively. This suggests that even partial digitalization, when strategically utilized, can lead to substantial gains in sustainable development. Additionally, Networking, Digital Protection, and Digital Tech Transfer are DEE components that present a higher magnitude in social, environmental, and economic development in Latin American countries. This study not only contributes to a deeper understanding of a DEE’s role in fostering sustainable development, but it also offers actionable insights for policymakers and entrepreneurs to leverage DEEs for broader societal benefits. The implications of the findings present perspectives under the existing literature, and the conclusion shows recommendations for future research and strategy development.","author":[{"family":"Pigola","given":"Angélica"},{"family":"Fischer","given":"Bruno"},{"family":"Moraes","given":"Gustavo"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/su16187928","URL":"https://doi.org/10.3390/su16187928","source":"openalex"},{"id":"oa:W4399207319","type":"article-journal","title":"Towards a Digital Twin of Liege: The Core 3D Model based on Semantic Segmentation and Automated Modeling of LiDAR Point Clouds","abstract":"Abstract. The emergence of Digital Twins in city planning and management marks a contemporary trend, elevating the realm of 3D modeling and simulation for cities. In this context, the use of semantic point clouds to generate 3D city models for Digital Twins proves instrumental in addressing this evolving need. This article introduces a processing pipeline for the automatic modeling of buildings, roads, and vegetation based on the semantic segmentation results of 3D LiDAR point clouds. It employs a semantic segmentation approach that integrates multiple training datasets to achieve precise extraction of target objects. Open-source reconstruction tools have been adapted for building and road modeling, while a Python code was optimized for tree modeling, leveraging a foundational code. The case study was conducted in the city of Liège, Belgium. The obtained results were satisfactory, and the schemas and geometry of the developed models were validated. An evaluation of the adopted reconstruction methods was conducted, along with their comparison to other methods from the literature.","author":[{"family":"Ballouch","given":"Zouhair"},{"family":"Jeddoub","given":"Imane"},{"family":"Hajji","given":"Rafika"},{"family":"Kasprzyk","given":"Jean"},{"family":"Billen","given":"Roland"}],"issued":{"date-parts":[[2024]]},"DOI":"10.5194/isprs-annals-x-4-w4-2024-13-2024","URL":"https://doi.org/10.5194/isprs-annals-x-4-w4-2024-13-2024","source":"openalex"},{"id":"oa:W4401622700","type":"article-journal","title":"A human-centric methodology for the co-evolution of operators’ skills, digital tools and user interfaces to support the Operator 4.0","abstract":"The concept of Operator 4.0 has been recently defined to evolve the modern industrial scenarios by defining a knowledge sharing process from/to operators and industrial systems, creating personalized skills, and introducing digital tools towards socially sustainable factories. In this context, dynamic and adaptive user interfaces can make humans part of the intelligent factory system, supporting human work contextually and providing specific contents when needed, preserving the human wellbeing. This paper defines a human-centric methodology for the symbiotic co-evolution of operators’ skills, assistive digital tools and user interfaces, developed within the Horizon Europe project titled “DaCapo - Digital assets and tools for Circular value chains and manufacturing products”. The project focuses on defining a new set of human-centric digital tools and services for the manufacturing industry capable of boosting the application of circular economy (CE) throughout the manufacturing value chains. The proposed methodology can link the specific needs of an industrial case to the definition of the most proper assistive digital tools and functionalities to drive the design of adaptive, proactive user interfaces for the Operator 4.0. The method has been applied and validated on one of the project use cases, involving a manufacturing company operating in warehousing and logistics.","author":[{"family":"Grandi","given":"Fabio"},{"family":"Giuditta","given":"Contini"},{"family":"Peruzzini","given":"Margherita"},{"family":"Raffaeli","given":"Roberto"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.rcim.2024.102854","URL":"https://doi.org/10.1016/j.rcim.2024.102854","source":"openalex"},{"id":"oa:W4392656056","type":"manuscript","title":"A Multidisciplinary Hyper-Modeling Scheme in Personalized In Silico Oncology: Coupling Cell Kinetics With Metabolism, Signaling Networks and Biomechanics As Plug-In Component Models of a Cancer Digital Twin","abstract":"The massive amount of human biological, imaging and clinical data produced by multiple and diverse sources, necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels as well as their orchestration and links are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof of concept study cases. Personalized simulations over the actual anatomy of a patient have been carried out. The hypermodel has also applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin based clinical decision support system and the core of future in silico trial platforms, although additional retrospective adaptation and validation is necessary.","author":[{"family":"Kolokotroni","given":"Eleni"},{"family":"Abler","given":"Daniel"},{"family":"Ghosh","given":"Alokendra"},{"family":"Tzamali","given":"Eleftheria"},{"family":"Grogan","given":"James"},{"family":"Georgiadi","given":"Eleni"},{"family":"Büchler","given":"Philippe"},{"family":"Radhakrishnan","given":"Ravi"},{"family":"Byrne","given":"Helen"},{"family":"Sakkalis","given":"Vangelis"},{"family":"Nikiforaki","given":"Katerina"},{"family":"Karatzanis","given":"Ioannis"}],"issued":{"date-parts":[[2024]]},"DOI":"10.20944/preprints202403.0490.v1","URL":"https://doi.org/10.20944/preprints202403.0490.v1","source":"preprints"},{"id":"oa:W4381435445","type":"article-journal","title":"PROBLEMS OF THE LEGAL NATURE OF DIGITAL TWINS","abstract":"The article discusses various approaches to the definition of the concept of digital twins in the context of the development of the digital economy, the author's definition of the concept of digital twins is proposed, their essence, content and regulation are established. The direction of the legislative process aimed at the development of digital twins is shown, the problems of legal support of digital twins are analyzed, including in the field of aviation, astronautics, medicine, healthcare and architecture. The study used formal-logical methods, analysis and synthesis, as well as a technical-legal method. Attention is drawn to the need for legal regulation of this activity. It is concluded that a digital twin is a virtual copy of any material (and sometimes nonmaterial) object, process or phenomenon. The main goal of digital twins is the range of tasks to be solved, one of which is optimization. The use of digital twins, like many other information technologies associated with the use of the Internet, is necessarily associated with the risk of violating human and civil rights and their legitimate interests. However, many industries are finding innovative ways to create and use digital twins. It is fixed that the concept of \"digital twin\" can be considered as a general concept for a digital character and a digital profile. The article also reflects the need to revise approaches to state regulation of relations on the use of digital twins and develop common principles harmonized with other states, for example, such legislative norms that, on the one hand, do not interfere with the development of relevant technologies and services, and, on the other hand, protect human rights and legitimate interests.","author":[{"family":"Bogun","given":"Sergey"},{"family":"Healthcare"}],"issued":{"date-parts":[[2023]]},"DOI":"10.14529/law230209","URL":"https://doi.org/10.14529/law230209","source":"openalex"},{"id":"oa:W4392709668","type":"article-journal","title":"Digital twin modeling and intelligent optimization for rail operation safety assessment","abstract":"Currently, the use of fixed empirical parameters combined with traditional algorithms to construct train parameter prediction models for estimating train energy consumption is often used. However, due to changes in train related parameters, there is a significant error between the estimated results of this method and the actual values, which cannot reflect the true state of train operation. It affects the subsequent maintenance and repair of trains, thereby affecting the safety of the entire subway operation system. To address the above issues, a train traction power flow model based on digital twin technology is proposed. The swarm intelligence optimization algorithm is not used to correct model parameters. By correcting the deviation of train passenger load, accurate prediction of train energy consumption can be achieved. The experimental results show that the power flow model constructed by the research institute can reduce the power error of single interval trains by over 11.91%. The average DC voltage error of the train power flow model after parameter correction is 0.19%. The average DC current error is 12.07%. The root mean square error range of passenger capacity for similar day neural network models is [0.0521,0.0811]. The experimental results indicate that the model constructed by the research institute can accurately predict train energy consumption and ensure the safety of the subway operation system.","author":[{"family":"Wang","given":"Ling"},{"family":"Chen","given":"Xiang"},{"family":"Feng","given":"Ding"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1051/smdo/2024002","URL":"https://doi.org/10.1051/smdo/2024002","source":"openalex"},{"id":"oa:W4391751283","type":"article-journal","title":"Lake Water Temperature Modeling in an Era of Climate Change: Data Sources, Models, and Future Prospects","abstract":"Abstract Lake thermal dynamics have been considerably impacted by climate change, with potential adverse effects on aquatic ecosystems. To better understand the potential impacts of future climate change on lake thermal dynamics and related processes, the use of mathematical models is essential. In this study, we provide a comprehensive review of lake water temperature modeling. We begin by discussing the physical concepts that regulate thermal dynamics in lakes, which serve as a primer for the description of process‐based models. We then provide an overview of different sources of observational water temperature data, including in situ monitoring and satellite Earth observations, used in the field of lake water temperature modeling. We classify and review the various lake water temperature models available, and then discuss model performance, including commonly used performance metrics and optimization methods. Finally, we analyze emerging modeling approaches, including forecasting, digital twins, combining process‐based modeling with deep learning, evaluating structural model differences through ensemble modeling, adapted water management, and coupling of climate and lake models. This review is aimed at a diverse group of professionals working in the fields of limnology and hydrology, including ecologists, biologists, physicists, engineers, and remote sensing researchers from the private and public sectors who are interested in understanding lake water temperature modeling and its potential applications.","author":[{"family":"Piccolroaz","given":"Sebastiano"},{"family":"Zhu","given":"Senlin"},{"family":"Ladwig","given":"Robert"},{"family":"Carrea","given":"Laura"},{"family":"Oliver","given":"Samantha"},{"family":"Piotrowski","given":"A"},{"family":"Ptak","given":"Mariusz"},{"family":"Shinohara","given":"Ryuichiro"},{"family":"Sojka","given":"Mariusz"},{"family":"Woolway","given":"RI"},{"family":"Zhu","given":"David"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1029/2023rg000816","URL":"https://doi.org/10.1029/2023rg000816","source":"openalex"},{"id":"oa:W4396976447","type":"article-journal","title":"Developing a virtual reality and AI-based framework for advanced digital manufacturing and nearshoring opportunities in Mexico","abstract":"The growing expansion of the manufacturing sector, particularly in Mexico, has revealed a spectrum of nearshoring opportunities yet is paralleled by a discernible void in educational tools for various stakeholders, such as engineers, students, and decision-makers. This paper introduces a state-of-the-art framework, incorporating virtual reality (VR) and artificial intelligence (AI) to metamorphose the pedagogy of advanced manufacturing systems. Through a case study focused on the design, production, and evaluation of a robotic platform, the framework endeavors to offer an exhaustive educational experience via an interactive VR environment, encapsulating (1) Robotic platform system design and modeling, enabling users to immerse themselves in the design and simulation of robotic platforms under varied conditions; (2) Virtual manufacturing company, presenting a detailed virtual manufacturing setup to enhance users' comprehension of manufacturing processes and systems, and problem-solving in realistic settings; and (3) Product evaluation, wherein users employ VR to meticulously assess the robotic platform, ensuring optimal functionality and customer satisfaction. This innovative framework melds theoretical acumen with practical application in advanced manufacturing, preparing entities to navigate Mexico's manufacturing sector's vibrant and competitive nearshoring landscape. It creates an immersive environment for understanding modern manufacturing challenges, fostering Mexico's manufacturing sector growth, and maximizing nearshoring opportunities for stakeholders.","author":[{"family":"Ponce","given":"Pedro"},{"family":"Anthony","given":"Brian"},{"family":"Bradley","given":"Russel"},{"family":"Maldonado-Romo","given":"Javier"},{"family":"Méndez","given":"Juana"},{"family":"Montesinos","given":"Luis"},{"family":"Molina","given":"Arturo"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1038/s41598-024-61514-4","URL":"https://doi.org/10.1038/s41598-024-61514-4","source":"openalex"},{"id":"oa:W4403276210","type":"manuscript","title":"Connection-Aware Digital Twin for Mobile Adhoc Networks in the 5G Era","abstract":"5G Mobile Adhoc Networks (5G-MANETs) are a popular and agile solution for data transmission in local contexts, while maintaining communication with remote entities via 5G. These characteristics have established 5G-MANETs as versatile communication infrastructures for deploying contextual applications, leveraging physical proximity while exploiting the possibilities of the Internet. As a result, there is growing interest in exploring the potential of these networks and their performance in real-world scenarios. However, the management and monitoring of 5G-MANETs is challenging due to their inherent characteristics, such as highly variable topology, unstable connections, energy consumption of individual devices, message routing, and occasional inability to connect to 5G. Considering these challenges, the proposed work aims to address real-time monitoring of 5G-MANETs using a connection-aware Digital Twin (DT). The approach provides two main functions: offering a live virtual representation of the network, even in scenarios where multiple nodes lack 5G connectivity, and estimating the performance of the infrastructure, enabling the specification of customized conditions. To achieve this, a communication architecture is proposed, analyzing its components and defining the involved processes. The DT is implemented and evaluated in a laboratory setting, assessing its accuracy in representing the physical network under varying conditions of topology and Internet availability. The results show 100% accuracy for the DT in fully connected topologies, with ultra-low latency averaging under 80 ms, and suitable performance in partially connected contexts, with latency averages below 3000 ms.","author":[{"family":"Jesús-Azabal","given":"Manuel"},{"family":"Zheng","given":"Zhang"},{"family":"Bingxia","given":"Gao"},{"family":"Jing","given":"Yang"},{"family":"Soares","given":"Vasco"},{"family":"Soares","given":"Vasco"}],"issued":{"date-parts":[[2024]]},"DOI":"10.20944/preprints202410.0367.v1","URL":"https://doi.org/10.20944/preprints202410.0367.v1","source":"preprints"},{"id":"oa:W4404189951","type":"article-journal","title":"Digital transformation: The geopolitical-organizational nexus","abstract":"This special issue aimed to attract articles situating digital transformation in the geopolitical-organizational nexus. Unlike innovation and change panaceas (or fads) like business process reengineering (BPR) which became popular in the 1990s, digital transformation is a multi-level concept. Extending beyond the redesign of organizational and business processes, the analytical boundaries of digital transformation include ecosystems, organizational networks, business and operational processes, organizational identities, governance structures, and quality/cost dynamics. However, the extant literature on digital transformation continues to use the organization as the primary unit of analysis. Definitions of digital transformation vary widely, with some not dissimilar to the BPR era. The papers included in this special issue provide analytical and empirical examples on the pervasive effects from contemporary digital technology for society, organizations, and citizens. Future work which isolates the digital technology artefact would benefit from further refinement of the digital transformation concept. A starting point is to revisit the digital technology evolution over past decades which reveal the inflection points of technological change, specifically for mainframes, PCs, and the Internet. Such analysis will increase our understanding and contextualization of past panaceas like BPR for generating new insights on how digital technologies are front and center in debates on digital transformation.","author":[{"family":"Currie","given":"Wendy"},{"family":"Weerakkody","given":"Vishanth"},{"family":"Vliet","given":"Ben"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1177/02683962241299822","URL":"https://doi.org/10.1177/02683962241299822","source":"openalex"},{"id":"oa:W4393273105","type":"article-journal","title":"A probabilistic neural twin for treatment planning in peripheral pulmonary artery stenosis","abstract":"The substantial computational cost of high-fidelity models in numerical hemodynamics has, so far, relegated their use mainly to offline treatment planning. New breakthroughs in data-driven architectures and optimization techniques for fast surrogate modeling provide an exciting opportunity to overcome these limitations, enabling the use of such technology for time-critical decisions. We discuss an application to the repair of multiple stenosis in peripheral pulmonary artery disease through either transcatheter pulmonary artery rehabilitation or surgery, where it is of interest to achieve desired pressures and flows at specific locations in the pulmonary artery tree, while minimizing the risk for the patient. Since different degrees of success can be achieved in practice during treatment, we formulate the problem in probability, and solve it through a sample-based approach. We propose a new offline-online pipeline for probabilistic real-time treatment planning which combines offline assimilation of boundary conditions, model reduction, and training dataset generation with online estimation of marginal probabilities, possibly conditioned on the degree of augmentation observed in already repaired lesions. Moreover, we propose a new approach for the parametrization of arbitrarily shaped vascular repairs through iterative corrections of a zero-dimensional approximant. We demonstrate this pipeline for a diseased model of the pulmonary artery tree available through the Vascular Model Repository.","author":[{"family":"Lee","given":"John"},{"family":"Richter","given":"Jakob"},{"family":"Pfaller","given":"Martin"},{"family":"Szafron","given":"Jason"},{"family":"Menon","given":"Karthik"},{"family":"Zanoni","given":"Andrea"},{"family":"Ma","given":"Michael"},{"family":"Feinstein","given":"Jeffrey"},{"family":"Kreutzer","given":"Jacqueline"},{"family":"Marsden","given":"Alison"},{"family":"Schiavazzi","given":"Daniele"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/cnm.3820","URL":"https://doi.org/10.1002/cnm.3820","source":"openalex"},{"id":"oa:W4403086305","type":"article-journal","title":"Deciphering the evolution of metaverse - A techno-functional perspective in digital marketing","abstract":"• The metaverse has disrupted the traditional marketing practices and it has potential to transform entire world of marketing activities with thrilling immersive experiences. • This study provides an analysis of evolving field of metaverse marketing and information systems (IS) using systematic literature review (SLR). • The clusters of the research illustrate that metaverse marketing encompassing consumer behaviour, consumer engagement, brand experience and virtual product design. • This study also reveals the emerging trends and gaps in literature that pave the ways for future research expansion in the metaverse marketing. • The results of this research provide valuable insights for the academicians and marketers by uncovering the existing research structures and future research prospects of metaverse marketing. The metaverse has disrupted the traditional marketing practices and it has potential to transform entire world of marketing activities with thrilling immersive experiences. This study provides an analysis of evolving field of metaverse marketing in the context of information systems using state of the art bibliometric and scientometric tools coupled with machine learning algorithms. Utilizing 257 documents from Scopus database that published between 1996 and 2024, this research maps and unveils the development of metaverse marketing from its inception and the role of information systems in its evolution. The analysis of literature resulted in five main emerging themes of the role of information systems in metaverse marketing research as User Experience, Customer engagement, Convergence of metaverse Technology, Design of virtual goods & experience and Global Social Interaction. The major sub-themes of the study are User Behaviors and Preferences, Branding on virtual environment, Virtual reality, Virtual wearables and Virtual Socialization. This study also reveals the emerging trends and gaps in literature that pave the ways for future research expansion in the information systems and metaverse marketing. Few of the important future research areas identified are understanding user experience, design of immersive customer engagement strategies, customer virtual presence and Security & privacy concerns of the users on metaverse platform.","author":[{"family":"Wasiq","given":"Mohammad"},{"family":"Bashar","given":"Abu"},{"family":"Nyagadza","given":"Brighton"},{"family":"Johri","given":"Amar"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.jjimei.2024.100296","URL":"https://doi.org/10.1016/j.jjimei.2024.100296","source":"openalex"},{"id":"oa:W4399365560","type":"article-journal","title":"Construction and Application of Energy Footprint Model for Digital Twin Workshop Oriented to Low-Carbon Operation","abstract":"To address the difficulty of accurately characterizing the fluctuations in equipment energy consumption and the dynamic evolution of whole energy consumption in low-carbon workshops, a low-carbon-operation-oriented construction method of the energy footprint model (EFM) for a digital twin workshop (DTW) is proposed. With a focus on considering the fluctuations in equipment energy consumption and the correlation between multiple pieces of equipment at the workshop production process level (CBMEatWPPL), the EFM of a DTW is obtained to characterize the dynamic evolution of whole energy consumption in the workshop. Taking a production unit as a case, on the one hand, an EFM of the production unit is constructed, which achieved the characterization and visualization of the fluctuations in equipment energy consumption and the dynamic evolution of whole energy consumption in the production unit; on the other hand, based on the EFM, an objective function of workshop energy consumption is established, which is combined with the tool life, robot motion stability, and production time to formulate a multi-objective optimization function. The bee colony algorithm is adopted to solve the multi-objective optimization function, achieving collaborative optimization of cross-equipment process parameters and effectively reducing energy consumption in the production unit. The effectiveness of the proposed method and constructed EFM is demonstrated from the above two aspects.","author":[{"family":"Zhang","given":"Lei"},{"family":"Zhuang","given":"Cunbo"},{"family":"Tian","given":"Ying"},{"family":"Yao","given":"Mengqi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/s24113670","URL":"https://doi.org/10.3390/s24113670","source":"openalex"},{"id":"oa:W4402734223","type":"article-journal","title":"Neil Armstrong’s digital twin: An integrative approach for movement analysis in simulated space missions","abstract":"Introduction and Purpose Space exploration is transitioning to a new era. NASA’s Artemis program is spearheading crewed missions to the Moon in the next decade, paving the way for eventual human exploration of Mars (Smith et al., 2020). However, space missions further afar from Earth require a shift in operational concepts towards an increasingly autonomous mission architecture due to communication delay (Belobrajdic et al., 2021). Analog space missions, such as AMADEE24, address these methodological challenges in a terrestrial simulation scenario (Preston & Dartnell, 2014). In order to imitate the biomechanical and perceptual constraints of suited operations in an analog mission, the astronauts wear space-suit simulators during extravehicular activities (EVA; Groemer et al., 2012). As EVAs account for the most physically-demanding and risky operations during space missions, the relevance for human movement science in space research is increasing. We propose an approach to integrate already available data sources to conduct comprehensive human movement analysis in planetary exploration scenarios. As a proof of concept, we aimed to identify sensitive kinematic and physiological markers for muscular fatigue in astronauts’ gait during the AMADEE24 mission conducted by the Austrian Space Forum. Methods The AMADEE24 Mars simulation took place from March 5th until April 5th 2024 in the Ararat province in Armenia, which was selected as simulation site for its geological similarities to areas on Mars. Six analog astronauts (two female, four male) lived isolated in a habitat for 21 days, conducting robotic, psychological and geoscientific experiments pertinent to future surface activities on Mars. Extensive high-resolution drone imaging of the analog region before the mission was conducted to compile a digital elevation model used for EVAs. Experiments in the field were conducted by two analog astronauts wearing the AOUDA space-suit simulator with two astronauts supporting them from the habitat using radio communication (Groemer et al., 2012). The recorded telemetry data of the suit included GPS location, heart rate, CO2- and O2-concentrations in the helmet as well as temperature and humidity measurements in the suit and primarily serves for medical monitoring of the astronauts during the EVA. Beneath the suit, the astronauts wore the inertial whole-body motion capture system XsensTM Awinda (Xsens Technologies B.V., Enschede, Netherlands) with 17 IMU-sensors and an 8-channel electromyography (EMG) system (Cometa myon, Barregio, Italy) for muscle activity recordings of the back, lower- and upper-extremities on the dominant side. For all experiments involving geoscientific operations by the analog astronauts, a remote-controlled robotic vehicle accompanied the astronauts in the field (Edlinger et al., 2022). The rover carried tools, samples and receiver for the motion-capture- and EMG-sensors. Additionally, the rover tracked the ambient conditions and took images of the surroundings, which are used to improve the 3D-environmental-model of the EVA region (see Figure 1). Biomechanical recordings were started remotely from the habitat. Prior to each EVA, astronauts prepared the experiment in the habitat following a controlled workflow. Four generic geoscientific operations common for geological sample-taking were performed at the beginning and end of the EVA by the test subject. The operations were performed at four different sites, each site approximately 40 to 60 m apart. A previously designed traverse plan shown in the head-up-display of the suit’s helmet defined the traverses for the astronauts. All four geoscientific operations as well as the ambulatory pathways were recorded by the motion capture- and EMG-systems. In a preliminary analysis of gait alterations, we investigated the pre- and post-EVA traverses to identify muscular fatigue accumulated over the 3 to 4 h-EVAs. The reprocessing of the motion capture recordings was performed ","author":[{"family":"Reimeir","given":"Benjamin"},{"family":"Wargel","given":"Anna"},{"family":"Riedl","given":"Franziska"},{"family":"Maach","given":"Sara"},{"family":"Weidner","given":"Robert"},{"family":"Grömer","given":"Gernot"},{"family":"Federolf","given":"Peter"}],"issued":{"date-parts":[[2024]]},"DOI":"10.36950/2024.4ciss018","URL":"https://doi.org/10.36950/2024.4ciss018","source":"openalex"},{"id":"oa:W4393312806","type":"article-journal","title":"The Application of Knowledge Engineering via the Use of a Biomimetic Digital Twin Ecosystem, Phenotype-Driven Variant Analysis, and Exome Sequencing to Understand the Molecular Mechanisms of Disease","abstract":"Applied artificial intelligence, particularly large language models, in biomedical research is accelerating, but effective discovery and validation requires a toolset without limitations or bias. On January 30, 2023, the National Academies of Sciences, Engineering, and Medicine (NAS) appointed an ad hoc committee to identify the needs and opportunities to advance the mathematical, statistical, and computational foundations of digital twins in applications across science, medicine, engineering, and society. On December 15, 2023, the NAS released a 164-page report, \"Foundational Research Gaps and Future Directions for Digital Twins.\" This report described the importance of using digital twins in biomedical research. The current study was designed to develop an innovative method that incorporated phenotype-ranking algorithms with knowledge engineering via a biomimetic digital twin ecosystem. This ecosystem applied real-world reasoning principles to nonnormalized, raw data to identify hidden or \"dark\" data. Clinical exome sequencing study on patients with endometriosis indicated four variants of unknown clinical significance potentially associated with endometriosis-related disorders in nearly all patients analyzed. One variant of unknown clinical significance was identified in all patient samples and could be a biomarker for diagnostics. To the best of our knowledge, this is the first study to incorporate the recommendations of the NAS to biomedical research. This method can be used to understand the mechanisms of any disease, for virtual clinical trials, and to identify effective new therapies.","author":[{"family":"Kearns","given":"WG"},{"family":"Stamoulis","given":"Georgios"},{"family":"Glick","given":"Joseph"},{"family":"Baisch","given":"Lawrence"},{"family":"Benner","given":"AT"},{"family":"Brough","given":"DE"},{"family":"Du","given":"Luke"},{"family":"Wilson","given":"Bradford"},{"family":"Kearns","given":"Laura"},{"family":"Ng","given":"Nicholas"},{"family":"Seshan","given":"Maya"},{"family":"Anchan","given":"Raymond"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.jmoldx.2024.03.004","URL":"https://doi.org/10.1016/j.jmoldx.2024.03.004","source":"openalex"},{"id":"oa:W4394990452","type":"article-journal","title":"Maximizing throughput in NOMA-enable industrial IoT networks using digital twin and reinforcement learning","abstract":"INTRODUCTION: Increased deployment of heterogeneous and complex Industrial Internet of Things (IIoT) applications such as predictive maintenance and asset tracking places a substantial strain on the limited computational and communication resources. To cater to the rigorous demands of these applications, it is imperative to devise an adaptive online resource allocation method to enhance the efficiency of the current network operations. Multiaccess edge computing (MEC) and digital twins (DTs) are promising solutions that facilitate the realization of edge intelligence and find applications in various industrial applications. Yet, little is known about the advantage the two technologies offer to IIoT networks. OBJECTIVE: This study presents a joint optimization of offloading and resource allocation approach where MEC-server DT is created at the edge, and nonorthogonal multiple access (NOMA) communication is considered between IIoT devices and the industrial gateways (IGWs) for spectral efficiency. Our proposed framework is tailored to reduce mean task completion latency and enhance overall IIoT network throughput. METHOD: To achieve our objective, we jointly optimize the computation resource allocation (RA), subchannel assignment (SA), and offloading decisions (OD). Given the inherent complexity of the problem, we further divide it into RA and SA/OD sub-problems. Employing Deep Reinforcement Learning (DRL), we have formulated a solution delineating the most efficient RA strategy and leveraged DT for optimal SA/OD strategies. RESULTS: Simulation results demonstrate the superior efficiency of our framework, realizing up to 92 % of the efficiency of the exhaustive search method while reducing computation and action decision time. CONCLUSION: In light of system dynamics considered for our work, the proposed framework perfomance showcase its robustness and potential application in real-world IIoT networks.","author":[{"family":"Jeremiah","given":"Sekione"},{"family":"Camacho","given":"David"},{"family":"Park","given":"Jong"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.jare.2024.04.021","URL":"https://doi.org/10.1016/j.jare.2024.04.021","source":"openalex"},{"id":"oa:W4404726869","type":"article-journal","title":"Research on Construction Digital Management System Based on Digital Twin","abstract":"In the context of transformation and upgrading of the construction industry, traditional project construction management is still a complex \"man-machine-environment\" system engineering. The emerging digital twin technology provides new methods and technical means to realize the digitalization of construction. In order to solve the problems of redundant information of traditional construction management elements and low management efficiency, a digital model of construction management for physical space and non-physical space in the whole construction process is constructed, and an intelligent management platform for data collection and transmission of all elements of construction management is established. A process-oriented digital construction management system is proposed to realize the digital control of the construction management process. The study shows that by establishing an integrated management platform and collecting various building information elements in the whole construction process, the organic integration of construction management and digital twins can be realized, and the construction process management capabilities and management efficiency can be improved.","author":[{"family":"Zhu","given":"Zhijie"},{"family":"Jiang","given":"Xiangyang"},{"family":"Ma","given":"Yi"},{"family":"Fu","given":"Hanghang"},{"family":"Wang","given":"Ran"}],"issued":{"date-parts":[[2024]]},"DOI":"10.70088/sh4xsb11","URL":"https://doi.org/10.70088/sh4xsb11","source":"openalex"},{"id":"oa:W4391885820","type":"article-journal","title":"All-organic transparent plant e-skin for noninvasive phenotyping","abstract":"Real-time in situ monitoring of plant physiology is essential for establishing a phenotyping platform for precision agriculture. A key enabler for this monitoring is a device that can be noninvasively attached to plants and transduce their physiological status into digital data. Here, we report an all-organic transparent plant e-skin by micropatterning poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) on polydimethylsiloxane (PDMS) substrate. This plant e-skin is optically and mechanically invisible to plants with no observable adverse effects to plant health. We demonstrate the capabilities of our plant e-skins as strain and temperature sensors, with the application to Brassica rapa leaves for collecting corresponding parameters under normal and abiotic stress conditions. Strains imposed on the leaf surface during growth as well as diurnal fluctuation of surface temperature were captured. We further present a digital-twin interface to visualize real-time plant surface environment, providing an intuitive and vivid platform for plant phenotyping.","author":[{"family":"Yang","given":"Yanqin"},{"family":"He","given":"Tianyiyi"},{"family":"Ravindran","given":"Pratibha"},{"family":"Wen","given":"Feng"},{"family":"Krishnamurthy","given":"Pannaga"},{"family":"Wang","given":"Luwei"},{"family":"Zhang","given":"Zixuan"},{"family":"Kumar","given":"Prakash"},{"family":"Chae","given":"Eunyoung"},{"family":"Lee","given":"Chengkuo"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1126/sciadv.adk7488","URL":"https://doi.org/10.1126/sciadv.adk7488","source":"openalex"},{"id":"oa:W4392763329","type":"article-journal","title":"Exploring the Intelligent Emergency Management Mode of Rural Natural Disasters in the Era of Digital Technology","abstract":"In recent years, rural areas of China have experienced frequent occurrences of various natural disasters. These calamities pose significant threats to the safety, property, and mental well-being of rural residents while also presenting substantial obstacles to the sustainable development of the rural economy. Currently, emergency management in China faces several challenges such as inadequate emergency institutions, insufficient security policies, weak disaster infrastructure, and difficulties in information sharing. In light of this situation, we propose an intelligent command mode based on modern digital technology that capitalizes on its advantages and integrates early warning systems with decision-making processes and rescue operations to establish a comprehensive emergency event processing system. This innovative approach opens up new avenues for exploring and researching effective modes of rural emergency management. The article elaborates on how the construction of a smart rural emergency management mode facilitates the digital integration of disaster elements while enhancing the efficiency of emergency response efforts and promoting sustainable development. The research methodology employed includes literature review methods along with field research techniques and analysis methods. Finally, this discussion evaluates both the benefits and challenges associated with implementing this mode within rural emergency management practices.","author":[{"family":"Yang","given":"Jimei"},{"family":"Hou","given":"Hanping"},{"family":"Hu","given":"Hanqing"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/su16062366","URL":"https://doi.org/10.3390/su16062366","source":"openalex"},{"id":"oa:W4402436275","type":"article-journal","title":"Evolution of aging mechanisms and performance degradation of lithium-ion battery from moderate to severe capacity loss scenarios","abstract":"• Combines fast-charging design with diagnostic methods for Li-ion battery aging. • Studies real-life aging mechanisms and develops a digital twin for EV batteries. • Identifies factors in performance decline and thresholds for severe degradation. • Analyzes electrode degradation with non-destructive methods and post-mortem analysis. The aging mechanisms of Nickel-Manganese-Cobalt-Oxide (NMC)/Graphite lithium-ion batteries are divided into stages from the beginning-of-life (BOL) to the end-of-life (EOL) of the battery. The corresponding changes in the battery performance across these stages have been analyzed, and a digital twin model is established to quantify the primary parameters that influence these aging mechanisms. Post-mortem analysis is applied to validate the results. This paper compares the aging mechanisms from BOL to EOL using two charging protocols: a multi-step fast charge protocol and a common constant-current fast charge protocol that applies the average current of multi-step currents. Notably, a transition from a linear to a non-linear degradation trend in capacity fade is observed, beginning from a 10% capacity reduction to EOL. From BOL to 10% degradation, the resistance of solid electrolyte interphase (SEI) grows steadily. The graphite anode’s crack depth exhibits a significant increase, accompanied by an evident collapse of cathode materials in all the test cases following a 10% degradation until EOL. This phenomenon can be attributed to one primary reason—the expansion of the corresponding simulated resistance of charge transfer (R ct ). Post-mortem analysis revealed the change in morphology, structure, and composition of various degradation conditions. This analysis proved that the primary driver of the linear aging stage is the SEI growth. Furthermore, it is evident that the transition to a non-linear aging degradation is dominated by electrode defects resulting from continuous mechanical stress during long-term aging.","author":[{"family":"Li","given":"Yaqi"},{"family":"Guo","given":"Wendi"},{"family":"Stroe","given":"Daniel‐ioan"},{"family":"Zhao","given":"Hongbo"},{"family":"Kristensen","given":"Peter"},{"family":"Jensen","given":"Lars"},{"family":"Pedersen","given":"Kjeld"},{"family":"Gurevich","given":"Leonid"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.cej.2024.155588","URL":"https://doi.org/10.1016/j.cej.2024.155588","source":"openalex"},{"id":"oa:W4403588552","type":"article-journal","title":"Conceptual Model of Graph-based Individual Tree and Its Utilization in Digital Twin and Metaverse of Urban Forest","abstract":"Abstract. 3D city models are an important cornerstone in the development of digital twin cities, allowing for various analyses and simulations. CityGML, as an open standard for 3D city models, emphasizes five main aspects: scale or level of detail (LoD), semantics, geometry, topology, and appearance. One of the important elements in CityGML 3D city models is representation of vegetation. Vegetation in CityGML, especially individual trees, is still limited in terms of detail and resolution, reducing its effectiveness for specific applications. This paper proposes a graph-based conceptual model for individual trees that conforms to the CityGML v2.0 specification. The model refers to the morphological structure of a tree consisting of roots, trunk, and crown (including branches, twigs, and leaves), and considers the five main aspects of CityGML. By enhancing semantic information and geometric details, the model aims to provide an information-rich and realistic representation of individual trees in a 3D city environment. The 3D tree model created based on this conceptual model may be applicable in the development of digital twin urban forests and virtual forest simulations that utilize immersive technologies such as the metaverse. This research opens up new opportunities in the development of solitary vegetation objects through CityGML ADE by including more detailed semantic and topological information.","author":[{"family":"Ambarwari","given":"Agus"},{"family":"Suwardhi","given":"Deni"},{"family":"Rani","given":"MR"},{"family":"Husni","given":"Emir"},{"family":"Junaidy","given":"Deny"},{"family":"Agirachman","given":"Fauzan"},{"family":"Murtiyoso","given":"Arnadi"},{"family":"Griess","given":"Verena"}],"issued":{"date-parts":[[2024]]},"DOI":"10.5194/isprs-archives-xlviii-4-2024-7-2024","URL":"https://doi.org/10.5194/isprs-archives-xlviii-4-2024-7-2024","source":"openalex"},{"id":"oa:W4396621084","type":"article-journal","title":"The digital lab manager: Automating research support","abstract":"Laboratory management automation is essential for achieving interoperability in the domain of experimental research and accelerating scientific discovery. The integration of resources and the sharing of knowledge across organisations enable scientific discoveries to be accelerated by increasing the productivity of laboratories, optimising funding efficiency, and addressing emerging global challenges. This paper presents a novel framework for digitalising and automating the administration of research laboratories through The World Avatar, an all-encompassing dynamic knowledge graph. This Digital Laboratory Framework serves as a flexible tool, enabling users to efficiently leverage data from diverse systems and formats without being confined to a specific software or protocol. Establishing dedicated ontologies and agents and combining them with technologies such as QR codes, RFID tags, and mobile apps, enabled us to develop modular applications that tackle some key challenges related to lab management. Here, we showcase an automated tracking and intervention system for explosive chemicals as well as an easy-to-use mobile application for asset management and information retrieval. Implementing these, we have achieved semantic linking of BIM and BMS data with laboratory inventory and chemical knowledge. Our approach can capture the crucial data points and reduce inventory processing time. All data provenance is recorded following the FAIR principles, ensuring its accessibility and interoperability.","author":[{"family":"Rihm","given":"Simon"},{"family":"Tan","given":"Yong"},{"family":"Ang","given":"Wilson"},{"family":"Hofmeister","given":"Markus"},{"family":"Deng","given":"Xinhong"},{"family":"Laksana","given":"Michael"},{"family":"Quek","given":"Hou"},{"family":"Bai","given":"Jiaru"},{"family":"Pascazio","given":"Laura"},{"family":"Siong","given":"Sim"},{"family":"Akroyd","given":"Jethro"},{"family":"Mosbach","given":"Sebastian"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.slast.2024.100135","URL":"https://doi.org/10.1016/j.slast.2024.100135","source":"openalex"},{"id":"oa:W4391132312","type":"article-journal","title":"A dynamic knowledge graph approach to distributed self-driving laboratories","abstract":"The ability to integrate resources and share knowledge across organisations empowers scientists to expedite the scientific discovery process. This is especially crucial in addressing emerging global challenges that require global solutions. In this work, we develop an architecture for distributed self-driving laboratories within The World Avatar project, which seeks to create an all-encompassing digital twin based on a dynamic knowledge graph. We employ ontologies to capture data and material flows in design-make-test-analyse cycles, utilising autonomous agents as executable knowledge components to carry out the experimentation workflow. Data provenance is recorded to ensure its findability, accessibility, interoperability, and reusability. We demonstrate the practical application of our framework by linking two robots in Cambridge and Singapore for a collaborative closed-loop optimisation for a pharmaceutically-relevant aldol condensation reaction in real-time. The knowledge graph autonomously evolves toward the scientist's research goals, with the two robots effectively generating a Pareto front for cost-yield optimisation in three days.","author":[{"family":"Bai","given":"Jiaru"},{"family":"Mosbach","given":"Sebastian"},{"family":"Taylor","given":"Connor"},{"family":"Karan","given":"Dogancan"},{"family":"Lee","given":"Kok"},{"family":"Rihm","given":"Simon"},{"family":"Akroyd","given":"Jethro"},{"family":"Lapkin","given":"Alexei"},{"family":"Kraft","given":"Markus"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1038/s41467-023-44599-9","URL":"https://doi.org/10.1038/s41467-023-44599-9","source":"openalex"},{"id":"doi:10.1080/21693277.2024.2387679","type":"article-journal","title":"From building information modeling to construction digital twin: a conceptual framework","abstract":"This article aims to investigate the transition from Building Information Modeling to Digital Twin (DT) technologies in building construction and facility management. The integration of BIM and DT has the potential to enhance decision-making, optimize performance, and improve sustainability throughout the building lifecycle. By conducting a review of the existing literature, this study identifies the current state-of-the-art, as well as key trends, challenges, and opportunities for research and industry 4.0 associated with the adoption and implementation of DT as an extension of BIM. In the Discussion section, issues and gaps for the transition from a static BIM model to a dynamic DT are presented, such as the lack of a framework and protocols for sensor connections. The conclusions will focus on the creation of a protocol for the correct transition of BIM models in the DT environment and the characterization of DT for the construction sector with real use cases.","author":[{"family":"Revolti","given":"Andrea"},{"family":"Gualtieri","given":"Luca"},{"family":"Pauwels","given":"Pieter"},{"family":"Dallasega","given":"Patrick"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1080/21693277.2024.2387679","URL":"https://doi.org/10.1080/21693277.2024.2387679","source":"openalex"},{"id":"doi:10.20944/preprints202407.2606.v1","type":"manuscript","title":"Digital Twins and Additive Manufacturing: Exploring the Integration of Digital Twin Technology with Additive Manufacturing to Enhance Design, Simulation, and Production Processes","abstract":"The convergence of digital twin technology with additive manufacturing (AM) represents a transformative advancement in the fields of design, simulation, and production. Digital twins&amp;mdash;virtual replicas of physical assets&amp;mdash;enable real-time monitoring, simulation, and optimization of manufacturing processes by mirroring their physical counterparts. When integrated with additive manufacturing, which allows for the creation of complex geometries and rapid prototyping, digital twins enhance the ability to design, test, and refine products with unprecedented precision and efficiency. This integration facilitates iterative design improvements, predictive maintenance, and real-time process adjustments, leading to more accurate simulations and optimized production workflows. By leveraging data from digital twins, manufacturers can anticipate issues, reduce material waste, and shorten development cycles. This abstract explores how the fusion of digital twin technology with AM not only refines traditional manufacturing paradigms but also paves the way for more innovative and adaptive manufacturing practices.","author":[{"family":"Egon","given":"Axel"},{"family":"Bell","given":"Chris"},{"family":"Shad","given":"Ralph"}],"issued":{"date-parts":[[2024]]},"DOI":"10.20944/preprints202407.2606.v1","URL":"https://doi.org/10.20944/preprints202407.2606.v1","source":"europepmc"},{"id":"doi:10.3897/arphapreprints.e125077","type":"manuscript","title":"Prototype Biodiversity Digital Twin: Grassland Biodiversity Dynamics","abstract":"European grassland management has often favored high production through frequent mowing and heavy fertilization over biodiversity conservation, which is typically supported by less intensive management. Besides management, climate change and extremes are increasingly affecting grassland productivity and biodiversity, requiring timely adaptation of management practices. Here, we describe the development of a prototype Digital Twin (pDT) of grassland biodiversity dynamics intended to support researchers, farmers or regulatory decision-makers in monitoring the current state of selected grassland sites and projecting their future state under various management and climate scenarios.","author":[{"family":"Taubert","given":"Franziska"},{"family":"Rossi","given":"Tuomas"},{"family":"Wohner","given":"Christoph"},{"family":"Venier","given":"Sarah"},{"family":"Martinovič","given":"Tomáš"},{"family":"Khan","given":"Taimur"},{"family":"Gordillo","given":"Julian"},{"family":"Banitz","given":"Thomas"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3897/arphapreprints.e125077","URL":"https://doi.org/10.3897/arphapreprints.e125077","source":"preprints"},{"id":"oa:W4404617052","type":"article-journal","title":"Embodied AI-Guided Interactive Digital Teachers for Education","abstract":"Traditional education is considered incapable of providing prompt feedback, facilitating proactive learning, and giving indiscriminate responses.This has been observed in both in-person classes and online courses, especially when students' questions fall outside the instructors' knowledge base or are considered trivial by instructors.Nowadays, the advent of large language models (LLMs) has transformed knowledge acquisition.The LLM-based chatbots enable fast learning through interactive question-answering, which serves as an effective supplement to traditional educational approaches and even shows potential for replacement.To utilize such advancements in education, we propose MAGI, a novel system providing Embodied AI-Guided Interactive digital teachers for education, which integrates LLM-based chatbot technology.To ensure MAGI generates answers without hallucination, we employ a novel retrieval-augmented generation (RAG) paradigm to organize and retrieve useful educational documents for the LLM.Moreover, we create animatable 3D avatars powered by text-to-speech and audioto-motion models to provide students with interactive conversation experiences.We highlight the possibility of MAGI to enhance education accessibility and improve the overall learning experience.","author":[{"family":"Zhao","given":"Zhuoran"},{"family":"Yin","given":"Zhizhuo"},{"family":"Sun","given":"Jia"},{"family":"Hui","given":"Pan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1145/3680533.3697070","URL":"https://doi.org/10.1145/3680533.3697070","source":"openalex"},{"id":"oa:W4403644078","type":"article-journal","title":"TRANSFORMING OFFSET PRINTING WITH DIGITAL TWINS AND AI: INSIGHTS FROM RESEARCH INITIATIVES","abstract":"The manufacturing industry has a long tradition in the European Union, being one of the key employers providing jobs for highly skilled and qualified staff. Despite this, the sector is currently facing challenges related to global competition and rising costs, leading to declining profit margins. Additionally, companies are required to meet new environmental initiatives, demanding an ambitious voluntary commitment effort from their side, which has been proven to be difficult to implement. At the same time, manufacturing companies generate vast amounts of unstructured data daily yet struggle to leverage this data for supply chain optimization. This problem is especially noticeable in situations when there are many semi-structured data sources, like the ones found in offset printing operations (images, sensor data, etc.), typically leading to the creation of data silos storage and inefficiencies. Thus, a systematic approach is needed to optimize the process of receiving, combining, and analyzing data, which can, in turn, promote the creation of innovative business models based on manufacturing data. Similarly, the usage of a digital twin in production offers several advantages, primarily enhancing productivity, quality and cost efficiency. This paper presents two use cases illustrating how Digital Twin technologies and the CyclOps platform can be applied to offset printing operations, digitalizing factory processes and enabling AI-driven models, towards achieving Zero-Defect Manufacturing (ZDM), fostering improved efficiency and innovation in the manufacturing process.","author":[{"family":"Trochoutsos","given":"Christos"},{"family":"Kalafatelis","given":"Alexandros"},{"family":"Trakadas","given":"Panagiotis"}],"issued":{"date-parts":[[2024]]},"DOI":"10.24867/grid-2024-p46","URL":"https://doi.org/10.24867/grid-2024-p46","source":"openalex"},{"id":"oa:W4405254051","type":"manuscript","title":"Towards Civic Digital Twins: Co-Design the Citizen-Centric Future of Bologna","abstract":"We introduce Civic Digital Twin (CDT), an evolution of Urban Digital Twins designed to support a citizen-centric transformative approach to urban planning and governance. CDT is being developed in the scope of the Bologna Digital Twin initiative, launched one year ago by the city of Bologna, to fulfill the city's political and strategic goal of adopting innovative digital tools to support decision-making and civic engagement. The CDT, in addition to its capability of sensing the city through spatial, temporal, and social data, must be able to model and simulate social dynamics in a city: the behavior, attitude, and preference of citizens and collectives and how they impact city life and transform transformation processes. Another distinctive feature of CDT is that it must be able to engage citizens (individuals, collectives, and organized civil society) and other civic stakeholders (utilities, economic actors, third sector) interested in co-designing the future of the city. In this paper, we discuss the motivations that led to the definition of the CDT, define its modeling aspects and key research challenges, and illustrate its intended use with two use cases in urban mobility and urban development.","author":[{"family":"Luca","given":"Massimiliano"},{"family":"Lepri","given":"Bruno"},{"family":"Gallotti","given":"Riccardo"},{"family":"Paolazzi","given":"Stefania"},{"family":"Bigi","given":"Mauro"},{"family":"Pistore","given":"Marco"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2412.06328","URL":"https://doi.org/10.48550/arxiv.2412.06328","source":"openalex"},{"id":"oa:W4403975553","type":"article-journal","title":"Patterns and trends in the use of RFID within the construction industry and Digital Twin architecture: a Latent Semantic Analysis","abstract":"RFID technology is becoming increasingly popular in various industries due to its simplicity, affordability, and adaptability. However, its integration into the construction industry, particularly within the Digital Twin framework, remains limited. This study reviews current research and case studies on RFID in construction, focusing on its potential combination with Digital Twins. It examines the integration of RFID with BIM, sensors and other techniques to monitor building conditions. Using Latent Semantic Analysis, the study identifies key trends and patterns in the literature, revealing a predominant focus on the standalone use of RFID for localisation and tracking, with limited integration into other technologies. The findings highlight persistent barriers to wider adoption and underscore the need for further research to overcome these challenges.","author":[{"family":"Osadcha","given":"Iryna"},{"family":"Jurelionis","given":"Andrius"},{"family":"Fokaides","given":"Paris"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1080/14786451.2024.2421281","URL":"https://doi.org/10.1080/14786451.2024.2421281","source":"openalex"},{"id":"oa:W4414957516","type":"article-journal","title":"The Role of Digital Twins in Optimizing Renewable Energy Utilization and Energy Efficiency in Manufacturing","abstract":"Digital twin (DT) technology is revolutionizing manufacturing by bridging the gap between physical and virtual environments, enabling real-time monitoring, simulation, and optimization of processes. This paper explores the pivotal role of DTs in enhancing renewable energy utilization and energy efficiency within manufacturing ecosystems. The study delves into how DTs facilitate renewable energy forecasting, resource scheduling, and integration into manufacturing operations. Through real-time energy flow analysis, DTs aid in identifying inefficiencies, optimizing production processes, and implementing waste heat recovery systems. Specific applications in automotive and electronics manufacturing underscore the transformative impact of DTs, showcasing reductions in energy consumption and operational costs while improving resilience against energy variability. Case studies highlight successful integrations of DTs with renewable energy systems, such as photovoltaic installations, which strategically align energy-intensive activities with peak energy availability. Moreover, this research examines the challenges associated with DT adoption, including high implementation costs, data integration complexities, and organizational resistance, alongside emerging solutions tailored for scalability, particularly for small and medium-sized enterprises (SMEs). Future directions emphasize the incorporation of blockchain and artificial intelligence to enhance energy transaction security, data-driven decision-making, and operational autonomy. The paper also advocates for the development of global standards and supportive policies to foster widespread DT adoption. By showcasing both the current applications and future potential of DTs, this review underscores their critical role in driving sustainability, operational efficiency, and energy resilience in the manufacturing sector.","author":[{"family":"Igbokwe","given":"Nkemakonam"},{"family":"Nwamekwe","given":"Charles"},{"family":"Ono","given":"Chukwuma"},{"family":"Nwabunwanne","given":"Emeka"},{"family":"Aguh","given":"Patrick"}],"issued":{"date-parts":[[2024]]},"DOI":"10.38035/sijdb.v1i4.262","URL":"https://doi.org/10.38035/sijdb.v1i4.262","source":"openalex"},{"id":"oa:W4403753923","type":"manuscript","title":"Digital Twin Vehicular Edge Computing Network: Task Offloading and Resource Allocation","abstract":"With the increasing demand for multiple applications on internet of vehicles. It requires vehicles to carry out multiple computing tasks in real time. However, due to the insufficient computing capability of vehicles themselves, offloading tasks to vehicular edge computing (VEC) servers and allocating computing resources to tasks becomes a challenge. In this paper, a multi task digital twin (DT) VEC network is established. By using DT to develop offloading strategies and resource allocation strategies for multiple tasks of each vehicle in a single slot, an optimization problem is constructed. To solve it, we propose a multi-agent reinforcement learning method on the task offloading and resource allocation. Numerous experiments demonstrate that our method is effective compared to other benchmark algorithms.","author":[{"family":"Xie","given":"Yu"},{"family":"Wu","given":"Qiong"},{"family":"Fan","given":"Pingyi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2407.11310","URL":"https://doi.org/10.48550/arxiv.2407.11310","source":"openalex"},{"id":"oa:W4405737584","type":"article-journal","title":"Digital Transformation in the EU: Bibliometric Analysis and Digital Economy Trends Highlights","abstract":"This study highlights the Digital Transformation issues in recent scientific topics, as well as the trends in the European Union’s Digital Economy dynamics. The aim is to identify key and promising research topics in the digital field and define priorities for adopting digital innovations in the EU in terms of bibliographical and statistical aspects. The study includes a bibliographic analysis using publication metrics statistics, word cloud diagrams, and network clustering. There is also a quantitative analysis of the leading Digital Economy trends in the EU using correlation and cluster analyses and visualizations of the selected economic and Digital Transformation metrics. The results identify critical keywords in digitalization publications related to other key research and multidisciplinary areas. A grouping is proposed of research paper topics and research issues related to Digital Transformation in the EU and worldwide based on the identified trends in recent research proposals. The study examines the correlation of some digital indices and trends in EU countries’ GDP dynamics, R&D investment, and digital inclusion. From the clustering based on the data of a single digital market that promotes e-commerce for individuals and businesses, groups of EU countries have been identified as having the potential to increase digital inclusion and convergence growth rate. The results provide a basis for future research on Digital Transformation and determine the need for further intensification of EU digitalization.","author":[{"family":"Zherlitsyn","given":"Dmytro"},{"family":"Kolarov","given":"Kostadin"},{"family":"Rekova","given":"Nataliia"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/digital5010001","URL":"https://doi.org/10.3390/digital5010001","source":"openalex"},{"id":"oa:W4393033795","type":"article-journal","title":"Resilient Operations in Space with Digital Twin Integration for Solar PV and Energy Storage","abstract":"Space missions would not be possible without an available, reliable, autonomous, and resilient power system. Space-based power systems are different than Earth’s grid in terms of generation sources, needs, structure, and controllability. This research paper introduces a groundbreaking approach employing digital twin technology to emulate and enhance the performance of a physical nanogrid plant representing such a space-based power system. The proposed system encompasses three DC converters, a DC source, and a modular battery storage unit feeding a variable load. Rigorous testing across diverse operating points establishes the digital twin’s high-fidelity real-time representation, with root mean square error (RMSE) values consistently below 5%. The principal innovation lies in leveraging this digital twin to fortify system resilience against unforeseen events, beyond the capabilities of existing controllers and autonomy levels. By simulating scenarios that the current system may not be primed for, the digital twin provides operators with the tools to proactively respond to disruptions. Importantly, the approach offers an invaluable tool for scenarios where physical access to components is limited. This research introduces a modular battery storage solution as a key augmentation, capable of seamlessly compensating for power shortages at the source end that might arise from the dust effect on the Lunar surface or unexpected faults in the system. The proposed holistic approach not only validates the fidelity of the digital twin but also underscores its potential to revolutionize system operation, safeguard against uncertainties, and expedite response strategies in the face of unexpected contingencies. The proposed approach also paves the way for future development.","author":[{"family":"Ebrahimi","given":"Shayan"},{"family":"Seyedi","given":"Mohammad"},{"family":"Ullah","given":"Sm"},{"family":"Ferdowsi","given":"Farzad"}],"issued":{"date-parts":[[2024]]},"DOI":"10.31224/3628","URL":"https://doi.org/10.31224/3628","source":"openalex"},{"id":"oa:W4402642848","type":"article-journal","title":"Research on Model Reduction of AUV Underwater Support Platform Based on Digital Twin","abstract":"Digital twin technology, as a data-driven and model-driven innovation means, plays a crucial role in the process of digital transformation and intelligent upgrading of the marine industry, helping the industry to move towards a new stage of more intelligent and efficient development. In order to solve the defects of the Autonomous Underwater Vehicle (AUV) underwater support platform structure deformation field, digital twin technology and model reduction technology are applied to an AUV underwater support platform, and a five-dimensional digital twin model of the AUV underwater support platform is studied, including five dimensions: physical world, digital world, twin data center, service application, and data connection. The digital twin of the subsea support platform is established by using the digital twin modeling technology. The POD method is used to calculate the deformation field matrix of the support structure of the subsea support platform under the 0–5 sea state, and the corresponding eigenvalues and eigenvectors are obtained. By intercepting the eigenvectors corresponding to the eigenvalues of the high energy proportion, the low-order equation is constructed, and the reduced-order model under each sea state can be quickly solved. The experimental results show that the model reduction technology can greatly shorten the model solving time, and the calculated results are highly consistent with the simulation results of the finite element full-order model, which can realize the rapid analysis of the deformation response of the subsea support platform structure, and provide a theoretical basis and technical support for the subsequent simulation, state evaluation, visual monitoring, and predictive maintenance.","author":[{"family":"Lu","given":"Daohua"},{"family":"Ning","given":"Yichen"},{"family":"Wang","given":"Jia"},{"family":"Du","given":"Kaijie"},{"family":"Song","given":"Cancan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/jmse12091673","URL":"https://doi.org/10.3390/jmse12091673","source":"openalex"},{"id":"oa:W4403817442","type":"article-journal","title":"Digital Twins of Supply Chains: A Systems Approach","abstract":"We tackle the problem of digitalisation of Supply Chains, focusing on collaboration and sharing of information. By generalising the notion of Digital Twins, we review, develop, and conceptualise the (emerging) notion of Digital Twins of Supply Chains (DTofSC). Whereas Digital Twins is an active research area with data available from numerous industry projects, its application to Supply Chains is just emerging as a cross-discipline stemming from decades of maturing the notion of Digital Supply Chains. Whereas Digital Twins has been used in Supply Chains, the notion of digitalisation of Supply Chains is only a nascent area, with imprecise definition beyond key metaphors (e.g., visibility, traceability); as we conceptualise, the overall vision is to create technical and organisational mechanisms enabling any Supply Chain to be monitored and controlled from, e.g., a dashboard screen. After a literature review on the intersections between Digital Supply Chains, Digital Twins, and digital technologies (e.g. Blockchain), we (1) propose a synthesis systems architecture of DTofSC, (2) identify a key requirement gap (that we term addressability), and (3) to ground our contributions and in the absence of real-world use-cases in practice, we apply our conceptualised systems architecture to battery recycling based on feedback from an industry-targeted workshop.","author":[{"family":"Jesus","given":"Vítor"},{"family":"Kalaitzi","given":"Dimitra"},{"family":"Batista","given":"Luciano"},{"family":"Lopez","given":"Nestor"}],"issued":{"date-parts":[[2024]]},"DOI":"10.36227/techrxiv.24073527.v4","URL":"https://doi.org/10.36227/techrxiv.24073527.v4","source":"openalex"},{"id":"oa:W4405265656","type":"article-journal","title":"An FsQCA and NCA Analysis on the Drivers and Comprehensive Impact Analysis of the Implementation of Digital Twins","abstract":"The adoption of digital technology is one of the key processes in the digital transformation of China's construction industry. As a representative digital technology in the digital transformation process of Construction 4.0, digital twin technology has attracted widespread attention in various fields, and its practical application is also growing rapidly. However, its implementation in the construction industry (CI) still faces major challenges. Although previous studies have made significant progress in understanding the drivers and barriers to the implementation of digital twins (DTs) in the CI, these studies have neglected to explore the comprehensive impact of various factors, and the configuration relationship between them remains unclear. This study uses a quantitative method to conduct a questionnaire survey to obtain 33 case sample data. Necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis (FsQCA) methods are used for antecedent configuration analysis. The results show that: (1) The successful deployment of DTs in the CI does not depend on any single determinant, but is the adaptive result of the synergistic effect of multiple antecedent variables; (2) Six critical factors affecting the implementation of DTs in China's CI are identified, which can be summarized into four different causal paths or configurations, which are conducive to the implementation of DTs in China's CI. This study further explores and clarifies the comprehensive impact of antecedent variables on the implementation of DTs in China's CI provides a reference for the practice of digital transformation in the CI.","author":[{"family":"Khoo","given":"Terh"},{"family":"Wang","given":"Jiao"},{"family":"Esa","given":"Muneera"},{"family":"Sun","given":"Jiachen"}],"issued":{"date-parts":[[2024]]},"DOI":"10.37934/araset.53.2.283298","URL":"https://doi.org/10.37934/araset.53.2.283298","source":"openalex"},{"id":"oa:W4402270849","type":"article-journal","title":"Enhancing Signature Verification Using Triplet Siamese Similarity Networks in Digital Documents","abstract":"In contexts requiring user authentication, such as financial, legal, and administrative systems, signature verification emerges as a pivotal biometric method. Specifically, handwritten signature verification stands out prominently for document authentication. Despite the effectiveness of triplet loss similarity networks in extracting and comparing signatures with forged samples, conventional deep learning models often inadequately capture individual writing styles, resulting in suboptimal performance. Addressing this limitation, our study employs a triplet loss Siamese similarity network for offline signature verification, irrespective of the author. Through experimentation on five publicly available signature datasets—4NSigComp2012, SigComp2011, 4NSigComp2010, and BHsig260—various distance measure techniques alongside the triplet Siamese Similarity Network (tSSN) were evaluated. Our findings underscore the superiority of the tSSN approach, particularly when coupled with the Manhattan distance measure, in achieving enhanced verification accuracy, thereby demonstrating its efficacy in scenarios characterized by close signature similarity.","author":[{"family":"Tehsin","given":"Sara"},{"family":"Hassan","given":"Ali"},{"family":"Riaz","given":"Farhan"},{"family":"Nasir","given":"Inzamam"},{"family":"Fitriyani","given":"Norma"},{"family":"Syafrudin","given":"Muhammad"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/math12172757","URL":"https://doi.org/10.3390/math12172757","source":"openalex"},{"id":"oa:W4402054075","type":"article-journal","title":"The Impact of Digital Literacy on Farmers’ Green Production Behavior: Mediating Effects Based on Ecological Cognition","abstract":"Farmers’ green production behavior is one of the main determinants of the sustainability of the agricultural economy. In this study, Ordered Logit, OLS, and 2SLS models were conducted to evaluate the impact of digital literacy on farmers’ green production behavior. On this basis, the Propensity Score Matching (PSM) method was conducted to deal with the endogeneity bias that may result from the sample self-selection problem. We also adopt the mediation effect model to test the mediating mechanism of ecological cognition between digital literacy and farmers’ green production behavior. The results showed that three different types of digital literacy significantly improved farmers’ green production behavior. We also found that farmers’ green production behavior improved by 19.87%, 15.92%, and 24.16% through digital learning, social, and transaction literacy. Meanwhile, the mediating effect showed that digital literacy improves farmers’ green production behavior by increasing ecological cognition. We demonstrate that three different types of digital literacy significantly improved farmers’ green production behavior. Therefore, policies to increase digital literacy among farmers should be further improved to promote farmers’ green production behavior.","author":[{"family":"Liu","given":"Xiao"},{"family":"Wang","given":"Zhenyu"},{"family":"Han","given":"Xiaoyan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/su16177507","URL":"https://doi.org/10.3390/su16177507","source":"openalex"},{"id":"oa:W4407758838","type":"manuscript","title":"Advancing Health Care With Digital Twins: Meta-Review of Applications and Implementation Challenges (Preprint)","abstract":"BACKGROUND Digital twins (DTs) are digital representations of real-world systems, enabling advanced simulations, predictive modeling, and real-time optimization in various fields, including health care. Despite growing interest, the integration of DTs in health care faces challenges such as fragmented applications, ethical concerns, and barriers to adoption. OBJECTIVE This study systematically reviews the existing literature on DT applications in health care with three objectives: (1) to map primary applications, (2) to identify key challenges and limitations, and (3) to highlight gaps that can guide future research. METHODS A meta-review was conducted in a systematic fashion, adhering to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, and included 25 literature reviews published between 2021 and 2024. The search encompassed 5 databases: PubMed, CINAHL, Web of Science, Embase, and PsycINFO. Thematic synthesis was used to categorize DT applications, stakeholders, and barriers to adoption. RESULTS A total of 3 primary DT applications in health care were identified: personalized medicine, operational efficiency, and medical research. While current applications, such as predictive diagnostics, patient-specific treatment simulations, and hospital resource optimization, remain in their early stages of development, they highlight the significant potential of DTs. Challenges include data quality, ethical issues, and socioeconomic barriers. This review also identified gaps in scalability, interoperability, and clinical validation. CONCLUSIONS DTs hold transformative potential in health care, providing individualized care, operational optimization, and accelerated research. However, their adoption is hindered by technical, ethical, and financial barriers. Addressing these issues requires interdisciplinary collaboration, standardized protocols, and inclusive implementation strategies to ensure equitable access and meaningful impact. CLINICALTRIAL","author":[{"family":"Ringeval","given":"Mickaël"},{"family":"Sosso","given":"Faustin"},{"family":"Cousineau","given":"Martin"},{"family":"Paré","given":"Guy"}],"issued":{"date-parts":[[2024]]},"DOI":"10.2196/preprints.69544","URL":"https://doi.org/10.2196/preprints.69544","source":"openalex"},{"id":"oa:W4405953830","type":"article-journal","title":"Development of a Digital Twin of the Harbour Waters and Surrounding Infrastructure Based on Spatial Data Acquired with Multimodal and Multi-Sensor Mapping Systems","abstract":"Digital twin is an attractive technology for the representation of objects due to its ability to produce precise measurements and their geovisualisation. Of special interest is the application and fusion of various remote sensing techniques for shallow river and inland water areas, commonly measured using conventional surveying or multimodal photogrammetry. The construction of spatial digital twins of river areas requires the use of multi-platform and multi-sensor measurements to obtain reliable data of the river environment. Due to the high dynamics of river changes, the cost of measurements and the difficult-to-access measurement area, the mapping should be large-scale and simultaneous. To address these challenges, the authors performed an experiment using three measurement platforms (boat, plane, UAV) and multiple sensors to acquire both cloud and image spatial data, which were integrated temporally and spatially. The integration methods improved the accuracy of the resulting digital model by approximately 20 percent.","author":[{"family":"Tomczak","given":"Arkadiusz"},{"family":"Stępień","given":"G"},{"family":"Kogut","given":"Tomasz"},{"family":"Jedynak","given":"Łukasz"},{"family":"Zaniewicz","given":"Grzegorz"},{"family":"Łącka","given":"Małgorzata"},{"family":"Bodus-Olkowska","given":"Izabela"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/app15010315","URL":"https://doi.org/10.3390/app15010315","source":"openalex"},{"id":"oa:W4392824294","type":"manuscript","title":"Plotinus: A Satellite Internet Digital Twin System","abstract":"The development of an integrated space-air-ground network (SAGIN) requires sophisticated satellite Internet emulation tools that can handle complex, dynamic topologies and offer in-depth analysis. Existing emulation platforms struggle with challenges like the need for detailed implementation across all network layers, real-time response, and scalability. This paper proposes a digital twin system based on microservices for satellite Internet emulation, namely Plotinus, which aims to solve these problems. Plotinus features a modular design, allowing for easy replacement of the physical layer to emulate different aerial vehicles and analyze channel interference. It also enables replacing path computation methods to simplify testing and deploying algorithms. In particular, Plotinus allows for real-time emulation with live network traffic, enhancing practical network models. The evaluation result shows Plotinus's effective emulation of dynamic satellite networks with real-world devices. Its adaptability for various communication models and algorithm testing highlights Plotinus's role as a vital tool for developing and analyzing SAGIN systems, offering a cross-layer, real-time and scalable digital twin system.","author":[{"family":"Gao","given":"Yue"},{"family":"Qiu","given":"Kun"},{"family":"Chen","given":"Zhe"},{"family":"Zhu","given":"Wenjun"},{"family":"Zhang","given":"Qi"},{"family":"Luo","given":"Handong"},{"family":"Lin","given":"Quanwei"},{"family":"Yang","given":"Ziheng"},{"family":"Liu","given":"Wenhao"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2403.08515","URL":"https://doi.org/10.48550/arxiv.2403.08515","source":"openalex"},{"id":"oa:W4404116642","type":"article-journal","title":"Revisiting the sustainable industrialization paradigm in Africa : Exploring the influence of digitalization","abstract":"Abstract This research contributes to the ongoing discourse surrounding the sustainable industrialization of African nations, a pivotal aspect emphasized by the United Nations within the Sustainable Development Goals. Drawing inspiration from the burgeoning digitalization trends across Africa, this study examines the role of digitalization in mediating the environmental repercussions of industrialization within the 45 African countries spanning the years 2000–2022. The assessment of environmental sustainability is gauged through ecological footprint and biocapacity. Employing the Environmental Kuznets Curve, and the Stochastic Impacts by Regression on Population, Affluence, and Technology framework, empirical analyses leverage the Generalized Method of Moments and the mediation analysis using structural equation modeling to unveil insightful findings. The research findings highlight the detrimental impact of industrialization on ecological health, evidenced by its correlation with an increase in ecological footprint and a decrease in biocapacity. Conversely, digitalization emerges as a positive influence on environmental well‐being. These findings remain consistent across diverse categorizations of digitalization, and ecological balance. Further examination of their interplay reveals a discernible favorable impact on environmental sustainability, with mediation analysis suggesting that digitalization mitigates approximately 4% and 6% of the overall impact of industrialization on ecological footprint and biocapacity, respectively. Additionally, our analysis lends credence to the Environmental Kuznets Curve hypothesis. As a result, it is imperative for governments to incentivize industries to adopt eco‐friendly practices and technologies in order to mitigate their ecological footprint. At the same time, policies that promote digitalization should be encouraged to further enhance environmental quality.","author":[{"family":"Ketchoua","given":"Germain"},{"family":"Avenyo","given":"Elvis"},{"family":"Tregenna","given":"Fiona"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/sd.3248","URL":"https://doi.org/10.1002/sd.3248","source":"openalex"},{"id":"oa:W4403138040","type":"article-journal","title":"APPLICATION OF MACHINE LEARNING DURING MAINTENANCE AND EXPLOITATION OF ELECTRIC VEHICLES","abstract":"In the era of increasing demand for sources of renewable and cleaner energy, electric vehicles offer possible solutions in order to maintain and improve the mobility of transport systems. In parallel, the application of machine learning for digital twin technology greatly contributes to the development and optimization of vehicles and systems, saving time and resources, as well as material resources. In terms of electric vehicle components, electric batteries represent the most expensive elements where machine learning can help to optimize characteristics during exploitation and to predict maintenance time and their lifetime. This article related to the possibilities of future research, which, by intensifying the digitalization and machine learning for digital twin technology, will affect the improvement of the application and disposal of components, but the complete system of electric vehicles, during the entire life cycle, including the recycling.","author":[{"family":"Marinković","given":"Dragan"},{"family":"Dezső","given":"Gergely"},{"family":"Milojević","given":"Saša"}],"issued":{"date-parts":[[2024]]},"DOI":"10.46793/adeletters.2024.3.3.5","URL":"https://doi.org/10.46793/adeletters.2024.3.3.5","source":"openalex"},{"id":"oa:W4405089767","type":"article-journal","title":"Digital Media, Cognition, and Brain Development in Adolescence","abstract":"Abstract Drawing from the literature on adolescent cognitive development, we describe how digital media usage has been linked to cognitive control processes, including the regulation of affective responses. In addition, we highlight how digital media use is perceived as particularly gratifying for adolescents’ needs. The use of digital media for prolonged periods or in a problematic way has been associated with structural and functional changes in the brain regions related to top-down control and reward systems. Studies are still at an early stage, mostly cross-sectional and based on self-reports. Measures used to assess digital media use mainly cover time and frequency of use, or problematic digital media use, with little or no focus on specific activities and content. Reported effects tend to be negligible-to-small; however, studies have rarely examined the impact of mental health conditions, which can in themselves be the underlying driver of cognitive changes and digital media use. We suggest future research should focus on establishing causality and directionality while highlighting positive uses in relation to cognitive development. More data examining different types of uses and contexts, including vulnerable and underrepresented populations and areas, are necessary before generalizing results.","author":[{"family":"Marciano","given":"Laura"},{"family":"Dubicka","given":"Bernadka"},{"family":"Magisweinberg","given":"Lucía"},{"family":"Morese","given":"Rosalba"},{"family":"Viswanath","given":"Kasisomayajula"},{"family":"Weber","given":"René"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/978-3-031-69362-5_4","URL":"https://doi.org/10.1007/978-3-031-69362-5_4","source":"openalex"},{"id":"oa:W4410464439","type":"article-journal","title":"AI-POWERED SENTIMENT ANALYSIS IN DIGITAL MARKETING: A REVIEW OF CUSTOMER FEEDBACK LOOPS IN IT SERVICES","abstract":"This systematic review critically examines the evolving role of AI-powered sentiment analysis in optimizing digital marketing strategies, with a specific focus on its application within customer feedback loops in IT service environments. In the era of data-driven marketing, the ability to decode consumer emotions from unstructured textual sources—such as social media, product reviews, helpdesk transcripts, and chat logs—has become increasingly valuable for enhancing personalization, engagement, and service responsiveness. Adhering to the PRISMA 2020 methodology, this review rigorously analyzed 87 peer-reviewed articles published between 2010 and 2024, encompassing diverse disciplines including artificial intelligence, natural language processing, marketing analytics, and service operations. The findings reveal that while traditional stochastic models like Support Vector Machines remain widely used due to their computational efficiency and interpretability, deep learning architectures—particularly CNNs, LSTMs, and GRUs—have demonstrated superior performance in managing complex, context-rich sentiment patterns. Moreover, transformer-based models such as BERT and RoBERTa have emerged as state-of-the-art tools, excelling in multilingual sentiment interpretation and capturing nuanced emotional dynamics in long-form or domain-specific feedback. The integration of these models into customer feedback loops has enabled real-time marketing decision-making, automated customer relationship management, and sentiment-driven content optimization. However, the review also identifies key gaps, notably the underutilization of internal enterprise data sources and the lack of comprehensive adoption of explainable AI practices. Increasing scrutiny under data protection regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) has further underscored the need for transparency, user consent, and ethical handling of inferred emotional data. Overall, this review contributes to the growing body of literature by offering a comprehensive evaluation of current technologies, identifying operational challenges, and highlighting the need for ethically aligned and context-aware sentiment analytics frameworks in digital marketing ecosystems, particularly within the IT services sector.","author":[{"family":"Paul","given":"Rajesh"},{"family":"Imam","given":"MF"},{"family":"Mou","given":"Anika"}],"issued":{"date-parts":[[2023]]},"DOI":"10.63125/61pqqq54","URL":"https://doi.org/10.63125/61pqqq54","source":"openalex"},{"id":"oa:W4392916872","type":"article-journal","title":"Digital Transformation of the Economy: Pecularities of Industrialized Regions","abstract":"The concept of Industry 4.0 based on a set of information technologies forms a new economic paradigm and changes production models. These processes allow the most developed territories to create advantages by integrating digital technologies into their own economy. The purpose of the study is to identify the dynamics and features of the digital transformation processes of the economic sphere in the industrially developed regions of the Russian Federation. In the course of the study, the methods of structural, dynamic analysis of the indicators of official statistics of Russian Federal State Statistics Service in the sphere of digital technologies were used. The study showed the leadership of the macro-regions of the European part of Russia in terms of the digitalization of business, a larger use of digital technologies in industrial regions. The advance of the use of basic information technologies is up to 7 %, in the use of global networks – about 4%, automated data exchange – more than 5 %. In industrial regions, special software is used somewhat more often, especially for product lifecycle management, but less often in the field of scientific research. Such advanced digital technologies as geoinformation systems, digital platforms, artificial intelligence, industrial robots are used more often in industrial regions, and the Internet of Things and digital twins are used less often than in the whole of the Russian Federation. There is still a lag in terms of digitalization costs and the share of digital technology specialists in the economy of industrial regions, explained by the specifics of their production structure. The results obtained demonstrate the specifics of industrial regions and can be used in the process of forming the policy of the Russian Federation in the field of digitalization.","author":[{"family":"Lavrikova","given":"Yu"},{"family":"Bodrunov","given":"Sergey"},{"family":"Russia","given":"Free"},{"family":"Акбердина","given":"ВВ"},{"family":"Korovin","given":"GB"}],"issued":{"date-parts":[[2024]]},"DOI":"10.37930/1990-9780-2024-1-79-5-24","URL":"https://doi.org/10.37930/1990-9780-2024-1-79-5-24","source":"openalex"},{"id":"oa:W4396915563","type":"article-journal","title":"Challenges and opportunities in European smart buildings energy management: A critical review","abstract":"The substantial stock of European buildings, accounting for more than 40% of energy consumption, has prompted member states to establish a renovation standard with stringent performance criteria. As advancing into the era of digital transformation, the concept of smart buildings emerges as a solution to create sustainable, efficient, resilient, active, and comfortable living and working spaces. This is achieved through intelligent resource use optimization, including the smart management of energy production, storage and distribution systems. Smart buildings operate by harnessing monitoring data and leveraging artificial intelligence algorithms and big data techniques. The integration of monitoring data with contextual information, such as building information modelling, physics, or simulation models, enhances the intelligent management of resources. Moreover, the incorporation of metrics like the smart readiness indicator promotes the adoption of smart buildings. This study delves into the significance of these techniques, expanding on existing research in the field of smart buildings. It integrates concepts of data enrichment, smartness, and user-centric approaches. Key findings provide insights into future opportunities within the sector, emphasizing the need for user awareness strategies, the development of new smart algorithms, and services that incorporate contextual data and the smart readiness indicator. The study also advocates for the widespread adoption of building digital twins.","author":[{"family":"Hernández","given":"José"},{"family":"Miguel","given":"Ignacio"},{"family":"Vélez","given":"Fredy"},{"family":"Vasallo","given":"Ali"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.rser.2024.114472","URL":"https://doi.org/10.1016/j.rser.2024.114472","source":"openalex"},{"id":"oa:W4388639388","type":"article-journal","title":"Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses","abstract":"The recent wave of the artificial intelligence (AI) revolution has aroused unprecedented interest in the intelligentialize of human society. As an essential component that bridges the physical world and digital signals, flexible sensors are evolving from a single sensing element to a smarter system, which is capable of highly efficient acquisition, analysis, and even perception of vast, multifaceted data. While challenging from a manual perspective, the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm (machine learning) and the framework (artificial synapses) level. This review presents the recent progress of the emerging AI-driven, intelligent flexible sensing systems. The basic concept of machine learning and artificial synapses are introduced. The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed, which significantly advances the applications such as flexible sensory systems, soft/humanoid robotics, and human activity monitoring. As two of the most profound innovations in the twenty-first century, the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.","author":[{"family":"Sun","given":"Tianming"},{"family":"Feng","given":"Bin"},{"family":"Huo","given":"Jinpeng"},{"family":"Xiao","given":"Yu"},{"family":"Wang","given":"Wengan"},{"family":"Wang","given":"Wengan"},{"family":"Peng","given":"Jin"},{"family":"Li","given":"Zehua"},{"family":"Du","given":"Chengjie"},{"family":"Wang","given":"Wenxian"},{"family":"Wang","given":"Wenxian"},{"family":"Zou","given":"Guisheng"},{"family":"Liu","given":"Lei"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1007/s40820-023-01235-x","URL":"https://doi.org/10.1007/s40820-023-01235-x","source":"openalex"},{"id":"oa:W4396561058","type":"article-journal","title":"[Digital twin hospitals: transforming the future of healthcare].","abstract":"Since the concept of digital twin technology has been put forward, after decades of rapid development and wide application, it has not only made great achievements in many fields, but also brought broader prospects for the development of the medical field. As an important trend in the medical industry, digital twin hospitals play multiple roles by connecting physical hospitals and virtual hospitals and benefit the \"patient-medical staff-hospital administrators\", highlighting the immeasurable promising application of digital twin technology in smart hospitals. This review takes digital twin technology as an entry point, briefly introduces the progress of its application in various fields, focuses on the characteristics of digital twin technology, practical application cases in hospitals and their limitations, and also looks forward to its future development prospects, aiming to provide certain useful insights and guidance for the future of digital twin hospitals, and also expecting it to play an important role in changing the future of healthcare to a certain extent.","author":[{"family":"Hu","given":"Huijuan"},{"family":"Wang","given":"Mingbang"},{"family":"Lei","given":"Qifang"},{"family":"Yang","given":"Kai"},{"family":"Sun","given":"Haiyan"},{"family":"Liu","given":"Xiaocen"},{"family":"Wu","given":"Song"}],"issued":{"date-parts":[[2024]]},"DOI":"10.7507/1001-5515.202310041","URL":"https://doi.org/10.7507/1001-5515.202310041","source":"openalex"},{"id":"oa:W4399728958","type":"article-journal","title":"Modeling a digital twin for the optimization of a self-supply energy system for residential use","abstract":"The climate situation and the energy crisis have prompted a number of policies and strategies that foster the adoption of renewable energy sources. To tackle the intermittency and fluctuations associated with the operation of these sustainable energy sources, renewable hydrogen appears as an appealing solution to decarbonize different economic sectors. In this sense, the design and implementation of a hybrid renewable energy-hydrogen system has led to the first electrically self-sufficient social housing in Spain, located in the town of Novales (Cantabria). On the other hand, the digitization of this type of self-sufficient systems would allow automatic adaptation to changing situations, increasing energy efficiency. In this context, we introduce the design and initial implementation phases of a digital twin architecture that, using machine learning and artificial intelligence techniques, facilitates the optimization of the performance of the physical system by interacting with its control components. This involves the use of telemetry solutions that allow the capture and storage of data from the physical system itself, as well as from the environment, such as instance meteorological data. We also discuss some initial results of the digital twin, which features models of the electrical components of the physical system, based on both their logical behavior and machine learning techniques.","author":[{"family":"Lope","given":"Laura"},{"family":"Maestre","given":"VM"},{"family":"Díez","given":"Luis"},{"family":"Ortiz","given":"Alfredo"},{"family":"Agüero","given":"Ramón"},{"family":"Ortíz","given":"Inmaculada"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/syscon61195.2024.10553483","URL":"https://doi.org/10.1109/syscon61195.2024.10553483","source":"openalex"},{"id":"oa:W4402156069","type":"article-journal","title":"Digital Twin Based Topology Fingerprinting for Detecting False Data Injection Attacks in Cyber-Physical Systems","abstract":"A Cyber-Physical System (CPS) employs intercon-nected sensing and actuation modules and applies distributed control strategies. With the major advances in communication technology, the CPS design methodology is getting broadly adopted, including in safety and mission-critical applications. The incorporation of digital twins within a CPS facilitates localized decision-making by the individual control modules within the system in a timely manner without risking stability and performance. However, cyberattacks could be detrimental when false data is injected to degrade the accuracy of the underlying digital twins so that a CPS module takes non-optimal or even risky action that causes application failure. This paper proposes a novel approach for detecting such an attack scenario through a combination of a predictive data model and a topology fingerprinting scheme. Specifically, we employ a recurrent neural network (RNN) to predict the next state (data) for the individual modules and use it to reason about the periodic updates provided by these modules. Then, we apply a data-driven fingerprinting scheme that characterizes the inter-module interaction to infer and classify anomalies based on the module-provided data. The validation results using a dataset of a smart power grid application demonstrate the effectiveness of our approach.","author":[{"family":"Bahrami","given":"Javad"},{"family":"Ebrahimabadi","given":"Mohammad"},{"family":"Younis","given":"Mohamed"},{"family":"Karimi","given":"Naghmeh"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/icc51166.2024.10622750","URL":"https://doi.org/10.1109/icc51166.2024.10622750","source":"openalex"},{"id":"oa:W4396581498","type":"article-journal","title":"Leveraging computer vision towards high-efficiency autonomous industrial facilities","abstract":"Abstract Manufacturers face two opposing challenges: the escalating demand for customized products and the pressure to reduce delivery lead times. To address these expectations, manufacturers must refine their processes, to achieve highly efficient and autonomous operations. Current manufacturing equipment deployed in several facilities, while reliable and produces quality products, often lacks the ability to utilize advancements from newer technologies. Since replacing legacy equipment may be financially infeasible for many manufacturers, implementing digital transformation practices and technologies can overcome the stated deficiencies and offer cost-affordable initiatives to improve operations, increase productivity, and reduce costs. This paper explores the implementation of computer vision, as a cutting-edge, cost-effective, open-source digital transformation technology in manufacturing facilities. As a rapidly advancing technology, computer vision has the potential to transform manufacturing operations in general, and quality control in particular. The study integrates a digital twin application at the endpoint of an assembly line, effectively performing the role of a quality officer by utilizing state-of-the-art computer vision algorithms to validate end-product assembly orientation. The proposed digital twin, featuring a novel object recognition approach, efficiently classifies objects, identifies and segments errors in assembly, and schedules the paths through the data pipeline to the corresponding robot for autonomous correction. This minimizes the need for human interaction and reduces disruptions to manufacturing operations.","author":[{"family":"Yousif","given":"Ibrahim"},{"family":"Burns","given":"Liam"},{"family":"Kalach","given":"Fadi"},{"family":"Harik","given":"Ramy"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/s10845-024-02396-1","URL":"https://doi.org/10.1007/s10845-024-02396-1","source":"openalex"},{"id":"oa:W4405810002","type":"article-journal","title":"Evaluating the Impact of Digital Transformation on Urban Innovation Resilience","abstract":"Enhancing urban innovation resilience is crucial for adapting to change and pursuing innovation-driven, high-quality development. The global trend of digital transformation has profound implications for urban innovation; however, the specific effects of digital transformation on urban innovation resilience remain insufficiently explored. This study utilizes panel data from 285 prefecture-level and above cities in China, spanning from 2007 to 2022. It treats the Broadband China Pilot (BCP) policy as a quasi-natural experiment of digital transformation and employs a time-varying Difference-in-Differences (DID) method to investigate the impact of digital transformation on urban innovation resilience. The results yield several important insights: (i) digital transformation enhances urban innovation resilience; (ii) the effect of digital transformation on urban innovation resilience is heterogeneous across regions and city sizes; (iii) digital transformation improves urban innovation resilience through the mediation effect of green total factor productivity (GTFP); (iv) urban industrial upgrading and urban innovation vitality play significant moderating roles in the relationship between digital transformation and urban innovation resilience. These findings contribute to a deeper theoretical understanding of the relationship between digital transformation and urban innovation resilience.","author":[{"family":"Yu","given":"Ruoxi"},{"family":"Chen","given":"Yaqian"},{"family":"Jin","given":"Yuhuan"},{"family":"Zhang","given":"Sheng"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/systems13010008","URL":"https://doi.org/10.3390/systems13010008","source":"openalex"},{"id":"oa:W4391835855","type":"manuscript","title":"A Digital Twin prototype for traffic sign recognition of a learning-enabled autonomous vehicle","abstract":"In this paper, we present a novel digital twin prototype for a learning-enabled self-driving vehicle. The primary objective of this digital twin is to perform traffic sign recognition and lane keeping. The digital twin architecture relies on co-simulation and uses the Functional Mock-up Interface and SystemC Transaction Level Modeling standards. The digital twin consists of four clients, i) a vehicle model that is designed in Amesim tool, ii) an environment model developed in Prescan, iii) a lane-keeping controller designed in Robot Operating System, and iv) a perception and speed control module developed in the formal modeling language of BIP (Behavior, Interaction, Priority). These clients interface with the digital twin platform, PAVE360-Veloce System Interconnect (PAVE360-VSI). PAVE360-VSI acts as the co-simulation orchestrator and is responsible for synchronization, interconnection, and data exchange through a server. The server establishes connections among the different clients and also ensures adherence to the Ethernet protocol. We conclude with illustrative digital twin simulations and recommendations for future work.","author":[{"family":"Abdelsalam","given":"Mohamed"},{"family":"Loai","given":"Ali"},{"family":"Saddek","given":"Bensalem"},{"family":"Weicheng","given":"He"},{"family":"Katsaros","given":"Panagiotis"},{"family":"Kekatos","given":"Nikolaos"},{"family":"Doron","given":"Peled"},{"family":"Anastasios","given":"Temperekidis"},{"family":"Wu","given":"Changshun"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2402.09097","URL":"https://doi.org/10.48550/arxiv.2402.09097","source":"openalex"},{"id":"oa:W4403814065","type":"article-journal","title":"Research on the Possibilities of Expanding the Photovoltaic Installation in the Microgrid Structure of Kielce University of Technology Using Digital Twin Technology","abstract":"Global challenges related to sustainable development are increasingly focusing on the use of digital twin technology as a universal tool for optimizing and monitoring renewable energy installations. This article discusses digital twin technology as a support for sustainable development based on the analysis of microgrid structures. Digital twins allow the creation of virtual models of physical systems. This capability facilitated the accurate replication of the microgrid model at Kielce University of Technology using ETAP (Electrical Transient Analyzer Program) software (version 22.5). The operational parameters of the microgrid structure were analyzed for the examined power range of the photovoltaic installation to determine the possibilities of expanding the existing installation. The impact of the photovoltaic installation’s power on the operational parameters of the microgrid structure was visualized, and final conclusions were formulated. Moreover, the integration of digital twin technology into renewable energy systems not only enhances operational efficiency but also plays a pivotal role in advancing sustainability objectives. Through real-time monitoring and predictive maintenance, digital twin technology facilitates the optimization of energy production and distribution, thereby reducing waste and contributing to the overall sustainability of energy systems. This technology enables the simulation of various scenarios, such as fluctuations in energy demand or the integration of new renewable sources, which can inform more sustainable decision-making processes. In the context of microgrids, digital twin technology ensures that energy production is closely aligned with consumption patterns, minimizing energy losses and enhancing grid resilience. Furthermore, digital twin technology supports the sustainable expansion of renewable installations by providing detailed insights into potential environmental impacts and the long-term sustainability of various energy configurations. As the demand for clean energy continues to grow, digital twin technology will be indispensable in achieving a balance between energy needs and environmental stewardship, ensuring that the expansion of renewable energy sources contributes positively to global sustainability objectives.","author":[{"family":"Pawelec","given":"Artur"},{"family":"Pawlak","given":"Agnieszka"},{"family":"Pyk","given":"Aleksandra"},{"family":"Kossakowski","given":"P"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/su16219366","URL":"https://doi.org/10.3390/su16219366","source":"openalex"},{"id":"oa:W4401097639","type":"article-journal","title":"Greening AI? The new principle of sustainable digital products and services in the EU","abstract":"The EU legislature has so far focused on the data-privacy and consumer-protection aspects of AI technologies. At the same time, AI is seen as a key driver of the green strategies of the EU. Yet, the EU regulatory and policy framework tends to neglect the environmental implications of AI. The massive employment of AI technologies results in a significant increase in energy consumption and affects the exploitation of rare natural resources dramatically. The Declaration on Digital Rights and Principles for the Digital Decade, the final chapter of which is dedicated to digital sustainability, is a first step in the attempt to plug this gap. The present article assesses the nature of the principles that have been proposed and traces their conceptual genealogy within the EU regulatory and policy framework. It identifies the emergence of a new principle of sustainable digital products and services, which is made explicit by the Declaration through a process of normative retrofitting.The article questions the ambitions behind this principle by reference to the oxymoron of the twin transitions, which pervades the current economic model of the EU and its sustainability targets, and to the emerging idea of digital sobriety.","author":[{"family":"Victorio","given":"Alba"},{"family":"Celeste","given":"Edoardo"},{"family":"Quintavalla","given":"Alberto"}],"issued":{"date-parts":[[2024]]},"DOI":"10.54648/cola2024067","URL":"https://doi.org/10.54648/cola2024067","source":"openalex"},{"id":"oa:W4404638889","type":"article-journal","title":"Digital technology in occupational health of manufacturing industries: a systematic literature review","abstract":"In this study, we fill the gap of limited effort on systematic literature review into the field of digital technology for occupational health of manufacturing industries. Upon reviewing 53 publications selected by combined bibliometric and classical review methods, we present an integrated overview of the major research areas and hot topics and critically identify the prevalent digital technologies and application modes, the enablers and barriers to implementation, as well as the research agenda in the field of digital technologies in occupational health. The results show that, with the increasing popularity and penetration of digital items like wearable devices and sensors, human–robot collaboration, deep learning analytics, the identified enablers to digital technology implementation are: intelligent manufacturing, competitive condition, data-driven decision-making tool, considerations of welfare and health; and the barriers are: technological gap, privacy and data security, culture and acceptance, and cost consideration. Additionally, propositions on three aspects and six perspectives are recommended for future research in this field. Overall, this study provides insights through systematic analysis and synthesis, and offers the means to achieve Sustainable Development Goals (SDGs) by exploring efficient digital technologies to protect labor rights and improve occupational health in the manufacturing industries.","author":[{"family":"Jiang","given":"Luping"},{"family":"Zhang","given":"Jingdong"},{"family":"Wong","given":"Yiik"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/s42452-024-06349-4","URL":"https://doi.org/10.1007/s42452-024-06349-4","source":"openalex"},{"id":"oa:W4402480022","type":"article-journal","title":"Digital and Virtual Technologies for Work-Related Biomechanical Risk Assessment: A Scoping Review","abstract":"The field of ergonomics has been significantly shaped by the advent of evolving technologies linked to new industrial paradigms, often referred to as Industry 4.0 (I4.0) and, more recently, Industry 5.0 (I5.0). Consequently, several studies have reviewed the integration of advanced technologies for improved ergonomics in different industry sectors. However, studies often evaluate specific technologies, such as extended reality (XR), wearables, artificial intelligence (AI), and collaborative robot (cobot), and their advantages and problems. In this sense, there is a lack of research exploring the state of the art of I4.0 and I5.0 virtual and digital technologies in evaluating work-related biomechanical risks. Addressing this research gap, this study presents a comprehensive review of 24 commercial tools and 10 academic studies focusing on work-related biomechanical risk assessment using digital and virtual technologies. The analysis reveals that AI and digital human modelling (DHM) are the most commonly utilised technologies in commercial tools, followed by motion capture (MoCap) and virtual reality (VR). Discrepancies were found between commercial tools and academic studies. However, the study acknowledges limitations, including potential biases in sample selection and search methodology. Future research directions include enhancing transparency in commercial tool validation processes, examining the broader impact of emerging technologies on ergonomics, and considering human-centred design principles in technology integration. These findings contribute to a deeper understanding of the evolving landscape of biomechanical risk assessment.","author":[{"family":"Filho","given":"Paulo"},{"family":"Colim","given":"Ana"},{"family":"Jesus","given":"Cristiano"},{"family":"Lopes","given":"Sérgio"},{"family":"Carneiro"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/safety10030079","URL":"https://doi.org/10.3390/safety10030079","source":"openalex"},{"id":"oa:W4391709947","type":"manuscript","title":"Surrogate Modeling and Control of Medical Digital Twins","abstract":"The vision of personalized medicine is to identify interventions that maintain or restore a person's health based on their individual biology. Medical digital twins, computational models that integrate a wide range of health-related data about a person and can be dynamically updated, are a key technology that can help guide medical decisions. Such medical digital twin models can be high-dimensional, multi-scale, and stochastic. To be practical for healthcare applications, they often need to be simplified into low-dimensional surrogate models that can be used for the optimal design of interventions. This paper introduces surrogate modeling algorithms for the purpose of optimal control applications. As a use case, we focus on agent-based models (ABMs), a common model type in biomedicine for which there are no readily available optimal control algorithms. By deriving surrogate models that are based on systems of ordinary differential equations, we show how optimal control methods can be employed to compute effective interventions, which can then be lifted back to a given ABM. The relevance of the methods introduced here extends beyond medical digital twins to other complex dynamical systems.","author":[{"family":"Fonseca","given":"Luís"},{"family":"Böttcher","given":"Lucas"},{"family":"Mehrad","given":"Borna"},{"family":"Laubenbacher","given":"Reinhard"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2402.05750","URL":"https://doi.org/10.48550/arxiv.2402.05750","source":"openalex"},{"id":"oa:W4402504604","type":"article-journal","title":"Advancing forest biodiversity conservation with the EL-BIOS digital twin: an integration of LiDAR and multispectral earth observation data","abstract":"The growing threat to biodiversity and ecosystem degradation necessitates innovative methods for monitoring and managing forested areas. This paper introduces the LIFE EL-BIOS project, a pioneering initiative to develop a Digital Twin for forest biodiversity analysis using terrestrial and airborne Light Detection and Ranging (LiDAR) technologies. The project utilizes advanced equipment, including the DJI Matrice 300 UAV with airborne LiDAR, DJI Mavic 3E, Quantum Systems Trinity F90+ with RGB and multispectral sensors, a GeoSLAM ZEB REVO terrestrial SLAM device, and a Leica BLK360 terrestrial laser scanner. Research spans over 40 forest plots, each 2000 square meters, in Greece's Kotychi-Strofilia Wetlands and Northern Pindos National Parks. The methodology integrates and georeferences point clouds from aerial and terrestrial sources to create unified point clouds for each area. Advanced software tools, such as 3DFIN and 3DFOREST, are then used to extract precise biodiversity-relevant parameters. This innovative data extraction method is compared with traditional in-situ measurements to evaluate the potential and limitations of the Digital Twin approach. A preliminary assessment focused on the time- and cost-effectiveness, accuracy, and robustness of this multiscale Earth Observation (EO) based mapping framework. Initial results suggest that the combined use of terrestrial and airborne LiDAR, multispectral data, and advanced analysis pipelines enhances the accuracy and speed of biodiversity measurements. Moreover, it allows for the extraction of additional information critical for developing biodiversity indicators. This study highlights the potential of multiscale and multisource EO data in creating digital twins of ecologically sensitive areas, offering a revolutionary approach to environmental conservation.","author":[{"family":"Karolos","given":"Ionas"},{"family":"Bellos","given":"Konstantinos"},{"family":"Alexandridisale","given":"Vassileios"},{"family":"Chrysafis","given":"Irene"},{"family":"Georgiadis","given":"Harris"},{"family":"Pikridas","given":"Christos"},{"family":"Tsioukas","given":"Vasillios"},{"family":"Πατιάς","given":"Πέτρος"},{"family":"Mallinis","given":"Giorgos"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1117/12.3037300","URL":"https://doi.org/10.1117/12.3037300","source":"openalex"},{"id":"oa:W4403147433","type":"article-journal","title":"Exploiting the Efficient Data Modeling in Network Digital Twin to Empower Edge-Cloud Continuum","abstract":"Specifications for Network Digital Twin (NDT) from Standardization Development Organizations (SDOs), such as the Internet Engineering Task Force (IETF), and academic contributions focus primarily on benefiting network operators. However, they often overlook the needs of stakeholders in the Edge-Cloud Continuum (ECC), such as Service Providers, customers, and Platform or Infrastructure Providers. In ECC, resource heterogeneity, agile software component integration, and quality of service requirements are challenges. To address these challenges, continuous and granular monitoring of software and physical resources is required. In this paper, we present the design and ongoing implementation of a data model. It captures and characterizes the physical and software properties, i.e., Key Performance Indicators (KPIs), of Kubernetes-managed components in the ECC. Collected data is structured in NGSI-LD-compliant format and managed through interoperable context brokers for authenticating the requests of various stakeholder applications. We also demonstrate sample data curation from a lab-configured platform, its integration into the context broker, and how it responds to the queries concerning a particular component information, thereby representing a partial implementation of proposed data model to render the views for particular stakeholders.","author":[{"family":"Raza","given":"Syed"},{"family":"Minerva","given":"Roberto"},{"family":"Crespi","given":"Noël"},{"family":"Alvi","given":"Maira"},{"family":"Herath","given":"Manoj"},{"family":"Dutta","given":"Hrishikesh"}],"issued":{"date-parts":[[2024]]},"DOI":"10.23919/cnsm62983.2024.10814387","URL":"https://doi.org/10.23919/cnsm62983.2024.10814387","source":"openalex"},{"id":"oa:W4391881102","type":"article-journal","title":"Environmental financing: does digital economy matter?","abstract":"Sustainable development and ecological restoration are a common goal pursued by countries around the world to mitigate the collision between economic growth and the environment. Digital economy has been rather instrumental in settling this type of conflict. The study is intended to identify the relationship between digital financing and environmental financing by assessing the specificities of their temporal and industry-specific dynamics, as well as to determine the side effects that the digital economy has in terms of current environmental investments and costs. The special attention is paid to the effect of the digital economy on both total environmental financing and its components, namely, environmental investment and current environmental protection costs. The authors come up with two indicators to evaluate the impact of the digital economy, these are digital financing (direct impact) and digital capital (indirect impact). To calculate these indicators, the authors’ own method is developed. The impact of the digital economy on environmental financing was tested using the least squares method with clustering of annual standard deviation and individual fixed effects. The research data were retrieved from the Federal State Statistics Service (Rosstat) of the Russian Federation for 2012–2022. Our findings show that digital financing exerts a significant positive effect on environmental financing, which indicates that two dynamic processes in the economy—digital transformation and introduction of advanced environmental digital technologies—are synchronized. The authors prove that digital investments stimulate a comparable increase in environmental investment due to the effects created by digital technologies penetrating into environmental protection technologies. We demonstrate that the level of digitalization of the population, companies and the state assessed through the digital capital index has a positive effect on environmental financing. The results of the study are of use in the sphere of public policy.","author":[{"family":"Акбердина","given":"ВВ"},{"family":"Lavrikova","given":"Yu"},{"family":"Vlasov","given":"Maxim"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3389/fenvs.2023.1268286","URL":"https://doi.org/10.3389/fenvs.2023.1268286","source":"openalex"},{"id":"oa:W4403785587","type":"manuscript","title":"Towards Robust Surgical Automation via Digital Twin Representations from Foundation Models","abstract":"Large language model-based (LLM) agents are emerging as a powerful enabler of robust embodied intelligence due to their capability of planning complex action sequences. Sound planning ability is necessary for robust automation in many task domains, but especially in surgical automation. These agents rely on a highly detailed natural language representation of the scene. Thus, to leverage the emergent capabilities of LLM agents for surgical task planning, developing similarly powerful and robust perception algorithms is necessary to derive a detailed scene representation of the environment from visual input. Previous research has focused primarily on enabling LLM-based task planning while adopting simple yet severely limited perception solutions to meet the needs for bench-top experiments, but lacks the critical flexibility to scale to less constrained settings. In this work, we propose an alternate perception approach -- a digital twin (DT)-based machine perception approach that capitalizes on the convincing performance and out-of-the-box generalization of recent vision foundation models. Integrating our DT representation and LLM agent for planning with the dVRK platform, we develop an embodied intelligence system and evaluate its robustness in performing peg transfer and gauze retrieval tasks. Our approach shows strong task performance and generalizability to varied environmental settings. Despite a convincing performance, this work is merely a first step towards the integration of DT representations. Future studies are necessary for the realization of a comprehensive DT framework to improve the interpretability and generalizability of embodied intelligence in surgery.","author":[{"family":"Ding","given":"Hao"},{"family":"Seenivasan","given":"Lalithkumar"},{"family":"Shu","given":"Hongchao"},{"family":"Byrd","given":"Grayson"},{"family":"Zhang","given":"Han"},{"family":"Xiao","given":"Pufu"},{"family":"Barragan","given":"Juan"},{"family":"Taylor","given":"RH"},{"family":"Kazanzides","given":"Peter"},{"family":"Unberath","given":"Mathias"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2409.13107","URL":"https://doi.org/10.48550/arxiv.2409.13107","source":"openalex"},{"id":"oa:W4399252449","type":"manuscript","title":"Biodiversity data standards for the organization and dissemination of complex research projects and digital twins: a guide","abstract":"Biodiversity data are substantially increasing, spurred by technological advances and community (citizen) science initiatives. To integrate data is, likewise, becoming more commonplace. Open science promotes open sharing and data usage. Data standardization is an instrument for the organization and integration of biodiversity data, which is required for complex research projects and digital twins. However, just like with an actual instrument, there is a learning curve to understanding the data standards field. Here we provide a guide, for data providers and data users, on the logistics of compiling and utilizing biodiversity data. We emphasize data standards, because they are integral to data integration. Three primary avenues for compiling biodiversity data are compared, explaining the importance of research infrastructures for coordinated long-term data aggregation. We exemplify the Biodiversity Digital Twin (BioDT) as a case study. Four approaches to data standardization are presented in terms of the balance between practical constraints and the advancement of the data standards field. We aim for this paper to guide and raise awareness of the existing issues related to data standardization, and especially how data standards are key to data interoperability, i.e., machine accessibility. The future is promising for computational biodiversity advancements, such as with the BioDT project, but it rests upon the shoulders of machine actionability and readability, and that requires data standards for computational communication.","author":[{"family":"Andrew","given":"Carrie"},{"family":"Islam","given":"Sharif"},{"family":"Weiland","given":"Claus"},{"family":"Endresen","given":"Dag"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2405.19857","URL":"https://doi.org/10.48550/arxiv.2405.19857","source":"openalex"},{"id":"oa:W4403735583","type":"article-journal","title":"Advanced Digital Technologies in the Post-Disaster Reconstruction Process—A Review Leveraging Small Language Models","abstract":"Post-disaster reconstruction of the built environment represents a key global challenge that looks set to remain for the foreseeable future, but it also offers significant implications for the future sustainability and resilience of the built environment. The purpose of this research is to explore the current applications of advanced digital/Industry 4.0 technologies in the post-disaster reconstruction (PDR) process with a view to improving its effectiveness and efficiency and the sustainability and resilience of the built environment. The extant research literature from the Scopus database on built environment reconstruction is identified and described. In a novel literature review approach, small language models are used for the classification and filtering of technology-related articles. A qualitative content analysis is then carried out to understand the extent to which Industry 4.0 technologies are applied in current reconstruction practice, mapping their applications to specific phases of the PDR process and identifying dominant technologies and key trends in technology deployment. The study reveals a rapidly evolving landscape of technological innovation with transformative potential in enhancing the efficiency, effectiveness, and sustainability of rebuilding efforts, with dominant technologies including GIS, remote sensing, AI, and BIM. Key trends include increasing automation and data-driven decision-making, integration of multiple Industry 4.0/digital technologies, and a growing emphasis on incorporating community needs and local knowledge into reconstruction plans. The study highlights the need for future research to address key challenges, such as developing interoperable platforms, addressing the ethical implications of using AI and big data, and exploring the contribution of Industry 4.0/digital technologies to sustainable reconstruction practices.","author":[{"family":"Rawat","given":"Ankit"},{"family":"Witt","given":"Emlyn"},{"family":"Roumyeh","given":"Mohamad"},{"family":"Lill","given":"Irene"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/buildings14113367","URL":"https://doi.org/10.3390/buildings14113367","source":"openalex"},{"id":"oa:W4401507011","type":"article-journal","title":"Artificial Intelligence-Based Cybersecurity for the Metaverse: Research Challenges and Opportunities","abstract":"The metaverse, known as the next-generation 3D Internet, represents virtual environments that mirror the physical world. It is supported by innovative technologies such as digital twins and extended reality (XR), which elevate user experiences across various fields. However, the metaverse also introduces significant cybersecurity and privacy challenges that remain underexplored. Due to its complex multi-tech infrastructure, the metaverse requires sophisticated, automated, and intelligent cybersecurity measures to mitigate emerging threats effectively. Therefore, this paper is the first to explore Artificial Intelligence (AI)-driven cybersecurity techniques for the metaverse, examining academic and industrial perspectives. First, we provide an overview of the metaverse, presenting a detailed system model, diverse use cases, and insights into its current industrial status. We then present attack models and cybersecurity threats derived from the unique characteristics and technologies of the metaverse. Next, we review AI-driven cybersecurity solutions based on three critical aspects: User authentication, intrusion detection systems (IDS), and the security of digital assets, specifically for Blockchain and Non-fungible Tokens (NFTs). Finally, we highlight challenges and suggest future research opportunities to enhance metaverse security, privacy, and digital asset transactions.","author":[{"family":"Awadallah","given":"Abeer"},{"family":"Eledlebi","given":"Khouloud"},{"family":"Zemerly","given":"Mohamed"},{"family":"Puthal","given":"Deepak"},{"family":"Damiani","given":"Ernesto"},{"family":"Taha","given":"Kamal"},{"family":"Kim","given":"Tae‐yeon"},{"family":"Yoo","given":"Paul"},{"family":"Choo","given":"Kim‐kwang"},{"family":"Yim","given":"Man‐sung"},{"family":"Yeun","given":"Chan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/comst.2024.3442475","URL":"https://doi.org/10.1109/comst.2024.3442475","source":"openalex"},{"id":"oa:W4404646241","type":"article-journal","title":"Digital twin framework and platform for zero‐emission heavy haul locomotive design and development","abstract":"Abstract In recent years, significant development activity has been seen in battery electric and hydrogen locomotives. To fully understand the potential benefits of these zero‐emission technologies and their application in locomotive design, a design study utilising a digital twin framework can be employed. While current research on the use of digital twins for battery and hydrogen‐powered rail vehicles is limited, recent studies conducted at the Centre for Railway Engineering at CQUniversity indicate potential challenges with implementing standard 6‐axle locomotives for zero‐emission designs considering heavy haul operational needs and scenarios. These challenges are related to limitations in energy storage capacity and optimisation of train operation scenarios. By considering an 8‐axle locomotive design concept and employing a digital twin framework in the design process, a more comprehensive assessment of conceptual development, design and requirements can be achieved. This will ensure the locomotive design meets standards, guidelines, and codes of practice, ultimately contributing to achieving net‐zero emission goals in locomotive traction.","author":[{"family":"Spiryagin","given":"Maksym"},{"family":"Bernal","given":"Esteban"},{"family":"Ahmad","given":"Sanjar"},{"family":"Wu","given":"Qing"},{"family":"Cole","given":"Colin"},{"family":"Mcsweeney","given":"Tim"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1049/dgt2.12017","URL":"https://doi.org/10.1049/dgt2.12017","source":"openalex"},{"id":"oa:W4401113504","type":"article-journal","title":"Internet of robotic things with a local LoRa network for teleoperation of an agricultural mobile robot using a digital shadow","abstract":"Abstract In unstructured agricultural fields where autonomous navigation is challenging and demands additional safety, the operator’s experience and knowledge are essential for supervising operations and making decisions beyond the robot’s autonomous capabilities. Local networks with long-range wireless communication combined with digital twin concepts are promising solutions that can be used for robot teleoperation. The purpose of this study was to demonstrate the feasibility of supervising a mobile robot inside berry orchards using a digital shadow from a long-range distance (between 300 and 3000 m), with the primary objective of assisting the robot in navigating in complex situations such as row-end turning. This involved creating a virtual representation of the robot that mirrors its state and actions, allowing the remote operator to monitor and guide the robot effectively. The system comprised a GPS-based navigation controller with collision avoidance sensors, two sets of LoRa transmitters and repeaters, a simulation environment with a digital shadow of the robot, and a graphical user interface for the remote operator. Information about the digital shadow’s state, including location, orientation, and distances to obstacles, was received as a message by the LoRa gateway and was used to update the path for the actual robot that interfaced with the Robot Operating System (ROS). The main research hypothesis aimed to test the quality of the LoRa communication link between the robot and the operator, as well as the robustness of the robot’s control system, with an emphasis on the architecture, communication link, and situation awareness creation. Preliminary results showed that depending on the environment, the average packet loss was 12% at distances of approximately 2300 m. Our results highlight some of the core technical challenges that need to be addressed for an effective teleoperation system, including latency, stability, and the limited range of wireless communication. Future works involves evaluating the performance and reliability of the proposed method under different field conditions and scenarios, as well as considering the use of the 5G network for a significant improvement in data transmission speed, navigation efficiency, and visual feedback. Upon successful implementation, this study has the potential to enhance the efficiency and safety of robot navigation, providing a practical solution for remote supervision in challenging environments.","author":[{"family":"Shamshiri","given":"Redmond"},{"family":"Navas","given":"Eduardo"},{"family":"Dworak","given":"Volker"},{"family":"Schütte","given":"Tjark"},{"family":"Weltzien","given":"Cornelia"},{"family":"Cheein","given":"Fernando"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/s42452-024-06106-7","URL":"https://doi.org/10.1007/s42452-024-06106-7","source":"openalex"},{"id":"doi:10.1115/msec2024-125094","type":"article-journal","title":"Advancing Digital Twin Technology in Manufacturing: A Comprehensive Study on Data Capture and Simulation of End Mills","abstract":"Abstract This research presents a significant advancement in digital twin technology within the manufacturing sector, focusing on enhancing data acquisition and simulation processes during critical product lifecycle phases of endmill: design modeling and finite element analysis (FEA). The core of this study lies in the innovative creation of virtual assets that emulate real-time end milling operations. Our approach leverages CAD/CAE kernels as a pivotal bridge, connecting physical assets with virtual processes through process identification (pid) numbers. This methodology not only captures core utilization and other vital characteristics of computer systems as time series data signals but also introduces a novel angle in the data capture process, enhancing the fidelity of digital twins in manufacturing simulations. A key understanding of our research is the establishment of a direct correlation between CPU signal spikes and enhanced processing capacity, especially in relation to CAD/CAE kernel activities. This insight is critical for informed decision-making in tool and material selection, significantly reducing the development time for new material mathematical models. Our findings underscore the efficiency and practicality of digital twins in real-time milling processes, offering a robust framework for decision-making in both design and simulation phases. The study’s methodological innovations promise substantial contributions to digital twin technology, setting a new benchmark for precision and efficacy in manufacturing simulations.","author":[{"family":"Anbalagan","given":"Arivazhagan"},{"family":"Kauffman","given":"Marcos"},{"family":"Long","given":"Tengfei"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1115/msec2024-125094","URL":"https://doi.org/10.1115/msec2024-125094","source":"openalex"},{"id":"doi:10.1002/9781394195336.ch1","type":"article-journal","title":"Journey to Digital Twin Technology in Industrial Production: Evolution, Challenges, and Trends","abstract":"The Digital Twin is one of the game-changing inventions ushering in the Fourth Industrial Revolution that has the ability to completely alter the manufacturing landscape. A physical asset, method, or system's “digital twin” can be monitored, analyzed, and optimized in real time. The purpose of this piece is to inform readers about the history, current use, and promising future of digital twins in manufacturing. Beginning around the turn of the 2000, the idea of a “digital twin” emerged. It became a powerful resource due to steady improvements in sensor technology, data analytics, and network infrastructure. In this essay, we trace the extraordinary evolution of the Digital Twin from theoretical framework to usable industrial tool, illuminating the key moments and ideas that shaped it along the way. We also go over the difficulties that businesses experience when trying to introduce Digital Twin solutions. Data integration and interoperability issues, cybersecurity concerns, and a high cost of deployment are just a few of the challenges that prohibit Digital Twins from being fully integrated into industrial production processes. Digital Twins are explored in terms of their potential applications and future growth in the industrial sector. Another example is the management of supply chains that uses AI and ML combined to increase predictive capacity, or the creation of Digital Twins for usage in collaborative multi-enterprise scenarios. The study investigates how Digital Twin technology could improve maintenance procedures and productivity. The research concludes with an in-depth discussion of the increasing prevalence of Digital Twin applications in manufacturing. Understanding the development of Digital Twin technology, being aware of its problems, and embracing the changing trends can help businesses optimize production processes, enhance decision-making, and drive success during the Fourth Industrial Revolution period.","author":[{"family":"Samuel","given":"Prithi"},{"family":"Dhanaraj","given":"Rajesh"},{"family":"Balusamy","given":"Balamurugan"},{"family":"Bashir","given":"Ali"},{"family":"Kadry","given":"Seifedine"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/9781394195336.ch1","URL":"https://doi.org/10.1002/9781394195336.ch1","source":"openalex"},{"id":"oa:W4414846868","type":"article-journal","title":"Micro-entrepreneurs towards the twin sustainable and digital transition. Does financial literacy play a role?","abstract":"Abstract The digital and sustainable transitions represent two strategic drivers of growth and innovation for micro-, small-, and medium-sized enterprises. This is especially relevant for micro-firms, which significantly lag behind larger firms in these areas. Financial literacy can play a key role in guiding small entrepreneurs to make sound financial choices and make the so-called twin transition successful. We exploit a survey conducted by the Bank of Italy in 2021 – involving about 2,000 non-financial firms with less than 10 employees – to investigate whether financial literacy acts as a driver for the twin transition. Through instrumental variable estimation, we find evidence of a causal link between financial literacy and both digitalisation and engagement in sustainable activities.","author":[{"family":"Dignazio","given":"Alessio"},{"family":"Marconi","given":"Daniela"},{"family":"Stacchini","given":"Massimiliano"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1017/flw.2025.10002","URL":"https://doi.org/10.1017/flw.2025.10002","source":"openalex"},{"id":"oa:W4366989298","type":"article-journal","title":"Using digital technologies to plan and manage the pipelines network in city","abstract":"Abstract Promoting the intelligent level of urban pipelines network planning and management is an important way to improve the rational development and utilisation of urban underground space and ensure the safe operation of urban infrastructure systems. The research on using the rapid and visual expression technology of 3D pipelines network model data, which has the functions of techno‐economic indexes calculation and automatic comparison of underground pipeline construction projects, effectively avoids possible errors in manual calculation and comparison and improves the efficiency and accuracy of the digital declaration process for project planning. In the 3D Geographic Information Systems (GIS) platform environment, this research help to develop many analysis and approval functions based on the data of the underground pipelines network model and the integrated pipes gallery Building Information Modelling, such as evaluating the compliance, feasibility and scientific of the planning scheme of the underground pipeline construction project, comparing the completion data with the data approved by the administrative departments of the project, evaluating the consistency of them and judging the compliance of the project completion data. The application results of some actual projects cases show that this research can improve the efficiency of planning declaration and approval analysis.","author":[{"family":"Huang","given":"Yufang"},{"family":"Peng","given":"Hongtao"},{"family":"Wen","given":"Luxin"},{"family":"Xing","given":"Tingyan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1049/smc2.12054","URL":"https://doi.org/10.1049/smc2.12054","source":"openalex"},{"id":"oa:W4388049812","type":"article-journal","title":"Research on Intelligent Operation and Maintenance (O＆M) Method of Complex Products based on Digital Twin","abstract":"With the development of advanced data analysis technology, the manufacturing industry is moving towards the direction of intelligence. To solve the problems of low operation and maintenance (O&M) efficiency, passive O&M personnel and low intelligence of complex products, a digital twin-based intelligent O&M method for complex products is proposed. A digital twin intelligent O&M model with the physical O&M center, virtual O&M center, twin data platform and O&M service system is established. In the case of product fault classification, the maintenance mechanism is designed and the O&M process in different states is analyzed. Then the implementation process and key technologies are described in detail. Through the digital twin model, the virtual-real interaction and data dynamic update of O&M are realized. Finally, taking the key components of a certain type of EMU bogie as an example, the K-means clustering and Apriori algorithm are used to analyze the fault data. Moreover, the validity and feasibility of the proposed model are verified by applying the fault data to the digital twin architecture. The proposed model and key technologies can provide a new solution for the intelligent O&M of complex products.","author":[{"family":"Zhang","given":"Chuanwei"},{"family":"Zhang","given":"Lingling"},{"family":"Dong","given":"Yunrui"}],"issued":{"date-parts":[[2023]]},"DOI":"10.53106/199115992023103405003","URL":"https://doi.org/10.53106/199115992023103405003","source":"openalex"},{"id":"oa:W4386831926","type":"article-journal","title":"The Role of Digitalization on Manufacturing SME Firm Performance in India","abstract":"This conceptual paper aims to look into how the performance of manufacturing SMEs in India has been influenced by digitalisation. Prior marketing circumstances are constantly changing in the digital age, and real problems must be solved to cover the skills gap built by digital advancements. Past research stated that theoretical and empirical contributions address the problems caused by the digitalization of marketing channels and the exponential growth in the total knowledge. In addition, the study aims to define how digitalization affects India's SMEs in manufacturing. Digitalization has a substantial impact on the performance of manufacturing SMEs. In order to avoid experiencing poor effect, the article underlines the crucial importance of digital capabilities for SMEs owners/managers to take into account while acting on behalf of their organization. Dynamic Capability theory serves as the conceptual foundation and an explanation of the interactions between the variables. Additionally, the theoretical and practical implications of this conceptual model are addressed.","author":[{"family":"Kampoowale","given":"Isha"},{"family":"Singh","given":"Harcharanjit"},{"family":"Sakka","given":"Ayu"},{"family":"Iwuchukwu","given":"Ekene"},{"family":"Al-Shaikhli","given":"Essra"}],"issued":{"date-parts":[[2023]]},"DOI":"10.6007/ijarbss/v13-i9/18060","URL":"https://doi.org/10.6007/ijarbss/v13-i9/18060","source":"openalex"},{"id":"oa:W4401709610","type":"article-journal","title":"Exploring the convergence of Metaverse, Blockchain, and AI : A comprehensive survey of enabling technologies, applications, challenges, and future directions","abstract":"Abstract The Metaverse, distinguished by its capacity to integrate the physical and digital realms seamlessly, presents a dynamic virtual environment offering diverse opportunities for engagement across innovation, entertainment, socialization, and commercial endeavors. However, the Metaverse is poised for a transformative evolution through the convergence of contemporary technological advancements, including artificial intelligence (AI), Blockchain, Robotics, augmented reality, virtual reality, and mixed reality. This convergence is anticipated to revolutionize the global digital landscape, introducing novel social, economic, and operational paradigms for organizations and communities. To comprehensively elucidate the future potential of this technological fusion and its implications for digital innovation, this research endeavors to undertake a thorough analysis of scholarly discourse and research pertaining to the Metaverse, AI, Blockchain, and associated technologies. This survey delves into various critical facets of the Metaverse ecosystem, encompassing component analysis, exploration of digital currencies, assessment of AI utilization in virtual environments, and examination of Blockchain's role in enhancing digital content and data security. Leveraging articles retrieved from esteemed digital repositories including ScienceDirect, IEEE Xplore, Springer Nature, Google Scholar, and ACM, published between 2017 and 2023, this study adopts an analytical approach to engage with these materials. Through rigorous examination and discourse, this research aims to provide insights into the emerging trends, challenges, and future directions in the convergence of the Metaverse, Blockchain, and AI. This article is categorized under: Application Areas > Industry Specific Applications","author":[{"family":"Uddin","given":"Mueen"},{"family":"Obaidat","given":"Muath"},{"family":"Manickam","given":"Selvakumar"},{"family":"Laghari","given":"Shams"},{"family":"Dandoush","given":"Abdulhalim"},{"family":"Ullah","given":"Hidayat"},{"family":"Ullah","given":"Syed"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/widm.1556","URL":"https://doi.org/10.1002/widm.1556","source":"openalex"},{"id":"oa:W4403475669","type":"article-journal","title":"Enterprise digital management: research review, current status and prospects","abstract":"Abstract With the advent of the digital economy era, digital management has become a hot topic of concern in both the industry and academia. Focusing on digital management in enterprises, this article consists of 750 CSSCI source journals indexed in the CNKI database from 2000 to 2022, 1303 articles in the literature and Web of Science core database were used as research objects, using CiteSpace and VOSviewer Perform bibliometric analysis using visual tools. Firstly, conduct data statistics on the overall collection and apply the author literature coupling method. Analyze representative literature. Secondly, by means of thematic temporal evolution and keyword emergence, we will sort out the development of domestic and foreign research. Expand the context. Next, we use keyword clustering method to explore recent hot topics in domestic and international research. Based on citation analysis and word cluster analysis, with the comprehensive results of \"basic elements—management process—management effectiveness\", a digital management theory for enterprises has been constructed on the IPO Panoramic Research Framework Model. Finally, future research directions are proposed. Firstly, the issue of digital technology abuse must be addressed through standardized management protocols. Secondly, the mechanisms by which digital technology impacts organizational performance warrant thorough investigation. Thirdly, the paradigm of collaboratively applying multiple digital technologies should be explored. Lastly, the design of an innovative digital ecosystem strategy based on a platform approach needs to be developed.","author":[{"family":"Han","given":"Xiao"},{"family":"Hu","given":"Yixuan"},{"family":"Li","given":"Wang"},{"family":"Zhou","given":"Rui"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/s44176-024-00032-z","URL":"https://doi.org/10.1007/s44176-024-00032-z","source":"openalex"},{"id":"oa:W4403689477","type":"article-journal","title":"The Coupling Coordination Relationship and Driving Factors of the Digital Economy and High-Quality Development of Rural Tourism: Insights from Chinese Experience Data","abstract":"Globally, rural tourism development faces challenges such as inadequate infrastructure, insufficient marketing resources, and unreliable service quality, all of which limit its potential. However, digital technology offers unprecedented opportunities to address these barriers. China’s experience in integrating digital technology into rural tourism provides a valuable case study for understanding the digitalization of rural tourism. This study constructs an index system to assess the coupling coordination relationship between the digital economy and the high-quality development of rural tourism (HQDRT). By employing methods such as the entropy method, coupling coordination degree model, obstacle factor model, and geographic detector, the study examines the evolution of this coupling coordination relationship and its driving mechanisms across 31 provinces (including regions and municipalities) in China from 2012 to 2021. The findings reveal that (1) The development of the digital economy generally lags behind that of the rural tourism, but the coupling coordination relationship between the two is steadily improving. (2) The level of coupling coordination increases from west to east, with spatial distribution patterns evolving from ‘antagonism’ to ‘adaptation’ and then to ‘coordination’ as they move eastward. Most provinces belong to the ‘adaptation’ type. (3) From a nationwide perspective, the primary obstacles impeding the development of the digital economy include an insufficient internet penetration rate, which consequently leads to underdeveloped internet finance development and telecommunications industry development. The major barriers to the HQDRT stem from an inadequate number of tourists and a lack of physical infrastructure. (4) Population density, consumer spending, and R&D are significant drivers of the coupling coordination relationship, with the interaction between urbanization rates and other factors generally weakening the degree of coupling.","author":[{"family":"Liu","given":"Hanni"},{"family":"Tan","given":"Zhixiong"},{"family":"Xia","given":"Zancai"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/land13111734","URL":"https://doi.org/10.3390/land13111734","source":"openalex"},{"id":"oa:W4405574038","type":"article-journal","title":"Examining patient safety protocols amidst the rise of digital health and telemedicine: nurses’ perspectives","abstract":"BACKGROUND: Integrating digital health and telemedicine technologies is transforming healthcare delivery. In light of this transition, it is critical to ascertain the efficacy of patient safety protocols and evaluate the awareness of healthcare professionals, particularly nurses, regarding the integration of digital health technologies. AIM: This study examines the factors influencing the successful adoption of digital health and telemedicine technologies from the nurses' perspective, focusing on ensuring patient safety and enhancing organizational readiness for digital health integration. METHODS: A cross-sectional study included 246 nurses from outpatient healthcare centers in Egypt. The data collected included demographic information and responses to a series of questionnaires, namely the Patient Safety Culture Survey (PSCS), the Telemedicine Risk Assessment and Mitigation Matrix (TRAMM), the Digital Health Adoption Readiness Assessment (DHARA), and the Digital Health Impact Assessment Tool (DHIA). The descriptive statistical analyses were conducted using the IBM SPSS Statistics software, version 26. RESULTS: The sample was predominantly composed of nurses aged 18-35 (40.65%) and 36-55 (44.72%), with a near-equal gender distribution (48.78% male, 51.22% female). Most nurses held college degrees (73.17%) and were familiar with telemedicine (73.17%). The PSCS indicated positive scores for Communication Openness (4.5), Leadership Support (4.2), Teamwork (4.3), and Organizational Learning (4.1), with an overall mean score of 4.275. The TRAMM scores were notably high (total mean score 4.9), indicating effective risk management. The DHARA demonstrated considerable preparedness, as evidenced by a Total Mean Score of 7.85. The DHIA further substantiated this readiness, indicating a robust anticipated impact, particularly in Patient Engagement (9.0) and Usability (8.2). CONCLUSION: The favorable assessment scores indicate a strong awareness of integrating digital health and telemedicine, suggesting the potential for enhanced patient care and healthcare delivery. It is recommended that healthcare organizations prioritize providing ongoing training and support for nurses, enabling them to utilize digital health tools and thereby enhance patient safety effectively. CLINICAL TRIAL NUMBER: Not applicable.","author":[{"family":"Ibrahim","given":"Ateya"},{"family":"Alenezi","given":"Ibrahim"},{"family":"Aa","given":"Mahfouz"},{"family":"Mohamed","given":"Ishraga"},{"family":"Shahin","given":"Marwa"},{"family":"Abdelhalim","given":"Elsayeda"},{"family":"Mohammed","given":"Laila"},{"family":"Abd-Elhady","given":"Takwa"},{"family":"Salama","given":"Reda"},{"family":"Kamel","given":"Aziza"},{"family":"Gouda","given":"Rania"},{"family":"Eldiasty","given":"Noura"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1186/s12912-024-02591-8","URL":"https://doi.org/10.1186/s12912-024-02591-8","source":"openalex"},{"id":"oa:W4390575816","type":"article-journal","title":"How do innovation intermediaries’ business models cope with their need to develop new digital services?","abstract":"This study explores relationships among various aspects of Innovation Intermediaries' (IIs) business models and their intention to provide digital and data-enabled services to their members/customers. Using mixed research methods with data collected from Danish IIs, we find that IIs' current use level of digital resources has a positive relationship with their intention of offering digital and data services, while the level of existing digital services demotivates or prevents IIs from providing them. We also find that the breadth of IIs' customers and partnerships is not directly associated with their intention to offer more digital services in the future. These findings are enriched with nuanced insights from a follow-up qualitative study showing that strategic partners do not provide the required support for intermediaries to develop and provide digital offerings. Instead, IIs rely on system integrators to equip themselves with the needed digital capacity to support their members/customers. The study contributes to the understanding of IIs’ business models linked to their service catalogue, particularly on digital offerings and their function as digitalization champions in a shifting paradigm of industrial digital transformation. Furthermore, it adds knowledge about open innovation by researching service offerings and relevant resources and capabilities of IIs as network organizations.","author":[{"family":"Sala-Vilar","given":"Lluís"},{"family":"Liying","given":"Jason"},{"family":"Traunecker","given":"Tim"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.technovation.2023.102950","URL":"https://doi.org/10.1016/j.technovation.2023.102950","source":"openalex"},{"id":"oa:W4405265886","type":"article-journal","title":"Factors Affecting the Implementation of the Digital Twins in the Construction Industry: An Interpretive Structural Modelling Analysis","abstract":"With the extensive use of digital technologies, the modern construction industry has made progress in improving productivity and safety. Despite this, construction productivity remains among the lowest in the industry. With the development of Industrial Revolution 4.0, the construction industry has also benefited from it, forming the idea behind Construction 4.0, which is founded on: the digitization of the construction sector and the industrialization of the construction procedure. The current use of digital twins in the construction industry is considered among the most successful and influential ways to achieve Construction 4.0, optimize construction links, and improve coordination among stakeholders. Many factors are impacting the construction industry's adoption of digital twins. Previous studies have failed to propose a practical model to facilitate the implementation of digital twins in the construction industry. This study fills this gap. First, this study conducted a systematic literature review (SLR) based on Web of Science and Scopus databases to identify negative and positive factors. SLR identifies four aspects of factors, including technical factors, stakeholder factors, external factors, and economic factors. A conceptual model is then proposed using an interpretive structural modeling analysis approach. The model is used to describe the interaction of these factors in digital twins implementation, and finally, recommendations are made to mitigate the negative factors based on the model. This conceptual model helps guide digital twin implementation in the construction industry and helps build a knowledge system of digital technology. The findings will support practitioners in the construction industry using or planning to use digital twins.","author":[{"family":"Khoo","given":"Khoo"},{"family":"Wang","given":"Jiao"},{"family":"Esa","given":"Muneera"},{"family":"Sun","given":"Hui"}],"issued":{"date-parts":[[2024]]},"DOI":"10.37934/araset.53.2.263282","URL":"https://doi.org/10.37934/araset.53.2.263282","source":"openalex"},{"id":"oa:W4392007761","type":"article-journal","title":"Development of an Intelligent Oil Field Management System based on Digital Twin and Machine Learning","abstract":"This article introduces an innovative approach to oil field management using digital twin technology and machine learning. A detailed experimental setup was designed using oil displacement techniques, equipped with sensors, actuators, flow meters, and solenoid valves. The experiments focused on displacing oil using water, polymer, and oil, from which valuable data was gathered. This data was pivotal in crafting a digital twin model of the oil field. Utilizing the digital twin, ML algorithms were trained to predict oil production rates, detect potential equipment malfunctions, and prevent operational issues. Our findings highlight a notable 10-15% improvement in oil production efficiency, underscoring the transformative potential of merging DT and ML in the petroleum industry.","author":[{"family":"Tasmurzayev","given":"Nurdaulet"},{"family":"Amangeldy","given":"Bibars"},{"family":"Nurakhov","given":"Yedil"},{"family":"Shinassylov","given":"Shona"},{"family":"Bekele","given":"Samson"}],"issued":{"date-parts":[[2023]]},"DOI":"10.37394/232017.2023.14.12","URL":"https://doi.org/10.37394/232017.2023.14.12","source":"openalex"},{"id":"oa:W4403402994","type":"article-journal","title":"Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine","abstract":"Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep learning, and other advanced computational methods. These innovations have unlocked unprecedented opportunities for the acceleration of drug discovery and delivery, the optimization of treatment regimens, and the improvement of patient outcomes. AI is swiftly transforming the pharmaceutical industry, revolutionizing everything from drug development and discovery to personalized medicine, including target identification and validation, selection of excipients, prediction of the synthetic route, supply chain optimization, monitoring during continuous manufacturing processes, or predictive maintenance, among others. While the integration of AI promises to enhance efficiency, reduce costs, and improve both medicines and patient health, it also raises important questions from a regulatory point of view. In this review article, we will present a comprehensive overview of AI's applications in the pharmaceutical industry, covering areas such as drug discovery, target optimization, personalized medicine, drug safety, and more. By analyzing current research trends and case studies, we aim to shed light on AI's transformative impact on the pharmaceutical industry and its broader implications for healthcare.","author":[{"family":"Serrano","given":"Dolores"},{"family":"Luciano","given":"Francis"},{"family":"Anaya","given":"Brayan"},{"family":"Öngoren","given":"Baris"},{"family":"Kara","given":"Aytug"},{"family":"Molina","given":"Gracia"},{"family":"Ramirez","given":"Bianca"},{"family":"Sánchez-Guirales","given":"Sergio"},{"family":"Simón","given":"Jj"},{"family":"Tomietto","given":"Greta"},{"family":"Rapti","given":"Chrysi"},{"family":"Ruiz","given":"Helga"},{"family":"Rawat","given":"Satyavati"},{"family":"Kumar","given":"Dinesh"},{"family":"Lalatsa","given":"Aikaterini"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/pharmaceutics16101328","URL":"https://doi.org/10.3390/pharmaceutics16101328","source":"openalex"},{"id":"oa:W4392847213","type":"article-journal","title":"Unmanned Aerial Systems (UAS)-Derived 3D Models for Digital Twin Construction Applications","abstract":"The advent of Construction 4.0 has marked a paradigm shift in industrial development, integrating advanced technologies such as cyber-physical systems (CPS), sensors, unmanned aerial systems (UAS), building information modeling (BIM), and robotics. Notably, UASs have emerged as invaluable tools seamlessly embedded in construction processes, facilitating the comprehensive monitoring and digitization of construction projects from the early design phase through construction to the post-construction phases. Equipped with various sensors, such as imaging sensors, light detection and rangers (LiDAR), and thermal sensors, UASs play an important role in data collection processes, especially for 3D point cloud generation. Presently, UASs are recognized as one of the most effective means of generating a Digital Twin (DT) of construction projects, surpassing traditional methods in terms of speed and accuracy. This chapter provides a comprehensive overview of the applications of UAS-derived 3D models in DT, outlining their advantages and barriers and offering recommendations to augment their quality and accuracy.","author":[{"family":"Martinez","given":"Jhonattan"},{"family":"Alarcon","given":"Luis"},{"family":"Wandahl","given":"Søren"}],"issued":{"date-parts":[[2024]]},"DOI":"10.5772/intechopen.1004746","URL":"https://doi.org/10.5772/intechopen.1004746","source":"openalex"},{"id":"oa:W4405787366","type":"article-journal","title":"Digital Twins in the Metaverse for Collaborative Discovery of Contextual Factors","abstract":"In this paper we outline how digital twins of cities can create Metaverse spaces which stimulate and facilitate collaborative brainstorming on societal problems whilst helping discover relevant contextual factors. Such digital twins of places in effect constitute boundary objects bridging the spheres of interest and understanding between stakeholders from different backgrounds, allowing them to understand each other better and derive better collaborative outcomes. To illustrate our contribution, we use the example of the Manchester Digital Twin, a model of Manchester within the Data Visualisation Observatory which we use to overlay a variety of geographically relevant datasets. Switching between the sets and using the built-in capabilities of simulation, we can facilitate brainstorming between city planners, public health officials and local community leaders, for example, on how to address societal problems such as obesity prevalence and associated health outcomes. We illustrate how, in the process of working with the digital twin, the stakeholders can become aware of relevant yet previously unconsidered contextual factors such as proximity to green spaces, bike lanes and fast-food outlets.","author":[{"family":"Menukhin","given":"Olga"},{"family":"Mehandjiev","given":"Nikolay"},{"family":"Quboa","given":"Qudamah"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/imeta62882.2024.10808107","URL":"https://doi.org/10.1109/imeta62882.2024.10808107","source":"openalex"},{"id":"oa:W4402480106","type":"article-journal","title":"Probabilistic digital twin for continuous bridge performance modelling","abstract":"The multiplicity of possible different and possibly interacting processes contributing or governing deterioration processes in bridges requires systems representations way beyond the deterministic approach where the focus is on few processes and corresponding models. A Probabilistic Digital Twin (PDT), supported by Structural Health Monitoring (SHM) and big data from observations and monitoring, can provide a novel contribution to support integrity management with knowledge improved over time. This paper explores the preliminary analyses for the future full development of the PDT as part of the Bridgitise Project. An approach to build the PDT of a bridge will be developed using FEM modelling of the deterioration effects. The simulated structural responses under deterioration progressing in time will be used to develop a PDT model that will then be utilized as a representation of the best available knowledge and applied to generate simulations of very significant numbers of structural performance scenarios over time.","author":[{"family":"Daró","given":"Paola"},{"family":"Mazza","given":"Dario"},{"family":"Basone","given":"F"},{"family":"Mancini","given":"G"},{"family":"Limongelli","given":"MP"},{"family":"Faber","given":"MH"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1201/9781003483755-409","URL":"https://doi.org/10.1201/9781003483755-409","source":"openalex"},{"id":"oa:W4391272823","type":"manuscript","title":"Health Digital Twins Supported by Artificial Intelligence-based Algorithms and Extended Reality in Cardiology","abstract":"Recently, significant efforts have been made to create Health Digital Twins (HDTs), digital twins for clinical applications. Heart modeling is one of the fastest-growing fields, which favors the effective application of HDTs. The clinical application of HDTs will be increasingly widespread in the future of healthcare services and has a huge potential to form part of the mainstream in medicine. However, it requires the development of both models and algorithms for the analysis of medical data, and advances in Artificial Intelligence (AI) based algorithms have already revolutionized image segmentation processes. Precise segmentation of lesions may contribute to an efficient diagnostics process and a more effective selection of targeted therapy. In this paper, a brief overview of recent achievements in HDT technologies in the field of cardiology, including interventional cardiology was conducted. HDTs were studied taking into account the application of Extended Reality (XR) and AI, as well as data security, technical risks, and ethics-related issues. Special emphasis was put on automatic segmentation issues. It appears that improvements in data processing will focus on automatic segmentation of medical imaging in addition to three-dimensional (3D) pictures to reconstruct the anatomy of the heart and torso that can be displayed in XR-based devices. This will contribute to the development of effective heart diagnostics. The combination of AI, XR, and an HDT-based solution will help to avoid technical errors and serve as a universal methodology in the development of personalized cardiology. Additionally, we describe potential applications, limitations, and further research directions.","author":[{"family":"Rudnicka","given":"Zofia"},{"family":"Proniewska","given":"Klaudia"},{"family":"Perkins","given":"Mark"},{"family":"Pręgowska","given":"Agnieszka"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2401.14208","URL":"https://doi.org/10.48550/arxiv.2401.14208","source":"openalex"},{"id":"oa:W4405432276","type":"article-journal","title":"Enhanced digital twin development for a conveyor belt system: integrating PLC control, CNN decision-making, Gradio-based HMI, and fuzzy logic","abstract":"This paper introduces an advanced Digital Twin (DT) of a conveyor belt system, designed to enhance industrial automation and decision-making in the context of Industry 4.0. Built using Factory I/O, the DT simulates the physical conveyor's behavior, integrating seamlessly with a Programmable Logic Controller (PLC) for real-time control. A Convolutional Neural Network (CNN) enhances decision-making by analyzing conveyor activity, such as defect detection and sorting optimization. A Fuzzy Logic (FL) system also refines CNN outputs, improving reliability by incorporating factors like confidence scores and operational parameters. A Gradio-based Human-Machine Interface (HMI) offers an intuitive platform for real-time monitoring, interaction, and manual control. The system demonstrates robust synchronization between virtual and physical components, showcasing its ability to improve efficiency, accuracy, and adaptability in industrial processes. This work contributes to smart manufacturing advancements by combining DT technology, intelligent algorithms, and adaptive control for enhanced industrial supervision.","author":[{"family":"Aniba","given":"Yehya"},{"family":"Bouhedda","given":"Mounir"},{"family":"Bachene","given":"Mourad"},{"family":"Seddiki","given":"Mahdi"},{"family":"Tobbal","given":"Abdelhafid"},{"family":"Hamrani","given":"Abdelmoumin"},{"family":"Benyezza","given":"Hamza"}],"issued":{"date-parts":[[2024]]},"DOI":"10.38152/bjtv7n4-035","URL":"https://doi.org/10.38152/bjtv7n4-035","source":"openalex"},{"id":"oa:W4390824527","type":"article-journal","title":"Digital Twin: From Buzzword To Solutions [Guest Editorial]","abstract":"When we talk about digitization and digitalization, the termdigital twinis not far away; data and information are the new oil for the economy. But hasn’t electrical power always been at the forefront with computational models and computer applications for the secure operation of power systems? With the development of computer systems in the middle of the last century, power systems were one of the first civilian applications. Many standard computing methods and models in power systems have been established for more than half a century. Why are we suddenly researching and talking so much about digital twins, and which new solutions will really be established in practice? In this special issue, we want to explore these questions and examine them from different perspectives.","author":[{"family":"Rehtanz","given":"Christian"},{"family":"Häger","given":"Ulf"},{"family":"Liu","given":"Chen‐ching"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/mpe.2023.3339094","URL":"https://doi.org/10.1109/mpe.2023.3339094","source":"openalex"},{"id":"oa:W4402227152","type":"article-journal","title":"Digital economy and the medical and health service supply in China","abstract":"The impact of the digital economy on the healthcare sector is becoming increasingly profound. This article focuses on the relationship between the development of China's digital economy and medical and health services supply. Based on panel data from 30 provinces in China from 2012 to 2021, the CRITIC weight method was applied to measure the supply capacity of medical and health services and the level of digital economy development, and the kernel density estimation method and Dagum Gini coefficient method was used to characterize the evolutionary trends and regional differences. Additionally, a two-way fixed-effects model is adopted to investigate the impact of digital economy development on medical and health services supply. The results show that both the supply capacity of healthcare services and the level of digital economy development have been increasing continuously in terms of evolutionary trends. From the perspective of regional differences, compared to the supply level of healthcare services, the regional differences in digital economy development are more significant. The intra-regional differences in medical and health services supply are greater than the inter-regional differences, while the development of the digital economy exhibits the opposite trend. The findings of this paper provide supports for China to enhance the development level of digital economy and improve supply of medical and health service.","author":[{"family":"Guan","given":"Xueling"},{"family":"Xu","given":"Jiayue"},{"family":"Huang","given":"Xinru"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3389/fpubh.2024.1441513","URL":"https://doi.org/10.3389/fpubh.2024.1441513","source":"openalex"},{"id":"oa:W4391878449","type":"article-journal","title":"Digital Innovation Hubs and portfolio of their services across European economies","abstract":"Research background: Digital ecosystems in Europe are heterogenous organizations involving different economies, industries, and contexts. Among them, Digital Innovation Hubs (DIHs) are considered a policy-driven organization fostered by the European Commission to push companies’ digital transition through a wide portfolio of supporting services. Purpose of the article: There are DIHs existing in all European economies, but literature needs more precise indications about their status and nature. The purpose is to study a distribution of DIHs and differences in portfolios of DIHs’ services across European economies. Therefore, the paper wants to deliver more precise data on effects on national and European policies. This is required to define their final role and scope in the complex dynamics of the digital transition, depending on regional context and heterogeneity of industries. Methods: Data on 38 economies was collected from the S3 platform (on both existing and in preparation DIHs) and further verified by native speaking researchers using manual web scrapping of websites of DIHs identified from S3. To find potential similarities of digital ecosystems in different economies as emanated by the existence of DIHs, clusterization (Ward’s method and Euclidean distances) was applied according to the services offered. Economies were clustered according to the number of DIHs and the spread of DIHs intensity in different cities. The results were further analyzed according to the scope of the provided services. Findings & value added: The applied clustering classified European economies in four different sets, according to the types of services offered by the DIHs. These sets are expression of the different digitalization statuses and strategies of the selected economies and, as such, the services a company can benefit from in a specific economy. Potential development-related reasons behind the data-driven clustering are then conjectured and reported, to guide companies and policy makers in their digitalization strategies.","author":[{"family":"Гавкалова","given":"Наталія"},{"family":"Gładysz","given":"Bartłomiej"},{"family":"Quadrini","given":"Walter"},{"family":"Sassanelli","given":"Claudio"},{"family":"Asplund","given":"Fredrik"},{"family":"Ramli","given":"Muhammad"},{"family":"Detzner","given":"Peter"},{"family":"Deville","given":"Jane"},{"family":"Dragıc","given":"Miroslav"},{"family":"Erp","given":"Tim"},{"family":"Georgescu","given":"Amalia"},{"family":"Price","given":"Liz"}],"issued":{"date-parts":[[2024]]},"DOI":"10.24136/oc.2757","URL":"https://doi.org/10.24136/oc.2757","source":"openalex"},{"id":"oa:W4385367981","type":"article-journal","title":"How Does the Digital Capability Advantage Affect Green Supply Chain Innovation? An Inter-Organizational Learning Perspective","abstract":"Green supply chain innovation has gained significant attention from academics and practitioners due to its ability to mitigate chain liability risks, meet consumer environmental demands, and create sustainable competitive advantages. Digital technology, a valuable tool for enhancing organizational information processing capabilities, plays a crucial role in promoting successful green supply chain innovation. However, existing research has a limited understanding of how digital capability advantage influences green supply chain innovation. Therefore, based on an inter-organizational learning perspective, this study aims to explore the impact of digital capability advantage on green supply chain innovation and examine the mediating role of green supply chain learning (green supplier learning and green customer learning). The survey results from 221 Chinese manufacturing firms indicate that digital capability advantages contribute directly and positively to green supply chain innovation and also indirectly enhance it through green supplier learning and green customer learning. This study establishes the positive relationship between digital capability advantages and green supply chain innovation and highlights the mediating role of green supplier learning and green customer learning. The research conclusions not only enhance our understanding of the factors and key success paths of green supply chain innovation from a digital perspective but also provide theoretical guidance for its effective implementation in manufacturing firms.","author":[{"family":"Qiao","given":"Jianqi"},{"family":"Li","given":"Suicheng"},{"family":"Xiong","given":"Su"},{"family":"Li","given":"Na"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/su151511583","URL":"https://doi.org/10.3390/su151511583","source":"openalex"},{"id":"oa:W4401672992","type":"article-journal","title":"Digitally twin driven ship cooling pump fault monitoring system and application case","abstract":"The rise of digital twin technology has provided innovative methods for monitoring and optimizing ship cooling pumps. This paper proposes a digital twin-based framework for the status monitoring and visualization of ship cooling pumps. By establishing highly realistic physical and mathematical models and integrating actual operational data, a comprehensive virtual environment was created to simulate the operational status of ship cooling pumps. Using the random forest algorithm for data training and testing, the results showed that the root mean square error for the training set was 0.0037873, and for the test set, it was 0.008929, indicating high accuracy in predicting the status of cooling pumps. This system enables real-time monitoring, problem diagnosis, performance optimization, and decision support for cooling pumps. This study aims to leverage digital twin technology to design and apply a visualization monitoring system to enhance the intelligence of ship operation and maintenance.","author":[{"family":"Su","given":"Shaojuan"},{"family":"Miao","given":"Zhe"},{"family":"Zhao","given":"Yong"},{"family":"Song","given":"Nanzhe"}],"issued":{"date-parts":[[2024]]},"DOI":"10.21278/brod75403","URL":"https://doi.org/10.21278/brod75403","source":"openalex"},{"id":"oa:W4389964287","type":"article-journal","title":"Impacts of digital connectivity on Thailand’s Generation Z undergraduates’ social skills and emotional intelligence","abstract":"Notwithstanding the pervasive utilization of digital technology in social and educational realms, an in-depth understanding and exploration of the interrelationships amongst digital connectivity, social skills, and emotional intelligence, particularly within Generation Z demographic–known for their heavy reliance on digital platforms–remains elusive. This study endeavors to address this gap. Applying structural equation modeling, it examined the interrelationships between digital connectivity, social skills, and emotional intelligence, surveying a sample of 518 Generation Z students (comprising 77.61% females, 20.64% males, and 1.74% non-binary) across various academic years and disciplines at a university located in Southern Thailand. PLS-SEM software was employed to evaluate the structural model and substantiate the research hypotheses. Our findings suggest that digital connectivity did not detrimentally impact social skills. However, it negatively influenced emotional intelligence among Generation Z students, observable both at the operational level and in terms of fostering the capacity to regulate one’s own and others’ emotional states. Despite this, social skills proved to significantly enhance emotional intelligence. The same consistent pattern of a positive and significant influence is observed when testing the indirect effect of digital connectivity on emotional intelligence through social skills. Furthermore, it was found that robust and effective digital connectivity could potentially bolster understanding and management of emotions in the digital age, much like well-developed social skills. Hence, this study provides substantial insights into the nuanced impacts of digital connectivity on the social and emotional development of Generation Z students.","author":[{"family":"Imjai","given":"Narinthon"},{"family":"Aujirapongpan","given":"Somnuk"},{"family":"Jutidharabongse","given":"Jaturon"},{"family":"Usman","given":"Berto"}],"issued":{"date-parts":[[2023]]},"DOI":"10.30935/cedtech/14043","URL":"https://doi.org/10.30935/cedtech/14043","source":"openalex"},{"id":"oa:W4390842572","type":"article-journal","title":"A multi-omics data analysis workflow packaged as a FAIR Digital Object","abstract":"BACKGROUND: Applying good data management and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles in research projects can help disentangle knowledge discovery, study result reproducibility, and data reuse in future studies. Based on the concepts of the original FAIR principles for research data, FAIR principles for research software were recently proposed. FAIR Digital Objects enable discovery and reuse of Research Objects, including computational workflows for both humans and machines. Practical examples can help promote the adoption of FAIR practices for computational workflows in the research community. We developed a multi-omics data analysis workflow implementing FAIR practices to share it as a FAIR Digital Object. FINDINGS: We conducted a case study investigating shared patterns between multi-omics data and childhood externalizing behavior. The analysis workflow was implemented as a modular pipeline in the workflow manager Nextflow, including containers with software dependencies. We adhered to software development practices like version control, documentation, and licensing. Finally, the workflow was described with rich semantic metadata, packaged as a Research Object Crate, and shared via WorkflowHub. CONCLUSIONS: Along with the packaged multi-omics data analysis workflow, we share our experiences adopting various FAIR practices and creating a FAIR Digital Object. We hope our experiences can help other researchers who develop omics data analysis workflows to turn FAIR principles into practice.","author":[{"family":"Niehues","given":"Anna"},{"family":"Visser","given":"Casper"},{"family":"Hagenbeek","given":"Fiona"},{"family":"Kulkarni","given":"Purva"},{"family":"Pool","given":"René"},{"family":"Karu","given":"Naama"},{"family":"Kindt","given":"Alida"},{"family":"Singh","given":"Gurnoor"},{"family":"Vermeiren","given":"Robert"},{"family":"Boomsma","given":"Dorret"},{"family":"Dongen","given":"Jenny"},{"family":"Hoen","given":"Peter"},{"family":"Gool","given":"Alain"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1093/gigascience/giad115","URL":"https://doi.org/10.1093/gigascience/giad115","source":"openalex"},{"id":"oa:W4404187708","type":"article-journal","title":"The Economic and Regulatory Challenges of Implementing Digital Twins and Autonomous Vessels in U.S. Maritime Fleet Modernization","abstract":"The modernization of the U.S. maritime fleet is crucial to maintaining competitiveness in an evolving global landscape. This review examines the economic and regulatory challenges of implementing digital twins and autonomous vessels within this sector. Digital twins provide a virtual replica of vessels, enabling real-time monitoring, predictive maintenance, and operational efficiency, while autonomous vessels promise cost savings and enhanced safety by minimizing human error. However, adopting these technologies poses significant challenges, including high initial investment, integration with legacy systems, and regulatory gaps. This paper discusses the current limitations within U.S. regulatory frameworks, economic impacts, and international standards that impact fleet modernization efforts. It further discusses collaborative approaches to overcome funding and technical barriers, emphasizing the need for dynamic, adaptive regulations to balance innovation with safety and compliance in an increasingly automated maritime industry.","author":[{"family":"Ogundare","given":"Tunde"},{"family":"Ibokette","given":"Akan"},{"family":"Anyebe","given":"Abraham"},{"family":"During","given":"Adegboyega"}],"issued":{"date-parts":[[2024]]},"DOI":"10.38124/ijisrt/ijisrt24nov075","URL":"https://doi.org/10.38124/ijisrt/ijisrt24nov075","source":"openalex"},{"id":"oa:W4396967417","type":"article-journal","title":"A Human–Machine Interaction Mechanism: Additive Manufacturing for Industry 5.0—Design and Management","abstract":"Industry 5.0 is an emerging value-driven manufacturing model in which human–machine interface-oriented intelligent manufacturing is one of the core concepts. Based on the theoretical human–cyber–physical system (HCPS), a reference framework for human–machine collaborative additive manufacturing for Industry 5.0 is proposed. This framework establishes a three-level product–economy–ecology model and explains the basic concept of human–machine collaborative additive manufacturing by considering the intrinsic characteristics and functional evolution of additive manufacturing technology. Key enabling technologies for product development process design are discussed, including the Internet of Things (IoT), artificial intelligence (AI), digital twin (DT) technology, extended reality, and intelligent materials. Additionally, the typical applications of human–machine collaborative additive manufacturing in the product, economic, and ecological layers are discussed, including personalized product design, interactive manufacturing, human–machine interaction (HMI) technology for the process chain, collaborative design, distributed manufacturing, and energy conservation and emission reductions. By developing the theory of the HCPS, for the first time its core concepts, key technologies, and typical scenarios are systematically elaborated to promote the transformation of additive manufacturing towards the Industry 5.0 paradigm of human–machine collaboration and to better meet the personalized needs of users.","author":[{"family":"Rani","given":"Sunanda"},{"family":"Jining","given":"Dong"},{"family":"Shoukat","given":"Khadija"},{"family":"Shoukat","given":"Muhammad"},{"family":"Nawaz","given":"Saqib"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/su16104158","URL":"https://doi.org/10.3390/su16104158","source":"openalex"},{"id":"oa:W4396821170","type":"manuscript","title":"A real-time digital twin of azimuthal thermoacoustic instabilities","abstract":"When they occur, azimuthal thermoacoustic oscillations can detrimentally affect the safe operation of gas turbines and aeroengines. We develop a real-time digital twin of azimuthal thermoacoustics of a hydrogen-based annular combustor. The digital twin seamlessly combines two sources of information about the system (i) a physics-based low-order model; and (ii) raw and sparse experimental data from microphones, which contain both aleatoric noise and turbulent fluctuations. First, we derive a low-order thermoacoustic model for azimuthal instabilities, which is deterministic. Second, we propose a real-time data assimilation framework to infer the acoustic pressure, the physical parameters, and the model and measurement biases simultaneously. This is the bias-regularized ensemble Kalman filter (r-EnKF), for which we find an analytical solution that solves the optimization problem. Third, we propose a reservoir computer, which infers both the model bias and measurement bias to close the assimilation equations. Fourth, we propose a real-time digital twin of the azimuthal thermoacoustic dynamics of a laboratory hydrogen-based annular combustor for a variety of equivalence ratios. We find that the real-time digital twin (i) autonomously predicts azimuthal dynamics, in contrast to bias-unregularized methods; (ii) uncovers the physical acoustic pressure from the raw data, i.e., it acts as a physics-based filter; (iii) is a time-varying parameter system, which generalizes existing models that have constant parameters, and capture only slow-varying variables. The digital twin generalizes to all equivalence ratios, which bridges the gap of existing models. This work opens new opportunities for real-time digital twinning of multi-physics problems.","author":[{"family":"Nóvoa","given":"Andrea"},{"family":"Noiray","given":"Nicolas"},{"family":"Dawson","given":"James"},{"family":"Magri","given":"Luca"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2404.18793","URL":"https://doi.org/10.48550/arxiv.2404.18793","source":"openalex"},{"id":"oa:W4401945049","type":"article-journal","title":"Artificial Intelligence and Machine Learning Technologies for Personalized Nutrition: A Review","abstract":"Modern lifestyle trends, such as sedentary behaviour and unhealthy diets, have been associated with obesity, a major health challenge increasing the risk of multiple pathologies. This has prompted many to reassess their routines and seek expert guidance on healthy living. In the digital era, users quickly turn to mobile apps for support. These apps monitor various aspects of daily life, such as physical activity and calorie intake; collect extensive user data; and apply modern data-driven technologies, including artificial intelligence (AI) and machine learning (ML), to provide personalised diet and lifestyle recommendations. This work examines the state of the art in data-driven technologies for personalised nutrition, including relevant data collection technologies, and explores the research challenges in this field. A literature review, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline, was conducted using three databases, covering studies from 2021 to 2024, resulting in 67 final studies. The data are presented in separate subsections for recommendation systems (43 works) and data collection technologies (17 works), with a discussion section identifying research challenges. The findings indicate that the fields of data-driven innovation and personalised nutrition are predominately amalgamated in the use of recommender systems.","author":[{"family":"Tsolakidis","given":"Dimitris"},{"family":"Gymnopoulos","given":"Lazaros"},{"family":"Dimitropoulos","given":"Kosmas"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/informatics11030062","URL":"https://doi.org/10.3390/informatics11030062","source":"openalex"},{"id":"oa:W4410538574","type":"article-journal","title":"Digital Procurement 4.0: Redesigning Government Contracting Systems with AI-Driven Ethics, Compliance, and Performance Optimization","abstract":"The advent of Digital Procurement 4.0 marks a transformative shift in government contracting systems, integrating artificial intelligence (AI), data analytics, and automation to enhance transparency, efficiency, and ethical compliance. This study explores the redesign of public procurement frameworks using AI-driven models that ensure not only cost-effectiveness but also adherence to legal, ethical, and performance standards. Traditional procurement systems often grapple with inefficiencies, corruption, lack of accountability, and delayed service delivery. Digital Procurement 4.0 presents an opportunity to counter these limitations through predictive analytics, blockchain-based audit trails, robotic process automation (RPA), and intelligent contract management systems. This paper proposes a comprehensive AI-driven framework that embeds real-time risk detection, compliance verification, vendor performance monitoring, and ethical safeguards throughout the procurement lifecycle. By integrating natural language processing (NLP) for contract analysis, machine learning algorithms for bid evaluation, and automated compliance checkers, governments can ensure fairness, reduce fraud, and promote value-for-money outcomes. Moreover, digital twin technologies enable simulations that forecast procurement outcomes under varying socio-economic scenarios, thus enhancing strategic decision-making. The research draws on recent case studies from digitally advanced governments, demonstrating how AI integration has improved procurement efficiency by up to 45%, reduced fraud incidences by 30%, and enhanced stakeholder trust. Additionally, the study outlines a regulatory and governance blueprint to mitigate algorithmic bias and ensure accountability in AI-led procurement systems. Particular emphasis is placed on ethical algorithm design, data transparency, and participatory oversight mechanisms involving civil society and independent watchdogs. Ultimately, this paper underscores the national importance of adopting Digital Procurement 4.0 in public sector governance. As public expenditure accounts for over 12% of global GDP, optimizing this function through technology has widespread implications for fiscal sustainability, public trust, and socio-economic development. This research offers policy recommendations, implementation strategies, and a roadmap for governments aiming to build ethical, efficient, and AI-enabled contracting ecosystems.","author":[{"family":"Ayobami","given":"Amusa"},{"family":"Mike-Olisa","given":"Uchenna"},{"family":"Ogeawuchi","given":"Jeffrey"},{"family":"Abayomi","given":"Abraham"},{"family":"Agboola","given":"Oluwademilade"}],"issued":{"date-parts":[[2024]]},"DOI":"10.32628/cseit24102138","URL":"https://doi.org/10.32628/cseit24102138","source":"openalex"},{"id":"oa:W4405514853","type":"article-journal","title":"CGRclust: Chaos Game Representation for twin contrastive clustering of unlabelled DNA sequences","abstract":"BACKGROUND: Traditional supervised learning methods applied to DNA sequence taxonomic classification rely on the labor-intensive and time-consuming step of labelling the primary DNA sequences. Additionally, standard DNA classification/clustering methods involve time-intensive multiple sequence alignments, which impacts their applicability to large genomic datasets or distantly related organisms. These limitations indicate a need for robust, efficient, and scalable unsupervised DNA sequence clustering methods that do not depend on sequence labels or alignment. RESULTS: This study proposes CGRclust, a novel combination of unsupervised twin contrastive clustering of Chaos Game Representations (CGR) of DNA sequences, with convolutional neural networks (CNNs). To the best of our knowledge, CGRclust is the first method to use unsupervised learning for image classification (herein applied to two-dimensional CGR images) for clustering datasets of DNA sequences. CGRclust overcomes the limitations of traditional sequence classification methods by leveraging unsupervised twin contrastive learning to detect distinctive sequence patterns, without requiring DNA sequence alignment or biological/taxonomic labels. CGRclust accurately clustered twenty-five diverse datasets, with sequence lengths ranging from 664 bp to 100 kbp, including mitochondrial genomes of fish, fungi, and protists, as well as viral whole genome assemblies and synthetic DNA sequences. Compared with three recent clustering methods for DNA sequences (DeLUCS, iDeLUCS, and MeShClust v3.0.), CGRclust is the only method that surpasses 81.70% accuracy across all four taxonomic levels tested for mitochondrial DNA genomes of fish. Moreover, CGRclust also consistently demonstrates superior performance across all the viral genomic datasets. The high clustering accuracy of CGRclust on these twenty-five datasets, which vary significantly in terms of sequence length, number of genomes, number of clusters, and level of taxonomy, demonstrates its robustness, scalability, and versatility. CONCLUSION: CGRclust is a novel, scalable, alignment-free DNA sequence clustering method that uses CGR images of DNA sequences and CNNs for twin contrastive clustering of unlabelled primary DNA sequences, achieving superior or comparable accuracy and performance over current approaches. CGRclust demonstrated enhanced reliability, by consistently achieving over 80% accuracy in more than 90% of the datasets analyzed. In particular, CGRclust performed especially well in clustering viral DNA datasets, where it consistently outperformed all competing methods.","author":[{"family":"Alipour","given":"Fatemeh"},{"family":"Hill","given":"Kathleen"},{"family":"Kari","given":"Lila"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1186/s12864-024-11135-y","URL":"https://doi.org/10.1186/s12864-024-11135-y","source":"openalex"},{"id":"oa:W4401200967","type":"manuscript","title":"Photogrammetry for Digital Twinning Industry 4.0 (I4) Systems","abstract":"The onset of Industry 4.0 is rapidly transforming the manufacturing world through the integration of cloud computing, machine learning (ML), artificial intelligence (AI), and universal network connectivity, resulting in performance optimization and increase productivity. Digital Twins (DT) are one such transformational technology that leverages software systems to replicate physical process behavior, representing the physical process in a digital environment. This paper aims to explore the use of photogrammetry (which is the process of reconstructing physical objects into virtual 3D models using photographs) and 3D Scanning techniques to create accurate visual representation of the 'Physical Process', to interact with the ML/AI based behavior models. To achieve this, we have used a readily available consumer device, the iPhone 15 Pro, which features stereo vision capabilities, to capture the depth of an Industry 4.0 system. By processing these images using 3D scanning tools, we created a raw 3D model for 3D modeling and rendering software for the creation of a DT model. The paper highlights the reliability of this method by measuring the error rate in between the ground truth (measurements done manually using a tape measure) and the final 3D model created using this method. The overall mean error is 4.97\\% and the overall standard deviation error is 5.54\\% between the ground truth measurements and their photogrammetry counterparts. The results from this work indicate that photogrammetry using consumer-grade devices can be an efficient and cost-efficient approach to creating DTs for smart manufacturing, while the approaches flexibility allows for iterative improvements of the models over time.","author":[{"family":"Alhamadah","given":"Ahmed"},{"family":"Mamun","given":"Muntasir"},{"family":"Harms","given":"Henry"},{"family":"Redondo","given":"Mathew"},{"family":"Lin","given":"Yu"},{"family":"Pacheco","given":"Jesús"},{"family":"Salehi","given":"Soheil"},{"family":"Satam","given":"Pratik"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2407.18951","URL":"https://doi.org/10.48550/arxiv.2407.18951","source":"openalex"},{"id":"oa:W4403444192","type":"manuscript","title":"Cyber-physical and business perspectives using Federated Digital Twins in multinational and multimodal transportation systems","abstract":"Digital Twin (DT) technologies promise to remove cyber-physical barriers in systems and services and provide seamless management of distributed resources effectively. Ideally, full-fledged instantiations of DT offer bi-directional features for physical-virtual representations, tackling data governance, risk assessment, security and privacy protections, resilience, and performance, to name a few characteristics. More broadly, Federated Digital Twins (FDT) are distributed physical-virtual counterparts that collaborate for enacting synchronisation and accurate mapping of multiple DT instances. In this work we focus on understanding and conceptualising the cyber-physical and business perspectives using FDT in multinational and multimodal transportation systems. These settings enforce a plethora of regulations, compliance, standards in the physical counterpart that must be carefully considered in the virtual mirroring. Our aim is to discuss the regulatory and technical underpinnings and, consequently, the existing operational and budgetary overheads to factor in when designing or operating FDT.","author":[{"family":"Czekster","given":"Ricardo"},{"family":"García-Pérez","given":"Alexeis"},{"family":"Kavakli","given":"Manolya"},{"family":"Nasri","given":"Seif"},{"family":"Shaikh","given":"Siraj"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2410.08479","URL":"https://doi.org/10.48550/arxiv.2410.08479","source":"openalex"},{"id":"oa:W4391361874","type":"article-journal","title":"Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review","abstract":"In this review, utilizing the PRISMA methodology, a comprehensive analysis of the use of Generative Artificial Intelligence (GAI) across diverse professional sectors is presented, drawing from 159 selected research publications. This study provides an insightful overview of the impact of GAI on enhancing institutional performance and work productivity, with a specific focus on sectors including academia, research, technology, communications, agriculture, government, and business. It highlights the critical role of GAI in navigating AI challenges, ethical considerations, and the importance of analytical thinking in these domains. The research conducts a detailed content analysis, uncovering significant trends and gaps in current GAI applications and projecting future prospects. A key aspect of this study is the bibliometric analysis, which identifies dominant tools like Chatbots and Conversational Agents, notably ChatGPT, as central to GAI’s evolution. The findings indicate a robust and accelerating trend in GAI research, expected to continue through 2024 and beyond. Additionally, this study points to potential future research directions, emphasizing the need for improved GAI design and strategic long-term planning, particularly in assessing its impact on user experience across various professional fields.","author":[{"family":"Naqbi","given":"Humaid"},{"family":"Bahroun","given":"Zied"},{"family":"Ahmed","given":"Vian"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/su16031166","URL":"https://doi.org/10.3390/su16031166","source":"openalex"},{"id":"oa:W4403032123","type":"article-journal","title":"FORMATION OF THE SUBJECT COMPETENCES OF THE STUDENTS OF THE SCIENCE, MATHEMATICS AND DIGITAL FIELDS BY MEANS OF DIGITAL TWINS","abstract":"У статті розглядається проблема формування предметних компетентностей у студентів природничо-математичної та цифрової галузей за допомогою засобів цифрових двійників (Digital Twins). Невпинний розвиток науково-технічного прогресу, обумовлений прискореним упровадженням досягнень наукових досліджень у всі сфери життя, скороченням часу між науковими відкриттями та їхнім упровадженням, характеризується сучасною промисловою революцією 4.0. Ця революція передбачає інтеграцію автоматизації в усі сфери виробництва, ефективний технологічний устрій, збір, обмін, збереження й передавання даних в єдину саморегульовану систему з мінімізацією ручної праці та втручанням людини у зазначені процеси. Впровадження цифрових технологій вимагає скорочення витрат на збір даних, їх аналіз та моделювання реальних об’єктів для прийняття ефективних рішень у реальному часі. Таку роль значною мірою виконують цифрові двійники. Цифрові двійники дозволяють створювати точні віртуальні копії реальних об’єктів, що сприяє оптимізації різних процесів у промисловості, аграрному секторі, транспорті, торгівлі, освіті та побуті. Вони забезпечують можливість постійного моніторингу, аналізу та вдосконалення реальних систем, знижуючи ризики та витрати на експерименти в реальних умовах. Використання цифрових двійників стає все більш актуальним у контексті розвитку технологій Інтернету речей (IoT), штучного інтелекту, хмарних обчислень та великих даних. У статті аналізується значущість цифрових двійників для формування новітніх компетентностей у студентів природничо-математичної та цифрової галузей. Автори підкреслюють, що сучасна освітня система повинна адаптуватися до вимог ринку праці, забезпечуючи студентів навичками, необхідними для ефективного використання цифрових двійників у професійній діяльності. Пропонується інтеграція технологій цифрових двійників у навчальні програми технічних спеціальностей, що включає як теоретичне вивчення концепцій і принципів роботи цифрових двійників, так і практичні заняття з використанням відповідного програмного забезпечення та обладнання. Впровадження таких програм дозволить підготувати висококваліфікованих фахівців, здатних до інноваційної діяльності в умовах цифрової економіки. Навчання з використанням цифрових двійників сприятиме розвитку критичного мислення, навичок аналізу та прийняття рішень, а також підвищенню адаптивності до швидких змін технологічного середовища. Відповідно, у статті робиться висновок про необхідність реформування освітніх програм для забезпечення підготовки спеціалістів, які володіють компетентностями в галузі цифрових двійників, що є ключовим фактором успіху в сучасному світі цифрових технологій.","author":[{"family":"Sadovyі","given":"Mykola"},{"family":"Трифонова","given":"Олена"},{"family":"Соменко","given":"Дмитро"}],"issued":{"date-parts":[[2024]]},"DOI":"10.36550/2415-7988-2024-1-215-91-96","URL":"https://doi.org/10.36550/2415-7988-2024-1-215-91-96","source":"openalex"},{"id":"oa:W4401852468","type":"article-journal","title":"Aligning Digital Educational Policies with the New Realities of Schooling","abstract":"Abstract To make sense of the changes provoked by the Covid-19 pandemic and its immediate aftermath, this paper critically examines digital education policy responses in the context of the ‘new realities’ faced by schooling. Based on seven case studies contributed by authors from Australia, India, Ireland, Italy, Japan, Canada, Sri Lanka, two key questions are addressed: (1) What are the ‘new realities’ of schooling post Covid-19? and (2) How have digital educational policies changed in response to the new realities of schooling? Findings highlight the complexity of the problem of aligning digital education policies at the macro level to the realities experienced at the meso and micro levels of schooling systems. The paper concludes with discussion of the need for, and challenges of, agile policy making at all levels (macro, meso and micro) that are necessary for schooling systems to meet the challenges and realities of a complex changing world.","author":[{"family":"Butler","given":"Deirdre"},{"family":"Leahy","given":"Margaret"},{"family":"Charania","given":"Amina"},{"family":"Gedara","given":"Peiris"},{"family":"Keane","given":"Therese"},{"family":"Laferrière","given":"Thérèse"},{"family":"Nakamura","given":"Kohei"},{"family":"Ueda","given":"Hiroshi"},{"family":"Bocconi","given":"Stefania"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/s10758-024-09776-9","URL":"https://doi.org/10.1007/s10758-024-09776-9","source":"openalex"},{"id":"oa:W4401380169","type":"article-journal","title":"2024 IEEE International Workshop on Metrology for Living Environment (MetroLivEnv)","abstract":"The emergence of BIM-assisted building digital twins is facilitating building digitalization efforts across various domains. These digital twins necessitate the creation of building energy models (BEM) derived from BIM data. These models are crucial for conducting building simulations, which in turn evaluate the thermal performance of buildings. To address this need, this study presents a semi-automated workflow for converting BIM data into BEMs. Specifically, the workflow utilizes IFC BIMs generated from point cloud data obtained through building scans. Manual intervention in this workflow is minimal, primarily focusing on detecting and correcting errors in BIM geometry resulting from the semi-automatic conversion of point cloud data to BIM format. The process is applied to an existing office building","author":[{"family":"Hasan","given":"Sayegh"},{"family":"Georgios N","given":"Lilis"},{"family":"Mathias","given":"Bouquerel"},{"family":"Thierry","given":"Duforestel"},{"family":"Kyriakos","given":"Katsigarakis"},{"family":"Dimitrios","given":"Rovas"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/metrolivenv60384.2024","URL":"https://doi.org/10.1109/metrolivenv60384.2024","source":"openalex"},{"id":"oa:W4402929034","type":"article-journal","title":"Digital Transformation in Maritime Ports: Defining Smart Gates through Process Improvement in a Portuguese Container Terminal","abstract":"As the digital paradigm stimulates changes in various areas, seaports, which are fundamental to logistics and the global supply chain, are also undergoing a digital revolution, evolving into smart ports. Smart gates are essential components in this transformation, playing a vital role in increasing port efficiency. In the context of smart gates, the aim of this study is to understand how process management can serve as a catalyst for digital transformation, promoting efficiency in traffic flow and logistics. To achieve this objective, the design science research (DSR) methodology was followed, which allowed for the integration of information from several sources of requirement, encompassing both theoretical and practical aspects. The practical component took place at one of Portugal’s largest container terminals, which allowed for the integration of information from various sources. As a result, this study presents the conceptual definition of a smart gate in terms of processes, main technologies, and key performance indicators that will support the monitoring and improvement of future operations. The results provide theoretical and practical contributions: on a practical level, they present a real application of the transformation towards a smart gate, serving as a model for other ports in their digitalization; on a theoretical level, they enrich the literature with a methodology for digitalizing maritime road gates, showing how the use of process management approaches, such as the BPMN, can increase operational efficiency in container terminals.","author":[{"family":"Basulo-Ribeiro","given":"Juliana"},{"family":"Pimentel","given":"Carina"},{"family":"Teixeira","given":"Leonor"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/fi16100350","URL":"https://doi.org/10.3390/fi16100350","source":"openalex"},{"id":"oa:W4402340224","type":"article-journal","title":"Spatial concentration of the ICT sector in the digital age in Central and Eastern Europe","abstract":"As new digital technologies become widespread, it is crucial to understand the role of spatiality and agglomeration economies in the digital age, especially in the ICT sector. The ICT sector, with its innovative strength and the ability to complement various sectors, drives digitalization and balanced economic development. Recognizing the importance of digitalization and the ICT sector for economic development, especially in the catching-up regions of Central and Eastern Europe, this study aims at exploring the role and the spatiality of the ICT sector in the urban and rural areas of the Visegrad countries and Romania. The analysis focuses on the spatial concentration of the ICT sector and the specialization of the regions on the NUTS 3 level, distinguishing capital, intermediate metropolitan, intermediate non-metropolitan and rural areas, utilizing data on employed persons in the period 2010–2020. Findings reveal the dynamic growth and spatial concentration of the ICT sector despite the ongoing process of digitalization, particularly in capital regions, alongside the increasing significance of modern business services in agglomeration economies. Additionally, the research proves the presence of division of labour among different types of regions, reveals capital and rural regions as highly specialized regions and points to the need for place-sensitive development policy.","author":[{"family":"Vas","given":"Zsófia"},{"family":"Kanó","given":"Izabella"},{"family":"Vida","given":"György"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1080/09654313.2024.2396485","URL":"https://doi.org/10.1080/09654313.2024.2396485","source":"openalex"},{"id":"oa:W4403787026","type":"article-journal","title":"DEVELOPMENT OF AN IMPROVED ALGORITHM FOR OPTIMAL CONTROL OF ELECTRICAL MODES FOR A LADLE-FURNACE BY USING A DIGITAL TWIN","abstract":"Within the framework of the article, a new algorithm for automatically switching of operating curves and on-load tap-changer stages in a ladle furnace is considered, depending on the level of the slag coefficient. A problem is formulated related to the complexity of determining the control parameter settings for various slag modes and blowing modes modes. As a solution to this problem, it is proposed to use a digital twin, which allows to calculate the most optimal combination of control settings for three phases. Upon completion of the calculation, the new setpoint values are transferred directly to the automatic control system for the electrical mode of the LF and are used for further operation of the unit. In conclusion, the results of the implementation of a new algorithm on the existing LF operating at one of the domestic metallurgical enterprises are presented.","author":[{"family":"Николаев","given":"АА"},{"family":"Tulupov","given":"PG"},{"family":"Ryzhevol","given":"SS"},{"family":"Bulanov","given":"MV"}],"issued":{"date-parts":[[2024]]},"DOI":"10.14529/power240304","URL":"https://doi.org/10.14529/power240304","source":"openalex"},{"id":"doi:10.1016/j.cie.2023.109839","type":"article-journal","title":"Improving safety management in railway stations through a simulation-based digital twin approach","abstract":"In the dynamic milieu of modern, bustling railway stations, the emphasis on safety and efficient pedestrian traffic management has never been more crucial, elevating the significance of Digital Twins (DTs). DTs bring transformative changes in the way we approach the design, operation, control, and maintenance of complex systems, such as transportation hubs. However, documented real-world applications are lacking, leaving scientists and practitioners without valuable insights on DT implementation. Drawing from a case study centered around a prominent Italian railway station, this paper showcases the prototype of a simulation-based DT that empowers station managers with capabilities such as pedestrian flow prediction, early congestion warnings, evacuation response planning, layout optimization, and intelligent gate management. The simulation-based DT acts as a sophisticated mirror reflecting the dynamics of a station's crowd, drawing data from its physical counterpart with a certain frequency, simulating the evolution of the system over a given time horizon, returning warning messages to the decision maker if issues are identified, and evaluating ex-ante different corrective solutions. The latter becomes crucial for controlling the physical world, providing a closed-loop system. Our case-based framework validates the effectiveness of methods and technical solutions engineered ad-hoc to achieve an acceptable tradeoff among accuracy, performance, and scalability. This includes addressing challenges related to the synchronization of the virtual and physical world, data integration and interoperability with existing systems, and human-system interaction. Ultimately, this contribution serves as a valuable resource, bridging the gap between theoretical concepts and tangible applications in the realm of transportation hub management.","author":[{"family":"Padovano","given":"Antonio"},{"family":"Longo","given":"Francesco"},{"family":"Manca","given":"Luigi"},{"family":"Grugni","given":"Roberto"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.cie.2023.109839","URL":"https://doi.org/10.1016/j.cie.2023.109839","source":"openalex"},{"id":"oa:W4323257261","type":"article-journal","title":"Development of the Digital Accounting and Its Impact on Financial Performance in Higher Education","abstract":"The emergence of digital society in industry 4.0 is one of the most visible changes in the XXI century. The creation of digitization has led to significant changes in accounting and financial management as features of an innovative University. This study aims to analyze the development of digital accounting and examine its impact on economic performance in higher education by using IBM SPSS Statistics 25 and the feasibility of the investment using the payback period approach. The development of digital accounting is based on a web 2.0-based ICT system using the Software Development Life Cycle (SDLC) method with the waterfall model and applying the latest financial accounting standards. Analysis of the impact of accounting digitization was carried out on 247 educational staff as a population and involved 152 respondents as samples selected using the Slovin formula. Data analysis consisted of descriptive statistics, correlation, and multiple regression analysis with an error rate of 5%. The findings showed a positive correlation between financial performance and accounting digitization. Accounting digitization significantly affected financial arrangement with a P-value of 0.000 is smaller than the alpha (α) of 0.05 or sig.T< 0.05, which means significant. The investment feasibility test using the payback period concludes that digital accounting is feasible to implement in higher education. The eligibility criteria based on the results of calculating the rate of return on investment is three years and two months, faster than the required payback period of four years. Received: 18 December 2022 / Accepted: 10 February 2023 / Published: 5 March 2023","author":[{"family":"Nurhayati","given":"Immas"},{"family":"Azis","given":"Azolla"},{"family":"Setiawan","given":"Foni"},{"family":"Yulia","given":"Iis"},{"family":"Riani","given":"Desmy"},{"family":"Endri","given":"Endri"}],"issued":{"date-parts":[[2023]]},"DOI":"10.36941/jesr-2023-0031","URL":"https://doi.org/10.36941/jesr-2023-0031","source":"openalex"},{"id":"oa:W4405960852","type":"article-journal","title":"DUAL PRIORITIES: DIGITAL TWINS AND HEALTH CARE DESIGN THAT SUPPORTS OLDER ADULTS IN THE CONTEXT OF STAFFING SHORTAGES","abstract":"Abstract Aging populations are associated with a growing need and demand for specialized care, including healthcare environments that accommodate unique needs such as mobility assistance, chronic disease management, post-acute care, and mental health support. Currently, there are more than 46 million Americans aged 65 or over, and this number is projected to double by 2060. This demographic aging calls for an increased focus on design solutions like creating age-friendly spaces and ensuring accessibility. Designing healthcare environments that better support older adults is complicated by the staffing shortages in the American healthcare system. For example, there are significant projected shortages of both essential support staff (over 3 million in the next five years) and physicians (roughly 140,000 by 2033). These staffing shortfalls pose critical challenges to patient care, workplace culture and cohesion, and safety. The design of healthcare environments that better support older adults must mitigate the negative impacts of inadequate staffing levels and facilitate more efficient workflows e.g., enhancing interdisciplinary staff collaboration, promoting novel training opportunities, etc. This presentation examines the use of digital twins, effectively indistinguishable virtual representations of real-world physical objects (e.g., the human body, buildings, etc.), as part of a holistic design process that considers older adult patients, staffing and care delivery, and facility optimization. Digital twins have high fidelity and are linked to real-time data. They hold significant potential for designing age-friendly healthcare environments, optimizing staff and resource allocation, asset tracking, accelerated risk assessment, real-time decision support, and novel training simulations, thus improving care for older adults.","author":[{"family":"Kabo","given":"Felix"},{"family":"Morrison","given":"Jake"},{"family":"Ritsema","given":"Chad"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1093/geroni/igae098.2022","URL":"https://doi.org/10.1093/geroni/igae098.2022","source":"openalex"},{"id":"oa:W4400985696","type":"article-journal","title":"Research on the impact of hard technology innovation on the high-quality development of SRDI enterprises: based on the moderating role of digital transformation","abstract":"Purpose This paper aims to investigate the relationship linking hard technology innovation with the high-quality development (HDP) of SRDI firms. SRDI firms are typically classified as medium-sized to moderately scaled businesses renowned for their specialized, refinement, differentiation and innovation (SRDI), with a focus on providing exceptional products or services to gain a competitive advantage in specific market segments. These firms are dedicated to expanding market share and enhancing innovation capacities both locally and globally. The research also aims to scrutinize the contextual effects of digital transformation within this framework. Design/methodology/approach Hard technology innovation consists of three essential components: innovative characteristics, newly developed technology-based intellectual property rights and the volume of R&D initiatives. The evaluation of HDP was performed utilizing the entropy method, with a specific emphasis on assessing value creation and value management capabilities. Subsequently, this study explores the impact of technological innovation on the HDP of firms using a dual-dimension fixed effects model. Findings Every aspect of hard technology innovation is essential for promoting the HDP of businesses. The digital transformation of businesses exerts a heterogeneous moderating influence in this process. This is evident in the constructive impact on the connection between innovation attributes and the volume of fruitful R&D initiatives, as well as the HDP of firms. Conversely, the moderating effect is deemed insignificant in the association between new technology-based intellectual property and HDP. Originality/value This research delves deeper into the underlying mechanisms that underlie the promotion of HDP through hard technology innovation, thereby expanding the scope of our exploration on the HDP of SRDI firms. It establishes a theoretical framework and practical directives for achieving enhanced development quality amidst the evolving landscape of digital transformation within firms.","author":[{"family":"Wei","given":"Yanhui"},{"family":"Meng","given":"Zhiling"},{"family":"Liu","given":"Na"},{"family":"Mao","given":"Jianqi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1108/apjie-04-2024-0069","URL":"https://doi.org/10.1108/apjie-04-2024-0069","source":"openalex"},{"id":"oa:W4313596626","type":"article-journal","title":"A Digital Framework for Locally and Geographically Distributed Simulation of Power Grids","abstract":"The power system sector is expected to contribute significantly to addressing the global climate change challenge through solutions such as the integration of distributed energy resources with low carbon emissions and demand side management as part of the flexibility solutions. However, the transformations in the power grids necessitate additional solutions to ensure the stable and reliable operation of the grids. Such novel solutions require detailed studies in laboratories before implementation in real grids. Power systems simulations combined with power‐hardware‐in‐the‐loop (P‐HIL) experiments provide a reliable form of conducting such studies. The current article introduces the Energy Grids Simulations and Analysis Laboratory of the Energy Lab 2.0 as a digital framework enabling local and distributed analysis of power grids. The outstanding feature of the laboratory is its ability to connect the simulation of validated networks directly to the real hardware of the Energy Lab 2.0 in form of P‐HIL setups and virtually to distant energy research infrastructures, thus enabling geographically distributed experimental studies. Results of the benchmark case studies show that the communication methods available in the simulation laboratory can be used to accurately set up locally and geographically distributed simulations, as well as for reliably interfacing physical hardware components to real‐time simulations.","author":[{"family":"Kyesswa","given":"Michael"},{"family":"Weber","given":"Moritz"},{"family":"Wiegel","given":"Friedrich"},{"family":"Wachter","given":"Jan"},{"family":"Waczowicz","given":"Simon"},{"family":"Kühnapfel","given":"Uwe"},{"family":"Hagenmeyer","given":"Veit"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1002/ente.202201186","URL":"https://doi.org/10.1002/ente.202201186","source":"openalex"},{"id":"oa:W4367693679","type":"article-journal","title":"Towards smart layout design for a reconfigurable manufacturing system","abstract":"Global competition and increased variety in products have created challenges for manufacturing companies. One solution to handle the variety in production is to use reconfigurable manufacturing systems (RMS). These are modular systems where machines can be rearranged depending on what is being manufactured. However, implementing a rearrangeable system drastically increases complexity, among which one challenge with RMS is how to design a new layout for a customized product in a highly autonomous and responsive fashion, known as the layout design problem. In this paper, we combine several Industry 4.0 technologies, i.e., IIoT, digital twin, simulation, advanced robotics, and artificial intelligence (AI), together with optimization to create a smart layout design system for RMS. The system automates the layout design process of RMS and removes the need for humans to design a new layout of the system.","author":[{"family":"Arnarson","given":"Halldor"},{"family":"Yu","given":"Hao"},{"family":"Olavsbråten","given":"Morten"},{"family":"Bremdal","given":"Bernt"},{"family":"Solvang","given":"Bjørn"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.jmsy.2023.03.012","URL":"https://doi.org/10.1016/j.jmsy.2023.03.012","source":"openalex"},{"id":"oa:W4399434472","type":"article-journal","title":"Advanced Optimal Twin‐Setting Protection Coordination Scheme for Maximizing Microgrid Resilience","abstract":"The increasing penetration of distribution generators (DGs), such as PV systems, has led to a significant power protection concern for optimal overcurrent coordination. However, existing literature indicates that the traditional phase over current relay (OCR) scheme faces challenges such as instability, insensitivity, and lack of selectivity when handling the integration of DGs and ground fault scenarios. To address this issue, this study proposes a new optimal twin‐setting OCR coordination scheme for phase and ground events using standard and nonstandard tripping characteristics. The water cycle optimization algorithm (WCOA) is utilized to develop a coordinated optimum strategy that mitigates the effects of DGs on the currents and locations of faults across the power grid. To demonstrate the efficacy of the proposed approach, different case studies of an IEEE power network (9 buses) equipped with two 5 MW PV systems are conducted using industrial software (ETAP). Under various fault conditions (phase and ground faults) and power network operation modes (with and without PVs and islanding modes), the outcomes of the newly developed optimal coordination scheme are compared to the results of conventional schemes. The proposed twin OCR coordinating scheme is found to reduce the total tripping time of OCRs up to 62.3% and increase the selectivity of the relays without miscoordination events.","author":[{"family":"Alasali","given":"Feras"},{"family":"Elnaily","given":"Naser"},{"family":"Saidi","given":"Abdelaziz"},{"family":"Elghaffar","given":"Amer"},{"family":"Holderbaum","given":"William"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1155/2024/7276352","URL":"https://doi.org/10.1155/2024/7276352","source":"openalex"},{"id":"oa:W4390544865","type":"article-journal","title":"The Role of Digital Building Logbooks for a Circular Built Environment","abstract":"Abstract Digital building logbooks (DBLs) are digital repositories of building-related data gathered throughout the full life cycle of a building. DBLs help increase transparency and access to information during the design, construction, operation, and end-of-life phase of a building. They thereby facilitate an efficient and cost-effective transition to a zero energy and circular built environment. DBLs could slow down resource loops by extending the service life of buildings through better coordination of maintenance and repair and close resource loops by promoting adaptability and reuse of the whole building and/or its components with multi-cycle approaches. This chapter analyses examples of DBLs developed in five countries to show that they are useful tools at different life stages of the building and for different stakeholders (homeowners, property managers, or building professionals). Challenges for establishing DBLs as a central tool for a circular built environment lie in improving the user experience and ease of implementation; enhancing interoperability; and effectively collecting, managing, and transforming data into actionable information for the management, maintenance, and reuse at building and district levels.","author":[{"family":"Gonçalves","given":"Joana"},{"family":"Lam","given":"Wai"},{"family":"Ritzen","given":"Michiel"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/978-3-031-39675-5_13","URL":"https://doi.org/10.1007/978-3-031-39675-5_13","source":"openalex"},{"id":"oa:W4405833856","type":"article-journal","title":"Evolution in electrophysiology 100 years after Einthoven: translational and computational innovations in rhythm control of atrial fibrillation","abstract":"In 1924, the Dutch physiologist Willem Einthoven received the Nobel Prize in Physiology or Medicine for his discovery of the mechanism of the electrocardiogram (ECG). Anno 2024, the ECG is commonly used as a diagnostic tool in cardiology. In the paper 'Le T&#xe9;l&#xe9;cardiogramme', Einthoven described the first recording of the now most common cardiac arrhythmia: atrial fibrillation (AF). The treatment of AF includes rhythm control, aiming to alleviate symptoms and improve quality of life. Recent studies found that early rhythm control might additionally improve clinical outcomes. However, current therapeutic options have suboptimal efficacy and safety, highlighting a need for better rhythm-control strategies. In this review, we address the challenges related to antiarrhythmic drugs (AADs) and catheter ablation for rhythm control of AF, including significant recurrence rates and adverse side effects such as pro-arrhythmia. Furthermore, we discuss potential solutions to these challenges including novel tools, such as atrial-specific AADs and digital-twin-guided AF ablation. In particular, digital twins are a promising method to integrate a wide range of clinical data to address the heterogeneity in AF mechanisms. This may enable a more mechanism-based tailored approach that may overcome the limitations of previous precision medicine approaches based on individual biomarkers. However, several translational challenges need to be addressed before digital twins can be routinely applied in clinical practice, which we discuss at the end of this narrative review. Ultimately, the significant advances in the detection, understanding, and treatment of AF since its first ECG documentation are expected to help reduce the burden of this troublesome condition.","author":[{"family":"Schuijt","given":"Eva"},{"family":"Scherr","given":"Douglas"},{"family":"Plank","given":"Gernot"},{"family":"Schotten","given":"Ulrich"},{"family":"Heijman","given":"Jordi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1093/europace/euae304","URL":"https://doi.org/10.1093/europace/euae304","source":"pubmed"},{"id":"oa:W4378905919","type":"article-journal","title":"Optimizing Interfaces of Construction Processes by Digitalization Using the Example of Hospital Construction in Germany","abstract":"In hospital construction, additional challenges must be considered, such as an increased number of stakeholders and building trades, such as medical and laboratory technology. Due to the increasing requirements and challenges, associated construction processes are becoming more intricate. Especially for complex building types, the effects of this development are clearly noticeable and cause considerable disruptions to the construction process. A main difficulty constitutes the missing definition of the interfaces of building trades and participants. In the present study, interfaces in hospital construction were identified and analyzed by guided interviews with experts from the health sector. The qualitative content analysis, according to Mayring, was used for the evaluation to derive appropriate solution approaches. This paper presents the interfaces using the example of hospital construction in Germany and general approaches of optimization. Hereby, the digital method Building Information Modeling (BIM) plays a decisive role in the optimization of interfaces, especially in complex buildings. Furthermore, a task and building trade control matrix is required to better coordinate the interfaces. The identified approach intends to alleviate potential disputes and misunderstandings among stakeholders, as well as to improve time and financial predictability, which are particularly valuable during inflationary periods.","author":[{"family":"Hartmann","given":"Sabine"},{"family":"Gossmann","given":"Dirk"},{"family":"Kalmuk","given":"Suzan"},{"family":"Klemtalbert","given":"Katharina"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/buildings13061421","URL":"https://doi.org/10.3390/buildings13061421","source":"openalex"},{"id":"oa:W4390411875","type":"article-journal","title":"Digital Shadows: Infrastructuring the Internet of Production","abstract":"Abstract Digitization in the field of production is fragmented in very different domains, ranging from materials to production technology to process and business models. Each domain comes with specialized knowledge, often incorporated into mathematical models. This heterogeneity makes it hard to naively exploit advances in data-driven machine learning that could facilitate situation adaptation and experience transfer. Innovative combinations of model-driven and data-driven solutions must be invented but also made comparable and interoperable to avoid ending up in information silos. In future World Wide Labs (WWLs), experiences can be shared, aggregated, and used for innovation. WWLs will be complex, evolving socio-technical networks of interconnected devices, software, data stores, and humans as users and contributors of expert knowledge and feedback. Integrating a large number of research labs, engineering, and production sites requires a capable cross-domain Internet of Production (IoP) infrastructure. The IoP project claims Digital Shadows (DSs) to offer a shared conceptual foundation for infrastructuring the IoP. In engineering, DSs were introduced as the data provision link to Digital Twins, whereas in computer science, DSs generalize the well-established concept of database views. In this chapter, we elaborate on the roles of DSs in infrastructuring the IoP from three perspectives: analytic functionality, conceptual organization, and technical networking. As an example where an integrative DS-like approach is already highly successful, we showcase the approach and infrastructure of the process mining field.","author":[{"family":"Aalst","given":"Wil"},{"family":"Jarke","given":"Matthias"},{"family":"Koren","given":"István"},{"family":"Quix","given":"Christoph"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1007/978-3-031-44497-5_25","URL":"https://doi.org/10.1007/978-3-031-44497-5_25","source":"openalex"},{"id":"oa:W4389131498","type":"article-journal","title":"Characterization and Provenance of Carbonate Rocks for Quicklime and Dololime Production in Twin-Shaft Regenerative Kilns from the Arabian Peninsula and Neighboring Countries","abstract":"This study analyzes high-grade carbonate rocks from several strategic deposits in the Arabian Peninsula and neighboring countries. The rocks are used locally for quicklime and dololime production in twin-shaft regenerative kilns. Stable C-O-Sr isotopes, along with chemical, mineralogical-petrographic analyses, micropaleontological investigations, cathodoluminescence microscopy, organic carbon speciation, and electron paramagnetic resonance spectroscopy, were used to trace the provenance of these rocks from economically significant non-metallic deposits. The resulting database can help identify and differentiate industrial raw materials that may appear similar chemically and/or macroscopically but have different textures/microstructures that can affect the properties of the derived burnt lime products. Various technological tests, including slaking reactivity, sticking tendency at high-temperature (i.e., 1300 °C), and physico-mechanical behavior of the lime, were performed to evaluate their suitability and predict lime performance in twin-shaft regenerative kilns. Comparison of laboratory and plant results validated the resulting database.","author":[{"family":"Vola","given":"Gabriele"},{"family":"Ardit","given":"Matteo"},{"family":"Frijia","given":"Gianluca"},{"family":"Benedetto","given":"Francesco"},{"family":"Fornasier","given":"Flavio"},{"family":"Lugli","given":"Federico"},{"family":"Natali","given":"Claudio"},{"family":"Sarandrea","given":"Luca"},{"family":"Schmitt","given":"Katharina"},{"family":"Cipriani","given":"Anna"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/min13121500","URL":"https://doi.org/10.3390/min13121500","source":"openalex"},{"id":"oa:W4403963510","type":"article-journal","title":"Auxiliary Diagnosis of Children With Attention-Deficit/Hyperactivity Disorder Using Eye-Tracking and Digital Biomarkers: Case-Control Study","abstract":"BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in school-aged children. The lack of objective biomarkers for ADHD often results in missed diagnoses or misdiagnoses, which lead to inappropriate or delayed interventions. Eye-tracking technology provides an objective method to assess children's neuropsychological behavior. OBJECTIVE: The aim of this study was to develop an objective and reliable auxiliary diagnostic system for ADHD using eye-tracking technology. This system would be valuable for screening for ADHD in schools and communities and may help identify objective biomarkers for the clinical diagnosis of ADHD. METHODS: We conducted a case-control study of children with ADHD and typically developing (TD) children. We designed an eye-tracking assessment paradigm based on the core cognitive deficits of ADHD and extracted various digital biomarkers that represented participant behaviors. These biomarkers and developmental patterns were compared between the ADHD and TD groups. Machine learning (ML) was implemented to validate the ability of the extracted eye-tracking biomarkers to predict ADHD. The performance of the ML models was evaluated using 5-fold cross-validation. RESULTS: We recruited 216 participants, of whom 94 (43.5%) were children with ADHD and 122 (56.5%) were TD children. The ADHD group showed significantly poorer performance (for accuracy and completion time) than the TD group in the prosaccade, antisaccade, and delayed saccade tasks. In addition, there were substantial group differences in digital biomarkers, such as pupil diameter fluctuation, regularity of gaze trajectory, and fixations on unrelated areas. Although the accuracy and task completion speed of the ADHD group increased over time, their eye-movement patterns remained irregular. The TD group with children aged 5 to 6 years outperformed the ADHD group with children aged 9 to 10 years, and this difference remained relatively stable over time, which indicated that the ADHD group followed a unique developmental pattern. The ML model was effective in discriminating the groups, achieving an area under the curve of 0.965 and an accuracy of 0.908. CONCLUSIONS: The eye-tracking biomarkers proposed in this study effectively identified differences in various aspects of eye-movement patterns between the ADHD and TD groups. In addition, the ML model constructed using these digital biomarkers achieved high accuracy and reliability in identifying ADHD. Our system can facilitate early screening for ADHD in schools and communities and provide clinicians with objective biomarkers as a reference.","author":[{"family":"Liu","given":"Zhongling"},{"family":"Li","given":"Jinkai"},{"family":"Zhang","given":"Yuanyuan"},{"family":"Wu","given":"Dan"},{"family":"Huo","given":"Yanyan"},{"family":"Yang","given":"Jianxin"},{"family":"Zhang","given":"Musen"},{"family":"Dong","given":"Chuanfei"},{"family":"Jiang","given":"Luhui"},{"family":"Sun","given":"Ruohan"},{"family":"Zhou","given":"Ruoyin"},{"family":"Li","given":"Fei"},{"family":"Yu","given":"Xiaodan"},{"family":"Zhu","given":"Daqian"},{"family":"Guo","given":"Yao"},{"family":"Chen","given":"Jinjin"}],"issued":{"date-parts":[[2024]]},"DOI":"10.2196/58927","URL":"https://doi.org/10.2196/58927","source":"openalex"},{"id":"oa:W4324134927","type":"article-journal","title":"Non-Fungible Tokens: A Review","abstract":"Non Fungible Tokens (NFTs) are among the most promising technologies that have emerged in recent years. NFTs enable the efficient verification and ownership management of digital assets and therefore, offer the means to secure them. NFT is similar to blockchain that was first used by the cryptocurrency and then by numerous other technologies. At first, the NFT concept attracted the attention of the digital art community. However, NFT has the potential to enable a plethora of different applications and sce We present a review of the NFT technology. We describe the basic components of NFTs and how NFTs work. Then, we present and discuss the different applications of the NFTs. Finally, we discuss various challenges that the NFT technology must address in the future.","author":[{"family":"Hammi","given":"Badis"},{"family":"Zeadally","given":"Sherali"},{"family":"Pérez","given":"Alfredo"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/iotm.001.2200244","URL":"https://doi.org/10.1109/iotm.001.2200244","source":"openalex"},{"id":"oa:W4406771574","type":"article-journal","title":"Digital transformation of healthcare in the Russian Federation","abstract":"The history of creating and using various information and communication technologies for medicine and healthcare in Russia dates back to the 1950s–1960s, when the first scientific research was launched in the USSR and the first practical developments and proprietary technologies were created. The creation and application of the first software products was aimed at the collecting and automating statistical reports and partial automation of auxiliary departments, such as accounting, personnel departments, etc. In the early 2000s, Russia began to form a commercial market of specialized software for medicine and healthcare. In 2011, by order of the President and with the active participation of the professional community, the Russian Ministry of Health and Social Development launched a federal project to create a “Unified State Information System in Healthcare”, which became the starting point for the mass introduction of various information systems in the healthcare sector of the Russian Federation. In 2019, the federal project “Creation of a unified digital health care circuit based on Unified State Information System in Healthcare” was launched in Russia as part of the “Healthcare” national project. The implementation of the projects in 2011–2024 allowed to achieve high rates of application of medical information systems, as well as to move to projects on digital transformation of the industry, including the introduction of artificial intelligence technologies and various digital services and assistants for patients, doctors, and managers. The article presents a brief history of the development of digital projects, the current key directions in developing information technologies for healthcare and the results achieved so far.","author":[{"family":"Vankov","given":"VV"},{"family":"Artemova","given":"OR"},{"family":"Gusev","given":"AV"}],"issued":{"date-parts":[[2024]]},"DOI":"10.47093/3034-4700.2024.1.1.20-34","URL":"https://doi.org/10.47093/3034-4700.2024.1.1.20-34","source":"openalex"},{"id":"oa:W7165370556","type":"article-journal","title":"A Systematic Review of Digital Twin Technology Integration into Well and Reservoir Fluid Management Workflows for Real-Time Subsurface Monitoring","abstract":"Digital twin technology creates continuously updated virtual replicas of physical petroleum production systems through real-time data assimilation, offering transformative potential for well and reservoir fluid management through dynamic model-based decision support. This narrative review draws on published case literature and methodological evidence across petroleum engineering, digital technology, and organizational management within a five-dimension maturity framework covering data architecture completeness, model updating frequency, production optimization functionality, human-machine interface design, and organizational adoption evidence. IoT monitoring deployments, cloud infrastructure scaling, ensemble data assimilation, machine learning production forecasting, blockchain-enabled audit trails, and compliance governance from adjacent digital sectors provide organizational infrastructure analogues. Niger Delta multi-reservoir well performance evidence provides regional context for evaluating digital twin applicability in complex clastic settings. Key findings confirm that successful implementations combine physics-based reservoir simulation with data-driven components within governance frameworks providing appropriate human-machine decision allocation. A structured methods section, maturity model table, implementation summary table, and four-layer architecture framework diagram are provided.","author":[{"family":"Duvbiama-Owasanoye","given":"Omolara"},{"family":"Onwumere","given":"Alexander"},{"family":"Erhueh","given":"Ovie"}],"issued":{"date-parts":[[2023]]},"DOI":"10.62225/2583049x.2023.3.6.6433","URL":"https://doi.org/10.62225/2583049x.2023.3.6.6433","source":"openalex"},{"id":"oa:W4313446009","type":"article-journal","title":"Minding the gap between the front and back offices: A systemic analysis of the offshore oil and gas upstream supply chain for framing digital transformation","abstract":"Abstract The offshore oil and gas upstream supply chain operations are part of a complex system with many stakeholders and intricate relationships. Traditionally, these operations are managed manually, which leads to inefficiencies. Despite the innovative and engineering‐orientated approaches adopted in other technical operations of the industry, the supply chain activities remain unchanged, relying heavily on legacy systems. However, cutting‐edge technology opportunities are available for adoption in supply chain management systems in the oil and gas industry. Such a transformative upgrade relies on first understanding the operational inefficiencies and preparing an accurate picture for how these operations should be performed. This study adopts a systemic approach to examine the oil and gas offshore supply chain operations of a case company to identify areas for improvement. The objective is to address the following research questions: (1) what is the current “AS‐IS” supply chain operations support; and (2) what is the desired “TO‐BE” state for these operations. This research adopts a soft systems lenses applied in an action research project to capture and analyze existing operations. The research revealed that information exchange is a major barrier, and that technology and organizational gaps are the primary hindrance for a digital transformation. The conclusion is that there is a need for a higher level of data exchange and increased data quality in any proposed transformation.","author":[{"family":"Czachorowski","given":"Karen"},{"family":"Haskins","given":"Cecilia"},{"family":"Mansouri","given":"Mo"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1002/sys.21652","URL":"https://doi.org/10.1002/sys.21652","source":"openalex"},{"id":"oa:W4324291262","type":"article-journal","title":"Design of Digital Twin System for DC Contactor Condition Monitoring","abstract":"Digital twin technology provides insight to solve the problems of state monitoring and life evaluation of electromagnetic devices. When performing digital twin system design, it is necessary to face the challenges of multi-physical field and multi-scale modeling, dynamic time-varying parameters, and data interaction. In this paper, a digital twin system design scheme for DC contactors is proposed. The modeling approach describes and defines the model at three levels: geometric, mechanistic, and data. Based on the constructed model, the knowledge acquisition and data mapping processes of the contactor operation process are investigated. In addition, the fidelity assessment method of the digital twin model is given in order to evaluate the validity of the constructed model. The empirical validation shows that the proposed digital twin high-fidelity modeling method is effective and the model can be evaluated.","author":[{"family":"Zhang","given":"Bo"},{"family":"Zhang","given":"Miao"},{"family":"Dong","given":"Ting"},{"family":"Lu","given":"Mingquan"},{"family":"Li","given":"Haitao"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/tia.2023.3256978","URL":"https://doi.org/10.1109/tia.2023.3256978","source":"openalex"},{"id":"oa:W4390659370","type":"article-journal","title":"Confluence of Digital Twins and Metaverse for Consumer Electronics: Real World Case Studies","abstract":"Digital twins and Metaverse have independent applications across several industries, such as manufacturing, art, construction, healthcare, transportation, automotive, and aerospace, but they can be seamlessly integrated, thanks to their mutually supportive and complementary features, enabling several highly improvised applications. For the first time, we explore the impact of the confluence of digital twins and Metaverse on the consumer electronics industry and elaborately describe the concerning applications. To understand the practicality and feasibility of the proposed applications, we implemented three case studies: robot-based digital twin-enabled remote consumer electronics manufacturing, digital twin-enabled consumer electronics showroom experience in the Metaverse, and digital twin-aided collaborative design and development of consumer electronics. We have built the case studies using actual hardware and software related to digital twins and Metaverse, like Meta Quest 2 and Harfang3D. We have created a digital twin of Reachy with the help of URDF (Unified Robot Description Format) files and modeled the translation of real-world movements to virtual-world movements using inverse kinematics.","author":[{"family":"Sai","given":"Siva"},{"family":"Prasad","given":"Manish"},{"family":"Upadhyay","given":"Aniket"},{"family":"Chamola","given":"Vinay"},{"family":"Herencsár","given":"Norbert"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/tce.2024.3351441","URL":"https://doi.org/10.1109/tce.2024.3351441","source":"openalex"},{"id":"oa:W4402300333","type":"article-journal","title":"Blockchain-Aided Digital Twin Offloading Mechanism in Space-Air-Ground Networks","abstract":"Space-air-ground (SAG) integrated heterogenous networks can provide pervasive intelligence services for various ground users (GUs). The network can help cellular networks release network resources and alleviate congestion pressure. Moreover, one important application of the network is that digital twin (DT) can enable nearly-instant wireless connectivity and highly-reliable data mapping from physical systems to digital world in a real-time fashion. The integration of SAG and DT (SAG-DT) reduces the gap between data analysis and physical status, which can further realize robust edge intelligence services. However, the random computation task arrival, time-varying channel gains, and the lack of mutual trust among ground GUs hinder better quality of service in the promising SAG-DT network. In this paper, we envision a SAG-DT integrated blockchain model to transfer the task data to the aerial network, and then perform the computation offloading, energy harvesting and privacy protection. Moreover, we propose a Lyapunov-aided multi-agent deep federated reinforcement learning (MADFRL) algorithm framework to optimize the CPU cycle frequency, the size of block, the number of DTs, and harvested energy to minimize the execution costs and privacy overhead. Extensive performance analyses indicate that the MADFRL algorithm framework can strengthen the data privacy via blockchain verification mechanism and approaches the optimal performance on the basis of lower computation complexity. Finally, simulation results corroborate that the proposed Lyapunov-aided MADFRL algorithm is superior to advanced benchmarks in terms of execution costs, task processing quantities and privacy overhead.","author":[{"family":"Gong","given":"Yongkang"},{"family":"Yao","given":"Haipeng"},{"family":"Xiong","given":"Zehui"},{"family":"Chen","given":"CLP"},{"family":"Niyato","given":"Dusit"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/tmc.2024.3455417","URL":"https://doi.org/10.1109/tmc.2024.3455417","source":"openalex"},{"id":"oa:W4389203599","type":"article-journal","title":"Reshaping the Digital Twin Construct with Levels of Digital Twinning (LoDT)","abstract":"While digital twins (DTs) have achieved significant visibility, they continue to face a problem of lack of harmonisation regarding their interpretation and definition. This diverse and interchangeable use of terms makes it challenging for scientific activities to take place and for organisations to grasp the existing opportunities and how can these benefit their businesses. This article aims to shift the focus away from debating a definition for a DT. Instead, it proposes a conceptual approach to the digital twinning of engineering physical assets as an ongoing process with variable complexity and evolutionary capacity over time. To accomplish this, the article presents a functional architecture of digital twinning, grounded in the foundational elements of the DT, to reflect the various forms and levels of digital twinning (LoDT) of physical assets throughout their life cycles. Furthermore, this work presents UNI-TWIN—a unified model to assist organisations in assessing the LoDT of their assets and to support investment planning decisions. Three case studies from the road and rail sector validate its applicability. UNI-TWIN helps to redirect the discussion around DTs and emphasise the opportunities and challenges presented by the diverse realities of digital twinning, namely in the context of engineering asset management.","author":[{"family":"Vieira","given":"João"},{"family":"Martins","given":"João"},{"family":"Almeida","given":"N"},{"family":"Patrício","given":"Hugo"},{"family":"Morgado","given":"João"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/asi6060114","URL":"https://doi.org/10.3390/asi6060114","source":"openalex"},{"id":"oa:W4405584294","type":"article-journal","title":"Applications of Artificial Intelligence-Based Patient Digital Twins in Decision Support in Rehabilitation and Physical Therapy","abstract":"Artificial intelligence (AI)-based digital patient twins have the potential to make breakthroughs in research and clinical practices in rehabilitation. They make it possible to personalise treatment plans by simulating different rehabilitation scenarios and predicting patient-specific outcomes. DTs can continuously monitor a patient’s progress, adjusting therapy in real time to optimise recovery. They also facilitate remote rehabilitation by providing virtual models that therapists can use to guide patients without having to be physically present. Digital twins (DTs) can help identify potential complications or failures at an early stage, enabling proactive interventions. They also support the training of rehabilitation professionals by offering realistic simulations of different patient conditions. They can also increase patient engagement by visualising progress and potential future outcomes, motivating adherence to therapy. They enable the integration of multidisciplinary care, providing a common platform for different professionals to collaborate and improve rehabilitation strategies. The article aims to trace the current state of knowledge, research priorities, and research gaps in order to properly guide further research and shape decision support in rehabilitation.","author":[{"family":"Mikołajewska","given":"Emilia"},{"family":"Masiak","given":"Jolanta"},{"family":"Mikołajewski","given":"Dariusz"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/electronics13244994","URL":"https://doi.org/10.3390/electronics13244994","source":"openalex"},{"id":"oa:W4380685702","type":"article-journal","title":"Digital-Twin-Driven AGV Scheduling and Routing in Automated Container Terminals","abstract":"Automated guided vehicle (AGV) scheduling and routing are critical factors affecting the operation efficiency and transportation cost of the automated container terminal (ACT). Searching for the optimal AGV scheduling and routing plan are effective and efficient ways to improve its efficiency and reduce its cost. However, uncertainties in the physical environment of ACT can make it challenging to determine the optimal scheduling and routing plan. This paper presents the digital-twin-driven AGV scheduling and routing framework, aiming to deal with uncertainties in ACT. By introducing the digital twin, uncertain factors can be detected and handled through the interaction and fusion of physical and virtual spaces. The improved artificial fish swarm algorithm Dijkstra (IAFSA-Dijkstra) is proposed for the optimal AGV scheduling and routing solution, which will be verified in the virtual space and further fed back to the real world to guide actual AGV transport. Then, a twin-data-driven conflict prediction method is proposed to predict potential conflicts by constantly comparing the differences between physical and virtual ACT. Further, a conflict resolution method based on the Yen algorithm is explored to resolve predicted conflicts and drive the evolution of the scheme. Case study examples show that the proposed method can effectively improve efficiency and reduce the cost of AGV scheduling and routing in ACT.","author":[{"family":"Lou","given":"Ping"},{"family":"Zhong","given":"Yutong"},{"family":"Hu","given":"Jiwei"},{"family":"Fan","given":"Chuannian"},{"family":"Chen","given":"Xiao"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/math11122678","URL":"https://doi.org/10.3390/math11122678","source":"openalex"},{"id":"oa:W4389105099","type":"article-journal","title":"A Federated Digital Twin Framework for UAVs-Based Mobile Scenarios","abstract":"With the development of communication networks and Artificial Intelligence (AI) technologies, Digital Twin (DT) now emerges to support various applications such as engineering, monitoring, controlling, healthcare and the optimization of cyber-physical systems. There is an increasing demand to create DTs that can represent physical entities for improving operational efficiency. A conventional DT consists of monitoring, imitation, and feedback control. However, conventional DTs cannot ensure efficient real-time imitation due to the high dynamics of physical systems such as UAV-based target tracking scenario. To address this issue, we propose a federated DT framework to support the imitation of mobile systems. It can guarantee real-time and accurate imitations under the prerequisite of comprehensive information acquired by a cooperative collection algorithm with the aid of UAVs. The framework can rapidly aggregate local DT models using an attention-based mechanism to improve mobile imitation accuracy. Additionally, we propose a multimodal-based DT inspection algorithm that can correct the postures of UAVs affected by winds for reliable imitations. We implement the framework in Gazebo. Our system simulations demonstrate the efficiency of the proposed federated DT framework. Our solution can reduce the imitation latency by an average of 68.4%, meanwhile, can improve the imitation accuracy by 16.4% on average when compared to traditional centralized and distributed imitation schemes.","author":[{"family":"Zhou","given":"Longyu"},{"family":"Leng","given":"Supeng"},{"family":"Wang","given":"Qing"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/tmc.2023.3335386","URL":"https://doi.org/10.1109/tmc.2023.3335386","source":"openalex"},{"id":"oa:W4365801565","type":"article-journal","title":"Digital-Twins-Based Internet of Robotic Things for Remote Health Monitoring of COVID-19 Patients","abstract":"The deadly coronavirus disease (COVID-19) has highlighted the importance of remote health monitoring (RHM). The digital twins (DTs) paradigm enables RHM by creating a virtual replica that receives data from the physical asset, representing its real-world behavior. However, DTs use passive internet of things (IoT) sensors, which limit their potential to a specific location or entity. This problem can be addressed by using the internet of robotic things (IoRT), which combines robotics and IoT, allowing the robotic things (RTs) to navigate in a particular environment and connect to IoT devices in the vicinity. Implementing DTs in IoRT, creates a virtual replica (virtual twin) that receives real-time data from the physical RT (physical twin) to mirror its status. However, DTs require a user interface for real-time interaction and visualization. Virtual reality (VR) can be used as an interface due to its natural ability to visualize and interact with DTs. This research proposes a real-time system for RHM of COVID-19 patients using the DTs-based IoRT and VR-based user interface. It also presents and evaluates robot navigation performance, which is vital for remote monitoring. The virtual twin (VT) operates the physical twin (PT) in the real environment (RE), which collects data from the patient-mounted sensors and transmits it to the control service to visualize in VR for medical examination. The system prevents direct interaction of medical staff with contaminated patients, protecting them from infection and stress. The experimental results verify the monitoring data quality (accuracy, completeness, timeliness) and high accuracy of PT’s navigation.","author":[{"family":"Khan","given":"Sangeen"},{"family":"Ullah","given":"Sehat"},{"family":"Khan","given":"Habib"},{"family":"Rehman","given":"Inam"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/jiot.2023.3267171","URL":"https://doi.org/10.1109/jiot.2023.3267171","source":"openalex"},{"id":"oa:W4387914700","type":"article-journal","title":"DT-SFC-6G: Digital Twins Assisted Service Function Chains in Softwarized 6G Networks for Emerging V2 X","abstract":"Vehicle-to-X (V2X) with specific user-defined performance metrics emerges as one vital application scenario in sixth generation (6G) networks. According to released reports and whitepapers, 6G networks are designed to have softwarization attributes. Through softwarization, tailored V2X services, constituted by softwarized (resource and function) blocks, can be deployed on top of underlying network appliances. Chaining these softwarized blocks in predefined order is abbreviated as service function chain (SFC). However, existing SFC studies are conducted on the assumption that no performance descending of network appliance exists. Due to inherent shortcomings of softwarization, the softwarized 6G network appliances will bring about performance descending, compared with dedicated hardware. Emerging digital twin (DT) technology paves one way for studying SFC placement and scheduling without worrying about performance descending. By creating a digital replica of softwarized 6G networks, tailored SFCs can be implemented efficiently. This article investigates the SFC placement and scheduling in DT-em-powered softwarized 6G networks for emerging V2X. First, a novel business model and a problem model are presented. Next, one framework design, abbreviated as DT-SFC-6G, is proposed, including all technical details. The DT-SFC-6G design guarantees to provide efficient placement and scheduling solution per SFC request and feedback SFC solution and digital replica's state to softwarized 6G networks in time. Furthermore, experimental work of DT-SFC-6G is conducted. A variety of SFC algorithms, inserted in the DT-SFC-6G design, are evaluated in order to highlight the feasibility and merits of DT-SFC-6G. Finally, three most promising directions of SFC in DT-empowered softwarized 6G networks are selected for discussions.","author":[{"family":"Cao","given":"Haotong"},{"family":"Lin","given":"Zhi"},{"family":"Yang","given":"Longxiang"},{"family":"Wang","given":"Jiangzhou"},{"family":"Guizani","given":"Mohsen"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/mnet.009.2300028","URL":"https://doi.org/10.1109/mnet.009.2300028","source":"openalex"},{"id":"oa:W4389056599","type":"article-journal","title":"Research progress and prospect of digital twin in bridge engineering","abstract":"The concept of digital twins in bridge engineering is still vague and even confused with the Bridge Information Model (BrIM). Therefore, this study provides a detailed review of 42 papers related to digital twins in bridge engineering, focusing on a proper definition, key features and creation techniques for bridge digital twin (BDT). The paper also compares BDT and BrIM from the perspectives of their elements, features, fidelity, services provided, and degree of development. The applications of BDT at different life cycle stages are identified, and the related technologies are analyzed in detail. The results show that the research clusters of BDT are divided into geometric model generation, finite element model updating, and management and are focused on the operation and maintenance phase while lacking attention in the design and construction phase. Besides, a reference framework of BDT based on the life cycle of bridges is proposed, and directions for future research are suggested.","author":[{"family":"Yang","given":"Yuanliang"},{"family":"Zhu","given":"Yichen"},{"family":"Cai","given":"CS"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1177/13694332231218764","URL":"https://doi.org/10.1177/13694332231218764","source":"openalex"},{"id":"oa:W4382133803","type":"article-journal","title":"Development and Application of Digital Twin–BIM Technology for Bridge Management","abstract":"The concept and technology of a digital twin, which represent a replica of a real object in a virtual space called Industry 4.0, are widely used across all industries and purposes. Similarly, in the architecture, engineering, and construction (AEC) industries, there is an urgent need to develop a technology called BIM, a form of digital twin based on 3D models, for the purpose of improving productivity and reducing costs. Bridge structures are required to be safe, reliable, and durable, and various research studies have been conducted on maintenance and repair strategies and their development by fusing health monitoring and digital twins. In this study, we explore the development of digital twin–BIM technology and demonstrate its various applications for an existing bridge structure where the implementation of health monitoring is planned. Moreover, we evaluate the characteristics of the structural performance of the bridge structure using digital twin–BIM technology.","author":[{"family":"Tita","given":"Elfrido"},{"family":"Watanabe","given":"Gakuho"},{"family":"Shao","given":"Peilun"},{"family":"Arii","given":"Kenji"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/app13137435","URL":"https://doi.org/10.3390/app13137435","source":"openalex"},{"id":"oa:W4393071653","type":"article-journal","title":"Aircraft Structural Design and Life-Cycle Assessment through Digital Twins","abstract":"Numerical modeling tools are essential in aircraft structural design, yet they face challenges in accurately reflecting real-world behavior due to factors like material properties scatter and manufacturing-induced deviations. This article addresses the potential impact of digital twins on overcoming these limitations and enhancing model reliability through advanced updating techniques based on machine learning. Digital twins, which are virtual replicas of physical systems, offer a promising solution by integrating sensor data, operational inputs, and historical records. Machine learning techniques enable the calibration and validation of models, combining experimental inputs with simulations through continuous updating processes that refine digital twins, improving their accuracy in predicting structural behavior and performance throughout an aircraft’s life cycle. These refined models enable real-time monitoring and precise damage assessment, supporting decision making in diverse contexts. By integrating sensor data and updating techniques, digital twins contribute to improved design and maintenance operations by providing valuable insights into structural health, safety, and reliability. Ultimately, this approach leads to more efficient and safer aviation operations, demonstrating the potential of digital twins to revolutionize aircraft structural analysis and design. This article explores various advancements and methodologies applicable to structural assessment, leveraging machine learning tools. These include the utilization of physics-informed neural networks, which enable the handling of diverse uncertainties. Such approaches empower a more informed and adaptive strategy, contributing to the assurance of structural integrity and safety in aircraft structures throughout their operational life.","author":[{"family":"Tavares","given":"Sérgio"},{"family":"Ribeiro","given":"João"},{"family":"Ribeiro","given":"Bruno"},{"family":"Castro","given":"PMST"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/designs8020029","URL":"https://doi.org/10.3390/designs8020029","source":"openalex"},{"id":"oa:W4391540890","type":"article-journal","title":"Design and research of digital twin platform for handicraft intangible cultural heritage -Yangxin Cloth Paste","abstract":"Abstract In the context of the 5G era, the rapid development of digital technology and its integration with intangible cultural heritage (ICH) can facilitate the dynamic transmission of ICH.The research purposes to construct a virtual experience platform for handmade ICH using the handmade ICH of East Hubei Province in China—Yangxin Cloth Paste as a case study through Digital Twin technology. It explores the application of digital twin technology in the field of handmade ICH transmission and aids the dynamic transmission of handmade ICH. Firstly, the research collected tangible and procedural data of the Yangxin Cloth Paste. By using photogrammetric techniques, a model of the handicraft was built and an effective digital twin conversion procedure was designed. Next, the research set up a framework for a digital twin platform for handmade ICH, designing systems for the production, display, and transaction of ICH handicrafts. Lastly, its effectiveness was validated by user satisfaction evaluation guiding subsequent optimization direction. The platform innovatively uses digital twin technology to help users visualize handicraft ICH. Through the combination of digital twin technology and virtual reality technology, it creates a realistic virtual reality experience of ICH of handicraft, stimulates users' interest in exploring ICH of handicraft, and contributes to the process protection, dissemination and development of handicraft ICH.","author":[{"family":"Li","given":"Min"},{"family":"Xu","given":"Shengtao"},{"family":"Tang","given":"Jie"},{"family":"Chen","given":"Wenfeng"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1186/s40494-024-01161-0","URL":"https://doi.org/10.1186/s40494-024-01161-0","source":"openalex"},{"id":"oa:W4316661322","type":"article-journal","title":"Task-Efficiency Oriented V2X Communications: Digital Twin Meets Mobile Edge Computing","abstract":"Digital Twin (DT) has emerged as an enabling technology for sixth generation (6G) vehicle-to-everything (V2X) communications. However, there are two crucial issues on leveraging DT for 6G V2X communications. First, what kind of DT capabilities can be combined with the 6G V2X networks? Second, how can we transform the DT capabilities into practical V2X network performance gain? Motivated to solve these problems, this article investigates the DT capabilities under a DT and mobile edge computing empowered 6G V2X network architecture. Specifically, three DT capabilities are presented: First, strengthening the human-machine interaction, via driving behavior analysis; second, improving traffic safety via knowledge-based vehicle fault diagnosis; and third, analyzing spatial-temporal traffic characteristics, via data aggregation. Furthermore, we investigate two case studies for illustrating how to utilize DT capabilities to perform task-efficiency oriented V2X network scheduling. In the first case study, the driver behavior analysis result is combined with the V2X channel scheduling strategy. In the second case study, a deep reinforcement learning-based vehicle merging decision is devised in the DT domain. Then, a coalition-based V2X channel scheduling strategy is proposed, to help accomplish the vehicle merging decision task. Finally, we evaluate the performance of our proposed task-efficiency oriented V2X channel scheduling schemes, and highlight the future research directions.","author":[{"family":"Cai","given":"Guoqiang"},{"family":"Fan","given":"Bo"},{"family":"Dong","given":"Yiwei"},{"family":"Li","given":"Tongfei"},{"family":"Yuan","given":"Wu"},{"family":"Zhang","given":"Yan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/mwc.012.2200465","URL":"https://doi.org/10.1109/mwc.012.2200465","source":"openalex"},{"id":"oa:W4387098043","type":"article-journal","title":"A digital twin for DNA data storage based on comprehensive quantification of errors and biases","abstract":"Archiving data in synthetic DNA offers unprecedented storage density and longevity. Handling and storage introduce errors and biases into DNA-based storage systems, necessitating the use of Error Correction Coding (ECC) which comes at the cost of added redundancy. However, insufficient data on these errors and biases, as well as a lack of modeling tools, limit data-driven ECC development and experimental design. In this study, we present a comprehensive characterisation of the error sources and biases present in the most common DNA data storage workflows, including commercial DNA synthesis, PCR, decay by accelerated aging, and sequencing-by-synthesis. Using the data from 40 sequencing experiments, we build a digital twin of the DNA data storage process, capable of simulating state-of-the-art workflows and reproducing their experimental results. We showcase the digital twin's ability to replace experiments and rationalize the design of redundancy in two case studies, highlighting opportunities for tangible cost savings and data-driven ECC development.","author":[{"family":"Gimpel","given":"Andreas"},{"family":"Stark","given":"Wendelin"},{"family":"Heckel","given":"Reinhard"},{"family":"Grass","given":"Robert"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1038/s41467-023-41729-1","URL":"https://doi.org/10.1038/s41467-023-41729-1","source":"openalex"},{"id":"oa:W4319297859","type":"article-journal","title":"Feasibility of Digital Twins to Manage the Operational Risks in the Production of a Ready-Mix Concrete Plant","abstract":"The ready-mix concrete supply chain is highly disruptive due to its product perishability and Just-in-Time (JIT) production style. A lack of technology makes the ready-mix concrete (RMC) industry suffer from frequent production failures, ultimately causing high customer dissatisfaction and loss of revenues. In this paper, we propose the first-ever digital twin (DT) system in the RMC industry that can serve as a decision support tool to manage production risk efficiently and effectively via predictive maintenance. This study focuses on the feasibility of digital twins for the RMC industry in three main areas holistically: (1) the technical feasibility of the digital twin system for ready-mix concrete plant production risk management; (2) the business value of the proposed product to the construction industry; (3) the challenges of implementation in the real-world RMC industry. The proposed digital twin system consists of three main phases: (1) an IoT system to get the real-time production cycle times; (2) a digital twin operational working model with descriptive analytics; (3) an advanced analytical dashboard with predictive analytics to make predictive maintenance decisions. Our proposed digital twin solution can provide efficient and interpretable predictive maintenance insights in real time based on anomaly detection, production bottleneck identification, process disruption forecast and cycle time analysis. Finally, this study emphasizes that state-of-the-art solutions such as digital twins can effectively manage the production risks of ready-mix concrete plants by automatically detecting and predicting the bottlenecks without waiting until a production failure happens to react.","author":[{"family":"Weerapura","given":"Vihan"},{"family":"Sugathadasa","given":"PTRS"},{"family":"Silva","given":"MMD"},{"family":"Nielsen","given":"Izabela"},{"family":"Thibbotuwawa","given":"Amila"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/buildings13020447","URL":"https://doi.org/10.3390/buildings13020447","source":"openalex"},{"id":"oa:W4399533123","type":"article-journal","title":"Digital twin-driven prognostics and health management for industrial assets","abstract":"As a facilitator of smart upgrading, digital twin (DT) is emerging as a driving force in prognostics and health management (PHM). Faults can lead to degradation or malfunction of industrial assets. Accordingly, DT-driven PHM studies are conducted to improve reliability and reduce maintenance costs of industrial assets. However, there is a lack of systematic research to analyze and summarize current DT-driven PHM applications and methodologies for industrial assets. Therefore, this paper first analyzes the application of DT in PHM from the application field, aspect, and hierarchy at application layer. The paper next deepens into the core and mechanism of DT in PHM at theory layer. Then enabling technologies and tools for DT modeling and DT system are investigated and summarized at implementation layer. Finally, observations and future research suggestions are presented.","author":[{"family":"Xiao","given":"Bin"},{"family":"Zhong","given":"Jingshu"},{"family":"Bao","given":"Xiangyu"},{"family":"Chen","given":"Liang"},{"family":"Bao","given":"Jinsong"},{"family":"Zheng","given":"Yu"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1038/s41598-024-63990-0","URL":"https://doi.org/10.1038/s41598-024-63990-0","source":"openalex"},{"id":"oa:W4362683559","type":"article-journal","title":"Artificial Intelligence-Driven Digital Twin of a Modern House Demonstrated in Virtual Reality","abstract":"A digital twin is a powerful tool that can help monitor and optimize physical assets in real-time. Simply put, it is a virtual representation of a physical asset, enabled through data and simulators, that can be used for a variety of purposes such as prediction, monitoring, and decision-making. However, the concept of digital twin can be vague and difficult to understand, which is why a new concept called \"capability level\" has been introduced. This concept categorizes digital twins based on their capability and defines a scale from zero to five, with each level indicating an increasing level of functionality. These levels are standalone, descriptive, diagnostic, predictive, prescriptive, and autonomous. By understanding the capability level of a digital twin, we can better understand its potential and limitations. To demonstrate the concepts, we use a modern house as an example. The house is equipped with a range of sensors that collect data about its internal state, which can then be used to create digital twins of different capability levels. These digital twins can be visualized in virtual reality, allowing users to interact with and manipulate the virtual environment. The current work not only presents a blueprint for developing digital twins but also suggests future research directions to enhance this technology. Digital twins have the potential to transform the way we monitor and optimize physical assets, and by understanding their capabilities, we can unlock their full potential.","author":[{"family":"Elfarri","given":"Elias"},{"family":"Rasheed","given":"Adil"},{"family":"San","given":"Omer"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/access.2023.3265191","URL":"https://doi.org/10.1109/access.2023.3265191","source":"openalex"},{"id":"oa:W4386766970","type":"article-journal","title":"GNN-Based Power Allocation and User Association in Digital Twin Network for the Terahertz Band","abstract":"The digital twin (DT) and terahertz (THz) wireless communication technologies have promoted the innovative development and application of 6G networks. Combining DT can obtain efficient, collaborative, and intelligent management for THz wireless networks. However, the conflicts between large amounts of twin data and limited network resources make it difficult to improve the performance of DT networks. In this paper, a DT architecture for THz wireless networks is proposed, which maps a physical network in the THz band into a virtual DT network and represents the DT network as a graph structure. Furthermore, the THz channel model is provided, and the resource management problem with weighted mean rate as the optimization objective is proposed, which is transformed into a graph optimization problem. Based on this, a distributed message propagation algorithm is proposed, which uses the graph neural network to provide a solution. Simulation results show that the proposed scheme improves the weighted mean rate of the DT network for the THz band and outperforms the benchmark methods. It is also proved that the proposed distributed message propagation algorithm is scalable and can maintain good performance under different conditions.","author":[{"family":"Zhang","given":"Haijun"},{"family":"Ma","given":"Xu"},{"family":"Liu","given":"Xiangnan"},{"family":"Li","given":"Linpei"},{"family":"Sun","given":"Kai"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/jsac.2023.3313192","URL":"https://doi.org/10.1109/jsac.2023.3313192","source":"openalex"},{"id":"oa:W4403616133","type":"article-journal","title":"Enhancing internal supply chain management in manufacturing through a simulation-based digital twin platform","abstract":"• Simulation-based digital twin platform for internal supply chain management. • Exploiting real-time simulation for multi-plant production planning. • Ease of use, flexibility and scalability for company competitiveness. • Data integration and standardization for efficient information flow. • Case Study in the Oil&Gas Sector for testing and validation. Digital Twin (DT) technology is profoundly changing the manufacturing landscape and supply chain management with its ability to create real-time digital replicas of physical processes, allowing for enhanced monitoring and optimized decision-making. However, the analysis of scientific literature reveals that further efforts are needed to spread the use of Industry 4.0 technologies, in the specific context of Internal Supply Chains (ISCs). The main aim of this study is to design, develop test and validate a multi-plant Simulation-Based DT production planning platform for ISCs management. A modular architecture is adopted, and the focus is on a Simulation-Based Digital Twin module, which uses an object-oriented structure and enables what-if analyses, involving several scheduling rules and ISC configurations. The proposed solution ensures flexibility and scalability, two crucial features in a constantly evolving market environment. The platform is tested and validated through a case study, involving a corporate group in the Oil & Gas manufacturing sector, which needs to improve the ISC performance, under a Make-To-Order production strategy. The comparison with a baseline scenario, where the platform is not adopted, shows that the proposed approach can significantly reduce the average flow time, the average tardiness, the number of late orders. This study has important practical implications because enables proactive and smart decision-making, aimed at resource optimization and continuous improvement, through predictive analytics and scenario analysis.","author":[{"family":"Cimino","given":"Antonio"},{"family":"Longo","given":"Francesco"},{"family":"Mirabelli","given":"Giovanni"},{"family":"Solina","given":"Vittorio"},{"family":"Veltri","given":"Pierpaolo"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.cie.2024.110670","URL":"https://doi.org/10.1016/j.cie.2024.110670","source":"openalex"},{"id":"oa:W4394996194","type":"article-journal","title":"Digital twin for production estimation, scheduling and real-time monitoring in offsite construction","abstract":"The variability in production operations in offsite construction factories undermines the effectiveness of using average production rates for estimating production time and scheduling. In fact, production schedules based on average rates often exhibit significant deviations from actual production. This study proposes a digital twin for production estimation, scheduling, and real-time monitoring in offsite construction. By integrating computer vision, ultrasonic sensors, machine learning-based prediction models, and 3D simulation, the digital twin continuously collects time data from the shop floor, estimates cycle times, simulates operations, generates production schedules, virtually mirrors operations in real time, and enables the generation of updated schedules based on actual progress. In a case application to a wall framing workstation, the production schedule generated using the digital twin for the framing of wall panels during a work shift achieves an 81% reduction in deviation from actual production time compared to the conventional fixed-rate method commonly used in current practice.","author":[{"family":"Alsakka","given":"Fatima"},{"family":"Yu","given":"Haitao"},{"family":"El-Chami","given":"Ibrahim"},{"family":"Hamzeh","given":"Farook"},{"family":"Alhussein","given":"Mohamed"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.cie.2024.110173","URL":"https://doi.org/10.1016/j.cie.2024.110173","source":"openalex"},{"id":"oa:W4391893371","type":"article-journal","title":"Forum on immune digital twins: a meeting report","abstract":"Medical digital twins are computational models of human biology relevant to a given medical condition, which are tailored to an individual patient, thereby predicting the course of disease and individualized treatments, an important goal of personalized medicine. The immune system, which has a central role in many diseases, is highly heterogeneous between individuals, and thus poses a major challenge for this technology. In February 2023, an international group of experts convened for two days to discuss these challenges related to immune digital twins. The group consisted of clinicians, immunologists, biologists, and mathematical modelers, representative of the interdisciplinary nature of medical digital twin development. A video recording of the entire event is available. This paper presents a synopsis of the discussions, brief descriptions of ongoing digital twin projects at different stages of progress. It also proposes a 5-year action plan for further developing this technology. The main recommendations are to identify and pursue a small number of promising use cases, to develop stimulation-specific assays of immune function in a clinical setting, and to develop a database of existing computational immune models, as well as advanced modeling technology and infrastructure.","author":[{"family":"Laubenbacher","given":"Reinhard"},{"family":"Adler","given":"Fred"},{"family":"An","given":"Gary"},{"family":"Castiglione","given":"Filippo"},{"family":"Eubank","given":"Stephen"},{"family":"Fonseca","given":"Luís"},{"family":"Glazier","given":"James"},{"family":"Helikar","given":"Tomáš"},{"family":"Jetttilton","given":"Marti"},{"family":"Kirschner","given":"Denise"},{"family":"Macklin","given":"Paul"},{"family":"Mehrad","given":"Borna"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1038/s41540-024-00345-5","URL":"https://doi.org/10.1038/s41540-024-00345-5","source":"openalex"},{"id":"oa:W4386158973","type":"article-journal","title":"Digital Twin Modeling of Power Electronic Converters","abstract":"A real-time digital twin of a DC-DC boost converter is developed and verified experimentally using various load scenarios. The developed DT can be used to provide a comprehensive understanding of the system's behavior and support improved decision-making and predictive maintenance. Moreover, this digital twin can be integrated into a larger digital twin system that represents the entire power system hardware. By connecting these digital twins together, a complete digital model of the power system can be created. Results confirm the capability of the developed digital twin and its hardware to reflect the electrical behaviors of the physical twin in real-time. The maximum deviation between the digital twin and the physical twin was ±2%.","author":[{"family":"Sado","given":"Kerry"},{"family":"Hannum","given":"Jack"},{"family":"Booth","given":"Kristen"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/ests56571.2023.10220465","URL":"https://doi.org/10.1109/ests56571.2023.10220465","source":"openalex"},{"id":"oa:W4392173067","type":"article-journal","title":"Underwater Simulators Analysis for Digital Twinning","abstract":"The underwater environment is among Earth’s most challenging domains, where failures incur elevated risks and costs for both technology and human endeavors. As a consequence, forecasting the behavior of mechatronic systems through simulation has become increasingly important. Underwater Robotic Simulators (URSs) allow researchers and engineers to safely develop and assess submarine systems. The selection of an appropriate URS from the list of available tools is not trivial. Moreover, the integration of this software with the Digital Twin (DT) concept presents numerous advantages, particularly the ability to link the simulated environment with actual underwater vehicles. This connection is facilitated by performing validation and simulation tests using Software In the Loop (SIL), Model In the Loop, and Hardware In the Loop (HIL) techniques. This paper extensively reviews URSs in the context of both robots and unmanned vehicles in light of the DT paradigm. The article critically examines distinctions among existing URSs, offering valuable insights to aid researchers in selecting the most fitting tool for their specific applications. Additionally, the review explores the practical applications of the identified simulators, categorizing their usage across different fields to illuminate the preferences within the scientific community and showcase prominent case studies.","author":[{"family":"Ciuccoli","given":"Nicolò"},{"family":"Screpanti","given":"Laura"},{"family":"Scaradozzi","given":"David"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/access.2024.3370443","URL":"https://doi.org/10.1109/access.2024.3370443","source":"openalex"},{"id":"oa:W4321354548","type":"article-journal","title":"Digital twins for selecting the optimal ventilated strawberry packaging based on the unique hygrothermal conditions of a shipment from farm to retailer","abstract":"Berries are one of the most challenging products to preserve after harvest due to their high perishability and short shelf life. Ventilated packaging plays a key role in maintaining fruit quality along the supply chain. However, every supply chain is composed of different unit operations, and every shipment encounters unique hygrothermal conditions such as air temperature fluctuations over time, sub-optimal humidity conditions, and the risk of condensation. Therefore, every supply chain has an optimal packaging that provides the best hygrothermal climate and ventilation to the fruit. Given the vast space of potential supply chain scenarios and packaging configurations, in-silico studies are an attractive alternative for selecting this optimal packaging. In this study, we developed physics-based digital twins for ventilated packaging of strawberries. We utilized measured air temperature and humidity data from an actual supply chain from the farm to the retail store. With these digital twins, we mimicked in-silico how the strawberries evolve hygrothermally, physiologically, and microbiologically along the supply chain inside 21 different types of ventilated packaging. We predicted actionable metrics of fruit quality and shelf life for these 21 packages. These metrics include total mass loss, risk of putative mold infection due to Botrytis cinerea, retention time of condensate, and remaining shelf life based on respiration, transpiration, and mold growth. In addition, we analyzed the impact of package-related metrics, such as total vent area, degree of filling, pressure drop across the package, and seven-eighths cooling time, on fruit quality metrics. With this approach, we pinpointed the critical quality loss points in the supply chain for every package. We identified the package that performs best in balancing the three-way trade-off between the respiration-driven biochemical shelf life, transpiration-driven physical shelf life, and mold growth-driven microbial shelf life of fruit. Our findings showed that the performance of open trays is comparable to ventilated clamshells, as long as a high humidity is maintained along the supply chain. Flow-wrapped packages presented the highest risk of condensation and microbial growth. We also quantified the spatial heterogeneity in fruit quality within the packages and highlighted the most vulnerable locations for quality loss inside each packaging type. Our study presents a novel, holistic approach to select the optimal ventilated packaging of strawberries from farm to retailer based on its measured hygrothermal fingerprint. This approach can help reduce food loss and contribute towards making supply chains smart and efficient.","author":[{"family":"Shrivastava","given":"Chandrima"},{"family":"Schudel","given":"Seraina"},{"family":"Shoji","given":"Kanaha"},{"family":"Onwude","given":"Daniel"},{"family":"Silva","given":"Fátima"},{"family":"Turan","given":"Deniz"},{"family":"Paillart","given":"MJM"},{"family":"Defraeye","given":"Thijs"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.postharvbio.2023.112283","URL":"https://doi.org/10.1016/j.postharvbio.2023.112283","source":"openalex"},{"id":"oa:W4360992202","type":"article-journal","title":"Digital twin for healthy indoor environment: A vision for the post-pandemic era","abstract":"Indoor environment has significant impacts on human health as people spend 90% of their time indoors. The COVID-19 pandemic and the increased public health awareness have further elevated the urgency for cultivating and maintaining a healthy indoor environment. The advancement in emerging digital twin technologies including building information modeling (BIM), Internet of Things (IoT), data analytics, and smart control have led to new opportunities for building design and operation. Despite the numerous studies on developing methods for creating digital twins and enabling new functionalities and services in smart building management, very few have focused on the health of indoor environment. There is a critical need for understanding and envisaging how digital twin paradigms can be geared towards healthy indoor environment. Therefore, this study reviews the techniques for developing digital twins and discusses how the techniques can be customized to contribute to public health. Specifically, the current applications of BIM, IoT sensing, data analytics, and smart building control technologies for building digital twins are reviewed, and the knowledge gaps and limitations are discussed to guide future research for improving environmental and occupant health. Moreover, this paper elaborates a vision for future research on integrated digital twins for a healthy indoor environment with special considerations of the above four emerging techniques and issues. This review contributes to the body of knowledge by advocating for the consideration of health in digital twin modeling and smart building services and presenting the research roadmap for digital twin-enabled healthy indoor environment.","author":[{"family":"Cai","given":"Jiannan"},{"family":"Chen","given":"Jianli"},{"family":"Hu","given":"Yuqing"},{"family":"Li","given":"Shuai"},{"family":"He","given":"Qiang"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1007/s42524-022-0244-y","URL":"https://doi.org/10.1007/s42524-022-0244-y","source":"openalex"},{"id":"oa:W4405739785","type":"article-journal","title":"Digital Twins of Business Processes: A Research Manifesto","abstract":"Modern organizations necessitate continuous business processes improvement to maintain efficiency, adaptability, and competitiveness. In the last few years, the Internet of Things , via the deployment of sensors and actuators, has heavily been adopted in organizational and industrial settings to monitor and automatize physical processes influencing and enhancing how people and organizations work. Such advancements are now pushed forward by the rise of the Digital Twin paradigm applied to organizational processes. Advanced ways of managing and maintaining business processes come within reach as there is a Digital Twin of a business process - a virtual replica with real-time capabilities of a real process occurring in an organization. Combining business process models with real-time data and simulation capabilities promises to provide a new way to guide day-to-day organization activities. However, integrating Digital Twins and business processes is a non-trivial task, presenting numerous challenges and ambiguities. This manifesto paper aims to contribute to the current state of the art by clarifying the relationship between business processes and Digital Twins, identifying ongoing research and open challenges, thereby shedding light on and driving future exploration of this innovative interplay.","author":[{"family":"Fornari","given":"Fabrizio"},{"family":"Compagnucci","given":"Ivan"},{"family":"Donato","given":"Massimo"},{"family":"Bertrand","given":"Yannis"},{"family":"Beyel","given":"Harry"},{"family":"Carrión","given":"Emilio"},{"family":"Franceschetti","given":"Marco"},{"family":"Groher","given":"Wolfgang"},{"family":"Grüger","given":"Joscha"},{"family":"Kilic","given":"Emre"},{"family":"Koschmider","given":"Agnes"},{"family":"Leotta","given":"Francesco"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.iot.2024.101477","URL":"https://doi.org/10.1016/j.iot.2024.101477","source":"openalex"},{"id":"oa:W4401485792","type":"article-journal","title":"From data to action in flood forecasting leveraging graph neural networks and digital twin visualization","abstract":"Forecasting floods encompasses significant complexity due to the nonlinear nature of hydrological systems, which involve intricate interactions among precipitation, landscapes, river systems, and hydrological networks. Recent efforts in hydrology have aimed at predicting water flow, floods, and quality, yet most methodologies overlook the influence of adjacent areas and lack advanced visualization for water level assessment. Our contribution is two-fold: firstly, we introduce a graph neural network model (LocalFLoodNet) equipped with a graph learning module to capture the interconnections of water systems and the connectivity between stations to predict future water levels. Secondly, we develop a simulation prototype offering visual insights for decision-making in disaster prevention and policy-making. This prototype visualizes predicted water levels and facilitates data analysis using decades of historical information. Focusing on the Greater Montreal Area (GMA), particularly Terrebonne, Quebec, Canada, we apply LocalFLoodNet and prototype to demonstrate a comprehensive method for assessing flood impacts. By utilizing a digital twin of Terrebonne, our simulation tool allows users to interactively modify the landscape and simulate various flood scenarios, thereby providing valuable insights into preventive strategies. This research aims to enhance water level prediction and evaluation of preventive measures, setting a benchmark for similar applications across different geographic areas.","author":[{"family":"Roudbari","given":"Naghmeh"},{"family":"Punekar","given":"Shubham"},{"family":"Patterson","given":"Zachary"},{"family":"Eicker","given":"Ursula"},{"family":"Poullis","given":"Charalambos"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1038/s41598-024-68857-y","URL":"https://doi.org/10.1038/s41598-024-68857-y","source":"openalex"},{"id":"oa:W4317538611","type":"article-journal","title":"On the Design of a Network Digital Twin for the Radio Access Network in 5G and Beyond","abstract":"A Network Digital Twin (NDT) is a high-fidelity digital mirror of a real network. Given the increasing complexity of 5G and beyond networks, the use of an NDT becomes useful as a platform for testing configurations and algorithms prior to their application in the real network, as well as for predicting the performance of such algorithms under different conditions. While an NDT can be defined for the different subsystems of the network, this paper proposes an NDT architecture focusing on the Radio Access Network (RAN), describing the components to represent and model the operation of the different RAN elements, and to perform emulations. Different application use cases are identified, and among them, the paper puts the focus on the training of Reinforcement Learning (RL) solutions for the RAN. For this use case, the paper introduces a framework aligned with O-RAN specifications and discusses the functionalities needed to integrate the NDT. This use case is illustrated with the description of a RAN NDT implementation used for training an RL-based capacity-sharing solution for network slicing. Presented results demonstrate that the implemented RAN NDT is a suitable platform to successfully train the RL solution, achieving service-level agreement satisfaction values above 85%.","author":[{"family":"Vilà","given":"Irene"},{"family":"Sallent","given":"O"},{"family":"Pérez-Romero","given":"J"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/s23031197","URL":"https://doi.org/10.3390/s23031197","source":"openalex"},{"id":"oa:W4393385780","type":"article-journal","title":"Exploiting microservices and serverless for Digital Twins in the cloud-to-edge continuum","abstract":"R4.2 In the Industry 4.0 era, Digital Twins (DTs) serve as virtual representations of physical objects and intermediaries between the physical world and the digital realm. DTs require proper modeling, design, and development to ensure their seamless integration along the cloud-to-edge continuum. In particular, this work introduces a microservices-based and serverless-ready model for DTs, laying the foundation for cost-effective DT deployment and orchestration. The joint adoption of microservices and serverless computing offers significant potential to address various challenges, including accommodating variable application requirements, managing load imbalances, and mitigating network faults. The proposed DT model has been implemented in different flavors: two serverless implementations—one that relies on a serverless framework of a cloud provider and one running at the edge on-premises—and a microservices one. These implementations have been experimentally evaluated with particular emphasis on the quality of cyber–physical entanglement. This work not only discusses the advantages and drawbacks of different implementations from a qualitative perspective but also quantitatively evaluates them with the in-the-field collection of experimental performance results. Notably, we report that a serverless implementation typically performs an order of magnitude worse than a microservices one in terms of entanglement, i.e., hundreds vs. tens of milliseconds.","author":[{"family":"Bellavista","given":"Paolo"},{"family":"Bicocchi","given":"Nicola"},{"family":"Fogli","given":"Mattia"},{"family":"Giannelli","given":"Carlo"},{"family":"Mamei","given":"Marco"},{"family":"Picone","given":"Marco"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.future.2024.03.052","URL":"https://doi.org/10.1016/j.future.2024.03.052","source":"openalex"},{"id":"oa:W4379471822","type":"article-journal","title":"Digital Twin Implementation for Manufacturing of Adjuvants","abstract":"Pharmaceutical manufacturing processes are moving towards automation and real-time process monitoring with the help of process analytical technologies (PATs) and predictive process models representing the real system. In this paper, we present a digital twin developed for an adjuvant manufacturing process involving a microfluidic formation of lipid particles. The twin uses a hybrid model for estimating the current state of the process and predicting system behavior in real time. The twin is used to control the adjuvant particle size, a critical quality attribute, by varying process parameters such as the temperature and inlet flow rates. We describe steps in the design and implementation of the twin, starting from the conception of the mechanistic model, up to the generation of its surrogate model used as state estimator, PATs and the setup of the information technology—Operational technology architecture. We demonstrate the performance of the twin by introducing different disturbances in the process and comparing the effect on the product critical quality attributes with and without the control of the digital twin. Finally, we showcase the digital twin implementation for the process in good manufacturing practice, through an engineering run, which demonstrated the robustness of the process when controlled by the digital twin.","author":[{"family":"Phalak","given":"Poonam"},{"family":"Tomba","given":"Emanuele"},{"family":"Jehoulet","given":"Philippe"},{"family":"Kapitan-Gnimdu","given":"André"},{"family":"Soladana","given":"Pablo"},{"family":"Vagaggini","given":"Loredana"},{"family":"Brochier","given":"Maxime"},{"family":"Stevens","given":"Ben"},{"family":"Peel","given":"Thomas"},{"family":"Strodiot","given":"Laurent"},{"family":"Dessoy","given":"Sandrine"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/pr11061717","URL":"https://doi.org/10.3390/pr11061717","source":"openalex"},{"id":"oa:W4392589950","type":"article-journal","title":"Bidirectional graphics-based digital twin framework for quantifying seismic damage of structures using deep learning networks","abstract":"Tremendous effort has been devoted toward developing automated post-earthquake inspection techniques, including automated image collection and damage identification. However, few studies have attempted to establish the complex relationship between visible damage and structural conditions. Moreover, the lack of training data further hinders the potential use of deep learning algorithms. This paper proposes a framework, termed Bidirectional Graphics-based Digital Twin (Bi-GBDT), that allows for assessment of the structural condition based on post-earthquake photographic surveys. The procedure contains two parts: (i) A GBDT of a target structure, containing a computer graphics model and a finite element (FE) model, is developed (ii) Synthetic data subsequently is generated from the GBDT to train neural networks to predict the damage measures and structural conditions. To demonstrate the proposed approach, a seismically-designed reinforced concrete shear wall is considered. First, the GBDT of the shear wall is constructed and calibrated so that the associated damage patterns simulated by the corresponding FE model match well with the experimental results. Next, synthetic images of the damage patterns are created from the validated GBDT, along with the corresponding structural damage measures, and used to train Residual Neural Network and Conditional Generative Adversarial Networks to determine the maximum drift, the stress/strain fields and the structural condition. The neural networks trained on synthetic data are shown to perform well for the experimental data, confirming the proposed approach. Subsequently, the neural networks are tested on the synthetic data for a wide variety of loading conditions to demonstrate the robustness of the approach. In addition, the realistic images rendered from the GBDT are utilized as input to predict the structural condition, showcasing the comprehensive Bi-GBDT framework. These results demonstrate the efficacy of the proposed approach to generate accurate digital twins and point toward its future application for development of automated post-earthquake assessment strategies.","author":[{"family":"Zhai","given":"Guanghao"},{"family":"Xu","given":"Yongjia"},{"family":"Spencer","given":"Billie"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1177/14759217241231299","URL":"https://doi.org/10.1177/14759217241231299","source":"openalex"},{"id":"oa:W4391450304","type":"article-journal","title":"Lung-DT: An AI-Powered Digital Twin Framework for Thoracic Health Monitoring and Diagnosis","abstract":"The integration of artificial intelligence (AI) with Digital Twins (DTs) has emerged as a promising approach to revolutionize healthcare, particularly in terms of diagnosis and management of thoracic disorders. This study proposes a comprehensive framework, named Lung-DT, which leverages IoT sensors and AI algorithms to establish the digital representation of a patient's respiratory health. Using the YOLOv8 neural network, the Lung-DT system accurately classifies chest X-rays into five distinct categories of lung diseases, including \"normal\", \"covid\", \"lung_opacity\", \"pneumonia\", and \"tuberculosis\". The performance of the system was evaluated employing a chest X-ray dataset available in the literature, demonstrating average accuracy of 96.8%, precision of 92%, recall of 97%, and F1-score of 94%. The proposed Lung-DT framework offers several advantages over conventional diagnostic methods. Firstly, it enables real-time monitoring of lung health through continuous data acquisition from IoT sensors, facilitating early diagnosis and intervention. Secondly, the AI-powered classification module provides automated and objective assessments of chest X-rays, reducing dependence on subjective human interpretation. Thirdly, the twin digital representation of the patient's respiratory health allows for comprehensive analysis and correlation of multiple data streams, providing valuable insights as to personalized treatment plans. The integration of IoT sensors, AI algorithms, and DT technology within the Lung-DT system demonstrates a significant step towards improving thoracic healthcare. By enabling continuous monitoring, automated diagnosis, and comprehensive data analysis, the Lung-DT framework has enormous potential to enhance patient outcomes, reduce healthcare costs, and optimize resource allocation.","author":[{"family":"Avanzato","given":"Roberta"},{"family":"Beritelli","given":"Francesco"},{"family":"Lombardo","given":"Alfio"},{"family":"Ricci","given":"Carmelo"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/s24030958","URL":"https://doi.org/10.3390/s24030958","source":"openalex"},{"id":"oa:W4360584415","type":"article-journal","title":"SIGNED: Smart cIty diGital twiN vErifiable Data Framework","abstract":"Smart city digital twins can provide useful insights by making effective use of multi disciplinary urban data from diverse sources. Whilst these insights provide new information that helps cities in decision making, verifying the authenticity, integrity, traceability and data ownership across various functional units have become critical characteristics to ensure the data is from an authentic and trustworthy source. However, these characteristics are rarely considered in a digital twin ecosystem. In this research we introduce a novel framework, namely, ‘SIGNED: Smart cIty diGital twiN vErifiable Data framework’ that is designed on the basis of data ownership, selective disclosure and verifiability principles. Using Verifiable Credentials, SIGNED ensures digital twin data are verifiably authentic i.e., it covers provenance, transparency, and reliability through verifiable presentation. A proof of concept is designed and evaluated based on a smart water management use case to demonstrate the effectiveness of SIGNED in securing verifiable exchange of digital twin data across multiple functional units. The proof-of-concept demonstrates that SIGNED successfully allows the exchange of data in a trusted and verifiable manner at negilgible performance cost, thus enhancing security and alleviating privacy issues when sharing data between various functional units in a smart city.","author":[{"family":"Pervez","given":"Zeeshan"},{"family":"Khan","given":"Zaheer"},{"family":"Ghafoor","given":"Abdul"},{"family":"Soomro","given":"Kamran"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/access.2023.3260621","URL":"https://doi.org/10.1109/access.2023.3260621","source":"openalex"},{"id":"oa:W4383000537","type":"article-journal","title":"Development of a Robot-Assisted Telerehabilitation System With Integrated IIoT and Digital Twin","abstract":"Upper limb dysfunction (ULD) is common following a stroke, spinal cord injury, trauma, and occupational accidents. Post-stroke patients with ULD need long-term assistance from therapists for their rehabilitation, which generally occurs at the hospital or outpatient clinic. Physical therapists are unavailable because of geographical, financial, and scheduling concerns, and continuity of care needs to be improved due to the need to travel to multiple locations for therapy. As a result, providing specific, tailored therapy programs is challenging due to the absence of feedback and real-time monitoring. An effective telerehabilitation system can address this issue and is more cost-effective for healthcare providers and patients than traditional inpatient or person-to-person rehabilitation. Remotely operating robotic devices and using advanced technology improves patient and healthcare provider safety and reduces injuries. In this study, we developed a novel telerehabilitation framework for rehabilitation robots utilizing PTC’s Industrial Internet of Things (IIoT) platform to remotely provide robot-aided therapies for individuals with ULD. With the developed telerehabilitation framework, an operator can teleoperate the rehab robots to deliver Upper-limb (UL) exercises via an Augmented Reality (AR) based graphical user interface (GUI). This AR platform communicates bidirectionally using ThingWorx IIOT. It leverages the digital twin (DT) structure facilitated by Vuforia studio to visualize the physical robot motions happening in remote places. The telerehabilitation framework was validated through a commercially available robot (xArm 5), an exoskeleton (SREx), and an end-effector type rehabilitation robot (DMRbot) developed at Biorobotics Lab, UWM. The experiment results show that the telerehabilitation system can successfully provide UL rehab exercises in 2D and 3D planes via AR. The proposed framework is developed to facilitate robust and more promising robot-aided rehabilitation sessions remotely, and it can also be applied in other medical applications.","author":[{"family":"Khan","given":"Md"},{"family":"Sunny","given":"Md"},{"family":"Ahmed","given":"Tanvir"},{"family":"Shahria","given":"Md"},{"family":"Modi","given":"Preet"},{"family":"Zarif","given":"Md"},{"family":"Sanjuan","given":"Javier"},{"family":"Ahamed","given":"Sheikh"},{"family":"Ahmed","given":"Helal"},{"family":"Ketchum","given":"Erin"},{"family":"Rahman","given":"Mohammad"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/access.2023.3291803","URL":"https://doi.org/10.1109/access.2023.3291803","source":"openalex"},{"id":"oa:W4386275618","type":"article-journal","title":"Radar Imaging Based UAV Digital Twin for Wireless Channel Modeling in Mobile Networks","abstract":"This paper looks into the realization of digital twin (DT) technology in unmanned aerial vehicle (UAV) networks. We propose, in particular, a framework for DT-based UAV applications in which distinct jobs in the digital twin interact with UAVs in the physical world via task manager scheduling. Furthermore, we investigate the use of 3D mmWave Radar imaging on UAVs and apply it to the process of radio frequency (RF) characterizing. After that, the method of 3D ray-tracing is employed to accomplish channel modelling of UAVs, which reflects RF domain digital twin match. Finally, we present numerical results to demonstrate that our developed digital twin platform can provide accurate RF presentation of UAV and therefore accomplish smart operating and administration of the actual UAV network.","author":[{"family":"Xie","given":"Weiliang"},{"family":"Qi","given":"Fei"},{"family":"Liu","given":"Lei"},{"family":"Liu","given":"Qiang"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/jsac.2023.3310085","URL":"https://doi.org/10.1109/jsac.2023.3310085","source":"openalex"},{"id":"oa:W4324290821","type":"article-journal","title":"Security Analysis of a Digital Twin Framework Using Probabilistic Model Checking","abstract":"Digital Twins (DTs) have been gaining popularity in various applications, such as smart manufacturing, smart energy, smart mobility, and smart healthcare. In simple terms, DT is described as a virtual replica of a given physical product, system, or process. It consists of three major segments: the physical entity, its virtual counterpart, and the connections between them. While the data is collected from a physical entity, processed at the virtual layer, and accessed in the form of a DT at the application layer, it is exposed to several security risks. To ensure the applicability of a DT system, it is imperative to understand these security risks and their implications. However, there is a lack of a framework that can be used to assess the security of a DT. This paper presents a framework in which the security of a DT can be analyzed with the help of a formal verification technique. The framework captures the defense of the system at different layers and considers various attacks at each layer. The security of the DT system is represented as a state-transition system and the security properties are captured in temporal logic. Probabilistic model checking (PMC) is used to verify the systems against these properties. In particular, the framework is used to analyze the probability of success and the cost of various potential attacks that can occur at each layer in a DT system. The applicability of the proposed framework is demonstrated with the help of a detailed case study in the healthcare domain.","author":[{"family":"Shaikh","given":"Eman"},{"family":"Al-Ali","given":"AR"},{"family":"Muhammad","given":"Shahabuddin"},{"family":"Mohammad","given":"Nazeeruddin"},{"family":"Aloul","given":"Fadi"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/access.2023.3257171","URL":"https://doi.org/10.1109/access.2023.3257171","source":"openalex"},{"id":"oa:W4313569656","type":"article-journal","title":"Security and Privacy Issues in IoT-Based Big Data Cloud Systems in a Digital Twin Scenario","abstract":"Due to its unique type of services, Cloud Computing could operate as a “base technology” for other technologies; this attracts researchers to develop sustainable Cloud systems. It is a new generation of services that offers an opportunity for users to access and manage their information, applications, and data regardless of place and time. Nevertheless, there is a type of service that can include large amounts of data, called Big Data, and it consists of the rapid use of the Internet of Things (IoT) to produce large data sets. In this work, initially, we present Cloud Computing (CC) and Big Data (BD) exported from IoT, focusing on the security and management challenges of both. Notably, we combine the two aforementioned technologies to examine their related characteristics and discover new perspectives and opportunities for their integration and to achieve a sustainable environment called a Digital Twin scenario. Subsequently, we present how Cloud Computing contributes to IoT-based Big Data, aiming to fill a scientific gap in the sector of their integration regarding security and privacy. Finally, we additionally survey the security challenges of the integrated model of BD and CC and then propose a novel security algorithm for sustainable Cloud systems in a Digital Twin scenario. The experimental results presented are based on the use of the encryption algorithms AES, RC5, and RSA, and our proposed model extends the advances of CC and IoT-based BD, offering a highly novel and scalable service platform to achieve better privacy and security services.","author":[{"family":"Stergiou","given":"Christos"},{"family":"Bompoli","given":"Elisavet"},{"family":"Psannis","given":"Kostas"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/app13020758","URL":"https://doi.org/10.3390/app13020758","source":"openalex"},{"id":"oa:W4402742630","type":"article-journal","title":"Data Integration for Digital Twins in Industrial Automation: A Systematic Literature Review","abstract":"The domain of industrial automation faces challenges, such as shortened product life cycles, shortage of skilled labor, and increased complexity. Addressing these issues necessitates innovative solutions, one of which is the Digital Twin, being a virtual counterpart of a physical asset. Central to the quality of a Digital Twin is the data it harnesses. While current Digital Twins primarly draw data from their corresponding physical assets, future interconnected production environments promise an influx of additional data from external devices. However, it remains uncertain how existing Digital Twins incorporate and leverage such data. In this systematic literature review, drawing from a pool of 1107 unique publications, we analyzed 141 works to shed light on data utilization in industrial Digital Twins. We categorized these publications based on Digital Twin types and classified them according to various criteria regarding different characteristics of data. Our findings reveal that the majority of Digital Twins predominantly rely on structured data sourced directly from their associated assets, often employing proprietary integration methods. Facing the trends towards agile and interconnected production ecosystems, as well as an increasing amount of unstructured data, we assert that current Digital Twins are not equipped to meet forthcoming demands in the industrial domain. Consequently, we propose necessary adaptations to fully unleash the potential of Digital Twins and outline future research fields, including automated data integration and evaluation.","author":[{"family":"Hildebrandt","given":"Gary"},{"family":"Dittler","given":"Daniel"},{"family":"Habiger","given":"Pascal"},{"family":"Drath","given":"Rainer"},{"family":"Weyrich","given":"Michael"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/access.2024.3465632","URL":"https://doi.org/10.1109/access.2024.3465632","source":"openalex"},{"id":"oa:W4385217783","type":"article-journal","title":"Digital Twin Development for the Airspace of the Future","abstract":"The UK aviation industry is committed to achieving net zero emissions by 2050 through sustainable measures and one of the key aspects of this effort is the implementation of Unmanned Traffic Management (UTM) systems. These UTM systems play a crucial role in enabling the safe and efficient integration of unmanned aerial vehicles (UAVs) into the airspace. As part of the Airspace of the Future (AoF) project, the development and implementation of UTM services have been prioritised. This paper aims to create an environment where routine drone services can operate safely and effectively. To facilitate this, a digital twin of the National Beyond Visual Line of Sight Experimentation Corridor has been created. This digital twin serves as a virtual replica of the corridor and allows for the synthetic testing of unmanned traffic management concepts. The implementation of the digital twin involves both simulated and hybrid flights with real drones. Simulated flights allow for the testing and refinement of UTM services in a controlled environment. Hybrid flights, on the other hand, involve the integration of real drones into the airspace to assess their performance and compatibility with the UTM systems. By leveraging the capabilities of UTM systems and utilising the digital twin for testing, the AoF project aims to advance the development of safer and more efficient drone operations. The Experimentation Corridor has been developed to simulate and test concepts related to managing unmanned traffic. The paper provides a detailed account of the implementation of the digital twin for the AoF project, including simulated and hybrid flights involving real drones.","author":[{"family":"Souanef","given":"Toufik"},{"family":"Alrubaye","given":"Saba"},{"family":"Tsourdos","given":"Antonios"},{"family":"Ayo","given":"Samuel"},{"family":"Panagiotakopoulos","given":"Dimitrios"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/drones7070484","URL":"https://doi.org/10.3390/drones7070484","source":"openalex"},{"id":"oa:W4390615208","type":"article-journal","title":"Digital Twin of Microgrid for Predictive Power Control to Buildings","abstract":"The increased focus on sustainability in response to climate change has given rise to many new initiatives to meet the rise in building load demand. The concept of distributed energy resources (DER) and optimal control of supply to meet power demands in buildings have resulted in growing interest to adopt microgrids for a precinct or a university campus. In this paper, a model for an actual physical microgrid has been constructed in OPAL-RT for real-time simulation studies. The load demands for SIT@NYP campus and its weather data are collected to serve as input to run on the digital twin model of DERs of the microgrid. The dynamic response of the microgrid model in response to fluctuations in power generation due to intermittent solar PV generation and load demands are examined via real-time simulation studies and compared with the response of the physical assets. It is observed that the simulation results match closely to the performance of the actual physical asset. As such, the developed microgrid model offers plug-and-play capability, which will allow power providers to better plan for on-site deployment of renewable energy sources and energy storage to match the expected building energy demand.","author":[{"family":"Jiang","given":"Hao"},{"family":"Tjandra","given":"Rudy"},{"family":"Soh","given":"Chew"},{"family":"Cao","given":"Shuyu"},{"family":"Soh","given":"Donny"},{"family":"Tan","given":"Kuan"},{"family":"Tseng","given":"King"},{"family":"Krishnan","given":"Sivaneasan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/su16020482","URL":"https://doi.org/10.3390/su16020482","source":"openalex"},{"id":"oa:W4391093011","type":"article-journal","title":"Digital Twin-Assisted Edge Service Caching for Consumer Electronics Manufacturing","abstract":"In recent years, the consumer electronics manufacturing (CEM) has increasingly recognized the role of the Internet of Things (IoT) in improving production efficiency and reducing costs. Manufacturing factories have chosen to deploy servers at the edge of network to cache services, reducing energy consumption during data transmission. However, due to the dynamic nature of edge networks and the unpredictability of service requests, obtaining the optimal caching strategy for IoT devices remains a significant challenge. In this paper, we employ digital twin (DT) to formulate dynamic digital models of IoT devices and edge servers for enhancing the caching management efficiency in manufacturing factories. Additionally, we propose a service caching scheme based on deep reinforcement learning (DRL) enabled by DT, named SCRD, to obtain the optimal caching strategy for IoT devices. Firstly, the service caching problem is formulated as a Markov decision process (MDP), which is then solved using a multi-agent algorithm based on the Double Dueling Deep Q-Network (D3QN). Finally, experimental results demonstrate the proposed scheme is more effective than the baseline schemes.","author":[{"family":"Liu","given":"Wei"},{"family":"Xu","given":"Xiaolong"},{"family":"Qi","given":"Lianyong"},{"family":"Zhou","given":"Xiaokang"},{"family":"Yan","given":"Hanzhi"},{"family":"Xia","given":"Xiaoyu"},{"family":"Dou","given":"Wanchun"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/tce.2024.3357136","URL":"https://doi.org/10.1109/tce.2024.3357136","source":"openalex"},{"id":"oa:W4403030791","type":"article-journal","title":"Self-adaptive digital twin of fuel cell for remaining useful lifetime prediction","abstract":"Accurate prediction of the remaining useful life (RUL) of proton exchange membrane fuel cells (PEMFCs) is essential for maximizing their operational lifespan. However, existing methods often face limitations in two key areas: long-term prediction (beyond 168 h, or one week) and adaptability to varying operating conditions. To address these challenges, we propose a novel self-adaptive digital twin (SADT) model for RUL prediction of PEMFCs. Our approach uniquely integrates a deep convolutional neural network to generate robust health indicators (HIs) that maintain consistent monotonicity across diverse operating conditions. Additionally, we introduce a novel quantile Huber loss (QH-loss) function to enhance prediction accuracy and incorporate a transfer learning technique to improve adaptability under varying operational scenarios. Experimental results on PEMFC degradation datasets demonstrate that our method outperforms state-of-the-art techniques in long-term prediction accuracy, highlighting its potential to significantly extend fuel cell lifetimes. • A novel self-adaptive digital twin for predicting RUL of the PEMFC. • Transfer Learning enhanced RUL prediction accuracy and adaptability. • Universal monotonic HI applicable to various PEMFC operating conditions.","author":[{"family":"Zhang","given":"Ming"},{"family":"Amiri","given":"Amirpiran"},{"family":"Xu","given":"Yuchun"},{"family":"Bastin","given":"Lucy"},{"family":"Clark","given":"Tony"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.ijhydene.2024.09.266","URL":"https://doi.org/10.1016/j.ijhydene.2024.09.266","source":"openalex"},{"id":"oa:W4405781903","type":"article-journal","title":"Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review","abstract":"Civil infrastructure assets' contribution to countries' economic growth is significantly increasing due to the rapid population growth and demands for public services. These civil infrastructures, including roads, bridges, railways, tunnels, dams, residential complexes, and commercial buildings, experience significant deterioration from the surrounding harsh environment. Traditional methods of visual inspection and non-destructive tests are generally undertaken to monitor and evaluate the structural health of the infrastructure. However, these methods lack reliability due to the need for instrumentation calibration and reliance on subjective visual judgments. Digital twin (DT) technology digitally replicates existing infrastructure, offering significant potential for real-time intelligent monitoring and assessment of structural health. This study reviews the existing applications of DTs across various sectors. It proposes an approach for developing DT applications in civil infrastructure, including using the Internet of Things, data acquisition, and modelling, together with the platform requirements and challenges that may be confronted during DT development. This comprehensive review is a state-of-the-art review of advancements and challenges in DT technology for intelligent monitoring and maintenance of civil infrastructure.","author":[{"family":"Sun","given":"Zhiyan"},{"family":"Jayasinghe","given":"Sanduni"},{"family":"Sidiq","given":"Amir"},{"family":"Shahrivar","given":"Farham"},{"family":"Mahmoodian","given":"Mojtaba"},{"family":"Setunge","given":"Sujeeva"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/s25010059","URL":"https://doi.org/10.3390/s25010059","source":"pubmed"},{"id":"doi:10.5281/zenodo.21745620","type":"article-journal","title":"Model for Integrating Private Debt Financing in Digital Transformation of Infrastructure Firms","abstract":"Digital transformation has emerged as a critical driver of efficiency, competitiveness, and sustainability in infrastructure firms, encompassing investments in smart systems, predictive analytics, IoT-enabled assets, and digital twin technologies. At the same time, private debt financing has become an increasingly prominent mechanism for supporting capital-intensive infrastructure projects, offering flexibility, tailored terms, and access to specialized financing structures. Integrating private debt financing into the digital transformation of infrastructure firms requires a structured approach that balances investment returns, risk exposure, and operational impact. This develops a comprehensive model to guide infrastructure firms and investors in strategically allocating private debt to digital initiatives. The model combines multi-dimensional inputs, including historical and projected financial statements, digital transformation costs, macroeconomic indicators, and firm-specific risk metrics. A risk assessment layer evaluates default probabilities, technology adoption risk, and implementation uncertainties, while scenario analyses and stress-testing quantify potential vulnerabilities under adverse market and operational conditions. At the core of the model is a multi-objective optimization engine that balances debt servicing costs, expected returns, operational efficiency gains, and risk-adjusted performance. Constraints related to leverage limits, liquidity requirements, regulatory compliance, and ESG considerations are embedded to ensure sustainable and compliant allocation decisions. The output layer provides actionable recommendations on debt allocation across digital initiatives, projected financial outcomes, and risk-return visualizations to support informed decision-making by investment committees and corporate executives. The framework emphasizes dynamic rebalancing, allowing firms to adjust financing strategies in response to project progress, market developments, and evolving digital priorities. By integrating private debt into digital transformation planning, the model enhances transparency, resilience, and strategic alignment, enabling infrastructure firms to realize operational improvements while maintaining financial stability. Future extensions include AI-driven predictive analytics, ESG optimization, and cross-border financing considerations, creating an adaptive, data-driven framework that aligns capital deployment with the evolving landscape of digital infrastructure.","author":[{"family":"Farounbi","given":"Blessing"},{"family":"Okafor","given":"Chizoba"},{"family":"Oguntegbe","given":"Esther"}],"issued":{"date-parts":[[2023]]},"DOI":"10.5281/zenodo.21745620","URL":"https://doi.org/10.5281/zenodo.21745620","source":"datacite"},{"id":"doi:10.5281/zenodo.21745621","type":"article-journal","title":"Model for Integrating Private Debt Financing in Digital Transformation of Infrastructure Firms","abstract":"Digital transformation has emerged as a critical driver of efficiency, competitiveness, and sustainability in infrastructure firms, encompassing investments in smart systems, predictive analytics, IoT-enabled assets, and digital twin technologies. At the same time, private debt financing has become an increasingly prominent mechanism for supporting capital-intensive infrastructure projects, offering flexibility, tailored terms, and access to specialized financing structures. Integrating private debt financing into the digital transformation of infrastructure firms requires a structured approach that balances investment returns, risk exposure, and operational impact. This develops a comprehensive model to guide infrastructure firms and investors in strategically allocating private debt to digital initiatives. The model combines multi-dimensional inputs, including historical and projected financial statements, digital transformation costs, macroeconomic indicators, and firm-specific risk metrics. A risk assessment layer evaluates default probabilities, technology adoption risk, and implementation uncertainties, while scenario analyses and stress-testing quantify potential vulnerabilities under adverse market and operational conditions. At the core of the model is a multi-objective optimization engine that balances debt servicing costs, expected returns, operational efficiency gains, and risk-adjusted performance. Constraints related to leverage limits, liquidity requirements, regulatory compliance, and ESG considerations are embedded to ensure sustainable and compliant allocation decisions. The output layer provides actionable recommendations on debt allocation across digital initiatives, projected financial outcomes, and risk-return visualizations to support informed decision-making by investment committees and corporate executives. The framework emphasizes dynamic rebalancing, allowing firms to adjust financing strategies in response to project progress, market developments, and evolving digital priorities. By integrating private debt into digital transformation planning, the model enhances transparency, resilience, and strategic alignment, enabling infrastructure firms to realize operational improvements while maintaining financial stability. Future extensions include AI-driven predictive analytics, ESG optimization, and cross-border financing considerations, creating an adaptive, data-driven framework that aligns capital deployment with the evolving landscape of digital infrastructure.","author":[{"family":"Farounbi","given":"Blessing"},{"family":"Okafor","given":"Chizoba"},{"family":"Oguntegbe","given":"Esther"}],"issued":{"date-parts":[[2023]]},"DOI":"10.5281/zenodo.21745621","URL":"https://doi.org/10.5281/zenodo.21745621","source":"datacite"},{"id":"oa:W4405113405","type":"article-journal","title":"From Reality to Virtuality: Revolutionizing Livestock Farming Through Digital Twins","abstract":"The impacts of climate change on agricultural production are becoming more severe, leading to increased food insecurity. Adopting more progressive methodologies, like smart farming instead of conventional methods, is essential for enhancing production. Consequently, livestock production is swiftly evolving towards smart farming systems, propelled by rapid advancements in technology such as cloud computing, the Internet of Things, big data, machine learning, augmented reality, and robotics. A Digital Twin (DT), an aspect of cutting-edge digital agriculture technology, represents a virtual replica or model of any physical entity (physical twin) linked through real-time data exchange. A DT conceptually mirrors the state of its physical counterpart in real time and vice versa. DT adoption in the livestock sector remains in its early stages, revealing a knowledge gap in fully implementing DTs within livestock systems. DTs in livestock hold considerable promise for improving animal health, welfare, and productivity. This research provides an overview of the current landscape of digital transformation in the livestock sector, emphasizing applications in animal monitoring, environmental management, precision agriculture, and supply chain optimization. Our findings highlight the need for high-quality data, comprehensive data privacy measures, and integration across varied data sources to ensure accurate and effective DT implementation. Similarly, the study outlines their possible applications and effects on livestock and the challenges and limitations, including concerns about data privacy, the necessity for high-quality data to ensure accurate simulations and predictions, and the intricacies involved in integrating various data sources. Finally, the paper delves into the possibilities of digital twins in livestock, emphasizing potential paths for future research and progress.","author":[{"family":"Arulmozhi","given":"Elanchezhian"},{"family":"Deb","given":"Nibas"},{"family":"Tamrakar","given":"Niraj"},{"family":"Kang","given":"Dae"},{"family":"Kang","given":"Myeong"},{"family":"Kook","given":"Junghoo"},{"family":"Basak","given":"Jayanta"},{"family":"Kim","given":"Hyeon"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/agriculture14122231","URL":"https://doi.org/10.3390/agriculture14122231","source":"openalex"},{"id":"oa:W4385453342","type":"article-journal","title":"A Hierarchical Digital Twin Network for Satellite Communication Networks","abstract":"Satellite communication networks promise to provide seamless global coverage in the 6G era. However, novel satellite networks face the challenges of high dynamics in terms of both communication and networking, which makes its design, emulation, deployment, and maintenance over-complicated. For these challenges, Digital Twin (DT) can establish a virtual replica of the physical system, providing a means of emulation, validation, prediction, and troubleshooting for the actual system whose benefits have been proven by many applications. In this work, we design a hierarchical digital twin network for satellite communication networks, which defines central-DT and edge-DT models that provide differentiated DT services such as communication DT and networking DT. Further, for the problem of model synchronization, we propose three approaches to improve the model synchronization efficiency, namely, dynamic DT migration, QoS-aware DT synchronization slice, and locator-identifier-isolation addressing mechanism. Simulation is conducted to validate the improvement of the proposed scheme, and provide proof of efficiency.","author":[{"family":"Zhou","given":"Yuke"},{"family":"Zhang","given":"Ran"},{"family":"Liu","given":"Jiang"},{"family":"Huang","given":"Tao"},{"family":"Tang","given":"Qinqin"},{"family":"Yu","given":"FR"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/mcom.001.2200864","URL":"https://doi.org/10.1109/mcom.001.2200864","source":"openalex"},{"id":"oa:W4401246740","type":"article-journal","title":"A Review of Digital Twinning for Rotating Machinery","abstract":"This review focuses on the definitions, modalities, applications, and performance of various aspects of digital twins (DTs) in the context of transmission and industrial machinery. In this regard, the context around Industry 4.0 and even aspirations for Industry 5.0 are discussed. The many definitions and interpretations of DTs in this domain are first summarized. Subsequently, their adoption and performance levels for rotating and industrial machineries for manufacturing and lifetime performance are observed, along with the type of validations that are available. A significant focus on integrating fundamental operations of the system and scenarios over the lifetime, with sensors and advanced machine or deep learning, along with other statistical or data-driven methods are highlighted. This review summarizes how individual aspects around DTs are extremely helpful for lifetime design, manufacturing, or decision making even when a DT can remain incomplete or limited.","author":[{"family":"Inturi","given":"Vamsi"},{"family":"Ghosh","given":"Bidisha"},{"family":"Sabareesh","given":"GR"},{"family":"Pakrashi","given":"Vikram"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/s24155002","URL":"https://doi.org/10.3390/s24155002","source":"europepmc"},{"id":"oa:W4396521016","type":"article-journal","title":"A cyclic and holistic methodology to exploit the Supply Chain Digital Twin concept towards a more resilient and sustainable future","abstract":"Recent major disruptions such as natural disasters, geopolitical tensions, Covid-19 pandemic have led supply chain managers to rethink strategies for achieving significant levels of sustainability and resilience. At the same time, new digital technologies are offering significant opportunities to increase company performance, while maintaining a high level of customer service. In this challenging context, the Supply Chain Digital Twin (SCDT) represents an emerging and promising concept, which deserves to be explored. In this paper, a holistic and cyclical methodology, based on simulation, is proposed to enable and exploit the SCDT Paradigm, with the main aim to increase sustainability and resilience of the chains. The proposed methodology is successfully tested and validated on a real case study in the agri-food sector, through the use of the anyLogistix software. The results return valuable information on the level of resilience of the supply chain in the face of any considered disruption and provide useful managerial insights on the actions to be taken to improve some performance indicators.","author":[{"family":"Cimino","given":"Antonio"},{"family":"Longo","given":"Francesco"},{"family":"Mirabelli","given":"Giovanni"},{"family":"Solina","given":"Vittorio"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.clscn.2024.100154","URL":"https://doi.org/10.1016/j.clscn.2024.100154","source":"openalex"},{"id":"oa:W4386203678","type":"article-journal","title":"Cloud-Based Digital Twins’ Storage in Emergency Healthcare","abstract":"Abstract In a medical emergency situation, real-time patient data sharing may improve the survivability of a patient. In this paper, we explore how Digital Twin (DT) technology can be used for real-time data storage and processing in emergency healthcare. We investigated various enabling technologies, including cloud platforms, data transmission formats, and storage file formats, to develop a feasible DT storage solution for emergency healthcare. Through our analysis, we found Amazon AWS to be the most suitable cloud platform due to its sophisticated real-time data processing and analytical tools. Additionally, we determine that the MQTT protocol is suitable for real-time medical data transmission, and FHIR is the most appropriate medical file storage format for emergency healthcare situations. We propose a cloud-based DT storage solution, in which real-time medical data are transmitted to AWS IoT Core, processed by Kinesis Data Analytics, and stored securely in AWS HealthLake. Despite the feasibility of the proposed solution, challenges such as insufficient access control, lack of encryption, and vendor conformity must be addressed for successful practical implementation. Future work may involve Hyperledger Fabric technology and HTTPS protocol to enhance security, while the maturation of DT technology is expected to resolve vendor conformity issues. By addressing these challenges, our proposed DT storage solution has the potential to improve data accessibility and decision-making in emergency healthcare settings.","author":[{"family":"Wang","given":"Erdan"},{"family":"Tayebi","given":"Pouria"},{"family":"Song","given":"Yeong"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1007/s44227-023-00011-y","URL":"https://doi.org/10.1007/s44227-023-00011-y","source":"openalex"},{"id":"oa:W4380269429","type":"article-journal","title":"Shifting focus of value creation through industrial digital twins—From internal application to ecosystem-level utilization","abstract":"Industrial organizations are increasingly using digital twins as the solutions offered by digital twin service providers are rapidly expanding. This study aims to investigate how the value creation mechanism changes when transitioning from an organizational digital twin to an ecosystem-level digital twin that functions as a two-sided or multi-sided platform. The study results are based on the multiple longitudinal case studies conducted in Finland, where data were gathered using various methods and replications across the cases were conducted to investigate the same phenomenon. The study makes the following main contributions: (1) although the focus of value creation through digital twins at the level of machines/production lines highlights a technological approach, value creation is increasingly complemented with a human approach when digital twins are used as factory-level internal platforms. (2) Owing to the well-recognized value creation logic in internal use, industrial organizations are inclined to expand their value creation beyond organizational boundaries and establish two-sided and multi-sided platforms around their digital twins. (3) Forerunner organizations are also looking for opportunities to establish multi-sided platforms around their digital twins even though they are not yet ready to shift their value creation logic from internal to ecosystem-level utilization.","author":[{"family":"Rantala","given":"Tero"},{"family":"Ukko","given":"Juhani"},{"family":"Nasiri","given":"Mina"},{"family":"Saunila","given":"Minna"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.technovation.2023.102795","URL":"https://doi.org/10.1016/j.technovation.2023.102795","source":"openalex"},{"id":"oa:W4386275697","type":"article-journal","title":"When Moving Target Defense Meets Attack Prediction in Digital Twins: A Convolutional and Hierarchical Reinforcement Learning Approach","abstract":"With rapid development of emerging technologies for Internet of Things (IoT), digital twins (DT) have been proposed to support a wide variety of applications. A mobile network is expected to be integrated with DT to form a DT mobile network (DTMN). Unfortunately, DTMN still faces security threats, which have attracted great research attention. Current defense mechanisms are mostly static, i.e., responding after attacks happening. To solve the aforementioned problem, moving target defense (MTD) has been proposed as an innovative solution. However, there exist three major challenges when applying MTD into DTMN. Firstly, less emphasis was paid to collaborative scheduling between multiple MTD schemes, which can improve the security of DTMN. Secondly, MTD schemes require lots of network resources, but few works focus on the time allocation of multiple MTD schemes to reduce network resource consumption. Thirdly, existing defense strategies only rely on current information, but do not consider future information. In this paper, we propose a collaborative mutation-based MTD (CM-MTD) in DTMN. We mainly consider two MTD schemes called host address mutation (HAM) and route mutation (RM), respectively, which adjust network properties and invalidate different stages of cyber kill chain. We firstly formulate a semi-Markov decision process (SMDP) to model time-varying security events and dynamic deployment of multiple MTD schemes. Then, security events are predicted by long short-term memory (LSTM), which are regarded as network states in SMDP. Next, infeasible actions that do not satisfy network constraints will be removed from the action space of the SMDP. Lastly, we design a hierarchical deep reinforcement learning algorithm for collaborative scheduling. Simulation results highlight the effectiveness of CM-MTD compared with baseline solutions.","author":[{"family":"Zhang","given":"Tao"},{"family":"Xu","given":"Changqiao"},{"family":"Lian","given":"Yibo"},{"family":"Tian","given":"Haijiang"},{"family":"Kang","given":"Jiawen"},{"family":"Kuang","given":"Xiaohui"},{"family":"Niyato","given":"Dusit"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/jsac.2023.3310072","URL":"https://doi.org/10.1109/jsac.2023.3310072","source":"openalex"},{"id":"oa:W4386275873","type":"article-journal","title":"Ultra-Low AoI Digital Twin-Assisted Resource Allocation for Multi-Mode Power IoT in Distribution Grid Energy Management","abstract":"Age of information (AoI) is an important metric of information timeliness, which determines digital twin (DT) consistency and energy management precision. However, AoI guarantee in the time-averaged sense is unreliable to avoid the occurrence of extreme event. In this paper, we propose a novel information timeliness metric named ultra-low AoI (ULAoI). Compared with AoI, ULAoI further considers the occurrence of extreme event and higher-order statistical characteristics of excess AoI value. Multi-dimensional resources of power internet of things (PIoT) are jointly allocated to achieve ULAoI guarantee from the perspective of sensing-communication-control integration. ULAoI-DT-Prioritized deep Q network (DQN) is proposed to achieve coordinated resource allocation by approximating unobservable information with the assistance of ULAoI-DT, and preventing DQN training from using samples with large AoI based on ULAoI-induced priority. Simulation results demonstrate the superior performance of the proposed algorithm in global loss function, ULAoI guarantee, and energy management optimality.","author":[{"family":"Liao","given":"Haijun"},{"family":"Zhou","given":"Zhenyu"},{"family":"Jia","given":"Zehan"},{"family":"Shu","given":"Yiling"},{"family":"Tariq","given":"Muhammad"},{"family":"Rodrıguez","given":"Jonathan"},{"family":"Frascolla","given":"Valerio"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/jsac.2023.3310101","URL":"https://doi.org/10.1109/jsac.2023.3310101","source":"openalex"},{"id":"oa:W4389936980","type":"article-journal","title":"Relativistic Digital Twin: Bringing the IoT to the future","abstract":"Complex IoT ecosystems often require the usage of Digital Twins (DTs) of their physical assets in order to perform predictive analytics and simulate what-if scenarios. DTs are able to replicate IoT devices and adapt over time to their behavioral changes. However, DTs in IoT are typically tailored to a specific use case, without the possibility to seamlessly adapt to different scenarios. Further, the fragmentation of IoT poses additional challenges on how to deploy DTs in heterogeneous scenarios characterized by the usage of multiple data formats and IoT network protocols. In this paper, we propose the Relativistic Digital Twin (RDT) framework, through which we automatically generate general-purpose DTs of IoT entities and tune their behavioral models over time by constantly observing their real counterparts. The framework relies on the object representation via the Web of Things (WoT), to offer a standardized interface to each of the IoT devices as well as to their DTs. To this purpose, we extended the W3C WoT standard in order to encompass the concept of behavioral model and define it in the Thing Description (TD) through a new vocabulary. Finally, we evaluated the RDT framework over two disjoint use cases to assess its correctness and learning performance, i.e., the DT of a simulated smart home scenario with the capability of forecasting the indoor temperature, and the DT of a real-world drone with the capability of forecasting its trajectory in an outdoor scenario. Experiments show that the generated DT can estimate the behavior of its real counterpart after an observation stage, regardless of the considered scenario.","author":[{"family":"Sciullo","given":"Luca"},{"family":"Marchi","given":"Alberto"},{"family":"Trotta","given":"Angelo"},{"family":"Montori","given":"Federico"},{"family":"Bononi","given":"Luciano"},{"family":"Felice","given":"Marco"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.future.2023.12.016","URL":"https://doi.org/10.1016/j.future.2023.12.016","source":"openalex"},{"id":"oa:W4384284075","type":"article-journal","title":"Blockchain-Based Decentralized Learning for Security in Digital Twins","abstract":"This work aims to analyze malicious communication behaviors that pose a threat to the security of digital twins (DTs) and safeguard user privacy. A unified and integrated multidimensional DTs Network (DTN) architecture is constructed. On this basis, the propagation process model of malware in the network is built to analyze the malicious propagation behavior that threatens network security. This model ensures the protection of mobile distributed machine learning system security. Blockchain technology is a distributed data protection mechanism with broad prospects. It is characterized by decentralization, transparency, and anonymity, which can help ensure secure network data sharing and privacy protection. Based on this, this work designs a secure distributed data sharing (DDS) architecture based on blockchain to improve the security and reliability of data protection with the support of the Internet of Things (IoT). Then, digital resource allocation based on semi-distributed learning is examined to propose a broad learning federated continuous learning (BL-FCL) algorithm combining blockchain and DTs. This algorithm significantly speeds up the model training process. Broad learning technology supports incremental learning. In this way, each client does not need to retrain when learning the newly generated data. In the experimental part, the prediction accuracy of BL-FCL on the mixed national institute of standards and technology data set is similar to that of the FedAvg-50 and FedAvg-80 schemes. As the number of devices increases from 1 to 6, the detection probability exhibits a rapid decrease. However, as the number of devices further increases from 6 to 10, the detection probability gradually decreases at a slower rate until it reaches 0. Comparatively, the prediction accuracy of the BL-FCL outperforms the federated averaging algorithm-based scheme by 20%–60%. The BL-FCL reported here can deal with the problem of inaccurate training while ensuring the privacy and security of users. This work is of great significance for ensuring the security of the DTN and promoting the development of the digital economy. The results can provide references for applying blockchain and distributed learning in the DT field.","author":[{"family":"Lv","given":"Zhihan"},{"family":"Cheng","given":"Chen"},{"family":"Lv","given":"Haibin"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/jiot.2023.3295499","URL":"https://doi.org/10.1109/jiot.2023.3295499","source":"openalex"},{"id":"oa:W4316660823","type":"article-journal","title":"T6CONF: Digital Twin Networking Framework for IPv6-Enabled Net-Zero Smart Cities","abstract":"An efficient serving of predictive management and what-if-analysis of smart cities is the only way to achieve a net-zero waste target. With the aid of the enhanced learning capabilities of digital twin, net-zero aims of smart cities can be obtained with highly accurate results in the prediction of waste-to-energy and candidate truck paths. However, there is no unified communication model yet for a digital twin to maintain complete data and control flow in a fully synchronized way. Without having a clear communication model for the digital twin, the interaction between the physical and digital replica cannot be sustained. To handle this, we propose a digital twin networking framework called T6CONF, based on an IPv6 infrastructure, to solve the end-to-end two-way communication and synchronization problem of the resource-constrained Internet of Things networks. Besides, T6CONF serves two specific net-zero waste services, waste-to-energy and planned-truck-routing prediction services, for the net-zero goal. We evaluate the proposed digital twin communication model with changing fidelity levels over the twinning rate and round-trip time. Additionally, we prove that the proposed T6CONF model increases the accuracy of service layer operations.","author":[{"family":"Ak","given":"Elif"},{"family":"Duran","given":"Kübra"},{"family":"Dobre","given":"Octavia"},{"family":"Duong","given":"Trung"},{"family":"Canberk","given":"Berk"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/mcom.003.2200315","URL":"https://doi.org/10.1109/mcom.003.2200315","source":"openalex"},{"id":"oa:W4384521487","type":"article-journal","title":"Construction of Digital Twin System for Cold Chain Logistics Stereo Warehouse","abstract":"The current stereo warehouse in the cold chain logistics industry faces problems such as high product loss rate, severe temperature deviations, and low level of informatization. To ensure the food quality and safety of cold chain logistics warehouses, and achieve cost reduction and efficiency improvement, this study focuses on the operational scenarios of stereo warehouses in cold chain logistics, and designs a five-dimensional digital twin model with full mapping and multidimensional simulation. By integrating heterogeneous data from multiple sources, it achieves real-time visualization and monitoring of all elements in warehouses, and proposes a model optimization strategy that supports system-linked decision-making. This strategy intelligently adjusts the load and thermal distribution in the temperature-controlled zones of warehouses to maximize operational efficiency and reduce operating costs. Using this approach, a digital twin system for cold chain logistics warehouses was constructed. By comparing the warehouse operation data before and after optimization, the loss rate of fresh vegetables under the same storage conditions was reduced by 25-30%. This system achieves precise mapping and coordinated operation of real-time data from cold chain logistics warehouses and dynamic virtual models. The practical application of this solution is demonstrated in a cold-chain warehouse of a supply chain company in Guangdong, forming an integrated control model for cold chain logistics warehouses. This model provides a reference for the application of digital twin technology in the operation, scheduling, decision-making, and collaborative operations of cold chain logistics warehouses and offers new possibilities for establishing improved packaging for perishable products and ensuring cold chain food quality and safety.","author":[{"family":"Bin","given":"Hu"},{"family":"Guo","given":"Hui"},{"family":"Tao","given":"Xiongjie"},{"family":"Zhang","given":"Yingyi"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/access.2023.3295819","URL":"https://doi.org/10.1109/access.2023.3295819","source":"openalex"},{"id":"oa:W4393146824","type":"article-journal","title":"Virtual Reality and Internet of Things Based Digital Twin for Smart City Cross-Domain Interoperability","abstract":"The fusion of Internet of Things (IoT), Digital Twins, and Virtual Reality (VR) technologies marks a pivotal advancement in urban development, offering new services to citizens and municipalities in urban environments. This integration promises enhanced urban planning, management, and engagement by providing a comprehensive, real-time digital reflection of the city, enriched with immersive experiences and interactive capabilities. It enables smarter decision-making, efficient resource management, and personalized citizen services, transforming the urban landscape into a more sustainable, livable, and responsive environment. The research presented herein focuses on the practical implementation of a DT concept for managing cross-domain smart city services, leveraging VR technology to create a virtual replica of the urban environment and IoT devices. Imperative for cross-domain city services is interoperability, which is crucial not only for the seamless operation of these advanced tools but also for unlocking the potential of cross-service applications. Through the deployment of our model at the IoTMADLab facilities, we showcase the integration of IoT devices within varied urban infrastructures. The outcomes demonstrate the efficacy of VR interfaces in simplifying complex interactions, offering pivotal insights into device functionality, and enabling informed decision-making processes.","author":[{"family":"Campo","given":"Guillermo"},{"family":"Saavedra","given":"Edgar"},{"family":"Piovano","given":"Luca"},{"family":"Luque","given":"Francisco"},{"family":"Santamaría","given":"Asunción"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/app14072747","URL":"https://doi.org/10.3390/app14072747","source":"openalex"},{"id":"oa:W4395451384","type":"article-journal","title":"Co-evolutionary digital twins: A multidimensional dynamic approach to digital engineering","abstract":"Digital Engineering (DE) must be able to maximize efficiency and update dynamically in order to keep up with the wave of global interconnection. The evolution of the Digital Twin (DT) plays a significant role in DE as it enables autonomous optimization and an iterative cycle. However, the intricacy of real-world settings renders conventional evolutionary investigations of a solitary DT inadequate in tackling intricate systems at a comprehensive lifecycle magnitude. To address this, this paper presents the Co-evolutionary DTs (CoEDT), which has several key characteristics. (1) CoEDT study the evolutionary behavior of interconnected multi-DT. (2) CoEDT use a co-evolutionary distributed system architecture and is a DT technology that integrate MBSE . (3) CoEDT offers detailed dynamic models for the complex interactions and co-evolution among multi-DT throughout the lifecycle. It also supports real time measurement of multi-DT behavior to detect system anomalies. The significance of CoEDT lies in providing a more comprehensive insight for future product development by constructing a parallel world that simulates the lifecycle. In the CoEDT, we tackle the behavioral identification and structure of these evolving multi-DT throughout product lifecycle through the following approaches. Initially, drawing inspiration from biological cytology, we have conceived a concept of Collective DTs (CollDTs) to observing a collective behavioral of multi-DT. Subsequently, we further developed CoEDT to depict co-evolutionary behavior patterns and established a co-evolution architecture for all DT throughout the lifecycle by fusing Model-Based Systems Engineering (MBSE). Then, dynamic expressions and algorithm that can measure the co-evolution of every DT are inferred using information theory . Finally, the viability of the proposed CoEDT framework is demonstrated through the development of a solid rocket engine , which promotes the application of DT in the DE.","author":[{"family":"Tong","given":"XC"},{"family":"Bao","given":"Jinsong"},{"family":"Tao","given":"Fei"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.aei.2024.102554","URL":"https://doi.org/10.1016/j.aei.2024.102554","source":"openalex"},{"id":"oa:W4362608901","type":"article-journal","title":"Human-Focused Digital Twin Applications for Occupational Safety and Health in Workplaces: A Brief Survey and Research Directions","abstract":"Occupational safety and health is among the most challenging issues in many industrial workplaces, in that various factors can cause occupational illness and injury. Robotics, automation, and other state-of-the-art technologies represent risks that can cause further injuries and accidents. However, the tools currently used to assess risks in workplaces require manual work and are highly subjective. These tools include checklists and work assessments conducted by experts. Modern Industry 4.0 technologies such as a digital twin, a computerized representation in the digital world of a physical asset in the real world, can be used to provide a safe and healthy work environment to human workers and can reduce occupational injuries and accidents. These digital twins should be designed to collect, process, and analyze data about human workers. The problem is that building a human-focused digital twin is quite challenging and requires the integration of various modern hardware and software components. This paper aims to provide a brief survey of recent research papers on digital twins, focusing on occupational safety and health applications, which is considered an emerging research area. The authors focus on enabling technologies for human data acquisition and human representation in a virtual environment, on data processing procedures, and on the objectives of such applications. Additionally, this paper discusses the limitations of existing studies and proposes future research directions.","author":[{"family":"Park","given":"Jin‐sung"},{"family":"Lee","given":"Dong"},{"family":"Jimenez","given":"Jesus"},{"family":"Lee","given":"Sung"},{"family":"Kim","given":"Jun"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/app13074598","URL":"https://doi.org/10.3390/app13074598","source":"openalex"},{"id":"oa:W4390744672","type":"article-journal","title":"Development and usability testing of a patient digital twin for critical care education: a mixed methods study","abstract":"Background: to minimize preventable patient harm. Our group has developed a novel application software utilizing a digital twin patient model based on electronic health record (EHR) variables to simulate clinical trajectories during the initial 6 h of critical illness. This study aimed to assess the usability, workload, and acceptance of the digital twin application as an educational tool in critical care. Methods: A mixed methods study was conducted during seven user testing sessions of the digital twin application with thirty-five first-year internal medicine residents. Qualitative data were collected using a think-aloud and semi-structured interview format, while quantitative measurements included the System Usability Scale (SUS), NASA Task Load Index (NASA-TLX), and a short survey. Results: Median SUS scores and NASA-TLX were 70 (IQR 62.5-82.5) and 29.2 (IQR 22.5-34.2), consistent with good software usability and low to moderate workload, respectively. Residents expressed interest in using the digital twin application for ICU rotations and identified five themes for software improvement: clinical fidelity, interface organization, learning experience, serious gaming, and implementation strategies. Conclusion: A digital twin application based on EHR clinical variables showed good usability and high acceptance for critical care education.","author":[{"family":"Rovati","given":"Lucrezia"},{"family":"Gary","given":"Phillip"},{"family":"Cubro","given":"Edin"},{"family":"Dong","given":"Yue"},{"family":"Kılıçkaya","given":"Oğuz"},{"family":"Schulte","given":"Phillip"},{"family":"Zhong","given":"Xiang"},{"family":"Wörster","given":"Malin"},{"family":"Kelm","given":"Diana"},{"family":"Gajic","given":"Ognjen"},{"family":"Niven","given":"Alexander"},{"family":"Lal","given":"Amos"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3389/fmed.2023.1336897","URL":"https://doi.org/10.3389/fmed.2023.1336897","source":"openalex"},{"id":"oa:W4405656363","type":"article-journal","title":"Pivotal role of digital twins in the metaverse: A review","abstract":"The ascent of the metaverse signifies a profound transformation in our digital landscape, ushering in a complex network of interlinked virtual domains and digital spaces. In this burgeoning metaverse, a paradigm shift is seen in how people engage, collaborate, and become immersed in digital environments. An especially intriguing concept taking root within this metaverse landscape is that of digital twins. Initially rooted in industrial and Internet of Things (IoT) contexts, digital twins are now making their mark in the metaverse, presenting opportunities to elevate user experiences, introduce novel dimensions of interaction, and seamlessly bridge the divide between the virtual and physical realms. Digital twins, conceived initially to replicate physical entities in real-time, have transcended their industrial origins in this new metaverse context. They no longer solely replicate physical objects but extend their domain to encompass digital entities, avatars, virtual environments, and users. Despite the vital contributions of digital twins in the metaverse, there has been no research that has explored the applications and scope of digital twins in the metaverse comprehensively. However, there are a few papers focusing on some particular applications. Addressing this research gap, we present an in-depth review of the pivotal role of application digital twins in the metaverse. We present 15 digital twin applications in the metaverse, ranging from simulation and training to emergency preparedness. This study outlines the critical limitations of integrating digital twins and metaverse and several future research directions.","author":[{"family":"Sai","given":"Siva"},{"family":"Sharma","given":"Pulkit"},{"family":"Gaur","given":"Aanchal"},{"family":"Chamola","given":"Vinay"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.dcan.2024.12.003","URL":"https://doi.org/10.1016/j.dcan.2024.12.003","source":"openalex"},{"id":"oa:W4385719398","type":"article-journal","title":"Digital Twin based Smart Manufacturing; From Design to Simulation and Optimization Schema","abstract":"The advent of new-generation information and communication technologies, such as Generative AI, Internet of Things (IoT), big data analytics, Blockchain technology, and artificial intelligence (AI), has led to the emergence of the era of big data in recent years. Digital twin has emerged as one of the most active components in smart manufacturing, garnering significant attention from enterprises, research institutes, and researchers. By creating a digital twin, manufacturers can simulate different scenarios and test various configurations without disrupting the actual production process. This allows for more efficient testing and optimization of production processes, as well as improved quality control and predictive maintenance. Overall, digital twins are an important tool in smart production that can help manufacturers improve efficiency and reduce costs while ensuring high-quality output. In this paper, after reviewing the literature on the subject, in this article, by reviewing the literature, we presented a framework of the digital twin in smart manufacturing, which includes Optimization, Predictive Maintenance, Quality Control, Design, and Simulation, which can be a good guide for future studies.","author":[{"family":"Ebni","given":"Mohsen"},{"family":"Bamakan","given":"Seyed"},{"family":"Qu","given":"Qiang"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.procs.2023.08.109","URL":"https://doi.org/10.1016/j.procs.2023.08.109","source":"openalex"},{"id":"oa:W4403186935","type":"article-journal","title":"Digital Twin Technology and Social Sustainability: Implications for the Construction Industry","abstract":"To date, a plethora of research has been published investigating the value of using Digital Twin (DT) technology in the construction industry. However, the contribution of DT technology to promoting social sustainability in the industry has largely been unexplored. Therefore, the current paper aims to address this gap by exploring the untapped potential of DT technology in advancing social sustainability within the construction industry. To this end, a comprehensive systematic literature review was conducted, which identified 298 relevant studies. These studies were subsequently analysed with respect to their use of DT technology in supporting social sustainability. The findings indicated that the studies contributed to 8 of the 17 UN Sustainable Development Goals (SDGs), with a strong focus on SDG11 (77 publications), followed by SDG3 and SDG9, with 58 and 48 studies, respectively, focusing on promoting health and well-being and fostering resilient infrastructure and innovation. Other contributions were identified for SDG13 (30 studies), SDG7 (27 studies), SDG12 (26 studies), SDG4 (21 studies), and SDG6 (11 studies), covering areas such as climate action, responsible consumption, affordable energy, quality education, and clean water and sanitation. This paper also proposes future research directions for advancing DT technology to further enhance social sustainability in the construction industry. These include (i) enhancing inclusivity and diversity, (ii) workforce safety and well-being, (iii) training and skill development, (iv) policy and regulatory support, and (v) cross-disciplinary collaboration.","author":[{"family":"Omrany","given":"Hossein"},{"family":"Mehdipour","given":"Armin"},{"family":"Oteng","given":"Daniel"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/su16198663","URL":"https://doi.org/10.3390/su16198663","source":"openalex"},{"id":"oa:W4382560803","type":"article-journal","title":"Digital twins and 3D information modeling in a smart city for traffic controlling: A review","abstract":"The idea of a smart city has evolved in recent years from limiting the city’s physical growth to a comprehensive idea that includes physical, social, information, and knowledge infrastructure. As of right now, many studies indicate the potential advantages of smart cities in the fields of education, transportation, and entertainment to achieve more sustainability, efficiency, optimization, collaboration, and creativity. So, it is necessary to survey some technical knowledge and technology to establish the smart city and digitize its services. Traffic and transportation management, together with other subsystems, is one of the key components of creating a smart city. We specify this research by exploring digital twin (DT) technologies and 3D model information in the context of traffic management as well as the need to acquire them in the modern world. Despite the abundance of research in this field, the majority of them concentrate on the technical aspects of its design in diverse sectors. More details are required on the application of DTs in the creation of intelligent transportation systems. Results from the literature indicate that implementing the Internet of Things (IoT) to the scope of traffic addresses the traffic management issues in densely populated cities and somewhat affects the air pollution reduction caused by transportation systems. Leading countries are moving towards integrated systems and platforms using Building Information Modelling (BIM), IoT, and Spatial Data Infrastructure (SDI) to make cities smarter. There has been limited research on the application of digital twin technology in traffic control. One reason for this could be the complexity of the traffic system, which involves multiple variables and interactions between different components. Developing an accurate digital twin model for traffic control would require a significant amount of data collection and analysis, as well as advanced modeling techniques to account for the dynamic nature of traffic flow. We explore the requirements for the implementation of the digital twin in the traffic control industry and a proper architecture based on 6 main layers is investigated for the deployment of this system. In addition, an emphasis on the particular function of DT in simulating high traffic flow, keeping track of accidents, and choosing the optimal path for vehicles has been reviewed. Furthermore, incorporating user-generated content and volunteered geographic information (VGI), considering the idea of the human as a sensor, together with IoT can be a future direction to provide a more accurate and up-to-date representation of the physical environment, especially for traffic control, according to the literature review. The results show there are some limitations in digital twins for traffic control. The current digital twins are only a 3D representation of the real world. The difficulty of synchronizing real and virtual world information is another challenge. Eventually, in order to employ this technology as effectively as feasible in urban management, the researchers must address these drawbacks.","author":[{"family":"Rezaei","given":"Zahra"},{"family":"Vahidnia","given":"Mohammad"},{"family":"Aghamohammadi","given":"Hossein"},{"family":"Azizi","given":"Zahra"},{"family":"Behzadi","given":"Saeed"}],"issued":{"date-parts":[[2023]]},"DOI":"10.24294/jgc.v6i1.1865","URL":"https://doi.org/10.24294/jgc.v6i1.1865","source":"openalex"},{"id":"oa:W4388918225","type":"article-journal","title":"Towards Human Digital Twins to enhance workers' safety and production system resilience","abstract":"Industry 5.0 complements Industry 4.0 aiming to create a sustainable, human-centered, and resilient industry. In this context, enabling technologies, such as artificial intelligence, internet of everything, and digital twins, can be used to monitor and enhance the workforce to improve the efficiency and resilience of the entire manufacturing system. By developing socio-technical digital twin architectures, companies will be able in the short future to monitor machines, products, and workers' real-time states as a whole ecosystem. In this study, the authors focus their attention on human digital twin solutions for manufacturing systems, enabling dynamic scheduling of jobs by minimizing the makespan and considering a set of workers’ parameters that are continuously monitored through an ergonomic digital platform. This paper proposes the architecture of a real-time monitoring system and how it can help detect awkward postural behavior or unbalanced workload among workers, according to their individual features. At the same time, the system interacts with the human digital twin system which proposes a rescheduling of the jobs whenever it is necessary. Finally, a discussion on the practical limitations of human digital twin implementations in industrial environments is provided.","author":[{"family":"Berti","given":"Nicola"},{"family":"Finco","given":"Serena"},{"family":"Guidolin","given":"Mattia"},{"family":"Battini","given":"Daria"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.ifacol.2023.10.809","URL":"https://doi.org/10.1016/j.ifacol.2023.10.809","source":"openalex"},{"id":"oa:W4402389761","type":"article-journal","title":"State-of-the-art review and synthesis: A requirement-based roadmap for standardized predictive maintenance automation using digital twin technologies","abstract":"Recent digital advances have popularized predictive maintenance (PMx), offering enhanced efficiency, automation, accuracy, cost savings, and independence in maintenance processes. Yet, PMx continues to face numerous limitations such as poor explainability, sample inefficiency of data-driven methods, complexity of physics-based methods, and limited generalizability and scalability of knowledge-based methods. This paper proposes leveraging Digital Twins (DTs) to address these challenges and enable automated PMx adoption on a larger scale. While DTs have the potential to be transformative, they have not yet reached the maturity needed to bridge these gaps in a standardized manner. Without a standard definition guiding this evolution, the transformation lacks a solid foundation for development. This paper provides a requirement-based roadmap to support standardized PMx automation using DT technologies. Our systematic approach comprises two primary stages. First, we methodically identify the Informational Requirements (IRs) and Functional Requirements (FRs) for PMx, which serve as a foundation from which any unified framework must emerge. Our approach to defining and using IRs and FRs as the backbone of any PMx DT is supported by the proven success of these requirements as blueprints in other areas, such as product development in the software industry. Second, we conduct a thorough literature review across various fields to assess how these IRs and FRs are currently being applied within DTs, enabling us to identify specific areas where further research is needed to support the progress and maturation of requirement-based PMx DTs.","author":[{"family":"Ma","given":"Sizhe"},{"family":"Flanigan","given":"Katherine"},{"family":"Bergés","given":"Mario"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.aei.2024.102800","URL":"https://doi.org/10.1016/j.aei.2024.102800","source":"openalex"},{"id":"oa:W4402508647","type":"article-journal","title":"Two-Timescale Synchronization and Migration for Digital Twin Networks: A Multi-Agent Deep Reinforcement Learning Approach","abstract":"Digital twins (DTs) have emerged as a promising enabler for representing the real-time states of physical worlds and realizing self-sustaining systems. In practice, DTs of physical devices, such as mobile users (MUs), are commonly deployed in multi-access edge computing (MEC) networks for the sake of reducing latency. To ensure the accuracy and fidelity of DTs, it is essential for MUs to regularly synchronize their status with their DTs. However, MU mobility introduces significant challenges to DT synchronization. Firstly, MU mobility triggers DT migration which could cause synchronization failures. Secondly, MUs require frequent synchronization with their DTs to ensure DT fidelity. Nonetheless, DT migration among MEC servers, caused by MU mobility, may occur infrequently. Accordingly, we propose a two-timescale DT synchronization and migration framework with reliability consideration by establishing a non-convex stochastic problem to minimize the long-term average energy consumption of MUs. We use Lyapunov theory to convert the reliability constraints and reformulate the new problem as a partially observable Markov decision-making process (POMDP). Furthermore, we develop a heterogeneous agent proximal policy optimization with Beta distribution (Beta-HAPPO) method to solve it. Numerical results show that our proposed Beta-HAPPO method achieves significant improvements in energy savings when compared with other benchmarks.","author":[{"family":"Liu","given":"Wenshuai"},{"family":"Fu","given":"Yaru"},{"family":"Guo","given":"Yongna"},{"family":"Wang","given":"Fu"},{"family":"Sun","given":"Wen"},{"family":"Zhang","given":"Yan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/twc.2024.3452689","URL":"https://doi.org/10.1109/twc.2024.3452689","source":"openalex"},{"id":"oa:W4387986919","type":"article-journal","title":"Thermal Digital Twin of Power Electronics Modules for Online Thermal Parameter Identification","abstract":"The assessment of the state of health of power semiconductors and the use of thermal observers rely on precise knowledge of the thermal impedance of the device, which is hard to monitor online with state-of-the-art approaches. This work proposes thermal digital twins (DTs), which create a real-time-capable digital replica of the physical thermal behavior and enable monitoring the thermal impedance online. The particle swarm optimization (PSO) algorithm and the dual extended Kalman filter (DEKF) are used to extract the thermal model for online monitoring. This is demonstrated for both approaches via a real-time simulation (RTS) where the reference chip temperature is given by a digital thermal model. A comparison of the approaches is given and the DEKF-based approach is chosen for the implementation of a multichip model with thermal cross-coupling. The convergence of the DEKF-based DTs is experimentally validated in the laboratory.","author":[{"family":"Kuprat","given":"Johannes"},{"family":"Debbadi","given":"Karthik"},{"family":"Schaumburg","given":"Joscha"},{"family":"Liserre","given":"Marco"},{"family":"Langwasser","given":"Marius"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/jestpe.2023.3328219","URL":"https://doi.org/10.1109/jestpe.2023.3328219","source":"openalex"},{"id":"oa:W4391248422","type":"article-journal","title":"A Battery Digital Twin From Laboratory Data Using Wavelet Analysis and Neural Networks","abstract":"Lithium-ion (Li-ion) batteries are the preferred choice for energy storage applications. Li-ion performances degrade with time and usage, leading to a decreased total charge capacity and to an increased internal resistance. In this article, the wavelet analysis is used to filter the voltage and current signals of the battery to estimate the internal complex impedance as a function of state of charge (SoC) and state of health (SoH). The collected data are then used to synthesize a battery digital twin (BDT). This BDT outputs a realistic voltage signal as a function of SoC and SoH inputs. The BDT is based on feedforward neural networks trained to simulate the complex internal impedance and the open-circuit voltage generator. The effectiveness of the proposed method is verified on the dataset from the prognostics data repository of NASA.","author":[{"family":"Fonso","given":"Roberta"},{"family":"Teodorescu","given":"Remus"},{"family":"Cecati","given":"Carlo"},{"family":"Bharadwaj","given":"Pallavi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/tii.2024.3355124","URL":"https://doi.org/10.1109/tii.2024.3355124","source":"openalex"},{"id":"oa:W4379980154","type":"article-journal","title":"Digital Twins and Automation of Care in the Intensive Care Unit","abstract":"Healthcare is under increasing demand pressure as societies age and expectations rise, multiplied by increasing incidence of chronic diseases and decreasing available funding. The fundamental issue is the signal lack of productivity gains in medical care over the last four decades with the advent of digital technologies compared to many other fields of human endeavor. There is thus a need to bring digital technologies and automation to improve productivity and personalize care, improving costs and outcomes for patients and providers. Cyber–physical–human system s ( CPHS ), mixing digital technologies, computation, clinical staff, and patient physiology, offer a route forward. Critical care is one of the most technology-laden areas of healthcare, one of the biggest areas of patient growth with demographic change, and one of the costliest areas of care. Consuming 8–10% of healthcare expenditure (0.8–1.5% GDP) for less than 1% of patients, the intensive care unit ( ICU ) presents a major opportunity for CPHS systems to have an impact in creating the productive, next-generation care required to meet the demand for improved productivity and care. Personalized care, moving from today's one size fits all protocolized care to adaptive, model-based one method fits all care through model-based automation or clinician in the loop semiautomation is the means by which CPHS can enter this realm to positive impact. More specifically, digital twins or virtual patient models, personalized at the bedside in real-time, provide the means to optimize care by linking sensor measurements to outcome focused care actions, enabling personalized control. Digital twins and the so-called “hyper-automation” solutions have been leading technology trends for the last few years, but have yet to come to medicine. This review covers the increasing development of digital twins for medicine, and intensive care in particular, as the foundation for CPHS medical automation to improve care and productivity to meet rising demand. It covers the integrated role played by social sciences in the development, translation, and adoption of innovation, where medicine is historically conservative in adopting innovative solutions and technologies. It ends with a vision of the future from technical, social-behavioral, and combined overall perspectives for digital twins in this domain. CPHS solutions founded on digital twins offer the potential for a step change in ICU care, simultaneously increasing productivity, personalization, and quality of outcomes, while reducing the cost of care. Where the ICU is technology laden and thus most susceptible to this form of automation and disruption, the approach is general and will eventually spread to further areas of healthcare.","author":[{"family":"Chase","given":"JG"},{"family":"Zhou","given":"Cong"},{"family":"Knopp","given":"Jennifer"},{"family":"Möeller","given":"Knut"},{"family":"Benyó","given":"Balázs"},{"family":"Desaive","given":"Thomas"},{"family":"Wong","given":"Jennifer"},{"family":"Malinen","given":"Sanna"},{"family":"Näswall","given":"Katharina"},{"family":"Shaw","given":"Geoffrey"},{"family":"Lambermont","given":"Bernard"},{"family":"Chiew","given":"Yeong"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1002/9781119857433.ch17","URL":"https://doi.org/10.1002/9781119857433.ch17","source":"openalex"},{"id":"oa:W4316042010","type":"article-journal","title":"Game theory in network security for digital twins in industry","abstract":"To ensure the safe operation of industrial digital twins network and avoid the harm to the system caused by hacker invasion, a series of discussions on network security issues are carried out based on game theory. From the perspective of the life cycle of network vulnerabilities, mining and repairing vulnerabilities are analyzed by applying evolutionary game theory. The evolution process of knowledge sharing among white hats under various conditions is simulated, and a game model of the vulnerability patch cooperative development strategy among manufacturers is constructed. On this basis, the differential evolution is introduced into the update mechanism of the Wolf Colony Algorithm (WCA) to produce better replacement individuals with greater probability from the perspective of both attack and defense. Through the simulation experiment, it is found that the convergence speed of the probability (X) of white Hat 1 choosing the knowledge sharing policy is related to the probability (x0) of white Hat 2 choosing the knowledge sharing policy initially, and the probability (y0) of white hat 2 choosing the knowledge sharing policy initially. When y0 = 0.9, X converges rapidly in a relatively short time. When y0 is constant and x0 is small, the probability curve of the “cooperative development” strategy converges to 0. It is concluded that the higher the trust among the white hat members in the temporary team, the stronger their willingness to share knowledge, which is conducive to the mining of loopholes in the system. The greater the probability of a hacker attacking the vulnerability before it is fully disclosed, the lower the willingness of manufacturers to choose the \"cooperative development\" of vulnerability patches. Applying the improved wolf colony-co-evolution algorithm can obtain the equilibrium solution of the \"attack and defense game model\", and allocate the security protection resources according to the importance of nodes. This study can provide an effective solution to protect the network security for digital twins in the industry.","author":[{"family":"Feng","given":"Hailin"},{"family":"Chen","given":"Dongliang"},{"family":"Lv","given":"Haibin"},{"family":"Lv","given":"Zhihan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.dcan.2023.01.004","URL":"https://doi.org/10.1016/j.dcan.2023.01.004","source":"openalex"},{"id":"oa:W4404797425","type":"article-journal","title":"A Digital Twin-Based Digital Product Passport","abstract":"Food supply chains face increasing demands for transparency and sustainability. The Digital Product Passport (DPP), under development in the European Union, can contribute to this purpose by sharing relevant product information with all stakeholders. This research aims to develop a digital twin-based architecture for DPPs and design a prototype for GEOfood products that includes environmental, social, and economic sustainability. Our methodology follows the design science research paradigm. The work was conducted in cooperation with a UNESCO Global Geopark and the GEOfood seal, which certifies food production in regions with unique geological relevance protected by UNESCO. The results include (1) an architecture for digital twin-based DPPs and (2) the design of a DPP prototype for GEOfood products. A formative evaluation was conducted through qualitative interviews with industry experts. Our contribution also includes the integration of social and economic dimensions into the DPP, extending the traditional focus on environmental sustainability data and exemplifying its adoption in supply chains of certified products. Practitioners may find our results inspiring for digital infrastructures capable of real-time monitoring and automatic generation of DPPs that adhere to the tenets of circular economy and human-centric production.","author":[{"family":"Monteiro","given":"José"},{"family":"Barata","given":"João"},{"family":"Gentilini","given":"Sara"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.procs.2024.09.251","URL":"https://doi.org/10.1016/j.procs.2024.09.251","source":"openalex"},{"id":"oa:W4400275536","type":"article-journal","title":"Internet of Federated Digital Twins: Connecting Twins Beyond Borders for Society 5.0","abstract":"The concept of digital twin (DT), which enables the creation of a programmable, digital representation of physical systems, is expected to revolutionize future industries and will lie at the heart of the vision of a future smart society, namely, Society 5.0, in which high integration between cyber (digital) and physical spaces is exploited to bring economic and societal advancements. However, the success of such a DT-driven Society 5.0 requires a synergistic convergence of artificial intelligence and networking technologies into an integrated, programmable system that can coordinate DT networks to effectively deliver diverse Society 5.0 services. Prior works remain restricted to either qualitative study, simple analysis or software implementations of a single DT, and thus, they cannot provide the highly synergistic integration of digital and physical spaces as required by Society 5.0. In contrast, this paper envisions a novel concept of an Internet of Federated Digital Twins (IoFDT) that holistically integrates heterogeneous and physically separated DTs representing different Society 5.0 services within a single framework and system. For this concept of IoFDT, we first introduce a hierarchical architecture that integrates federated DTs through horizontal and vertical interactions, bridging cyber and physical spaces to unlock new possibilities. Then, we discuss challenges of realizing IoFDT, highlighting the intricacies across communication, computing, and AI-native networks while also underscoring potential innovative solutions. Subsequently, we elaborate on the importance of the implementation of a unified IoFDT platform that integrates all technical components and orchestrates their interactions, emphasizing the necessity of practical experimental platforms with a focus on real-world applications in areas like smart mobility.","author":[{"family":"Yu","given":"Tao"},{"family":"Li","given":"Zongdian"},{"family":"Hashash","given":"Omar"},{"family":"Sakaguchi","given":"Kei"},{"family":"Saad","given":"Walid"},{"family":"Debbah","given":"Mérouane"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/iotm.001.2300279","URL":"https://doi.org/10.1109/iotm.001.2300279","source":"openalex"},{"id":"oa:W4387564394","type":"article-journal","title":"Opportunities and challenges of digital twin technology in healthcare","abstract":"To the Editor: The classic case considered to be the primary application of the digital twin approach is the Apollo 13 mission in 1970. In 2003, the concept of the digital twin was presented by Prof. Michael Grieves at the University of Michigan. However, the widespread dissemination of the digital twin concept is attributed to the National Aeronautics and Space Administration's application of digital twin for aerospace vehicle health maintenance and assurance in 2011.[1] The improvement of new-generation information technology has led to a wider range of applications for digital twin technology, including healthcare. Digital twin technology has already started in healthcare, with promising applications in the fields of disease diagnosis and treatment, clinical medical research, and individualized health monitoring.[2] Supplementary Figure 1, https://links.lww.com/CM9/B793 overviews the application of digital twin technology in healthcare. Digital twin technology offers a new possibility in the field of disease diagnosis and treatment, in which the patient is not operated on initially, but a specific simulation of the patient's diseased organ is performed, and possible difficulties and complications are then investigated. This simulation is the “digital twin,” which allows the potential course of the disease to be predicted. Digital twin technology can assist in cardiac surgery planning, planning percutaneous coronary interventions, and addressing the challenge of preoperative evaluation of complex epilepsy surgeries. Digital twins are often used to conduct virtual clinical trials to shorten the development cycle of biopharmaceutical products and reduce costs. The digital twin model, applied in the phase I clinical trials, can effectively preclude the identification of contraindications to potential treatments. On the one hand, the digital twin approach can simulate the biological variability required for a clinical trial on the basis of a small sample size and provide advice on individual dose selection; on the other hand, digital twin modeling can also take into account special situations in which some subjects may have treatment-related contraindications or adverse drug reactions. Phase II clinical trials are a key stage in the drug development process to initially assess the therapeutic effect and safety of a drug in patients with the target indication. Virtual models accurately predict individual responses to interventions so that a larger virtual patient population can be generated, which can be used to identify adverse reactions. This process may help to identify potential problems and improve the success of drug development before proceeding to full phase III clinical studies. Phase III trials represent the most challenging trial phase because they are large and long-lasting. An important and potential benefit of virtual clinical trials is that the size of human trials can be reduced by making reliable predictions. Therefore, virtual clinical trials could significantly shorten the time-to-market for new drugs or therapeutic strategies and reduce the costs of development. Individual health monitoring is one of the applications of digital twin technology for individuals. Based on data that are dynamically collected in real time using wearable or environmental sensors, we can build digital twins that simulate specific objects in real time. In this way, recommendations can be provided for sub-healthy individuals who need strict self-management, or who are just at risk for certain diseases. Regarding personal health monitoring, digital twins can predict responses to new treatments in cancer patients and are used for personalized prevention of osteoporosis, nutritional management of diabetic patients, and public health. Digital twin technology is widely used in the field of healthcare. Digital twin technology can enable new methods of disease prediction, prevention, diagnosis, and treatment. There are many potentially valuab","author":[{"family":"Wang","given":"Mingbang"},{"family":"Hu","given":"Huijuan"},{"family":"Wu","given":"Song"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1097/cm9.0000000000002896","URL":"https://doi.org/10.1097/cm9.0000000000002896","source":"openalex"},{"id":"oa:W4396805343","type":"article-journal","title":"Digital twins in aircraft production and MRO: challenges and opportunities","abstract":"Abstract The digital twin (DT) concept, value-adding connecting the real and digital world, has been a rising trend in recent years, while the implementation and observation of challenges are still subject to research. Implementations of holistic Digital Twins of tangible and intangible assets of complex products or processes are often ideal-theoretic; instead, only subsystems and processes are replicated, which digital representations serve specific, meaningful applications. Specifically, with its distinct characteristics, the aviation industry and its production show various future application scenarios, which we use case-driven outline in this work. Therefore, we first summarize common, industry-neutral challenges of implementing Digital Twins and give an overview of aircraft production characteristics. Then, we will outline different fields of utilizing the Digital Twin concept and highlight integrational, organizational, and compliance-related challenges as well as opportunities in the context of aircraft production and Maintenance, Repair, and Overhaul (MRO). The use cases are located at different aircraft life cycle phases, from production system development, production supplying logistics, and Quality Assurance (QA) up to retrofit.","author":[{"family":"Moenck","given":"Keno"},{"family":"Rath","given":"Jan"},{"family":"Koch","given":"Julian"},{"family":"Wendt","given":"Arne"},{"family":"Kalscheuer","given":"Florian"},{"family":"Schüppstuhl","given":"Thorsten"},{"family":"Schoepflin","given":"Daniel"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/s13272-024-00740-y","URL":"https://doi.org/10.1007/s13272-024-00740-y","source":"openalex"},{"id":"oa:W4379386219","type":"article-journal","title":"Research on Rolling Bearing Fault Diagnosis Based on Digital Twin Data and Improved ConvNext","abstract":"This article introduces a novel framework for diagnosing faults in rolling bearings. The framework combines digital twin data, transfer learning theory, and an enhanced ConvNext deep learning network model. Its purpose is to address the challenges posed by the limited actual fault data density and inadequate result accuracy in existing research on the detection of rolling bearing faults in rotating mechanical equipment. To begin with, the operational rolling bearing is represented in the digital realm through the utilization of a digital twin model. The simulation data produced by this twin model replace traditional experimental data, effectively creating a substantial volume of well-balanced simulated datasets. Next, improvements are made to the ConvNext network by incorporating an unparameterized attention module called the Similarity Attention Module (SimAM) and an efficient channel attention feature referred to as the Efficient Channel Attention Network (ECA). These enhancements serve to augment the network's capability for extracting features. Subsequently, the enhanced network model is trained using the source domain dataset. Simultaneously, the trained model is transferred to the target domain bearing using transfer learning techniques. This transfer learning process enables the accurate fault diagnosis of the main bearing to be achieved. Finally, the proposed method's feasibility is validated, and a comparative analysis is conducted in comparison with similar approaches. The comparative study demonstrates that the proposed method effectively addresses the issue of low mechanical equipment fault data density, leading to improved accuracy in fault detection and classification, along with a certain level of robustness.","author":[{"family":"Zhang","given":"Chao"},{"family":"Qin","given":"Feifan"},{"family":"Zhao","given":"Wentao"},{"family":"Li","given":"Jianjun"},{"family":"Liu","given":"Tongtong"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/s23115334","URL":"https://doi.org/10.3390/s23115334","source":"openalex"},{"id":"oa:W4324146428","type":"article-journal","title":"Are digital twins improving urban-water systems efficiency and sustainable development goals?","abstract":"A digital twin is a tool, which enables a real-time simulation of the water systems and therefore, the water managers can make a decision in the management of the water system over time. The use of these new interaction tool implies the improvement of the awareness of the whole system and it lies in improving the sustainability and efficiency of the water systems with the integration of measurements. The research proposed a methodology to integrate GIS and water models, being the main goal the integration of social, economic, environmental and technical issues. This integration enables improvement in the accuracy and reliability of data and it increases the performance of water systems. This study proposes a pressure-reduction strategy and the implementation of pumps as turbines (PATs), applicable in Sta Cruz, Madeira water system. The use of the developed digital twin model assures a decrease of 3.3 hm3 in water-demand volume, increasing renewable generation by micro-hydropower up to 1.2 GWh. These actions would result in savings above 1.5 M€, decreasing around 530 tons of CO2 emissions each year. The consideration of these values implies the improvement of different indicators, which allows the evaluation of different targets linked to sustainable development goals (SDGs).","author":[{"family":"Ramos","given":"Helena"},{"family":"Kuriqi","given":"Alban"},{"family":"Coronado-Hernández","given":"Óscar"},{"family":"Jiménez","given":"Petra"},{"family":"Pérezsánchez","given":"Modesto"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1080/1573062x.2023.2180396","URL":"https://doi.org/10.1080/1573062x.2023.2180396","source":"openalex"},{"id":"oa:W4404687927","type":"article-journal","title":"Mobility-Aware Dependent Task Offloading in Edge Computing: A Digital Twin-Assisted Reinforcement Learning Approach","abstract":"Collaborative edge computing (CEC) has emerged as a promising paradigm, enabling edge nodes to collaborate and execute tasks from end devices. Task offloading is a fundamental problem in CEC that decides when and where tasks are executed upon the arrival of tasks. However, the mobility of users often results in unstable connections, leading to network failures and resource underutilization. Existing works have not adequately addressed joint mobility-aware dependent task offloading and network flow scheduling, resulting in network congestion and suboptimal performance. To address this, we formulate an online joint mobility-aware dependent task offloading and bandwidth allocation problem, to improve the quality of service by reducing task completion time and energy consumption. We introduce a Mobility-aware Digital Twin-assisted Deep Reinforcement Learning (MDT-DRL) algorithm. Our digital twin model equips the reinforcement learning process by providing future states of mobile users, enabling efficient offloading plans for adapting to the mobile CEC system. Experimental results on real-world and synthetic datasets show that MDT-DRL surpasses state-of-the-art baselines on average task completion time and energy consumption.","author":[{"family":"Chen","given":"Xiangchun"},{"family":"Cao","given":"Jiannong"},{"family":"Sahni","given":"Yuvraj"},{"family":"Zhang","given":"Mingjin"},{"family":"Liang","given":"Zhixuan"},{"family":"Yang","given":"Lei"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/tmc.2024.3506221","URL":"https://doi.org/10.1109/tmc.2024.3506221","source":"openalex"},{"id":"oa:W4396596966","type":"article-journal","title":"Bi-Directional Digital Twin and Edge Computing in the Metaverse","abstract":"The Metaverse has emerged to extend our lifestyle beyond physical limitations. As essential components in the Metaverse, digital twins (DTs) are the real-time digital replicas of physical items. Multi-access edge computing (MEC) provides responsive services to the end users, ensuring an immersive and interactive Metaverse experience. While the digital representation (DT) of physical objects, end users, and edge computing systems is crucial in the Metaverse, the construction of these DTs and the interplay between them have not been well-investigated. In this article, we discuss the bidirectional reliance between the DT and the MEC system and investigate the creation of DTs of objects and users on the MEC servers and DT-assisted edge computing (DTEC). To ensure seamless handover among MEC servers and to avoid intermittent Metaverse services, we also explore the interaction between local DTECs on local MEC servers and the global DTEC on the cloud server due to the dynamic nature of network states (e.g., channel state and users' mobility). We investigate a continual learning framework for resource allocation strategy in local DTEC through a case study. Our strategy mitigates the desynchronization between physical-digital twins, ensures higher learning outcomes, and provides a satisfactory Metaverse experience.","author":[{"family":"Yu","given":"Jiadong"},{"family":"Alhilal","given":"Ahmad"},{"family":"Hui","given":"Pan"},{"family":"Tsang","given":"Danny"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/iotm.001.2300173","URL":"https://doi.org/10.1109/iotm.001.2300173","source":"openalex"},{"id":"oa:W4402738631","type":"article-journal","title":"Development of immersive bridge digital twin platform to facilitate bridge damage assessment and asset model updates","abstract":"Conventional infrastructure asset management practices have heavily relied on static data collection and suffered from decision lags. Though advanced Structural Health Monitoring (SHM) systems were extensively explored based on multi-functional sensor deployment, asset model updating has not been achieved to facilitate timely and effective decision-making of infrastructure managers due to a lack of system integration. To address this challenge, this study develops the Immersive Bridge Digital Twin Platform (IBDTP) to allow infrastructure managers to automate the SHM processes of bridges and engage them in immersive decision-making processes based on Scan-to-BIM and Augmented Reality (AR) technologies. A novel 3D game engine is proposed as part of IBDTP and was tested using a single-span concrete arch bridge located in Poland. Results show that the measurement data collected and presented in IBDTP improves the infrastructure managers' accessibility to major damage data of the bridge to plan for future interventions. The functions of the IBDTP can be potentially scaled for different types of bridges and critical infrastructure, substantially improving the traditional SHM in terms of data management and 3D structural visualization.","author":[{"family":"Fawad","given":"Muhammad"},{"family":"Salamak","given":"Marek"},{"family":"Chen","given":"Qian"},{"family":"Uściłowski","given":"Mateusz"},{"family":"Koris","given":"Kálmán"},{"family":"Jasiński","given":"Marcin"},{"family":"Łaziński","given":"Piotr"},{"family":"Piotrowski","given":"Dawid"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.compind.2024.104189","URL":"https://doi.org/10.1016/j.compind.2024.104189","source":"openalex"},{"id":"oa:W4391420748","type":"article-journal","title":"AI in Energy Digital Twining: A Reinforcement Learning-Based Adaptive Digital Twin Model for Green Cities","abstract":"Digital Twins (DT) have become crucial to achieve sustainable and effective smart urban solutions. However, current DT modelling techniques cannot support the dynamicity of these smart city environments. This is caused by the lack of right-time data capturing in traditional approaches, resulting in inaccurate modelling and high resource and energy consumption challenges. To fill this gap, we explore spatiotemporal graphs and propose the Reinforcement Learning-based Adaptive Twining (RL-AT) mechanism with Deep Q Networks (DQN). By doing so, our study contributes to advancing Green Cities and showcases tangible benefits in accuracy, synchronisation, resource optimization, and energy efficiency. As a result, we note the spatiotemporal graphs are able to offer a consistent accuracy and 55% higher querying performance when implemented using graph databases. In addition, our model demonstrates right-time data capturing with 20% lower overhead and 25% lower energy consumption.","author":[{"family":"Çakır","given":"Lal"},{"family":"Duran","given":"Kübra"},{"family":"Thomson","given":"Craig"},{"family":"Broadbent","given":"Matthew"},{"family":"Canberk","given":"Berk"},{"family":"Cakir","given":"Lal"},{"family":"Duran","given":"Kubra"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/icc51166.2024.10622773","URL":"https://doi.org/10.1109/icc51166.2024.10622773","source":"openalex"},{"id":"oa:W4396920669","type":"article-journal","title":"Digital Twin-based bottleneck prediction for improved production control","abstract":"Bottlenecks in manufacturing systems may significantly reduce their efficiency and productivity. Therefore, bottleneck analysis is a consolidated topic in Industrial Engineering, both in research and practice. Recently, traditional methods for bottleneck analysis have been enhanced with data-driven approaches, such as artificial intelligence and big data analytics. Nevertheless, their exploitation built on the full scope of technologies from digitalization is still not fulfilled. Indeed, the integration with simulation-based methods remains under-explored. This work aims to address bottleneck prediction leveraging on Digital Twin simulation capabilities to predict manufacturing system behavior. For this purpose, the work first offers an extensive review of bottleneck identification methods, inclusive of the ones based on Digital Twin. The main contribution of the work lies in the proposal of a novel Digital Twin-based bottleneck prediction framework with the end purpose to achieve performance improvements actuated through production control. The framework utilizes the Digital Twin for predicting and mitigating bottlenecks in manufacturing systems. The Digital Twin enables the simulation of the future system behavior, while accounting for the current conditions. This insight can then be used by a bottleneck identification method to infer future system bottleneck. The information on the predicted bottleneck is eventually used to support production control decisions, by adapting the order release and sequencing according to the predicted bottleneck. The benefits of adapting production control to the predicted bottleneck are evaluated quantitatively, highlighting how system performance is enhanced. By doing so, this research contributes to bridging the gap between Digital Twin-based performance analysis and production control, providing knowledge and a practical framework transferable to researchers and industrial practitioners.","author":[{"family":"Ragazzini","given":"Lorenzo"},{"family":"Negri","given":"Elisa"},{"family":"Fumagalli","given":"Luca"},{"family":"Macchi","given":"Marco"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.cie.2024.110231","URL":"https://doi.org/10.1016/j.cie.2024.110231","source":"openalex"},{"id":"oa:W4387350568","type":"article-journal","title":"Digital Twins for Consumer Electronics","abstract":"Digital Twin(DT) is at the forefront of the Industry 4.0 revolution facilitated through advanced data analytics and the Internet of Things (IoT) connectivity. With this research, we intend to explore the applications of digital twins in the consumer electronics(CE) industry. This study delves into different realms within the consumer electronics sector to explore how digital twin technology could be beneficial while considering the potential limitations. Some CE fields that could benefit from digital twins include product design and development, predictive maintenance, personalization, virtual user manuals and training, product performance optimization, remote support and troubleshooting, supply chain optimization, and sustainability. This research also focuses on various aspects of the crucial role played by consumer electronics in implementing digital twins in the industry, including hardware integration, data collection methods and establishing reliable connectivity, software development, standards and interoperability, user experience and interaction design, data security and privacy, and feedback-driven improvements. It also discusses challenges like data accuracy, complexity, cost, limited scope of representation, data privacy and security concerns, user engagement and adoption, and integration and compatibility issues faced while implementing this technology.","author":[{"family":"Sai","given":"Siva"},{"family":"Rastogi","given":"Aditya"},{"family":"Chamola","given":"Vinay"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/mce.2023.3322013","URL":"https://doi.org/10.1109/mce.2023.3322013","source":"openalex"},{"id":"oa:W4387162866","type":"article-journal","title":"Exploring the Integration of Digital Twin and Generative AI in Agriculture","abstract":"Agriculture is seeking a modern transformation to meet the demands of efficient and sustainable production. The integration of new technologies is crucial in this endeavor. Digital Twin (DT) and Generative Artifcual Intelligence (AI) have emerged as promising technologies in various industries. However, their potential in the agricultural sector remains relatively unexplored. This paper aims to bridge this research gap by examining the current studies and potential applications of DT and Generative AI in agriculture. We investigate the synergies between these technologies and their opportunities and challenges in agricultural practices. This research sheds light on the integration of DT and Generatiev AI in agriculture, paving the way for future advancements in the field.","author":[{"family":"Liu","given":"Jian"},{"family":"Zhou","given":"Yongqi"},{"family":"Li","given":"Yu"},{"family":"Li","given":"Yong"},{"family":"Hong","given":"Sha"},{"family":"Li","given":"Qiang"},{"family":"Liu","given":"Xin"},{"family":"Lu","given":"Ming"},{"family":"Wang","given":"Xing"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/ihmsc58761.2023.00059","URL":"https://doi.org/10.1109/ihmsc58761.2023.00059","source":"openalex"},{"id":"oa:W4386275787","type":"article-journal","title":"A Bayesian Framework for Digital Twin-Based Control, Monitoring, and Data Collection in Wireless Systems","abstract":"Commonly adopted in the manufacturing and aerospace sectors, digital twin (DT) platforms are increasingly seen as a promising paradigm to control, monitor, and analyze software-based, “open”, communication systems that are expected to dominate 6G deployments. Notably, DT platforms provide a sandbox in which to test artificial intelligence (AI) solutions for communication systems, potentially reducing the need to collect data and test algorithms in the field, i.e., on the physical twin (PT). A key challenge in the deployment of DT systems is to ensure that virtual control optimization, monitoring, and analysis at the DT are safe and reliable, avoiding incorrect decisions caused by “model exploitation”. To address this challenge, this paper presents a general Bayesian framework with the aim of quantifying and accounting for model uncertainty at the DT that is caused by limitations in the amount and quality of data available at the DT from the PT. In the proposed framework, the DT builds a Bayesian model of the communication system, which is leveraged to enable core DT functionalities such as control via multi-agent reinforcement learning (MARL), monitoring of the PT for anomaly detection, prediction, data-collection optimization, and counterfactual analysis. To exemplify the application of the proposed framework, we specifically investigate a case-study system encompassing multiple sensing devices that report to a common receiver. Experimental results validate the effectiveness of the proposed Bayesian framework as compared to standard frequentist model-based solutions.","author":[{"family":"Ruah","given":"Clément"},{"family":"Simeone","given":"Osvaldo"},{"family":"Alhashimi","given":"Bashir"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/jsac.2023.3310093","URL":"https://doi.org/10.1109/jsac.2023.3310093","source":"openalex"},{"id":"oa:W4376645303","type":"article-journal","title":"Solar irradiance forecasting models using machine learning techniques and digital twin: A case study with comparison","abstract":"The ever-increasing demand for energy and power consumption due to population growth, economic expansion, and evolving consumer choices has led to the need for renewable energy sources. Traditional energy sources such as coal, oil, and gas have contributed to global pollution and have adverse effects on human health. As a result, the use of renewable energy for power generation has increased tremendously. One such area of research is solar irradiation prediction, which utilizes Artificial Intelligence and Machine Learning techniques. With the use of real-time predicted data, the digital twins are intended to add value to the organization by identifying and preventing problems, predicting performance, and improving operations. This paper provides an overview of various learning methods used for predicting irradiance and presents a new ensemble solar irradiance forecasting model that combines eight machine learning models to ensure model diversity. The model's most critical factors for predicting irradiance include temperature, cloudiness index, relative humidity, and day of the week. To conduct a comprehensive analysis, the proposed 8-Stacking Regression Cross Validation (8 STR-CV) model was tested using data from three different climatic zones in India. The model's high accuracy scores of 98.8% for Visakhapatnam, 98% for Nagpur, and 97.8% for the mountainous region make it a valuable tool for future prediction in various sectors, including power generation and utilization planning.","author":[{"family":"Sehrawat","given":"Neha"},{"family":"Vashisht","given":"Sahil"},{"family":"Singh","given":"Amritpal"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.ijin.2023.04.001","URL":"https://doi.org/10.1016/j.ijin.2023.04.001","source":"openalex"},{"id":"oa:W4402260162","type":"article-journal","title":"Digital Twins for Modern Power Electronics: An investigation into the enabling technologies and applications","abstract":"Digital twins are emerging in power electronics as a tool for optimized design, fast prototyping, and smart maintenance, given the increasing demand in terms of high power density, reliability, and low cost. A power electronics digital twin can be regarded as a virtual representation of a power electronics system, embodied by a high-fidelity model running in real time, of which the states and model parameters are updated based on the feedback from the sensors or their data fusions. Digital twin models are developed in multiple domains and run in real time or even faster than real time. The data collected from the physical entities are transferred with controlled latencies and quality, and then processed to iterate the models to represent physical power electronics from application-oriented views. However, due to the nonlinearities and fast switching behaviors of power electronics, one significant challenge is to ensure high fidelity and fast computation simultaneously, which stimulates the real-time simulation (RTS) of power electronics with an ultralow time step. Moreover, the electrical, thermal, and electrothermal aspects shall all be considered to improve the model’s accuracy. To consider the uncertainties, the parameters of the digital twin models are either identified by advanced optimization algorithms or represented by probabilistic expressions. To make it possible, real-time communication should be established between the physical and digital twins. Empowered by modern Internet of Things (IoT) technology, many sensor signals can be transferred in a timely fashion to ensure real-time capability of the digital twin. The digital twin gives insightful information about its physical counterpart based on which smart decisions can be made to improve the design, prototyping, control, and lifecycle management of power electronics converters and systems. In this article, we review the digital twin of modern power electronics, and get an insight into its enabling technologies and possible applications.","author":[{"family":"Bai","given":"Hao"},{"family":"Kuprat","given":"Johannes"},{"family":"Osório","given":"Caio"},{"family":"Liu","given":"Chen"},{"family":"Liserre","given":"Marco"},{"family":"Gao","given":"Fei"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/mele.2024.3423111","URL":"https://doi.org/10.1109/mele.2024.3423111","source":"openalex"},{"id":"oa:W4317241540","type":"article-journal","title":"Intelligent digital twin for federated learning in AIoT networks","abstract":"Federated Learning (FL) promises to solve the data privacy problem by training the local model on each node and sharing the model parameters instead of the data itself. Next, the FL server applies model aggregation techniques to aggregate the received models and broadcast the resulting model to the connected clients. This study proposes a Digital Twin-based Federated Learning (DT-FL) framework to virtually monitor and controls the remotely deployed physical clients and their training process. The connection-oriented protocol, Open Connectivity Foundation (OCF) Iotivity, connects the FL clients with the FL server to ensure packet delivery. OCF Iotivity sends/receives the models’ weights to/from the server, and Hyper Text Transfer Protocol (HTTP) is used to monitor clients’ local training. After receiving partially trained models from clients, the server performs the optimal model selection using the normal distribution method by considering the performance of the model. Finally, the best-selected models are aggregated, and the final model is broadcasted to the clients. The framework utilizes Raspberrypi 4 devices as clients with limited computational capabilities, due to which the experiments are conducted with structured energy consumption data. The dataset comprises of 8 multistory residential buildings located in different geographical locations of the Republic of Korea. Each residential building is treated as an FL client and registered on DT using the IP address and port number. The DT-FL framework can be used with classification and regression datasets, and the model architecture for that data can be designed on the DT platform. The experiments are conducted with the partial and full participation of clients. The results show the minimum delay time in physical and virtual object synchronization and better performance and generalization of the global model for each client. The source code of the proposed DT-FL framework is available on GitHub.","author":[{"family":"Rizwan","given":"Atif"},{"family":"Ahmad","given":"Rashid"},{"family":"Khan","given":"Anam"},{"family":"Xu","given":"Rongxu"},{"family":"Kim","given":"Do"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.iot.2023.100698","URL":"https://doi.org/10.1016/j.iot.2023.100698","source":"openalex"},{"id":"oa:W4352976997","type":"article-journal","title":"Shared Steering Control With Predictive Risk Field Enabled by Digital Twin","abstract":"A core issue of safe human-machine cooperative driving lies in dynamic assessment of the rapidly evolving driving risks. Given that, this paper proposes a shared controller for safe and human-friendly cooperative driving based on predictive risk assessment enabled by Digital Twin technologies. In the digital world, we create a fine-grained digital replica of the driving scene comprising historical motions of vehicles, as well as roadway geometries and topologies. On the basis of that, spatial-temporal interactive features are obtained with a deep learning-based model and subsequently decoded to predict future trajectories of each target vehicle in the neighborhood of the ego-vehicle. In the physical world, the predicted trajectories of neighboring vehicles are integrated into the risk distribution to construct predictive risk fields. A novel shared controller in the framework of multi-objective MPC is designed to minimize the driving risk while matching driver's commands, so that safe cooperative driving is achieved in a smooth and minimal-intervention manner. The results of driver-in-the-loop simulation experiments demonstrate the enabling role of the Digital Twin in improving the assessment of risk in highly dynamic scenes through taking the motion trends of dynamic agents into account. The results also show the superiority of the Digital Twin-based shared controller in terms of implementing cooperation in time while honoring the driver's commands whenever possible.","author":[{"family":"Liang","given":"Yang"},{"family":"Yin","given":"Zhishuai"},{"family":"Nie","given":"Linzhen"},{"family":"Ba","given":"Yuanxin"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/tiv.2023.3259970","URL":"https://doi.org/10.1109/tiv.2023.3259970","source":"openalex"},{"id":"oa:W4362703568","type":"article-journal","title":"Federated Data Modeling for Built Environment Digital Twins","abstract":"The digital twin (DT) approach is an enabler for data-driven decision making in architecture, engineering, construction, and operations. Various open data models that can potentially support the DT developments, at different scales and application domains, can be found in the literature. However, many implementations are based on organization-specific information management processes and proprietary data models, hindering interoperability. This article presents the process and information management approaches developed to generate a federated open data model supporting DT applications. The business process modeling notation and transaction and interaction modeling techniques are applied to formalize the federated DT data modeling framework, organized in three main phases: requirements definition, federation, validation and improvement. The proposed framework is developed adopting the cross-disciplinary and multiscale principles. A validation on the development of the federated building-level DT data model for the West Cambridge Campus DT research facility is conducted. The federated data model is used to enable DT-based asset management applications at the building and built environment levels.","author":[{"family":"Moretti","given":"Nicola"},{"family":"Xie","given":"Xiang"},{"family":"García","given":"Jorge"},{"family":"Chang","given":"Janet"},{"family":"Parlikad","given":"Ajith"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1061/jccee5.cpeng-4859","URL":"https://doi.org/10.1061/jccee5.cpeng-4859","source":"openalex"},{"id":"oa:W4385477163","type":"article-journal","title":"A multiscale predictive digital twin for neurocardiac modulation","abstract":"Cardiac function is tightly regulated by the autonomic nervous system (ANS). Activation of the sympathetic nervous system increases cardiac output by increasing heart rate and stroke volume, while parasympathetic nerve stimulation instantly slows heart rate. Importantly, imbalance in autonomic control of the heart has been implicated in the development of arrhythmias and heart failure. Understanding of the mechanisms and effects of autonomic stimulation is a major challenge because synapses in different regions of the heart result in multiple changes to heart function. For example, nerve synapses on the sinoatrial node (SAN) impact pacemaking, while synapses on contractile cells alter contraction and arrhythmia vulnerability. Here, we present a multiscale neurocardiac modelling and simulator tool that predicts the effect of efferent stimulation of the sympathetic and parasympathetic branches of the ANS on the cardiac SAN and ventricular myocardium. The model includes a layered representation of the ANS and reproduces firing properties measured experimentally. Model parameters are derived from experiments and atomistic simulations. The model is a first prototype of a digital twin that is applied to make predictions across all system scales, from subcellular signalling to pacemaker frequency to tissue level responses. We predict conditions under which autonomic imbalance induces proarrhythmia and can be modified to prevent or inhibit arrhythmia. In summary, the multiscale model constitutes a predictive digital twin framework to test and guide high-throughput prediction of novel neuromodulatory therapy. KEY POINTS: A multi-layered model representation of the autonomic nervous system that includes sympathetic and parasympathetic branches, each with sparse random intralayer connectivity, synaptic dynamics and conductance based integrate-and-fire neurons generates firing patterns in close agreement with experiment. A key feature of the neurocardiac computational model is the connection between the autonomic nervous system and both pacemaker and contractile cells, where modification to pacemaker frequency drives initiation of electrical signals in the contractile cells. We utilized atomic-scale molecular dynamics simulations to predict the association and dissociation rates of noradrenaline with the β-adrenergic receptor. Multiscale predictions demonstrate how autonomic imbalance may increase proclivity to arrhythmias or be used to terminate arrhythmias. The model serves as a first step towards a digital twin for predicting neuromodulation to prevent or reduce disease.","author":[{"family":"Yang","given":"Pei‐chi"},{"family":"Rose","given":"Adam"},{"family":"Demarco","given":"Kevin"},{"family":"Dawson","given":"John"},{"family":"Han","given":"Yanxiao"},{"family":"Jeng","given":"Mao"},{"family":"Harvey","given":"Robert"},{"family":"Santana","given":"Luis"},{"family":"Ripplinger","given":"Crystal"},{"family":"Vorobyov","given":"Igor"},{"family":"Lewis","given":"Timothy"},{"family":"Clancy","given":"Colleen"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1113/jp284391","URL":"https://doi.org/10.1113/jp284391","source":"openalex"},{"id":"oa:W4391991732","type":"article-journal","title":"A Hybrid Task Offloading and Resource Allocation Approach for Digital Twin-Empowered UAV-Assisted MEC Network Using Federated Reinforcement Learning for Future Wireless Network","abstract":"Federated learning (FL) is proposed as a different approach for distributed learning on the edges while maintaining privacy. Existing FL methods, are mainly focused on learning deep classifying and clustering models, with little consideration offered to the federated reinforcement learning (FRL) task on the edge, a difficult task in which several trained agents track local state and take local actions to train a global learning model without disclosing their local dataset. Several neural network models based on FRL have been presented recently to determine the best method for computation offloading (CO) and resource allocation (RA), particularly in Unmanned Aerial Vehicle (UAV) assisted Mobile Edge Computing (MEC). However, because of the complexity and variety of computational tasks involved in 6G and beyond networks, the FRL algorithms are challenging to apply directly to complicated UAV-assisted MEC scenarios. In this study, we present a generalized FRL approach based on a meta learning technique that incorporates RL models explained by numerous smart devices into a generic model. This research uses a normalized characteristic matrix to divide a complex network into small-scale units and provides a normalized network model for complex network situations based on the FRL meta critic method to determine the CO and RA strategy in a Digital Twin (DT)-enabled UAV-assisted MEC system. Numerical results show that the proposed scheme achieves higher and more reliable overall rewards. Proposed method achieves a 73.15% reduction in reward variance and a 14.23% increase in average rewards over 570 continuous operations.","author":[{"family":"Consul","given":"Prakhar"},{"family":"Budhiraja","given":"Ishan"},{"family":"Garg","given":"Deepak"},{"family":"Kumar","given":"Neeraj"},{"family":"Singh","given":"Ramendra"},{"family":"Almogren","given":"Ahmad"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/tce.2024.3368156","URL":"https://doi.org/10.1109/tce.2024.3368156","source":"openalex"},{"id":"doi:10.1109/cisce58541.2023.10142669","type":"article-journal","title":"A study of digital twin-based digital derivation mechanisms for manufacturing companies","abstract":"This paper starts from the endogenous causes of value creation of the digital twin of manufacturing enterprises and breaks down the composition and functions of the digital twin. Through the process linkage and collaboration of the digital twin, the 4.0 value chain architecture of manufacturing enterprises is dissected. On this basis, the endogenous driving mechanism of the supply chain and industrial chain derived from the 4.0 value chain of manufacturing enterprises is analysed using manufacturing big data, and the framework of the enterprise digital endogenous integration tower 3D process of manufacturing enterprises is proposed, and the nature and derivation mechanism of the supply chain of manufacturing enterprises based on the 4.0 value chain drive is analysed to systematise the formation mechanism and framing mode of the digital twin. The manufacturing enterprise industrial chain is the main body of the digital economy development and the fundamental research paradigm of the new theory of the newly created digital era, whose breakthrough and transformation is the basis for the future matching and optimisation of industrial core elements with industrial digital organisation and technological innovation resources. This is a newly innovative exploration of the digital knowledge system of manufacturing enterprises, which will have a profound impact on the construction of a digital enterprise industry chain with full perception, full connectivity, full scenario and full intelligence, boosting the development of the digital economy and building a new paradigm system of macro and micro interdisciplinary theories.","author":[{"family":"Wang","given":"Feng"},{"family":"Zhe","given":"Cao"},{"family":"Sun","given":"Mingwei"},{"family":"Cao","given":"Zhe"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/cisce58541.2023.10142669","URL":"https://doi.org/10.1109/cisce58541.2023.10142669","source":"openalex"},{"id":"doi:10.5281/zenodo.14441574","type":"article-journal","title":"Exploring Plasticity Rules in the Biologically Realistic Simulation of Neuronal Cultures","abstract":"This is a Master thesis for the MS Neuroengineering program at TU Munich. Abstract: Neuronal cell cultures have served as a pivotal platform for neuroscience experiments sincethe early 20th century. However, despite their long history of use, the processes governingthe development of connectivity and firing patterns in these cultures remain inadequatelyunderstood. In this master’s thesis, I endeavor to bridge this knowledge gap by integratingstraightforward plasticity rules with established models of neuronal culture growth andactivity. The objective is to create a comprehensive and realistic simulation of neuronal culturedevelopment, which can be effectively employed as a digital twin of real-world neuronalculture experiments. To demonstrate the utility of this simulation, I present a case studyinvolving the silencing of neuronal activity using CNQX as an example. This innovativeapproach promises to advance our understanding of neuronal culture dynamics, providingvaluable insights into the behavior of neuronal cell cultures. By offering a powerful digitaltool for experimentation and analysis, this work contributes to the ongoing exploration ofneuroscience and opens up new avenues for research and discovery.","author":[{"family":"Stefan","given":"Dvoretskii"},{"family":"Soriano Fradera","given":"Jordi"},{"family":"Houben","given":"Akke"},{"family":"Haeb","given":"Anna"},{"family":"Barcelona","given":"Universitat"},{"family":"Erasmus"}],"issued":{"date-parts":[[2023]]},"DOI":"10.5281/zenodo.14441574","URL":"https://doi.org/10.5281/zenodo.14441574","source":"datacite"},{"id":"oa:W4390099127","type":"article-journal","title":"Cellular immunity analysis by a modular acoustofluidic platform: CIAMAP","abstract":"The study of molecular mechanisms at the single-cell level holds immense potential for enhancing immunotherapy and understanding neuroinflammation and neurodegenerative diseases by identifying previously concealed pathways within a diverse range of paired cells. However, existing single-cell pairing platforms have limitations in low pairing efficiency, complex manual operation procedures, and single-use functionality. Here, we report a multiparametric cellular immunity analysis by a modular acoustofluidic platform: CIAMAP. This platform enables users to efficiently sort and collect effector-target (i.e., NK92-K562) cell pairs and monitor the real-time dynamics of immunological response formation. Furthermore, we conducted transcriptional and protein expression analyses to evaluate the pathways that mediate effector cytotoxicity toward target cells, as well as the synergistic effect of doxorubicin on the cellular immune response. Our CIAMAP can provide promising building blocks for high-throughput quantitative single-cell level coculture to understand intercellular communication while also empowering immunotherapy by precision analysis of immunological synapses.","author":[{"family":"Zhong","given":"Ruoyu"},{"family":"Sullivan","given":"Matthew"},{"family":"Upreti","given":"Neil"},{"family":"Chen","given":"Roy"},{"family":"Ganzó","given":"Agustin"},{"family":"Yang","given":"Kai‐chun"},{"family":"Yang","given":"Shujie"},{"family":"Jin","given":"Ke"},{"family":"He","given":"Ye"},{"family":"Li","given":"Ke"},{"family":"Xia","given":"Jianping"},{"family":"Ma","given":"Zhiteng"},{"family":"Lee","given":"Luke"},{"family":"Konry","given":"Tania"},{"family":"Huang","given":"Tony"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1126/sciadv.adj9964","URL":"https://doi.org/10.1126/sciadv.adj9964","source":"openalex"},{"id":"oa:W4391591089","type":"manuscript","title":"A Survey on Decentralized Identifiers and Verifiable Credentials","abstract":"Digital identity has always been considered the keystone for implementing secure and trustworthy communications among parties. The ever-evolving digital landscape has gone through many technological transformations that have also affected the way entities are digitally identified. During this digital evolution, identity management has shifted from centralized to decentralized approaches. The last era of this journey is represented by the emerging Self-Sovereign Identity (SSI), which gives users full control over their data. SSI leverages decentralized identifiers (DIDs) and verifiable credentials (VCs), which have been recently standardized by the World Wide Web Community (W3C). These technologies have the potential to build more secure and decentralized digital identity systems, remarkably contributing to strengthening the security of communications that typically involve many distributed participants. It is worth noting that the scope of DIDs and VCs extends beyond individuals, encompassing a broad range of entities including cloud, edge, and Internet of Things (IoT) resources. However, due to their novelty, existing literature lacks a comprehensive survey on how DIDs and VCs have been employed in different application domains, which go beyond SSI systems. This paper provides readers with a comprehensive overview of such technologies from different perspectives. Specifically, we first provide the background on DIDs and VCs. Then, we analyze available implementations and offer an in-depth review of how these technologies have been employed across different use-case scenarios. Furthermore, we examine recent regulations and initiatives that have been emerging worldwide. Finally, we present some challenges that hinder their adoption in real-world scenarios and future research directions.","author":[{"family":"Mazzocca","given":"Carlo"},{"family":"Acar","given":"Abbas"},{"family":"Uluagac","given":"Selcuk"},{"family":"Montanari","given":"Rebecca"},{"family":"Bellavista","given":"Paolo"},{"family":"Conti","given":"Mauro"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2402.02455","URL":"https://doi.org/10.48550/arxiv.2402.02455","source":"openalex"},{"id":"oa:W4386460083","type":"article-journal","title":"Integration of IoT and blockchain for decentralized management and ownership in the metaverse","abstract":"Summary This manuscript provides an in‐depth exploration of metaverses, charting their historical development, technological foundations, and potential multifarious applications. It critically assesses the prevailing challenges and explores potential pathways for the evolution of these expansive, virtual environments. In shedding light on the wide‐ranging implications of metaverses, it navigates societal, cultural, regulatory, and economic landscapes. It further elucidates the symbiosis between the Internet of Things (IoT) and metaverses, presenting empirical evidence derived from purpose‐built IoT frameworks for metaverse applications. A series of experiments were conducted to affirm the hypothesis that the integration of IoT into metaverse utilities, including advanced concepts such as smart buildings, the intricate task of power grid management, and the precision‐centric domain of agriculture, can drive significant progress. Quantitative findings provide compelling evidence of marked improvements in energy conservation, cost‐efficiency, and operational effectiveness arising from the incorporation of IoT into metaverse use cases. With observed mean improvements of 25% in energy conservation, 17% in cost reduction, and an impressive 22% increase in operational efficiency, specifically in the realms of smart building applications and power grid management, this study underscores the pressing need for sustained research and development initiatives in this emerging.","author":[{"family":"Din","given":"Ikram"},{"family":"Awan","given":"Kamran"},{"family":"Almogren","given":"Ahmad"},{"family":"Rodrigues","given":"Joel"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1002/dac.5612","URL":"https://doi.org/10.1002/dac.5612","source":"openalex"},{"id":"oa:W4402504708","type":"article-journal","title":"The Future of Manufacturing with AI and Data Analytics","abstract":"This chapter explores the potential of applying AI and data analytics to transform manufacturing. It provides an overview of new research trends in smart manufacturing, including the use of IoT, big data, and advanced AI technologies like machine learning and digital twins. The conceptual background of relevant AI approaches is discussed, including deep learning, reinforcement learning, unsupervised learning, and state-of-the-art models. A key focus is examining the role of AI in predictive maintenance through data-driven techniques for remaining useful life estimation, anomaly detection, prognostics, and optimizing maintenance strategies. Challenges and limitations such as noisy data, imbalanced datasets, and high computational requirements are addressed. The opportunities enabled by AI in manufacturing are highlighted, spanning synthetic data generation, real-time prediction, and enhancing asset utilization. The chapter concludes that transformative gains in productivity, sustainability, and resilience will arise from thoughtfully leveraging AI and data to inform decision-making in industrial settings. Adoption remains in the early stages, and realizing the full potential will require interdisciplinary collaboration and purposeful innovation.","author":[{"family":"Shah","given":"Neel"},{"family":"Shah","given":"Sneh"},{"family":"Bhanushali","given":"Janvi"},{"family":"Bhatt","given":"Nirav"},{"family":"Bhatt","given":"Nikita"},{"family":"Mewada","given":"Hiren"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/9781394303601.ch23","URL":"https://doi.org/10.1002/9781394303601.ch23","source":"openalex"},{"id":"oa:W4403729009","type":"article-journal","title":"Development of BIM‐Based Tunnel Information Modeling Prototype for Tunnel Design","abstract":"Designing and modeling tunnels are a complex and labor‐intensive process, exacerbated by the involvement of multiple designers and software applications to accommodate diverse geometric and subsurface conditions. This often results in reduced efficiency, productivity, and increased potential for errors. To address these challenges, the authors implemented a strategy integrating building information modeling and mathematical relationships governing tunnel geometries and rock support elements. Using Autodesk Revit, they developed a prototype that allows designers to model tunnels aligned with ground conditions without reliance on multiple software applications. This streamlined approach enhances productivity, simplifies complexities, and improves accuracy in tunnel design and review processes, including quantity take‐offs. A case study comparing the prototype with conventional methods demonstrated significant improvements in efficiency, productivity, and design accuracy. This research offers practical benefits to stakeholders in tunnel projects, optimizing work quality, and outcomes in tunnel design and construction.","author":[{"family":"Waleed","given":"Qazi"},{"family":"Azfar","given":"Rai"},{"family":"Sharafat","given":"Abubakar"},{"family":"Tanoli","given":"Waqas"},{"family":"Zubair","given":"Muhammad"},{"family":"Qureshi","given":"Hisham"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1155/2024/8118578","URL":"https://doi.org/10.1155/2024/8118578","source":"openalex"},{"id":"oa:W4392924151","type":"article-journal","title":"Real‐Time Jones Matrix Synthesis by Compact Polarization Inline Holographic Microscopy","abstract":"Abstract The Jones matrix is a powerful quantitative tool for polarimetric imaging and characterization, where the matrix elements represent the intrinsic optical properties of the anisotropic objects on interaction with the polarized light. Most of the state‐of‐the‐art single‐shot Jones‐matrix imaging techniques rely on interferometric methods, which makes the design complex with the use of large number of polarization optics and produces space‐bandwidth limitations. The simultaneous extraction of Jones matrix elements with a compact system design is still a technical challenge in view of its potential applications in biomedical and real‐time characterization scenarios. In this paper, the imaging features of the in‐line holography are exploited to develop a compact polarization in‐line holography (PIH) system capable of single‐shot extraction of Jones‐matrix elements. The technique achieves simultaneous orthogonal polarization state generation and corresponding polarization multiplexed in‐line hologram detection by utilizing a compact polarization geometry. The imaging compatibility and measurement accuracy of the method is experimentally validated by the real‐time synthesis of Jones‐matrix elements corresponding to custom designed polarization sensitive samples and standard birefringent resolution target. Furthermore, to demonstrate the application of the system in dynamic imaging, the transient polarization changes of a custom‐designed parallel nematic liquid crystal display (LCD) are investigated.","author":[{"family":"Liu","given":"Hanzi"},{"family":"Vinu","given":"RV"},{"family":"Chen","given":"Kaiquan"},{"family":"Liao","given":"Dongyang"},{"family":"Chen","given":"Ziyang"},{"family":"Pu","given":"Jixiong"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/lpor.202301261","URL":"https://doi.org/10.1002/lpor.202301261","source":"openalex"},{"id":"oa:W4319927876","type":"article-journal","title":"Green and Sustainable Hydrogen in Emerging European Smart Energy Framework","abstract":"Abstract Green and sustainable hydrogen has a major role in moving towards decarbonization of energy, providing viable solutions in all most challenging sectors of the national economies. It would penetrate practically all sectors of economic activity, such as long-haul transport, steel and chemical industries, power generation and energy storage. Green and sustainable hydrogen cost competitiveness is also closely linked to developments of large-scale renewable energy sources (in case of green hydrogen; hereinafter – RES) and further commercialization of carbon dioxide (in case of sustainable hydrogen produced from natural gas; hereinafter – CO 2 ) capture and storage ( hereinafter – CCS) technologies. In the European Union ( hereinafter – EU), sustainable and especially green hydrogen is gaining strong political and business momentum, emerging as one of major components in governments’ net zero plans within the European Green Deal and beyond. Being extremely versatile both in production and consumption sides, it is light, storable, has high energy content per unit mass and can be readily produced at an industrial scale. The key challenge comes from the fact that hydrogen is the lightest known chemical element and so has a low energy density per unit of volume, making some forms of long-distance transportation and storage complex and costly. In this paper, green and sustainable hydrogen is reviewed as a vital part of emerging European smart energy framework, which could contribute significantly to economy decarbonization agenda of the EU and Latvia in both in short- and mid-term perspective.","author":[{"family":"Jansons","given":"L"},{"family":"Zemīte","given":"Laila"},{"family":"Zeltins","given":"N"},{"family":"Geipele","given":"Ineta"},{"family":"Backurs","given":"Andris"}],"issued":{"date-parts":[[2023]]},"DOI":"10.2478/lpts-2023-0003","URL":"https://doi.org/10.2478/lpts-2023-0003","source":"openalex"},{"id":"oa:W4317796713","type":"article-journal","title":"Power Generation Control Algorithm for the Participation of Photovoltaic Panels in Network Stability","abstract":"The push for renewable energy and sustainable development has led to an ever-increasing integration of grid-tied photovoltaic (PV) systems. To maximize revenue, this resource generally operates in maximum power point trackers (MPPT) mode. However, to ensure grid stability and reliability, system operators will continue to introduce new requirements, eventually forcing PV plants to adhere to primary frequency regulation. To perform this task, PV plants will have to be capable of operating outside the MPP and varying their power production, to maintain an active power reserve, according to grid request. This article presents an innovative model-based (MB) tracking algorithm devoted to supporting power network regulation. Due to the updated formulation, the algorithm can vary the power curtailment according to a reduction factor given by the power system operators. Results show the remarkable performance and accuracy of the new algorithm, providing power regulation capability in the range 20%–100% of the maximum available power. Moreover, the impact of the employment of constant reduction coefficients on the algorithm performances has been evaluated. Validation has been performed based on the data collected over an observation interval of more than six months. Due to its flexibility, this could be the basis for the participation of PV systems to frequency regulation.","author":[{"family":"Cristaldi","given":"Loredana"},{"family":"Faifer","given":"Marco"},{"family":"Laurano","given":"Christian"},{"family":"Ottoboni","given":"Roberto"},{"family":"Petkovski","given":"Emil"},{"family":"Toscani","given":"Sergio"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/tim.2023.3238745","URL":"https://doi.org/10.1109/tim.2023.3238745","source":"openalex"},{"id":"oa:W4322216957","type":"article-journal","title":"4D Printed Shape Memory Anastomosis Ring with Controllable Shape Transformation and Degradation","abstract":"Abstract Biofragmentable anastomosis ring (BAR) is an ideal sutureless alternative for intestinal connection that is frequently demanded in colonic surgery. However, it is challenging to insert a bulky BAR into the soft and slippery intestine. Here 4D printing of an anastomosis ring with shape memory capability is presented via fused deposition modeling (FDM) 3D printing. The shape memory anastomosis ring can recover from a compressed shape that facilitates the insertion to the permanent shape for connection and supporting. Degradation kinetics is tuned by controlling the blending composition of polylactic acid and poly(lactic‐co‐glycolic acid), so that the device can be excreted after the intestine healing. The shape recovery temperature is adjusted to 50 °C that the human body can withstand for a while. Grid structure and hook lock are designed and printed to guarantee dimension reduction upon programming and stable connection after shape recovery, respectively. A conceptual anastomotic operation shows the advantages and prospects of shape transformation. The 4D printing strategy may promote intestinal anastomosis development and inspire more opportunities for minimally invasive medical surgery.","author":[{"family":"Peng","given":"Wenjun"},{"family":"Yin","given":"Jie"},{"family":"Zhang","given":"Xianming"},{"family":"Shi","given":"Yunpeng"},{"family":"Che","given":"Gang"},{"family":"Zhao","given":"Qian"},{"family":"Liu","given":"Jian"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1002/adfm.202214505","URL":"https://doi.org/10.1002/adfm.202214505","source":"openalex"},{"id":"oa:W4353039744","type":"article-journal","title":"Integrating biopolymer design with physical unclonable functions for anticounterfeiting and product traceability in agriculture","abstract":"Smallholder farmers and manufacturers in the Agri-Food sector face substantial challenges because of increasing circulation of counterfeit products (e.g., seeds), for which current countermeasures are implemented mainly at the secondary packaging level, and are generally vulnerable because of limited security guarantees. Here, by integrating biopolymer design with physical unclonable functions (PUFs), we propose a cryptographic protocol for seed authentication using biodegradable and miniaturized PUF tags made of silk microparticles. By simply drop casting a mixture of variant silk microparticles on a seed surface, tamper-evident PUF tags can be seamlessly fabricated on a variety of seeds, where the unclonability comes from the stochastic assembly of spectrally and visually distinct silk microparticles in the tag. Unique, reproducible, and unpredictable PUF codes are generated from both Raman mapping and microscopy imaging of the silk tags. Together, the proposed technology offers a highly secure solution for anticounterfeiting and product traceability in agriculture.","author":[{"family":"Sun","given":"Hui"},{"family":"Maji","given":"Saurav"},{"family":"Chandrakasan","given":"Anantha"},{"family":"Marelli","given":"Benedetto"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1126/sciadv.adf1978","URL":"https://doi.org/10.1126/sciadv.adf1978","source":"openalex"},{"id":"oa:W4392380538","type":"article-journal","title":"Interplay of Cathode–Halide Solid Electrolyte in Enhancing Thermal Stability of Charged Cathode Material in All-Solid-State Batteries","abstract":"All-solid-state batteries (ASSBs) are expected to address the thermal instability of conventional rechargeable batteries, given nonflammable inorganic solid electrolytes (SEs). However, the interaction between sulfide SEs and electrode materials can cause an exothermic reaction accompanied by the formation of explosive decomposition products. Herein, we demonstrate the enhanced thermal stability of a charged cathode material (Li 1– x Ni 0.6 Co 0.2 Mn 0.2 O 2, x ≈ 0.5) with a Li 3 InCl 6 halide SE compared to sulfide SEs. Li 3 InCl 6 and the cathode composite not only delay the decomposition of NCM622 but also mitigate oxygen evolution from the cathode via oxidation decomposition of the halide SE. Furthermore, the halide SE suppresses combustible oxygen-gas evolution by capturing oxygen species through a mitigated exothermic reaction accompanying an endothermic phase transition from oxychloride to oxide. Oxygen capture was also observed in other halide SEs (Li 3 YCl 6 and Li 2 ZrCl 6 ). These findings emphasize the pivotal role of the cathode–SE interfacial interplay in governing the thermal stability of ASSBs and suggest SE design criteria for thermally safe battery systems.","author":[{"family":"Lee","given":"Sangpyo"},{"family":"Kim","given":"Youngkyung"},{"family":"Park","given":"Chanhyun"},{"family":"Kim","given":"Jihye"},{"family":"Kim","given":"Jae‐seung"},{"family":"Jo","given":"Hyoi"},{"family":"Lee","given":"Chang"},{"family":"Choi","given":"Sinho"},{"family":"Seo","given":"Dong‐hwa"},{"family":"Jung","given":"Sung‐kyun"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1021/acsenergylett.4c00033","URL":"https://doi.org/10.1021/acsenergylett.4c00033","source":"openalex"},{"id":"oa:W4396214404","type":"article-journal","title":"Anomaly Detection in Smart Environments: A Comprehensive Survey","abstract":"Anomaly detection is a critical task in ensuring the security and safety of infrastructure and individuals in smart environments. This paper provides a comprehensive analysis of recent anomaly detection solutions in data streams supporting smart environments, with a specific focus on multivariate time series anomaly detection in various environments, such as smart home, smart transport, and smart industry. The aim is to offer a thorough overview of the current state-of-the-art in anomaly detection techniques applicable to these environments. This includes an examination of publicly available datasets suitable for developing these techniques. The survey is designed to inform future research and practical applications in the field, serving as a valuable resource for researchers and practitioners. It not only reviews a range of state-of-the-art anomaly detection methods, from statistical and proximity-based to those adopting deep learning-methods but also covers fundamental aspects of anomaly detection. These aspects include the categorization of anomalies, detection scenarios, challenges associated, and evaluation metrics for assessing the techniques’ performance.","author":[{"family":"Fährmann","given":"Daniel"},{"family":"Martín","given":"Laura"},{"family":"Sánchez","given":"Luı́s"},{"family":"Damer","given":"Naser"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/access.2024.3395051","URL":"https://doi.org/10.1109/access.2024.3395051","source":"openalex"},{"id":"oa:W4400596544","type":"article-journal","title":"Sustainable procurement practices: Balancing compliance, ethics, and cost-effectiveness","abstract":"Sustainable procurement, the acquisition of goods and services that ensures positive environmental, social, and economic impacts, is essential for contemporary business practices. This paper explores the integration of compliance, ethics, and cost-effectiveness within sustainable procurement. Compliance is governed by regulatory frameworks like ISO 20400 and government regulations, ensuring adherence to sustainability standards. Ethical procurement upholds fairness, transparency, integrity, and human rights principles, positively impacting stakeholders such as suppliers, employees, and communities. Cost-effectiveness in sustainable procurement brings significant economic benefits, including cost savings, efficiency gains, and long-term financial advantages. A holistic approach integrating these elements is crucial for developing a sustainable procurement strategy. Organizations are encouraged to prioritize sustainable procurement by developing clear policies, engaging stakeholders, providing training, managing suppliers effectively, and leveraging technology. The paper concludes that balancing these three aspects fosters trust among stakeholders, enhances brand reputation, and ensures long-term operational efficiency, contributing to broader sustainability goals and driving overall organizational success.","author":[{"family":"Adebayo","given":"Victor"},{"family":"Paul","given":"Patience"},{"family":"Eyo-Udo","given":"Nsisong"}],"issued":{"date-parts":[[2024]]},"DOI":"10.30574/gscarr.2024.20.1.0247","URL":"https://doi.org/10.30574/gscarr.2024.20.1.0247","source":"openalex"},{"id":"oa:W4386601326","type":"article-journal","title":"Port Digital Twin Development for Decarbonization: A Case Study Using the Pusan Newport International Terminal","abstract":"The maritime industry is a major carbon emission contributor. Therefore, the global maritime industry puts every effort into reducing carbon emissions in the shipping chain, which includes vessel fleets, ports, terminals, and hinterland transportation. A representative example is the carbon emission reduction standard mandated by the International Maritime Organization for international sailing ships to reduce carbon emissions this year. Among the decarbonization tools, the most immediate solution for reducing carbon emissions is to reduce vessel waiting time near ports and increase operational efficiency. The operation efficiency improvement in maritime stakeholders’ port operations can be achieved using data. This data collection and operational efficiency improvement can be realized using a digital twin. This study develops a digital twin that measures and reduces carbon emissions using the collaborative operation of maritime stakeholders. In this study, the authors propose a data structure and backbone scheduling algorithm for a port digital twin. The interactive scheduling between a port and its vessels is investigated using the digital twin. The digital twin’s interactive scheduling for the proposed model improved predictions of vessel arrival time and voyage carbon emissions. The result of the proposed digital twin model is compared to an actual operation case from the Busan New Port in September 2022, which shows that the proposed model saves over 75 % of the carbon emissions compared with the case.","author":[{"family":"Eom","given":"Jeong"},{"family":"Yoon","given":"Jeong"},{"family":"Yeon","given":"Jeong"},{"family":"Kim","given":"Sewon"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/jmse11091777","URL":"https://doi.org/10.3390/jmse11091777","source":"openalex"},{"id":"oa:W4378084601","type":"article-journal","title":"Educational Case Studies: Creating a Digital Twin of the Production Line in TIA Portal, Unity, and Game4Automation Framework","abstract":"In today's industry, the fourth industrial revolution is underway, characterized by the integration of advanced technologies such as artificial intelligence, the Internet of Things, and big data. One of the key pillars of this revolution is the technology of digital twin, which is rapidly gaining importance in various industries. However, the concept of digital twins is often misunderstood or misused as a buzzword, leading to confusion in its definition and applications. This observation inspired the authors of this paper to create their own demonstration applications that allow the control of both the real and virtual systems through automatic two-way communication and mutual influence in context of digital twins. The paper aims to demonstrate the use of digital twin technology aimed at discrete manufacturing events in two case studies. In order to create the digital twins for these case studies, the authors used technologies as Unity, Game4Automation, Siemens TIA portal, and Fishertechnik models. The first case study involves the creation of a digital twin for a production line model, while the second case study involves the virtual extension of a warehouse stacker using a digital twin. These case studies will form the basis for the creation of pilot courses for Industry 4.0 education and can be further modified for the development of Industry 4.0 educational materials and technical practice. In conclusion, selected technologies are affordable, which makes the presented methodologies and educational studies accessible to a wide range of researchers and solution developers tackling the issue of digital twins, with a focus on discrete manufacturing events.","author":[{"family":"Balla","given":"Michal"},{"family":"Haffner","given":"Oto"},{"family":"Kučera","given":"Erik"},{"family":"Cigánek","given":"Ján"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/s23104977","URL":"https://doi.org/10.3390/s23104977","source":"openalex"},{"id":"oa:W4391380591","type":"article-journal","title":"Digital product passports as enablers of digital circular economy: a framework based on technological perspective","abstract":"Abstract Taking into consideration the existing Industry 4.0 infrastructures and the rise of Industry 5.0 (I5.0), more and more solutions are being developed, aiming towards increased environmental consciousness through advanced technologies, and human centricity. However, there are ongoing requirements on data traceability, and access to the related actors, to ensure the establishment of sustainable solutions, within the context of a digital circular economy (DCE) environment. Digital product passports (DPPs) constitute such novel technological solution that can enable the transition toward DCE and sustainable I4.0 and I5.0, as digital identities that are assigned to physical products, capable of tracing their lifecycles through data such as their technical specifications, usage instructions, and repair and maintenance information. Although the respective research community has started providing a thorough analysis of DPPs potential to constitute a CE enabler, their technical requirements are still unclear. As part of our contribution to this issue, we propose a fundamental CE framework with integrated DPP characteristics, with the potential of being adapted in different sector stages for the generation and distribution of DPPs both for stakeholders and consumers. The corresponding solution is further supported through a systematic literature review that follows a technological approach to the DPPs implementation.","author":[{"family":"Voulgaridis","given":"Konstantinos"},{"family":"Λάγκας","given":"Θωμάς"},{"family":"Angelopoulos","given":"Constantinos"},{"family":"Boulogeorgos","given":"Alexandros–apostolos"},{"family":"Argyriou","given":"Vasileios"},{"family":"Sarigiannidis","given":"Panagiotis"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1007/s11235-024-01104-x","URL":"https://doi.org/10.1007/s11235-024-01104-x","source":"openalex"},{"id":"oa:W4389041371","type":"article-journal","title":"A Review of Research of Digital Twin Technology for CNC Machine Tools","abstract":"As manufacturing systems developed in the direction of digitization, networking and intelligence, digital twin technology has been developed so as to enhance communication between real machining and simulation. CNC machine tools equiped with digital twin technology can be seen as a kind of CNC machine tools in a virtual environment with digitalization and networking as the core, and is an important way to realize the intelligence and automation of CNC machine tools. The development of research on digital twin technology in CNC machining is reviewed in this paper, and the future development trend is prospected by combining the current research hotspots. The whole content can be divided into the following parts. First, the basic concept of digital twin CNC machine tools is introduced. Then, the related research at home and abroad is explained and analyzed from the aspects of error prediction, parameter optimization, real-time monitoring and troubleshooting, etc. Finally, the current problems are pointed out and future development trends and research directions are proposed, which provide some references to promote the realm of future manufacturing and also play a pivotal role in the exploration and implementation of digital twin technology.","author":[{"family":"Ye","given":"Weichong"},{"family":"Geng","given":"Cong"},{"family":"Zhang","given":"Han"},{"family":"Wang","given":"Jinjie"},{"family":"Meng","given":"Dehao"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/iai59504.2023.10327582","URL":"https://doi.org/10.1109/iai59504.2023.10327582","source":"openalex"},{"id":"oa:W4399251643","type":"manuscript","title":"Leveraging Generative AI for Urban Digital Twins: A Scoping Review on the Autonomous Generation of Urban Data, Scenarios, Designs, and 3D City Models for Smart City Advancement","abstract":"The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch of data-driven smart city applications for efficient and sustainable urban management. Despite their effectiveness, these applications often rely on massive amounts of high-dimensional and multi-domain data for monitoring and characterizing different urban sub-systems, presenting challenges in application areas that are limited by data quality and availability, as well as costly efforts for generating urban scenarios and design alternatives. As an emerging research area in deep learning, Generative Artificial Intelligence (AI) models have demonstrated their unique values in data and code generation. This survey paper aims to explore the innovative integration of generative AI techniques and urban digital twins to address challenges in the realm of smart cities in various urban sectors, such as transportation and mobility management, energy system operations, building and infrastructure management, and urban design. The survey starts with the introduction of popular generative AI models with their application areas, followed by a structured review of the existing urban science applications that leverage the autonomous capability of the generative AI techniques to facilitate (a) data augmentation for promoting urban monitoring and predictive analytics, (b) synthetic data and scenario generation, (c) automated 3D city modeling, and (d) generative urban design and optimization. Based on the review, this survey discusses potential opportunities and technical strategies that integrate generative AI models into the next-generation urban digital twins for more reliable, scalable, and automated management of smart cities.","author":[{"family":"Xu","given":"Haowen"},{"family":"Omitaomu","given":"Olufemi"},{"family":"Sabri","given":"Soheil"},{"family":"Zlatanova","given":"Sisi"},{"family":"Li","given":"Xiao"},{"family":"Song","given":"Yongze"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2405.19464","URL":"https://doi.org/10.48550/arxiv.2405.19464","source":"openalex"},{"id":"oa:W4388637778","type":"article-journal","title":"The UNITE database for molecular identification and taxonomic communication of fungi and other eukaryotes: sequences, taxa and classifications reconsidered","abstract":"UNITE (https://unite.ut.ee) is a web-based database and sequence management environment for molecular identification of eukaryotes. It targets the nuclear ribosomal internal transcribed spacer (ITS) region and offers nearly 10 million such sequences for reference. These are clustered into ∼2.4M species hypotheses (SHs), each assigned a unique digital object identifier (DOI) to promote unambiguous referencing across studies. UNITE users have contributed over 600 000 third-party sequence annotations, which are shared with a range of databases and other community resources. Recent improvements facilitate the detection of cross-kingdom biological associations and the integration of undescribed groups of organisms into everyday biological pursuits. Serving as a digital twin for eukaryotic biodiversity and communities worldwide, the latest release of UNITE offers improved avenues for biodiversity discovery, precise taxonomic communication and integration of biological knowledge across platforms.","author":[{"family":"Abarenkov","given":"Kessy"},{"family":"Nilsson","given":"RH"},{"family":"Larsson","given":"Karl‐henrik"},{"family":"Taylor","given":"Andy"},{"family":"May","given":"Tom"},{"family":"Frøslev","given":"Tobias"},{"family":"Pawłowska","given":"Julia"},{"family":"Lindahl","given":"Björn"},{"family":"Põldmaa","given":"Kadri"},{"family":"Truong","given":"Camille"},{"family":"Vu","given":"Duong"},{"family":"Hosoya","given":"Tsuyoshi"},{"family":"Niskanen","given":"Tuula"},{"family":"Piirmann","given":"Timo"},{"family":"Ivanov","given":"Filipp"},{"family":"Zirk","given":"Allan"},{"family":"Peterson","given":"Marko"},{"family":"Cheeke","given":"Tanya"},{"family":"Ishigami","given":"Yui"},{"family":"Jansson","given":"Tobias"},{"family":"Jeppesen","given":"Thomas"},{"family":"Kristiansson","given":"Erik"},{"family":"Mikryukov","given":"Vladimir"},{"family":"Miller","given":"Joseph"},{"family":"Oono","given":"Ryoko"},{"family":"Ossandon","given":"Francisco"},{"family":"Paupério","given":"Joana"},{"family":"Saar","given":"Irja"},{"family":"Schigel","given":"Dmitry"},{"family":"Suija","given":"Ave"},{"family":"Tedersoo","given":"Leho"},{"family":"Kõljalg","given":"Urmas"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1093/nar/gkad1039","URL":"https://doi.org/10.1093/nar/gkad1039","source":"openalex"},{"id":"oa:W4391621780","type":"manuscript","title":"Review on Fault Diagnosis and Fault-Tolerant Control Scheme for Robotic Manipulators: Recent Advances in AI, Machine Learning, and Digital Twin","abstract":"This comprehensive review article delves into the intricate realm of fault-tolerant control (FTC) schemes tailored for robotic manipulators. Our exploration spans the historical evolution of FTC, tracing its development over time, and meticulously examines the recent breakthroughs fueled by the synergistic integration of cutting-edge technologies such as artificial intelligence (AI), machine learning (ML), and digital twin technologies (DTT). The article places a particular emphasis on the transformative influence these contemporary trends exert on the landscape of robotic manipulator control and fault tolerance. By delving into the historical context, our aim is to provide a comprehensive understanding of the evolution of FTC schemes. This journey encompasses the transition from model-based and signal-based schemes to the role of sensors, setting the stage for an exploration of the present-day paradigm shift enabled by AI, ML, and DTT. The narrative unfolds as we dissect the intricate interplay between these advanced technologies and their applications in enhancing fault tolerance within the domain of robotic manipulators. Our review critically evaluates the impact of these advancements, shedding light on the novel methodologies, techniques, and applications that have emerged in recent times. The overarching goal of this article is to present a comprehensive perspective on the current state of fault diagnosis and fault-tolerant control within the context of robotic manipulators, positioning our exploration within the broader framework of AI, ML, and DTT advancements. Through a meticulous examination of both historical foundations and contemporary innovations, this review significantly contributes to the existing body of knowledge, offering valuable insights for researchers, practitioners, and enthusiasts navigating the dynamic landscape of robotic manipulator control.","author":[{"family":"Quamar","given":"Md"},{"family":"Nasir","given":"Ali"},{"family":"Quamar","given":"Md"},{"family":"Nasir","given":"Ali"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2402.02980","URL":"https://doi.org/10.48550/arxiv.2402.02980","source":"openalex"},{"id":"oa:W4385730007","type":"article-journal","title":"Preliminary Systemic Model of (Human) Digital Twin","abstract":"This paper is an ongoing work seeking to establish a generic definition and model of the Human Digital Twin (HDT) concept, independently from the application sector. The goal is to help researchers knowing more precisely what is or could be a HDT and an initial step step towards a unifying and generic definition and model grounded in the systemics theory. We propose a systemic model of Digital Twin (DT), where HDT is a specific class of DT. The last years of literature on HDT are reviewed, to build a generic definition, extract the main components and integrate them in a generic systemic model centred on the DT and HDT concepts as systems. Doing this, we make explicit the link between DT and the systems they twin, including the special system that is the human-being, when a DT becomes a HDT.","author":[{"family":"Naudet","given":"Yannick"},{"family":"Stahl","given":"Christoph"},{"family":"Gallais","given":"Marie"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1145/3594806.3596596","URL":"https://doi.org/10.1145/3594806.3596596","source":"openalex"},{"id":"oa:W4318478174","type":"article-journal","title":"Dynamic Scheduling and Optimization of AGV in Factory Logistics Systems Based on Digital Twin","abstract":"At present, discrete workshops demand higher transportation efficiency, but the traditional scheduling strategy of the logistics systems can no longer meet the requirements. In a transportation system with multiple automated guided vehicles (multi-AGVs), AGV path conflicts directly affect the efficiency and coordination of the whole system. At the same time, the uncertainty of the number and speed of AGVs will lead to excessive cost. To solve these problems, an AGVs Multi-Objective Dynamic Scheduling (AMODS) method is proposed which is based on the digital twin of the workshop. The digital twin of the workshop is built in the virtual space, and a two-way exchange and real-time control framework based on dynamic data is established. The digital twin system is adopted to exchange data in real time, create a real-time updated dynamic task list, determine the number of AGVs and the speed of AGVs under different working conditions, and effectively improve the efficiency of the logistics system. Compared with the traditional scheduling strategy, this paper is of practical significance for the scheduling of the discrete workshop logistics systems to improve the production efficiency, utilization rate of resources, and dynamic response capability.","author":[{"family":"Wu","given":"Shiqing"},{"family":"Xiang","given":"Wenting"},{"family":"Li","given":"Weidong"},{"family":"Chen","given":"Long"},{"family":"Wu","given":"Chenrui"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/app13031762","URL":"https://doi.org/10.3390/app13031762","source":"openalex"},{"id":"oa:W4392714280","type":"article-journal","title":"A review of mechanistic learning in mathematical oncology","abstract":"Mechanistic learning refers to the synergistic combination of mechanistic mathematical modeling and data-driven machine or deep learning. This emerging field finds increasing applications in (mathematical) oncology. This review aims to capture the current state of the field and provides a perspective on how mechanistic learning may progress in the oncology domain. We highlight the synergistic potential of mechanistic learning and point out similarities and differences between purely data-driven and mechanistic approaches concerning model complexity, data requirements, outputs generated, and interpretability of the algorithms and their results. Four categories of mechanistic learning (sequential, parallel, extrinsic, intrinsic) of mechanistic learning are presented with specific examples. We discuss a range of techniques including physics-informed neural networks, surrogate model learning, and digital twins. Example applications address complex problems predominantly from the domain of oncology research such as longitudinal tumor response predictions or time-to-event modeling. As the field of mechanistic learning advances, we aim for this review and proposed categorization framework to foster additional collaboration between the data- and knowledge-driven modeling fields. Further collaboration will help address difficult issues in oncology such as limited data availability, requirements of model transparency, and complex input data which are embraced in a mechanistic learning framework.","author":[{"family":"Metzcar","given":"John"},{"family":"Jutzeler","given":"Catherine"},{"family":"Macklin","given":"Paul"},{"family":"Köhnluque","given":"Alvaro"},{"family":"Brüningk","given":"Sarah"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3389/fimmu.2024.1363144","URL":"https://doi.org/10.3389/fimmu.2024.1363144","source":"openalex"},{"id":"oa:W4377982128","type":"article-journal","title":"Self-improving situation awareness for human–robot-collaboration using intelligent Digital Twin","abstract":"Abstract The situation awareness, especially for collaborative robots, plays a crucial role when humans and machines work together in a human-centered, dynamic environment. Only when the humans understands how well the robot is aware of its environment can they build trust and delegate tasks that the robot can complete successfully. However, the state of situation awareness has not yet been described for collaborative robots. Furthermore, the improvement of situation awareness is now only described for humans but not for robots. In this paper, the authors propose a metric to measure the state of situation awareness. Furthermore, the models are adapted to the collaborative robot domain to systematically improve the situation awareness. The proposed metric and the improvement process of the situation awareness are evaluated using the mobile robot platform Robotino. The authors conduct extensive experiments and present the results in this paper to evaluate the effectiveness of the proposed approach. The results are compared with the existing research on the situation awareness, highlighting the advantages of our approach. Therefore, the approach is expected to significantly improve the performance of cobots in human–robot collaboration and enhance the communication and understanding between humans and machines.","author":[{"family":"Müller","given":"Manuel"},{"family":"Ruppert","given":"Tamás"},{"family":"Jazdi","given":"Nasser"},{"family":"Weyrich","given":"Michael"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1007/s10845-023-02138-9","URL":"https://doi.org/10.1007/s10845-023-02138-9","source":"openalex"},{"id":"oa:W4406444811","type":"article-journal","title":"Digital Twins and their Impact on Industrial Machinery: A Comprehensive Systematic Review","abstract":"In the past decade, the incorporation of digital twins into industrial machinery has marked a transformative milestone, leading to more efficient and safer machines that have extended their lifespan and increased industrial productivity. Focusing on this phenomenon, the purpose of this study is to discern the current landscape of research regarding the influence of digital twins on industrial machinery over the past seven years. To achieve this, a systematic literature review was conducted, examining sources such as IEEE Xplore, Web of Science, Scopus, EBSCOhost, ProQuest, Hindawi, and ScienceDirect. Through meticulously calibrated search strategies, 4,881 relevant studies were identified. Eight rigorous exclusion criteria were applied, using the PRISMA diagram for filtering, and 61 high-quality studies were selected for review. The findings highlight China’s prominent contribution to the field and emphasize predictive maintenance as the most impactful area of application, with journals such as Hindawi and ProQuest leading the dissemination of knowledge. Overall, this research reveals significant insights that enhance the understanding of the impact of digital twins in the industrial machinery sector.","author":[{"family":"Nieves-Acosta","given":"Ayrton"},{"family":"Gamboa-Cruzado","given":"Javier"},{"family":"Farfán-Muñoz","given":"Ivar"},{"family":"López-Ramírez","given":"Blanca"}],"issued":{"date-parts":[[2024]]},"DOI":"10.13053/cys-28-4-5221","URL":"https://doi.org/10.13053/cys-28-4-5221","source":"openalex"},{"id":"oa:W4401667358","type":"article-journal","title":"LLM-Twin: mini-giant model-driven beyond 5G digital twin networking framework with semantic secure communication and computation","abstract":"Beyond 5G networks provide solutions for next-generation communications, especially digital twins networks (DTNs) have gained increasing popularity for bridging physical and digital space. However, current DTNs pose some challenges, especially when applied to scenarios that require efficient and multimodal data processing. Firstly, current DTNs are limited in communication and computational efficiency, since they require to transmit large amounts of raw data collected from physical sensors, as well as to ensure model synchronization through high-frequency computation. Second, current models of DTNs are domain-specific (e.g. E-health), making it difficult to handle DT scenarios with multimodal data processing requirements. Finally, current security schemes for DTNs introduce additional overheads that impair the efficiency. Against the above challenges, we propose a large language model (LLM) empowered DTNs framework, LLM-Twin. First, based on LLM, we propose digital twin semantic networks (DTSNs), which enable more efficient communication and computation. Second, we design a mini-giant model collaboration scheme, which enables efficient deployment of LLM in DTNs and is adapted to handle multimodal data. Then, we designed a native security policy for LLM-twin without compromising efficiency. Numerical experiments and case studies demonstrate the feasibility of LLM-Twin. To our knowledge, this is the first to propose an LLM-based semantic-level DTNs.","author":[{"family":"Hong","given":"Yang"},{"family":"Wu","given":"Jun"},{"family":"Morello","given":"Rosario"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1038/s41598-024-69474-5","URL":"https://doi.org/10.1038/s41598-024-69474-5","source":"openalex"},{"id":"oa:W4404799585","type":"article-journal","title":"Leveraging AI for energy-efficient manufacturing systems: Review and future prospectives","abstract":"Energy poses a significant challenge in the industrial sector, and the abundance of data generated by Industry 4.0 technologies offers the opportunity to leverage Artificial Intelligence (AI) for enhancing energy efficiency (EE) in manufacturing processes, particularly within manufacturing systems. However, fully realizing AI's potential in addressing energy challenges requires a comprehensive review of AI methodologies aimed at overcoming obstacles in energy-efficient manufacturing systems. This article provides a systematic review that combines both quantitative and qualitative analyses of literature from the past ten years, focusing on mitigating prevalent energy efficiency challenges in manufacturing systems through AI-related methodologies. These challenges include Monitoring and Prediction, Real-Time Control, Scheduling, and Parameters Optimization. The AI-related solutions proposed in the reviewed research articles utilize Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning (RL) techniques, either individually or in combination with other methods. A total of 67 journal papers on manufacturing systems, addressing the mentioned energy challenges through AI-related approaches, have been identified and thoroughly reviewed. As a result of this review, an Energy Efficient-Digital Twin (EE-DT) framework is proposed, demonstrating how a DT, equipped with AI techniques, can be applied to solve energy issues in manufacturing systems. This study provides scholars with a comprehensive guideline for selecting various types of AI methods to address common challenges in energy-efficient manufacturing systems, while also highlighting some promising future research directions. • A systematic literature review on AI-driven energy solutions for manufacturing systems. • Investigated common energy challenges in manufacturing systems and proposed AI-based solutions.. • Introduced a novel conceptual Energy Efficiency-Digital Twin (EE-DT) framework. • Discussed challenges and future directions for AI-driven energy-efficient manufacturing systems.","author":[{"family":"Abadi","given":"Mohamed"},{"family":"Liu","given":"Chao"},{"family":"Zhang","given":"Mingyu"},{"family":"Hu","given":"Youxi"},{"family":"Xu","given":"Yuchun"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.jmsy.2024.11.017","URL":"https://doi.org/10.1016/j.jmsy.2024.11.017","source":"openalex"},{"id":"oa:W4386558263","type":"article-journal","title":"Reengineering and Its Reliability: An Analysis of Water Projects and Watershed Management under a Digital Twin Scheme in China","abstract":"Water project and watershed management is currently being reengineered under digital twin schemes in China through pilot projects. An evaluation on pilot reengineering is important for its further implementation and improvement. This paper investigates national legislation and pilot projects’ implementations of a digital twin watershed and digital twin water project from the perspectives of design, policy, technology, investment, personnel, cyberspace security, co-construction, and sharing through interviews and expert review, and it uses a Bayesian network to study their reliability. First, the design of the digital twin watershed and digital twin water project is reasonable with regard to system architecture and business management. Second, although there are some national legislations on cyberspace security and geospatial data, they are incomplete for policy making and are probably infeasible for some technology. Third, there are insufficient mechanisms to sustainably support investment, personnel, and cyberspace security. Forth, co-construction and sharing are required for both inside and outside water departments. Fifth, the Bayesian network is useful for investigating the reliability of weak nodes, and it is helpful for the design and further implementation of the digital twin watershed and digital twin water project, as will be demonstrated with an anonymous example. This study could provide useful insights into the further reengineering of water projects and watershed management under a digital twin scheme in the world.","author":[{"family":"Sheng","given":"Dong"},{"family":"Lou","given":"Yu"},{"family":"Sun","given":"Feifei"},{"family":"Xie","given":"Jinping"},{"family":"Yu","given":"Yu"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/w15183203","URL":"https://doi.org/10.3390/w15183203","source":"openalex"},{"id":"oa:W4381617698","type":"article-journal","title":"A Theoretical Open Architecture Framework and Technology Stack for Digital Twins in Energy Sector Applications","abstract":"Digital twin is often viewed as a technology that can assist engineers and researchers make data-driven system and network-level decisions. Across the scientific literature, digital twins have been consistently theorized as a strong solution to facilitate proactive discovery of system failures, system and network efficiency improvement, system and network operation optimization, among others. With their strong affinity to the industrial metaverse concept, digital twins have the potential to offer high-value propositions that are unique to the energy sector stakeholders to realize the true potential of physical and digital convergence and pertinent sustainability goals. Although the technology has been known for a long time in theory, its practical real-world applications have been so far limited, nevertheless with tremendous growth projections. In the energy sector, there have been theoretical and lab-level experimental analysis of digital twins but few of those experiments resulted in real-world deployments. There may be many contributing factors to any friction associated with real-world scalable deployment in the energy sector such as cost, regulatory, and compliance requirements, and measurable and comparable methods to evaluate performance and return on investment. Those factors can be potentially addressed if the digital twin applications are built on the foundations of a scalable and interoperable framework that can drive a digital twin application across the project lifecycle: from ideation to theoretical deep dive to proof of concept to large-scale experiment to real-world deployment at scale. This paper is an attempt to define a digital twin open architecture framework that comprises a digital twin technology stack (D-Arc) coupled with information flow, sequence, and object diagrams. Those artifacts can be used by energy sector engineers and researchers to use any digital twin platform to drive research and engineering. This paper also provides critical details related to cybersecurity aspects, data management processes, and relevant energy sector use cases.","author":[{"family":"Gourisetti","given":"Sri"},{"family":"Bhadra","given":"Sraddhanjoli"},{"family":"Sebastian-Cardenas","given":"DJ"},{"family":"Touhiduzzaman","given":"Md"},{"family":"Ahmed","given":"Osman"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/en16134853","URL":"https://doi.org/10.3390/en16134853","source":"openalex"},{"id":"oa:W4388635224","type":"article-journal","title":"Revolutionizing the Garment Industry 5.0: Embracing Closed-Loop Design, E-Libraries, and Digital Twins","abstract":"This study presents an innovative approach for modernizing the garment industry through the fusion of digital human modeling (DHM), virtual modeling for fit sizing, ergonomic body-size data, and e-library resources. The integration of these elements empowers manufacturers to revolutionize their clothing design and production methods, leading to the delivery of unparalleled fit, comfort, and personalization for a wide range of body shapes and sizes. DHM, known for its precision in representing human bodies virtually and integrating anthropometric data, including ergonomic measurements, enhances the shopping experience by providing valuable insights. Consumers gain access to the knowledge necessary for making tailored clothing choices, thereby enhancing the personalization and satisfaction of their shopping experience. The incorporation of e-library resources takes the garment design approach to a data-driven and customer-centric level. Manufacturers can draw upon a wealth of information regarding body-size diversity, fashion trends, and customer preferences, all sourced from e-libraries. This knowledge supports the creation of a diverse range of sizes and styles, promoting inclusivity and relevance. Beyond improving garment fit, this comprehensive integration streamlines design and production processes by reducing the reliance on physical prototypes. This not only enhances efficiency but also contributes to environmental responsibility, fostering a more sustainable and eco-friendly future for the garment industry and embracing the future of fashion, where technology and data converge to create clothing that authentically fits, resonates with consumers, and aligns with the principles of sustainability. This study developed the mobile application integrating with the information in cloud database in order to present the best-suited garment for the user.","author":[{"family":"Dönmezer","given":"Semih"},{"family":"Demircioğlu","given":"Pınar"},{"family":"Böğrekçi","given":"İsmail"},{"family":"Bas","given":"G"},{"family":"Durakbasa","given":"Muhammet"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/su152215839","URL":"https://doi.org/10.3390/su152215839","source":"openalex"},{"id":"oa:W4405460991","type":"article-journal","title":"Integrating Digital Twins and Cyber-Physical Systems for Flexible Energy Management in Manufacturing Facilities: A Conceptual Framework","abstract":"This paper presents a conceptual framework aimed at integrating Digital Twins and cyber-physical production systems into the energy management of manufacturing facilities. To address the challenges of rising energy costs and environmental impacts, this framework combines digital modeling and customized energy management for direct manufacturing operations. Through a review of the existing literature, essential components such as physical models, a data platform, an energy optimization platform, and various interfaces are identified. Key requirements are defined in terms of functionality, performance, reliability, safety, and additional factors. The proposed framework includes the physical system, data platform, energy management system, and interfaces for both operators and external parties. The goal of this framework is to set the basis for allowing manufacturers to reduce energy consumption and costs during the lifecycle of assets more effectively, thereby improving energy efficiency in smart manufacturing. The study highlights opportunities for further research, such as real-world applications and sophisticated optimization methods. The advancement of Digital Twin technologies holds significant potential for creating more sustainable factories.","author":[{"family":"Rolofs","given":"Gerrit"},{"family":"Wilking","given":"Fabian"},{"family":"Goetz","given":"Stefan"},{"family":"Wartzack","given":"Sandro"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/electronics13244964","URL":"https://doi.org/10.3390/electronics13244964","source":"openalex"},{"id":"oa:W4320035893","type":"article-journal","title":"Research on coal mine safety management based on digital twin","abstract":"Coal mine safety management is the foundation and decisive factor of coal mining. The manual detection model is the main way for traditional coal mine safety management, which has problems such as inefficient identification of safety risks in coal mines, poor control accuracy and slow response measures and so on. Therefore, to make up for the shortcomings in the traditional coal mine safety management model, this paper introduces digital twin technology into coal mine safety management to achieve intelligent and efficient management of coal mine safety accidents. Firstly, we introduce the digital twin technology, select the five-dimensional model as the modeling basis, based on the existing twin model architecture, analyze the types of coal mine accidents and disasters, select the most destructive gas accidents as the research object, construct a twin safety management model for coal mine gas accidents using the digital twin five-dimensional model. Secondly, analyses of the actual operation mechanism of the digital twin model, and the advantages of the twin model in achieving prior prevention, rapid response and accurate control of gas incidents are pointed out. Finally, the house of quality of the gas accident digital twin model is established through the quality functional deployment tool, and key technical requirements for the construction of the twin model are given to accelerate the application of the gas accident twin model in the field. This study innovatively introduces digital twin technology into the field of coal mine safety management, proposes the application scenarios of emerging technologies such as digital twins in the coal mine field, and provides the possibility of multi-scene application of smart mine construction and technologies such as digital twins.","author":[{"family":"Wang","given":"Jiaqi"},{"family":"Huang","given":"Yanli"},{"family":"Zhai","given":"Wenrui"},{"family":"Li","given":"Junmeng"},{"family":"Ouyang","given":"Shenyang"},{"family":"Gao","given":"Huadong"},{"family":"Liu","given":"Yahui"},{"family":"Wang","given":"Guiyuan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.heliyon.2023.e13608","URL":"https://doi.org/10.1016/j.heliyon.2023.e13608","source":"openalex"},{"id":"oa:W4385553889","type":"article-journal","title":"A systematic review of the BIM in construction: from smart building management to interoperability of BIM & AI","abstract":"The main purpose of this study is to provide insight into the trend of AI-BIM integration, which has been studied by scholars around the world. To begin, a systematic review and bibliometric analysis was conducted to investigate English articles published between 2015 and 2022. This paper presents a systematic, scientometric, science mapping analysis through qualitative and quantitative evaluation and co-occurrence methods using VOSviewer, CiteSpace, and Gephi software. Conclusions indicate future research should concentrate on integrating AI and other smart systems with BIM to enhance digitalization and improve outcomes throughout the construction project life cycle. Based on the qualitative and quantitative evaluation of each scope (BIM and AI) and their status quo, this study suggests integrating the following domains with BIM to reduce complexity in the construction industry in the future: robotics, cloud systems, AIOT, digital twins, 4D printing, and block chain.","author":[{"family":"Heidari","given":"Ali"},{"family":"Peyvastehgar","given":"Yaghowb"},{"family":"Amanzadegan","given":"Mohammad"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1080/00038628.2023.2243247","URL":"https://doi.org/10.1080/00038628.2023.2243247","source":"openalex"},{"id":"oa:W4400980215","type":"article-journal","title":"Digitalization of agriculture for sustainable crop production: a use-case review","abstract":"The digitalization of agriculture is rapidly changing the way farmers do business. With the integration of advanced technology, farmers are now able to increase efficiency, productivity, and precision in their operations. Digitalization allows for real-time monitoring and management of crops, leading to improved yields and reduced waste. This paper presents a review of some of the use cases that digitalization has made an impact in the automation of open-field and closed-field cultivations by means of collecting data about soils, crop growth, and microclimate, or by contributing to more accurate decisions about water usage and fertilizer application. The objective was to address some of the most recent technological advances that are leading to increased efficiency and sustainability of crop production, reduction in the use of inputs and environmental impacts, and releasing manual workforces from repetitive field tasks. The short discussions included at the end of each case study attempt to highlight the limitations and technological challenges toward successful implementations, as well as to introduce alternative solutions and methods that are rapidly evolving to offer a vast array of benefits for farmers by influencing cost-saving measures. This review concludes that despite the many benefits of digitalization, there are still a number of challenges that need to be overcome, including high costs, reliability, and scalability. Most of the available setups that are currently used for this purpose have been custom designed for specific tasks and are still too expensive to be implemented on commercial scales, while others are still in their early stages of development, making them not reliable or scalable for widespread acceptance and adoption by farmers. By providing a comprehensive understanding of the current state of digitalization in agriculture and its impact on sustainable crop production and food security, this review provides insights for policy-makers, industry stakeholders, and researchers working in this field.","author":[{"family":"Shamshiri","given":"Redmond"},{"family":"Sturm","given":"Barbara"},{"family":"Weltzien","given":"Cornelia"},{"family":"Fulton","given":"John"},{"family":"Khosla","given":"Raj"},{"family":"Schirrmann","given":"Michael"},{"family":"Raut","given":"Sharvari"},{"family":"Basavegowda","given":"Deepak"},{"family":"Yamin","given":"Muhammad"},{"family":"Hameed","given":"Ibrahim"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3389/fenvs.2024.1375193","URL":"https://doi.org/10.3389/fenvs.2024.1375193","source":"openalex"},{"id":"oa:W4365150881","type":"article-journal","title":"Faceting the post-disaster built heritage reconstruction process within the digital twin framework for Notre-Dame de Paris","abstract":"April 15th, 2019: Notre-Dame Cathedral in Paris was burning, the spire collapsed on the nave, vaults crumbled and most of the timber roof was gone. In the post-disaster context, the authenticity and the monitoring of the archaeological remains are crucial for their potential reuse during reconstruction. This paper analyzes the collapsed transverse arch from the nave of Notre-Dame as a case study of reconstruction, using the digital twin framework. We propose four facets for the digital twin experiment-physical anastylosis, reverse engineering, spatio-temporal tracking of assets, and operational research-that are described in detail, while being assembled to support a hybrid reconstruction hypothesis. The digital twin can realize the parallel unfolding of physical-native and digital-native processes, while acquiring and storing heterogeneous information as semantically structured data. The results demonstrate that the proposed modeling method facilitates the formalization and validation of the reconstruction problem and increases solutions performances. As result, we present a digital twin framework application ranging from acquisition to data processing that informs a successful hybrid reconstruction hypothesis.","author":[{"family":"Gros","given":"Antoine"},{"family":"Guillem","given":"Anaïs"},{"family":"Luca","given":"Livio"},{"family":"Baillieul","given":"Élise"},{"family":"Duvocelle","given":"Benoît"},{"family":"Malavergne","given":"Olivier"},{"family":"Leroux","given":"Lise"},{"family":"Zimmer","given":"Thierry"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1038/s41598-023-32504-9","URL":"https://doi.org/10.1038/s41598-023-32504-9","source":"openalex"},{"id":"oa:W4387647935","type":"article-journal","title":"Artificial intelligence enabling circular business model innovation in digital servitization: Conceptualizing dynamic capabilities, AI capacities, business models and effects","abstract":"This study explores the potential of AI to enable circular business model innovation (CBMI) for industrial manufacturers and the corresponding AI capacities and dynamic capabilities required for their commercialization. Employing an analysis of six leading B2B firms engaged in digital servitization, we conceptualize the perceptive, predictive, and prescriptive capacities of AI, which enhance resource efficiency by automating and augmenting data-driven analysis and decision making. We further identify two innovative classes of AI-enabled CBMs – augmentation (e.g., optimization solutions) and automation (e.g., autonomous solutions) business models – and their main circular value drivers. Finally, our research reveals novel dynamic capabilities underpinning the innovation of AI-enabled business models – value discovery, value realization, and value optimization capabilities – which enable manufacturers to make economic and sustainable values come to life in collaborating with customers and ecosystem partners. This study represents an important step in our understanding of how AI can drive circularity and sustainable innovation in industrial digital servitization. Overall, our study contributes to practice and the academic literature on AI, circular business models, and digital servitization by highlighting the potential of AI to empower CBMs for industrial manufacturers and the underlying processes of this digital transformation.","author":[{"family":"Sjödin","given":"David"},{"family":"Parida","given":"Vinit"},{"family":"Kohtamäki","given":"Marko"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.techfore.2023.122903","URL":"https://doi.org/10.1016/j.techfore.2023.122903","source":"openalex"},{"id":"oa:W4390670783","type":"article-journal","title":"A digital twin solution for floating offshore wind turbines validated using a full-scale prototype","abstract":"Abstract. In this work, we implement, verify, and validate a physics-based digital twin solution applied to a floating offshore wind turbine. The digital twin is validated using measurement data from the full-scale TetraSpar prototype. We focus on the estimation of the aerodynamic loads, wind speed, and section loads along the tower, with the aim of estimating the fatigue lifetime of the tower. Our digital twin solution integrates (1) a Kalman filter to estimate the structural states based on a linear model of the structure and measurements from the turbine, (2) an aerodynamic estimator, and (3) a physics-based virtual sensing procedure to obtain the loads along the tower. The digital twin relies on a set of measurements that are expected to be available on any existing wind turbine (power, pitch, rotor speed, and tower acceleration) and motion sensors that are likely to be standard measurements for a floating platform (inclinometers and GPS sensors). We explore two different pathways to obtain physics-based models: a suite of dedicated Python tools implemented as part of this work and the OpenFAST linearization feature. In our final version of the digital twin, we use components from both approaches. We perform different numerical experiments to verify the individual models of the digital twin. In this simulation realm, we obtain estimated damage equivalent loads of the tower fore–aft bending moment with an accuracy of approximately 5 % to 10 %. When comparing the digital twin estimations with the measurements from the TetraSpar prototype, the errors increased to 10 %–15 % on average. Overall, the accuracy of the results is promising and demonstrates the possibility of using digital twin solutions to estimate fatigue loads on floating offshore wind turbines. A natural continuation of this work would be to implement the monitoring and diagnostics aspect of the digital twin to inform operation and maintenance decisions. The digital twin solution is provided with examples as part of an open-source repository.","author":[{"family":"Branlard","given":"Emmanuel"},{"family":"Jonkman","given":"Jason"},{"family":"Brown","given":"Cameron"},{"family":"Zhang","given":"Jiatian"}],"issued":{"date-parts":[[2024]]},"DOI":"10.5194/wes-9-1-2024","URL":"https://doi.org/10.5194/wes-9-1-2024","source":"openalex"},{"id":"oa:W4318205606","type":"article-journal","title":"Multi-material additive manufacturing: A systematic review of design, properties, applications, challenges, and 3D printing of materials and cellular metamaterials","abstract":"Extensive research on nature-inspired cellular metamaterials has globally inspired innovations using single material and limited multifunctionality. Additive manufacturing (AM) of intricate geometries using multi-materials provides additional functionality, environmental adaptation, and improved mechanical properties. Recently, several studies have been conducted on multi-material additive manufacturing (MMAM) technologies, including multi-materials, methodologies, design, and optimization. However, in the past six years, very few or no systematic and complete reviews have been conducted in this research domain. This review intends to comprehensively summarize MMAM systems and the working principles of its fundamental processes. Herein, the Multi-material combinations and their design, modeling, and analysis strategies have been reviewed systematically. In particular, the focus is on applications and opportunities for using MMAM for several industries and postprocessing MMAM fabricated parts. Furthermore, this review identified the limitations and challenges of existing software packages, MMAM processes, materials, and joining mechanisms, especially at the multi-material interfaces. Finally, we discuss the possible strategies to overcome the aforementioned technological challenges and state the future directions, which will provide insights to researchers and engineers designing and manufacturing complex nature-inspired objects.","author":[{"family":"Nazir","given":"Aamer"},{"family":"Gokcekaya","given":"Ozkan"},{"family":"Billah","given":"Kazi"},{"family":"Ertuğrul","given":"Onur"},{"family":"Jiang","given":"Jingchao"},{"family":"Sun","given":"Jiayu"},{"family":"Hussain","given":"Sajjad"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.matdes.2023.111661","URL":"https://doi.org/10.1016/j.matdes.2023.111661","source":"openalex"},{"id":"oa:W4392819024","type":"article-journal","title":"Big data in Earth science: Emerging practice and promise","abstract":"Improvements in the number and resolution of Earth- and satellite-based sensors coupled with finer-resolution models have resulted in an explosion in the volume of Earth science data. This data-rich environment is changing the practice of Earth science, extending it beyond discovery and applied science to new realms. This Review highlights recent big data applications in three subdisciplines-hydrology, oceanography, and atmospheric science. We illustrate how big data relate to contemporary challenges in science: replicability and reproducibility and the transition from raw data to information products. Big data provide unprecedented opportunities to enhance our understanding of Earth's complex patterns and interactions. The emergence of digital twins enables us to learn from the past, understand the current state, and improve the accuracy of future predictions.","author":[{"family":"Vance","given":"Tiffany"},{"family":"Huang","given":"Thomas"},{"family":"Butler","given":"Kevin"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1126/science.adh9607","URL":"https://doi.org/10.1126/science.adh9607","source":"openalex"},{"id":"oa:W4388399721","type":"manuscript","title":"Delving into the Digital Twin Developments and Applications Beyond BIM in the Construction Industry","abstract":"Construction 4.0 is witnessing exponential growth in Digital Twin (DT) technology developments and applications, revolutionizing the adoption of Building Information Modelling (BIM) and other emerging technologies used throughout the lifecycle of the built environment. BIM provides technologies, procedures, and data schemas representing building components and systems. At the same time, DT enhances this with real-time data for cyber-physical integration, enabling live asset monitoring and better decision-making. Despite being in the early stages of development, DT applications have rapidly progressed in the AEC sector, resulting in a diverse literature landscape due to the various technologies and parameters involved in fully developing the DT technology. The intricate complexities inherent in digital twin advancements have confused professionals and researchers. This confusion arises from the nuanced distinctions between the two technologies, i.e., BIM and DT, causing a convergence that hinders realizing their potential. To address this confusion and lead to a swift development of DT technology, this study presents a holistic review of the existing research focusing on the critical components responsible for developing DT applications in the construction industry. The study identifies five crucial elements: technologies, maturity levels, data layers, enablers, and functionalities. Additionally, it identifies research gaps and proposes future avenues for streamlined DT developments and applications in the AEC sector. Future researchers and practitioners can target data integrity, integration and transmission, bi-directional interoperability, nontechnical factors, and data security to achieve mature digital twin applications for AEC practices. This study highlights the growing significance of DTs in construction and provides a foundation for further advancements in this field to harness its potential to transform built environment practices.","author":[{"family":"Afzal","given":"Muhammad"},{"family":"Li","given":"Rita"},{"family":"Shoaib","given":"Muhammad"},{"family":"Ayyub","given":"Muhammad"},{"family":"Tagliabue","given":"Lavinia"},{"family":"Bilal","given":"Muhammad"},{"family":"Ghafoor","given":"Habiba"}],"issued":{"date-parts":[[2023]]},"DOI":"10.20944/preprints202311.0244.v1","URL":"https://doi.org/10.20944/preprints202311.0244.v1","source":"preprints"},{"id":"oa:W4393134186","type":"article-journal","title":"Cognitive systems and interoperability in the enterprise: A systematic literature review","abstract":"The transition from automated processes to mechanisms that manifest intelligence through cognitive abilities such as memorisation, adaptability and decision-making in uncertain contexts, has marked a turning point in the field of industrial systems, particularly in the development of cyber–physical systems and digital twins. This evolution, supported by advances in cognitive science and artificial intelligence, has opened the way to a new era in which systems are able to adapt and evolve autonomously, while offering more intuitive interaction with human users. This article proposes a systematic literature review to gather and analyse current research on Cognitive Cyber–Physical Systems (CCPS), Cognitive Digital Twins (CDT), and cognitive interoperability, which are pivotal in a contemporary Cyber–Physical Enterprise (CPE). From this review, we first seek to understand how cognitive capabilities that are traditionally considered as human traits have been defined and modelled in cyber–physical systems and digital twins in the context of Industry 4.0/5.0, and what cognitive functions they implement. We explore their theoretical foundations, in particular in relation to cognitive psychology and humanities definitions and theories. Then we analyse how interoperability between cognitive systems has been considered, leading to cognitive interoperability, and we highlight the role of knowledge representation and reasoning.","author":[{"family":"Ali","given":"Jana"},{"family":"Gaffinet","given":"Ben"},{"family":"Panetto","given":"Hervé"},{"family":"Naudet","given":"Yannick"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.arcontrol.2024.100954","URL":"https://doi.org/10.1016/j.arcontrol.2024.100954","source":"openalex"},{"id":"oa:W4389082672","type":"article-journal","title":"Cooperating and Competing Digital Twins for Industrie 4.0 in Urban Planning Contexts","abstract":"Digital twins are emerging as a prime analysis, prediction, and control concepts for enabling the Industrie 4.0 vision of cyber-physical production systems (CPPSs). Today’s growing complexity and volatility cannot be handled by monolithic digital twins but require a fundamentally decentralized paradigm of cooperating digital twins. Moreover, societal trends such as worldwide urbanization and growing emphasis on sustainability highlight competing goals that must be reflected not just in cooperating but also competing digital twins, often even interacting in “coopetition”. This paper argues for multi-agent systems (MASs) to address this challenge, using the example of embedding industrial digital twins into an urban planning context. We provide a technical discussion of suitable MAS frameworks and interaction protocols; data architecture options for efficient data supply from heterogeneous sensor streams and sovereignty in data sharing; and strategic analysis for scoping a digital twin systems design among domain experts and decision makers. To illustrate the way still in front of research and practice, the paper reviews some success stories of MASs in Industrie/Logistics 4.0 settings and sketches a comprehensive vision for digital twin-based holistic urban planning.","author":[{"family":"Herzog","given":"Otthein"},{"family":"Jarke","given":"Matthias"},{"family":"Wu","given":"Siegfried"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/sci5040044","URL":"https://doi.org/10.3390/sci5040044","source":"openalex"},{"id":"doi:10.20944/preprints202306.0841.v1","type":"manuscript","title":"Exploring Digital Twin-based Fault Monitoring: Challenges and Opportunities","abstract":"High efficiency and safety are critical factors in ensuring optimal performance and reliability of systems and equipment across various industries. Fault Monitoring (FM) techniques play a pivotal role in this regard by continuously monitoring system performance and identifying the presence of faults or abnormalities. However, traditional FM methods face limitations in fully capturing the complex interactions within a system and providing real-time monitoring capabilities. To overcome these challenges, Digital Twin (DT) technology has emerged as a promising solution to enhance existing FM practices. By creating a virtual replica or digital copy of a physical equipment or system, DT offers the potential to revolutionize fault monitoring approaches. This paper aims to explore and discuss the diverse range of predictive methods utilized in DT and their implementations in FM across industries. Furthermore, it will showcase successful implementations of DT in FM across a wide array of industries, including manufacturing, energy, transportation, and healthcare The utilization of DT in FM enables a comprehensive understanding of system behavior and performance by leveraging real-time data, advanced analytics, and machine learning algorithms. By integrating physical and virtual components, DT facilitates the monitoring and prediction of faults, providing valuable insights into the system’s health and enabling proactive maintenance and decision-making.","author":[{"family":"Bofill","given":"Jherson"},{"family":"Abisado","given":"Mideth"},{"family":"Sampedro","given":"Gabriel"}],"issued":{"date-parts":[[2023]]},"DOI":"10.20944/preprints202306.0841.v1","URL":"https://doi.org/10.20944/preprints202306.0841.v1","source":"preprints"},{"id":"doi:10.1109/iciss59129.2023.10291489","type":"article-journal","title":"Digital Twin Model for Smart Maintenance of Data Center Facilities : Study Literature Review","abstract":"Digital twin is a technology that supports the implementation of digital transformation. The digital twin was developed to support decision making in various sectors. The digital twin concept is almost 20 years old and continues to evolve for use cases for the technology in new industries. Maintenance is one of the important points of the product life cycle as the origin of the digital twin. The data center facility is one of the supporters of digital transformation which must be able to guarantee the availability of its services. The availability of data center services is affected by the chosen maintenance strategy. This paper will discuss data centers and maintenance strategies as well as definitions, characteristics to examples of implementing digital twins, especially in the case of implementing intelligent maintenance. It is hoped that with the description of this paper, more specific research opportunities related to optimizing the application of digital twins for maintenance specifically used in data center facilities are expected.","author":[{"family":"Ramdani","given":"Dani"},{"family":"Supangkat","given":"Suhono"},{"family":"Hidayat","given":"Fadhil"},{"family":"Purwoadi","given":"Michael"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/iciss59129.2023.10291489","URL":"https://doi.org/10.1109/iciss59129.2023.10291489","source":"openalex"},{"id":"doi:10.48550/arxiv.2311.06993","type":"manuscript","title":"State-of-the-art review and synthesis: A requirement-based roadmap for standardized predictive maintenance automation using digital twin technologies","abstract":"Recent digital advances have popularized predictive maintenance (PMx), offering enhanced efficiency, automation, accuracy, cost savings, and independence in maintenance processes. Yet, PMx continues to face numerous limitations such as poor explainability, sample inefficiency of data-driven methods, complexity of physics-based methods, and limited generalizability and scalability of knowledge-based methods. This paper proposes leveraging Digital Twins (DTs) to address these challenges and enable automated PMx adoption on a larger scale. While DTs have the potential to be transformative, they have not yet reached the maturity needed to bridge these gaps in a standardized manner. Without a standard definition guiding this evolution, the transformation lacks a solid foundation for development. This paper provides a requirement-based roadmap to support standardized PMx automation using DT technologies. Our systematic approach comprises two primary stages. First, we methodically identify the Informational Requirements (IRs) and Functional Requirements (FRs) for PMx, which serve as a foundation from which any unified framework must emerge. Our approach to defining and using IRs and FRs as the backbone of any PMx DT is supported by the proven success of these requirements as blueprints in other areas, such as product development in the software industry. Second, we conduct a thorough literature review across various fields to assess how these IRs and FRs are currently being applied within DTs, enabling us to identify specific areas where further research is needed to support the progress and maturation of requirement-based PMx DTs.","author":[{"family":"Ma","given":"Sizhe"},{"family":"Flanigan","given":"Katherine"},{"family":"Bergés","given":"Mario"}],"issued":{"date-parts":[[2023]]},"DOI":"10.48550/arxiv.2311.06993","URL":"https://doi.org/10.48550/arxiv.2311.06993","source":"datacite"},{"id":"doi:10.17863/cam.107918","type":"article-journal","title":"A Digital Twin Based Approach to Control Overgrowth of Roadside Vegetation","abstract":"Roadside vegetation poses a significant risk to road safety, often contributing to traffic accidents by obstructing drivers’ views and impeding visibility. This study investigates existing control methods, assesses their limitations, defines technology-agnostic information requirements for vegetation control, and proposes a Digital Twin-based solution. The methodology involves expert interviews, a literature review, and a real-world case study, demonstrating the solution’s applicability. The study contributes to the field by offering insights into current practices, defining information needs, and presenting a novel approach for more effective roadside vegetation management. This research contributes to advancing road safety practices by harnessing the capabilities of digital twin technology to proactively manage and mitigate the risks associated with overgrown roadside vegetation.","author":[{"family":"Reja","given":"Varun"},{"family":"Davletshina","given":"Diana"},{"family":"Yin","given":"Mengtian"},{"family":"Wei","given":"Ran"},{"family":"Adam","given":"Quentin"},{"family":"Brilakis","given":"Ioannis"},{"family":"Perrotta","given":"Federico"}],"issued":{"date-parts":[[2024]]},"DOI":"10.17863/cam.107918","URL":"https://doi.org/10.17863/cam.107918","source":"datacite"},{"id":"doi:10.48550/arxiv.2404.00954","type":"manuscript","title":"Digital Twins and Testbeds for Supporting AI Research with Autonomous Vehicle Networks","abstract":"Digital twins (DTs), which are virtual environments that simulate, predict, and optimize the performance of their physical counterparts, hold great promise in revolutionizing next-generation wireless networks. While DTs have been extensively studied for wireless networks, their use in conjunction with autonomous vehicles featuring programmable mobility remains relatively under-explored. In this paper, we study DTs used as a development environment to design, deploy, and test artificial intelligence (AI) techniques that utilize real-world (RW) observations, e.g. radio key performance indicators, for vehicle trajectory and network optimization decisions in autonomous vehicle networks (AVN). We first compare and contrast the use of simulation, digital twin (software in the loop (SITL)), sandbox (hardware-in-the-loop (HITL)), and physical testbed (PT) environments for their suitability in developing and testing AI algorithms for AVNs. We then review various representative use cases of DTs for AVN scenarios. Finally, we provide an example from the NSF AERPAW platform where a DT is used to develop and test AI-aided solutions for autonomous unmanned aerial vehicles for localizing a signal source based solely on link quality measurements. Our results in the physical testbed show that SITL DTs, when supplemented with data from RW measurements and simulations, can serve as an ideal environment for developing and testing innovative AI solutions for AVNs.","author":[{"family":"Gürses","given":"Anıl"},{"family":"Reddy","given":"Gautham"},{"family":"Masrur","given":"Saad"},{"family":"Özdemir","given":"Özgür"},{"family":"Güvenç","given":"İsmail"},{"family":"Sichitiu","given":"Mihail"},{"family":"Şahin","given":"Alphan"},{"family":"Alkhateeb","given":"Ahmed"},{"family":"Mushi","given":"Magreth"},{"family":"Dutta","given":"Rudra"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2404.00954","URL":"https://doi.org/10.48550/arxiv.2404.00954","source":"datacite"},{"id":"doi:10.48550/arxiv.2405.18092","type":"manuscript","title":"LLM experiments with simulation: Large Language Model Multi-Agent System for Simulation Model Parametrization in Digital Twins","abstract":"This paper presents a novel design of a multi-agent system framework that applies large language models (LLMs) to automate the parametrization of simulation models in digital twins. This framework features specialized LLM agents tasked with observing, reasoning, decision-making, and summarizing, enabling them to dynamically interact with digital twin simulations to explore parametrization possibilities and determine feasible parameter settings to achieve an objective. The proposed approach enhances the usability of simulation model by infusing it with knowledge heuristics from LLM and enables autonomous search for feasible parametrization to solve a user task. Furthermore, the system has the potential to increase user-friendliness and reduce the cognitive load on human users by assisting in complex decision-making processes. The effectiveness and functionality of the system are demonstrated through a case study, and the visualized demos and codes are available at a GitHub Repository: https://github.com/YuchenXia/LLMDrivenSimulation","author":[{"family":"Xia","given":"Yuchen"},{"family":"Dittler","given":"Daniel"},{"family":"Jazdi","given":"Nasser"},{"family":"Chen","given":"Haonan"},{"family":"Weyrich","given":"Michael"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2405.18092","URL":"https://doi.org/10.48550/arxiv.2405.18092","source":"datacite"},{"id":"doi:10.48550/arxiv.2407.11990","type":"manuscript","title":"Digital twins in sport: Concepts, Taxonomies, Challenges and Practical Potentials","abstract":"Digital twins belong to ten of the strategic technology trends according to the Gartner list from 2019, and have encountered a big expansion, especially with the introduction of Industry 4.0. Sport, on the other hand, has become a constant companion of the modern human suffering a lack of a healthy way of life. The application of digital twins in sport has brought dramatic changes not only in the domain of sport training, but also in managing athletes during competitions, searching for strategical solutions before and tactical solutions during the games by coaches. In this paper, the domain of digital twins in sport is reviewed based on papers which have emerged in this area. At first, the concept of a digital twin is discussed in general. Then, taxonomies of digital twins are appointed. According to these taxonomies, the collection of relevant papers is analyzed, and some real examples of digital twins are exposed. The review finishes with a discussion about how the digital twins affect changes in the modern sport disciplines, and what challenges and opportunities await the digital twins in the future.","author":[{"family":"Hliš","given":"Tilen"},{"family":"Fister","given":"Iztok"},{"family":"Fister","given":"Iztok"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2407.11990","URL":"https://doi.org/10.48550/arxiv.2407.11990","source":"datacite"},{"id":"doi:10.60692/wxb8w-cmr14","type":"article-journal","title":"Unleashing the potential of digital twins: a new era with aeronautics 4.0","abstract":"Abstract* Introduction The aerospace value chain consists of several processes, and digitizing it first requires an assessment of these processes and their ability to be transferred to the fully integrated digital thread perspective of smart factories. A digital thread refers to the continuous flow of data and information related to a product throughout its life cycle, integrating and connecting all aspects of a product's journey. Within this framework, digital twin technology, an essential element of Industry 4.0, comprises the implementation of a virtual presentation of a physical object, system, or process. It brings together the digital replica not only of the physical attributes but also of the behavioral performance of the physical twin. Methods To achieve a digital thread perspective for aeronautics, a research agenda is proposed, including all breakpoints in the current value chain through a PESTLE Analysis, which defines the value-added areas targeted by this transition to digital technology. An aeronautics 4.0 model Digital Thread Twin Smart Aeronautics D2TSAero is proposed, which provides a new perspective in the aeronautics field by integrating its main ecosystems into an interconnected model made possible by the integration of digital twin agent instances. Proof of Concept A use case that deals with the dependability management of an aircraft fuel distribution system is presented. Based on these results, we can see that the proposed twin model can help in reducing real system parts down time, and it can also improve the management of maintenance across the system life cycle by offering a single source of trust for all stakeholders involved in the digital thread cycle of the real twin. Conclusion A forward-looking perspective on the future of aeronautics with this integrated approach is presented, summarizing all the discussed points and the importance of digital twins in supporting the digitalization of the field.","author":[{"family":"Mezzour","given":"Ghita"},{"family":"Benhadou","given":"Siham"},{"family":"Benhadou","given":"Mariam"},{"family":"Abdellah","given":"Haddout"}],"issued":{"date-parts":[[2024]]},"DOI":"10.60692/wxb8w-cmr14","URL":"https://doi.org/10.60692/wxb8w-cmr14","source":"datacite"},{"id":"doi:10.60692/2v0ef-gad84","type":"article-journal","title":"Unleashing the potential of digital twins: a new era with aeronautics 4.0","abstract":"Abstract* Introduction The aerospace value chain consists of several processes, and digitizing it first requires an assessment of these processes and their ability to be transferred to the fully integrated digital thread perspective of smart factories. A digital thread refers to the continuous flow of data and information related to a product throughout its life cycle, integrating and connecting all aspects of a product's journey. Within this framework, digital twin technology, an essential element of Industry 4.0, comprises the implementation of a virtual presentation of a physical object, system, or process. It brings together the digital replica not only of the physical attributes but also of the behavioral performance of the physical twin. Methods To achieve a digital thread perspective for aeronautics, a research agenda is proposed, including all breakpoints in the current value chain through a PESTLE Analysis, which defines the value-added areas targeted by this transition to digital technology. An aeronautics 4.0 model Digital Thread Twin Smart Aeronautics D2TSAero is proposed, which provides a new perspective in the aeronautics field by integrating its main ecosystems into an interconnected model made possible by the integration of digital twin agent instances. Proof of Concept A use case that deals with the dependability management of an aircraft fuel distribution system is presented. Based on these results, we can see that the proposed twin model can help in reducing real system parts down time, and it can also improve the management of maintenance across the system life cycle by offering a single source of trust for all stakeholders involved in the digital thread cycle of the real twin. Conclusion A forward-looking perspective on the future of aeronautics with this integrated approach is presented, summarizing all the discussed points and the importance of digital twins in supporting the digitalization of the field.","author":[{"family":"Mezzour","given":"Ghita"},{"family":"Benhadou","given":"Siham"},{"family":"Benhadou","given":"Mariam"},{"family":"Abdellah","given":"Haddout"}],"issued":{"date-parts":[[2024]]},"DOI":"10.60692/2v0ef-gad84","URL":"https://doi.org/10.60692/2v0ef-gad84","source":"datacite"},{"id":"doi:10.60692/3vb0s-gpd17","type":"article-journal","title":"Systematic review of predictive maintenance and digital twin technologies challenges, opportunities, and best practices","abstract":"Background Maintaining machines effectively continues to be a challenge for industrial organisations, which frequently employ reactive or premeditated methods. Recent research has begun to shift its attention towards the application of Predictive Maintenance (PdM) and Digital Twins (DT) principles in order to improve maintenance processes. PdM technologies have the capacity to significantly improve profitability, safety, and sustainability in various industries. Significantly, precise equipment estimation, enabled by robust supervised learning techniques, is critical to the efficacy of PdM in conjunction with DT development. This study underscores the application of PdM and DT, exploring its transformative potential across domains demanding real-time monitoring. Specifically, it delves into emerging fields in healthcare, utilities (smart water management), and agriculture (smart farm), aligning with the latest research frontiers in these areas. Methodology Employing the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria, this study highlights diverse modeling techniques shaping asset lifetime evaluation within the PdM context from 34 scholarly articles. Results The study revealed four important findings: various PdM and DT modelling techniques, their diverse approaches, predictive outcomes, and implementation of maintenance management. These findings align with the ongoing exploration of emerging applications in healthcare, utilities (smart water management), and agriculture (smart farm). In addition, it sheds light on the critical functions of PdM and DT, emphasising their extraordinary ability to drive revolutionary change in dynamic industrial challenges. The results highlight these methodologies' flexibility and application across many industries, providing vital insights into their potential to revolutionise asset management and maintenance practice for real-time monitoring. Conclusions Therefore, this systematic review provides a current and essential resource for academics, practitioners, and policymakers to refine PdM strategies and expand the applicability of DT in diverse industrial sectors.","author":[{"family":"Wahab","given":"Noor"},{"family":"Hasikin","given":"Khairunnisa"},{"family":"Lai","given":"Khin"},{"family":"Xia","given":"Kaijian"},{"family":"Bei","given":"Lulu"},{"family":"Huang","given":"Kai"},{"family":"Wu","given":"Xiang"}],"issued":{"date-parts":[[2024]]},"DOI":"10.60692/3vb0s-gpd17","URL":"https://doi.org/10.60692/3vb0s-gpd17","source":"datacite"},{"id":"doi:10.60692/w0709-k9v49","type":"article-journal","title":"Systematic review of predictive maintenance and digital twin technologies challenges, opportunities, and best practices","abstract":"Background Maintaining machines effectively continues to be a challenge for industrial organisations, which frequently employ reactive or premeditated methods. Recent research has begun to shift its attention towards the application of Predictive Maintenance (PdM) and Digital Twins (DT) principles in order to improve maintenance processes. PdM technologies have the capacity to significantly improve profitability, safety, and sustainability in various industries. Significantly, precise equipment estimation, enabled by robust supervised learning techniques, is critical to the efficacy of PdM in conjunction with DT development. This study underscores the application of PdM and DT, exploring its transformative potential across domains demanding real-time monitoring. Specifically, it delves into emerging fields in healthcare, utilities (smart water management), and agriculture (smart farm), aligning with the latest research frontiers in these areas. Methodology Employing the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria, this study highlights diverse modeling techniques shaping asset lifetime evaluation within the PdM context from 34 scholarly articles. Results The study revealed four important findings: various PdM and DT modelling techniques, their diverse approaches, predictive outcomes, and implementation of maintenance management. These findings align with the ongoing exploration of emerging applications in healthcare, utilities (smart water management), and agriculture (smart farm). In addition, it sheds light on the critical functions of PdM and DT, emphasising their extraordinary ability to drive revolutionary change in dynamic industrial challenges. The results highlight these methodologies' flexibility and application across many industries, providing vital insights into their potential to revolutionise asset management and maintenance practice for real-time monitoring. Conclusions Therefore, this systematic review provides a current and essential resource for academics, practitioners, and policymakers to refine PdM strategies and expand the applicability of DT in diverse industrial sectors.","author":[{"family":"Wahab","given":"Noor"},{"family":"Hasikin","given":"Khairunnisa"},{"family":"Lai","given":"Khin"},{"family":"Xia","given":"Kaijian"},{"family":"Bei","given":"Lulu"},{"family":"Huang","given":"Kai"},{"family":"Wu","given":"Xiang"}],"issued":{"date-parts":[[2024]]},"DOI":"10.60692/w0709-k9v49","URL":"https://doi.org/10.60692/w0709-k9v49","source":"datacite"},{"id":"doi:10.60692/fg3g5-edd13","type":"article-journal","title":"Towards electric digital twin grid: Technology and framework review","abstract":"The major hindrances in the energy system are ecological consciousness, lack of clean and sustainable energy management, insufficient energy distribution–transmission–optimization, expensive power transfer costs, and increased customer knowledge of energy charges. Thus why, universal access to the grid with high cybersecurity, and reliability is needed to solve all these challenges. The digital twin concept turns a new dimension of technology into the world. Electric Digital Twin grid can perform online analysis of the grid in real-time and integrates all the past and present data and express the current grid status to the producers and consumers and also predicts the future grid status. Thus, the power grid transmission loss and location of the overheated line and power connection missing can be detected in addition decision-making and self-healing can possible. The future prediction saves the power grid from small to long accidents such as power outages and even blackout problems. The whole consumers and nation feel relief from these types of accidents and saves from large economic and business loss. The blockchain-enabled digital twin grid provides high security for the grid from cyberattacks. The paper conveys the framework of the electric digital twin grid and the concept of the DT grid processing and the way of serving the producer, prosumers, consumers even the whole nation in infrastructure, education, research, economic, business, and political development.","author":[{"family":"Sifat","given":"Md"},{"family":"Choudhury","given":"Safwat"},{"family":"Das","given":"Sajal"},{"family":"Ahamed","given":"Md"},{"family":"Muyeen","given":"SM"},{"family":"Hasan","given":"Md"},{"family":"Ali","given":"Mohamad"},{"family":"Tasneem","given":"Zinat"},{"family":"Islam","given":"Md"},{"family":"Islam","given":"Md"},{"family":"Badal","given":"Md"},{"family":"Abhi","given":"Sarafat"}],"issued":{"date-parts":[[2023]]},"DOI":"10.60692/fg3g5-edd13","URL":"https://doi.org/10.60692/fg3g5-edd13","source":"datacite"},{"id":"doi:10.60692/xpqzd-6zh10","type":"article-journal","title":"Towards electric digital twin grid: Technology and framework review","abstract":"The major hindrances in the energy system are ecological consciousness, lack of clean and sustainable energy management, insufficient energy distribution–transmission–optimization, expensive power transfer costs, and increased customer knowledge of energy charges. Thus why, universal access to the grid with high cybersecurity, and reliability is needed to solve all these challenges. The digital twin concept turns a new dimension of technology into the world. Electric Digital Twin grid can perform online analysis of the grid in real-time and integrates all the past and present data and express the current grid status to the producers and consumers and also predicts the future grid status. Thus, the power grid transmission loss and location of the overheated line and power connection missing can be detected in addition decision-making and self-healing can possible. The future prediction saves the power grid from small to long accidents such as power outages and even blackout problems. The whole consumers and nation feel relief from these types of accidents and saves from large economic and business loss. The blockchain-enabled digital twin grid provides high security for the grid from cyberattacks. The paper conveys the framework of the electric digital twin grid and the concept of the DT grid processing and the way of serving the producer, prosumers, consumers even the whole nation in infrastructure, education, research, economic, business, and political development.","author":[{"family":"Sifat","given":"Md"},{"family":"Choudhury","given":"Safwat"},{"family":"Das","given":"Sajal"},{"family":"Ahamed","given":"Md"},{"family":"Muyeen","given":"SM"},{"family":"Hasan","given":"Md"},{"family":"Ali","given":"Mohamad"},{"family":"Tasneem","given":"Zinat"},{"family":"Islam","given":"Md"},{"family":"Islam","given":"Md"},{"family":"Badal","given":"Md"},{"family":"Abhi","given":"Sarafat"}],"issued":{"date-parts":[[2023]]},"DOI":"10.60692/xpqzd-6zh10","URL":"https://doi.org/10.60692/xpqzd-6zh10","source":"datacite"},{"id":"doi:10.48550/arxiv.2406.08854","type":"manuscript","title":"Current applications and potential future directions of reinforcement learning-based Digital Twins in agriculture","abstract":"Digital Twins have gained attention in various industries for simulation, monitoring, and decision-making, relying on ever-improving machine learning models. However, agricultural Digital Twin implementations are limited compared to other industries. Meanwhile, machine learning, particularly reinforcement learning, has shown potential in agricultural applications like optimizing decision-making, task automation, and resource management. A key aspect of Digital Twins is representing physical assets or systems in a virtual environment, which aligns well with reinforcement learning's need for environment representations to learn the best policy for a task. Reinforcement learning in agriculture can thus enable various Digital Twin applications in agricultural domains. This review aims to categorize existing research employing reinforcement learning in agricultural settings by application domains like robotics, greenhouse management, irrigation systems, and crop management, identifying potential future areas for reinforcement learning-based Digital Twins. It also categorizes the reinforcement learning techniques used, including tabular methods, Deep Q-Networks (DQN), Policy Gradient methods, and Actor-Critic algorithms, to overview currently employed models. The review seeks to provide insights into the state-of-the-art in integrating Digital Twins and reinforcement learning in agriculture, identifying gaps and opportunities for future research, and exploring synergies to tackle agricultural challenges and optimize farming, paving the way for more efficient and sustainable farming methodologies.","author":[{"family":"Goldenits","given":"Georg"},{"family":"Mallinger","given":"Kevin"},{"family":"Raubitzek","given":"Sebastian"},{"family":"Neubauer","given":"Thomas"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2406.08854","URL":"https://doi.org/10.48550/arxiv.2406.08854","source":"datacite"},{"id":"doi:10.60692/1sn6y-zan39","type":"article-journal","title":"Resilience towarded Digital Twins to improve the adaptability of transportation systems","abstract":"This work aims to investigate the role of the resilience of Digital Twins on the applicability of the transportation system. A literature study is conducted to review the current status of research on transportation systems and Digital Twins. It is found that the current research on Digital Twins technology has achieved different degrees of success in different aspects of transportation systems. Yet, the system performance of Digital Twins has to be optimized. First, the application of Digital Twins in intelligent transportation systems is analyzed. Then, how the changes in traveler behavior patterns reflect the extent to which the traffic network is affected by uncertain events is analyzed from the traveler's perspective. Finally, an Internet of Vehicles (IoV) system based on Digital Twins and blockchain is established to solve the data redundancy and high computational volume problems of in-vehicle data sharing common in the IoV system. Moreover, the performance of the twin system is optimized by proposing a multi-intelligence body algorithm based on local perception, and a case validation is performed. The results demonstrate that the adaptability of the transportation system to uncertain events and its response and recovery measures taken are reflected to some extent in the traveler behavior model. Besides, data sharing between vehicles and infrastructure in the transportation network can be well solved by Digital Twins Blockchain. The locally-aware multi-intelligent body algorithm saves more than 50% communication overhead and improves operational efficiency by nearly 20% over traditional algorithms by increasing intelligent body infrastructure units. It is adequately suited for large-scale vehicle traffic twins. It can be seen that improving the resilience of Digital Twins is a very obvious change in the adaptability of the traffic system.","author":[{"family":"Feng","given":"Hailin"},{"family":"Lv","given":"Haibin"},{"family":"Lv","given":"Zhihan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.60692/1sn6y-zan39","URL":"https://doi.org/10.60692/1sn6y-zan39","source":"datacite"},{"id":"doi:10.60692/349fe-11665","type":"article-journal","title":"Resilience towarded Digital Twins to improve the adaptability of transportation systems","abstract":"This work aims to investigate the role of the resilience of Digital Twins on the applicability of the transportation system. A literature study is conducted to review the current status of research on transportation systems and Digital Twins. It is found that the current research on Digital Twins technology has achieved different degrees of success in different aspects of transportation systems. Yet, the system performance of Digital Twins has to be optimized. First, the application of Digital Twins in intelligent transportation systems is analyzed. Then, how the changes in traveler behavior patterns reflect the extent to which the traffic network is affected by uncertain events is analyzed from the traveler's perspective. Finally, an Internet of Vehicles (IoV) system based on Digital Twins and blockchain is established to solve the data redundancy and high computational volume problems of in-vehicle data sharing common in the IoV system. Moreover, the performance of the twin system is optimized by proposing a multi-intelligence body algorithm based on local perception, and a case validation is performed. The results demonstrate that the adaptability of the transportation system to uncertain events and its response and recovery measures taken are reflected to some extent in the traveler behavior model. Besides, data sharing between vehicles and infrastructure in the transportation network can be well solved by Digital Twins Blockchain. The locally-aware multi-intelligent body algorithm saves more than 50% communication overhead and improves operational efficiency by nearly 20% over traditional algorithms by increasing intelligent body infrastructure units. It is adequately suited for large-scale vehicle traffic twins. It can be seen that improving the resilience of Digital Twins is a very obvious change in the adaptability of the traffic system.","author":[{"family":"Feng","given":"Hailin"},{"family":"Lv","given":"Haibin"},{"family":"Lv","given":"Zhihan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.60692/349fe-11665","URL":"https://doi.org/10.60692/349fe-11665","source":"datacite"},{"id":"doi:10.48550/arxiv.2308.01941","type":"manuscript","title":"Digital twin brain: a bridge between biological intelligence and artificial intelligence","abstract":"In recent years, advances in neuroscience and artificial intelligence have paved the way for unprecedented opportunities for understanding the complexity of the brain and its emulation by computational systems. Cutting-edge advancements in neuroscience research have revealed the intricate relationship between brain structure and function, while the success of artificial neural networks highlights the importance of network architecture. Now is the time to bring them together to better unravel how intelligence emerges from the brain's multiscale repositories. In this review, we propose the Digital Twin Brain (DTB) as a transformative platform that bridges the gap between biological and artificial intelligence. It consists of three core elements: the brain structure that is fundamental to the twinning process, bottom-layer models to generate brain functions, and its wide spectrum of applications. Crucially, brain atlases provide a vital constraint, preserving the brain's network organization within the DTB. Furthermore, we highlight open questions that invite joint efforts from interdisciplinary fields and emphasize the far-reaching implications of the DTB. The DTB can offer unprecedented insights into the emergence of intelligence and neurological disorders, which holds tremendous promise for advancing our understanding of both biological and artificial intelligence, and ultimately propelling the development of artificial general intelligence and facilitating precision mental healthcare.","author":[{"family":"Xiong","given":"Hui"},{"family":"Chu","given":"Congying"},{"family":"Fan","given":"Lingzhong"},{"family":"Song","given":"Ming"},{"family":"Zhang","given":"Jiaqi"},{"family":"Ma","given":"Yawei"},{"family":"Zheng","given":"Ruonan"},{"family":"Zhang","given":"Junyang"},{"family":"Yang","given":"Zhengyi"},{"family":"Jiang","given":"Tianzi"}],"issued":{"date-parts":[[2023]]},"DOI":"10.48550/arxiv.2308.01941","URL":"https://doi.org/10.48550/arxiv.2308.01941","source":"datacite"},{"id":"doi:10.5281/zenodo.7548017","type":"article-journal","title":"Bibliographic Data from the Digital Twin Anomaly Detection Decision-Making for Bridge Management Systematic Review","abstract":"This database contains all the bibliographic information about the 8673 records found after applying the Search Strategy used for the Digital Twin Anomaly Detection Decision-Making for Bridge Management Systematic Review. Such strategy consisted on using seven initial keywords and similar terms of interest (namely: bridge and bridges, etc.): Bridge. Digital twin. Bridge information modelling. Finite elements. Bridge health monitoring. Anomaly detection algorithm. Cultural heritage. Six initial queries were done combining the first keyword with the rest of them: bridge* AND \"digital twin*\" bridge* AND (BrIM OR \"bridge information model*\") bridge* AND (FEM OR FEA OR \"finite element method*\" OR \"finite element analy*\") bridge* AND (\"bridge health monitoring\" OR \"structural health monitoring\") bridge* AND (ADA OR \"anomaly detection algorithm*\") bridge* AND (\"cultural heritage\" OR \"monument* bridge*\" OR \"old bridge*\" OR \"ancient bridge*\" OR \"historic* bridge*\") As a first screening step, the combination of these 6 initial searches was done to obtain relevant works containing at least three of the main keywords of interest: #1 AND #2 #1 AND #3 #1 AND #4 #1 AND #5 #1 AND #6 #2 AND #3 #2 AND #4 #2 AND #5 #2 AND #6 #3 AND #4 #3 AND #5 #3 AND #6 #4 AND #5 #4 AND #6 #5 AND #6 All records found in Scopus where downloaded both in .ris and .csv format and are included in this database. The search was conducted on 10/12/2022. Note: Searches 10, 14, 17 and 21 did not return any records.","author":[{"family":"Jiménez Rios","given":"Alejandro"},{"family":"Plevris","given":"Vagelis"},{"family":"Nogal","given":"Maria"}],"issued":{"date-parts":[[2023]]},"DOI":"10.5281/zenodo.7548017","URL":"https://doi.org/10.5281/zenodo.7548017","source":"datacite"},{"id":"doi:10.48550/arxiv.2401.05194","type":"manuscript","title":"Modelling, Positioning, and Deep Reinforcement Learning Path Tracking Control of Scaled Robotic Vehicles: Design and Experimental Validation","abstract":"Mobile robotic systems are becoming increasingly popular. These systems are used in various indoor applications, raging from warehousing and manufacturing to test benches for assessment of advanced control strategies, such as artificial intelligence (AI)-based control solutions, just to name a few. Scaled robotic cars are commonly equipped with a hierarchical control acthiecture that includes tasks dedicated to vehicle state estimation and control. This paper covers both aspects by proposing (i) a federeted extended Kalman filter (FEKF), and (ii) a novel deep reinforcement learning (DRL) path tracking controller trained via an expert demonstrator to expedite the learning phase and increase robustess to the simulation-to-reality gap. The paper also presents the formulation of a vehicle model along with an effective yet simple procedure for identifying tis paramters. The experimentally validated model is used for (i) supporting the design of the FEKF and (ii) serving as a digital twin for training the proposed DRL-based path tracking algorithm. Experimental results confirm the ability of the FEKF to improve the estimate of the mobile robot's position. Furthermore, the effectiveness of the DRL path tracking strateguy is experimentally tested along manoeuvres not considered during training, showing also the ability of the AI-based solution to outpeform model-based control strategies and the demonstrator. The comparison with benchmraking controllers is quantitavely evalueted through a set of key performance indicators.","author":[{"family":"Caponio","given":"Carmine"},{"family":"Stano","given":"Pietro"},{"family":"Carli","given":"Raffaele"},{"family":"Olivieri","given":"Ignazio"},{"family":"Ragone","given":"Daniele"},{"family":"Sorniotti","given":"Aldo"},{"family":"Montanaro","given":"Umberto"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2401.05194","URL":"https://doi.org/10.48550/arxiv.2401.05194","source":"datacite"},{"id":"doi:10.48550/arxiv.2401.02661","type":"manuscript","title":"Nurse-in-the-Loop Artificial Intelligence for Precision Management of Type 2 Diabetes in a Clinical Trial Utilizing Transfer-Learned Predictive Digital Twin","abstract":"Background: Type 2 diabetes (T2D) is a prevalent chronic disease with a significant risk of serious health complications and negative impacts on the quality of life. Given the impact of individual characteristics and lifestyle on the treatment plan and patient outcomes, it is crucial to develop precise and personalized management strategies. Artificial intelligence (AI) provides great promise in combining patterns from various data sources with nurses' expertise to achieve optimal care. Methods: This is a 6-month ancillary study among T2D patients (n = 20, age = 57 +- 10). Participants were randomly assigned to an intervention (AI, n=10) group to receive daily AI-generated individualized feedback or a control group without receiving the daily feedback (non-AI, n=10) in the last three months. The study developed an online nurse-in-the-loop predictive control (ONLC) model that utilizes a predictive digital twin (PDT). The PDT was developed using a transfer-learning-based Artificial Neural Network. The PDT was trained on participants self-monitoring data (weight, food logs, physical activity, glucose) from the first three months, and the online control algorithm applied particle swarm optimization to identify impactful behavioral changes for maintaining the patient's glucose and weight levels for the next three months. The ONLC provided the intervention group with individualized feedback and recommendations via text messages. The PDT was re-trained weekly to improve its performance. Findings: The trained ONLC model achieved &gt;=80% prediction accuracy across all patients while the model was tuned online. Participants in the intervention group exhibited a trend of improved daily steps and stable or improved total caloric and total carb intake as recommended.","author":[{"family":"Faruqui","given":"Syed"},{"family":"Alaeddini","given":"Adel"},{"family":"Du","given":"Yan"},{"family":"Li","given":"Shiyu"},{"family":"Sharma","given":"Kumar"},{"family":"Wang","given":"Jing"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2401.02661","URL":"https://doi.org/10.48550/arxiv.2401.02661","source":"datacite"},{"id":"oa:W4399389941","type":"article-journal","title":"Unlocking the Future of Drug Development: Generative AI, Digital Twins, and Beyond","abstract":"This article delves into the intersection of generative AI and digital twins within drug discovery, exploring their synergistic potential to revolutionize pharmaceutical research and development. Through various instances and examples, we illuminate how generative AI algorithms, capable of simulating vast chemical spaces and predicting molecular properties, are increasingly integrated with digital twins of biological systems to expedite drug discovery. By harnessing the power of computational models and machine learning, researchers can design novel compounds tailored to specific targets, optimize drug candidates, and simulate their behavior within virtual biological environments. This paradigm shift offers unprecedented opportunities for accelerating drug development, reducing costs, and, ultimately, improving patient outcomes. As we navigate this rapidly evolving landscape, collaboration between interdisciplinary teams and continued innovation will be paramount in realizing the promise of generative AI and digital twins in advancing drug discovery.","author":[{"family":"Mariam","given":"Zamara"},{"family":"Niazi","given":"Sarfaraz"},{"family":"Magoola","given":"Matthias"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/biomedinformatics4020079","URL":"https://doi.org/10.3390/biomedinformatics4020079","source":"openalex"},{"id":"oa:W4385759414","type":"article-journal","title":"Recent Inventions in Additive Manufacturing: Holistic Review","abstract":"This general review paper presents a condensed view of recent inventions in the Additive Manufacturing (AM) field. It outlines factors affecting the development and commercialization of inventions via research collaboration and discusses breakthroughs in materials and AM technologies and their integration with emerging technologies. The paper explores the impact of AM across various sectors, including the aerospace, automotive, healthcare, food, and construction industries, since the 1970s. It also addresses challenges and future directions, such as hybrid manufacturing and bio-printing, along with socio-economic and environmental implications. This collaborative study provides a concise understanding of the latest inventions in AM, offering valuable insights for researchers, practitioners, and decision makers in diverse industries and institutions.","author":[{"family":"Fidan","given":"Ismail"},{"family":"Huseynov","given":"Orkhan"},{"family":"Ali","given":"Mohammad"},{"family":"Alkunte","given":"Suhas"},{"family":"Rajeshirke","given":"Mithila"},{"family":"Gupta","given":"Ankit"},{"family":"Hasanov","given":"Seymur"},{"family":"Tantawi","given":"Khalid"},{"family":"Yasa","given":"Evren"},{"family":"Yılmaz","given":"Oğuzhan"},{"family":"Loy","given":"Jennifer"},{"family":"Popov","given":"Vladimir"},{"family":"Sharma","given":"Ankit"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/inventions8040103","URL":"https://doi.org/10.3390/inventions8040103","source":"openalex"},{"id":"oa:W4391995295","type":"article-journal","title":"Production digital twin: a systematic literature review of challenges","abstract":"The manufacturing industry is entering the fourth industrial revolution, which aims to shift the manufacturing paradigm to data-driven smart manufacturing. Many barriers still limit the adoption of this new revolution, although enabling technologies such as a digital twin (DT) have the potential to overcome them. Since the appearance of the digital twin technology, this has led to a significant increase in academic publications and industrial applications. However, significant challenges facing the implementation of this technology stem from the emergent field stage, a need for more comprehensive information, and a need for clarity and consistency in definitions and concepts. This review identifies and categorizes the potential digital twin challenges and provides a novel conceptual framework that structures them and links them to the principal digital twin components, along with an example that elucidates the proposed framework’s utilization. The emerging relationships unveil interesting insights into the current status and future research requirements.","author":[{"family":"Kerrouchi","given":"Slimane"},{"family":"Aghezzaf","given":"El‐houssaine"},{"family":"Cottyn","given":"Johannes"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1080/0951192x.2024.2314792","URL":"https://doi.org/10.1080/0951192x.2024.2314792","source":"openalex"},{"id":"oa:W4392271629","type":"manuscript","title":"Towards a Digital Twin Framework in Additive Manufacturing: Machine Learning and Bayesian Optimization for Time Series Process Optimization","abstract":"Laser-directed-energy deposition (DED) offers advantages in additive manufacturing (AM) for creating intricate geometries and material grading. Yet, challenges like material inconsistency and part variability remain, mainly due to its layer-wise fabrication. A key issue is heat accumulation during DED, which affects the material microstructure and properties. While closed-loop control methods for heat management are common in DED research, few integrate real-time monitoring, physics-based modeling, and control in a unified framework. Our work presents a digital twin (DT) framework for real-time predictive control of DED process parameters to meet specific design objectives. We develop a surrogate model using Long Short-Term Memory (LSTM)-based machine learning with Bayesian Inference to predict temperatures in DED parts. This model predicts future temperature states in real time. We also introduce Bayesian Optimization (BO) for Time Series Process Optimization (BOTSPO), based on traditional BO but featuring a unique time series process profile generator with reduced dimensions. BOTSPO dynamically optimizes processes, identifying optimal laser power profiles to attain desired mechanical properties. The established process trajectory guides online optimizations, aiming to enhance performance. This paper outlines the digital twin framework's components, promoting its integration into a comprehensive system for AM.","author":[{"family":"Karkaria","given":"Vispi"},{"family":"Goeckner","given":"Anthony"},{"family":"Zha","given":"Rujing"},{"family":"Chen","given":"Jie"},{"family":"Zhang","given":"Jianjing"},{"family":"Zhu","given":"Qi"},{"family":"Cao","given":"Jian"},{"family":"Gao","given":"Robert"},{"family":"Chen","given":"Wei"},{"family":"Karkaria","given":"Vispi"},{"family":"Goeckner","given":"Anthony"},{"family":"Zha","given":"Rujing"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2402.17718","URL":"https://doi.org/10.48550/arxiv.2402.17718","source":"openalex"},{"id":"oa:W4401449888","type":"article-journal","title":"Real-time quality prediction and local adjustment of friction with digital twin in sheet metal forming","abstract":"In sheet metal forming, the quality of a formed part is strongly influenced by the local lubrication conditions on the blank. Fluctuations in lubrication distribution can cause failures such as excessive thinning and cracks. Predicting these failures in real-time for the entire part is still a very challenging task. Machine learning (ML) based digital twins and advanced computing power offer new ways to analyze manufacturing processes inline in the shortest possible time. This study presents a digital twin for simulating a deep drawing process that incorporates an advanced ML model and optimization algorithm. Convolutional neural networks with RES-SE-U-Net architecture, were used to capture the full friction conditions on the blank. The ML model was trained with data from a calibrated finite element model. The ML model establishes a correlation between the local friction conditions across the blank and the quality of the drawn part. It accurately predicts the geometry and thinning of the formed part in real-time by assessing the friction conditions on the blank. A particle swarm optimization algorithm incorporates the ML model and provides tailored recommendations for adjusting local friction conditions to promptly correct detected quality deviations with minimal amount of additional lubricant. Experiments show that the ML model deployed on an industrial control system can predict part quality in real-time and recommend adjustments in case of quality deviation in 1.6 s. The error between prediction and ground truth is on average 0.16 mm for geometric accuracy and 0.02 % for thinning. • Highly accurate 3D predictions of deep drawn parts as a function of the initial lubrication on the blank are possible in real-time. • The system combines CNN and optimization to adjust the friction conditions in case of predicted part defects or quality deviations. • Computations can run in parallel with the manufacturing process as a digital twin on an industrial control system.","author":[{"family":"Link","given":"Patrick"},{"family":"Penter","given":"Lars"},{"family":"Rückert","given":"Ulrike"},{"family":"Klingel","given":"Lars"},{"family":"Verl","given":"Alexander"},{"family":"Ihlenfeldt","given":"Steffen"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.rcim.2024.102848","URL":"https://doi.org/10.1016/j.rcim.2024.102848","source":"openalex"},{"id":"oa:W4372349028","type":"article-journal","title":"On the Use of the Digital Twin Concept for the Structural Integrity Protection of Architectural Heritage","abstract":"Undoubtedly, heritage buildings serve as essential embodiments of the cultural richness and diversity of the world’s states, and their conservation is of the utmost importance. Specifically, the protection of the structural integrity of these buildings is highly relevant not only because of the buildings themselves but also because they often contain precious artworks, such as sculptures, paintings, and frescoes. When a disaster causes damage to heritage buildings, these artworks will likely be damaged, resulting in the loss of historical and artistic materials and an intangible loss of memory and identity for people. To preserve heritage buildings, state-of-the-art recommendations inspired by the Venice Charter of 1964 suggest real-time monitoring of the progressive damage of existing structures, avoiding massive interventions, and providing immediate action in the case of a disaster. The most up-to-date digital information and analysis technologies, such as digital twins, can be employed to fulfil this approach. The implementation of the digital twin paradigm can be crucial in developing a preventive approach for built cultural heritage conservation, considering its key features of continuous data exchange with the physical system and predictive analysis. This paper presents a comprehensive overview of the digital twin concept in the architecture, engineering, construction, and operation (AECO) domain. It also critically discusses some applications within the context of preserving the structural integrity of architectural heritage, with a particular emphasis on masonry structures. Finally, a prototype of the digital twin paradigm for the preservation of heritage buildings’ structural integrity is proposed.","author":[{"family":"Vuoto","given":"Annalaura"},{"family":"Funari","given":"Francesco"},{"family":"Lourénço","given":"Paulo"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/infrastructures8050086","URL":"https://doi.org/10.3390/infrastructures8050086","source":"openalex"},{"id":"oa:W4380359224","type":"article-journal","title":"Application of Life Cycle of Aeroengine Mainshaft Bearing Based on Digital Twin","abstract":"Aeroengine mainshaft bearings are key components in modern aeroengines, and their main functions are to support the rotation of the main shaft of the aeroengine in harsh environments, such as high temperature, heavy load, high speed and oil break; reduce the friction coefficient during the high-speed rotation of the main shaft; and reliably ensure the rotation accuracy and power transmission of the aeroengine’s main shaft during operation. The manufacture of aeroengine mainshaft bearings requires complex processes and precise machining to ensure high performance and reliability, and how to intelligently complete the production and manufacture of mainshaft bearings and ensure the strength and accuracy of the bearings, quickly distinguish the fault types of the bearings and efficiently calculate, analyze and predict the life of the bearings are the current research hotspots. Therefore, building a high-fidelity and computationally efficient digital twin life cycle of aeroengine mainshaft bearings is a valuable solution. This paper summarizes the key manufacturing technology, manufacturing mode and manufacturing process based on digital twins in the life cycle of aeroengine mainshaft bearings, including the metallurgical process, heat treatment process and grinding process of aeroengine mainshaft bearings. It presents a fault diagnosis and life analysis of mainshaft bearings of aeroengines, discussing the key technologies and research directions of the life cycle of mainshaft bearings based on digital twins.","author":[{"family":"Li","given":"Yunfeng"},{"family":"Li","given":"Ming"},{"family":"Yan","given":"Zhong"},{"family":"Li","given":"Ruoxuan"},{"family":"Tian","given":"Ao"},{"family":"Xu","given":"Xinming"},{"family":"Zhang","given":"Hang"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/pr11061768","URL":"https://doi.org/10.3390/pr11061768","source":"openalex"},{"id":"oa:W4378528384","type":"article-journal","title":"Remote Sensing Technology in the Construction of Digital Twin Basins: Applications and Prospects","abstract":"A digital twin basin serves as a virtual representation of a physical basin, enabling synchronous simulation, virtual–real interaction, and iterative optimization. The construction of a digital twin basin requires a basin database characterized by large-scale coverage, high-precision, high-resolution, and low-latency attributes. The advancements in remote sensing technology present a new technical means for acquiring essential variables of the basin. The purpose of this paper was to provide a comprehensive overview and discussion of the retrieval principle, data status, evaluation and inter-comparison, advantages and challenges, applications, and prospects of remote sensing technology in capturing seven essential variables, i.e., precipitation, surface temperature, evapotranspiration, water level, river discharge, soil moisture, and vegetation. It is indicated that remote sensing can be applied in some digital twin basin functions, such as drought monitoring, precipitation forecasting, and water resources management. However, more effort should be paid to improve the data accuracy, spatiotemporal resolution, and latency through data merging, data assimilation, bias correction, machine learning algorithms, and multi-sensor joint retrieval. This paper will assist in advancing the application of remote sensing technology in constructing a digital twin basin.","author":[{"family":"Wu","given":"Xiaotao"},{"family":"Lu","given":"Guihua"},{"family":"Wu","given":"Zhiyong"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/w15112040","URL":"https://doi.org/10.3390/w15112040","source":"openalex"},{"id":"oa:W4392915470","type":"article-journal","title":"Additive Manufacturing and 3D Printing Innovations","abstract":"Additive manufacturing (AM), commonly known as 3D printing, has emerged as a transformative technology with profound implications for multiple industries. The convergence of AM with Industry 4.0 principles and advanced technologies has given rise to Industry 5.0, a new era of manufacturing characterized by enhanced integration and digitalization. This chapter explores the dynamic landscape of AM within the context of Industry 5.0, highlighting research trends, innovations, and challenges. Key developments include materials advancements, multi-material printing, digital twins, bioprinting, AI-driven design, and sustainability initiatives. Industry 5.0's impact is felt globally, with applications spanning aerospace, healthcare, fashion, and beyond. Collaboration between academia and industry, regulatory frameworks, and the pursuit of sustainable practices are driving forces shaping the future of AM in Industry 5.0.","author":[{"family":"Gift","given":"MDM"},{"family":"Senthil","given":"TS"},{"family":"Hasan","given":"Dler"},{"family":"Alagarraja","given":"K"},{"family":"Jayaseelan","given":"P"},{"family":"Boopathi","given":"Sampath"}],"issued":{"date-parts":[[2024]]},"DOI":"10.4018/979-8-3693-0968-1.ch010","URL":"https://doi.org/10.4018/979-8-3693-0968-1.ch010","source":"openalex"},{"id":"oa:W4400583487","type":"article-journal","title":"Live fitting of process data within digital twins of manufacturing to use simulation and optimisation","abstract":"In production scenarios, uncertainty in production times, and scrap rates is common. Uncertainty can be described by stochastic models that need continuous updates due to changing conditions. This paper models probability distributions and estimates their parameters from real-world data on processing times and scrap rates. It uses live fitting to identify timely changes in the data sets, comparing different distributions. The fitting and live fitting approaches are applied to data from a real production system to compare the goodness of fit for different distributions and to demonstrate the reliability of the reaction to changes in the input data. Data and probability estimations are categorised, and a concept combining simulation and optimisation models is developed to optimise scheduling. The vision of the research presented in this paper is an online approach that determines quasi-optimal schedules for production systems based on current data from the system and its environment.","author":[{"family":"Schumacher","given":"Christin"},{"family":"Stilling","given":"Jonas"},{"family":"Kriege","given":"Jan"},{"family":"Buchholz","given":"Peter"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1080/17477778.2024.2376711","URL":"https://doi.org/10.1080/17477778.2024.2376711","source":"openalex"},{"id":"oa:W4400764755","type":"article-journal","title":"Exploring Data for Construction Digital Twins: Building Health and Safety and Progress Monitoring Twins Using the Unreal Gaming Engine","abstract":"Although digital twins have been established in manufacturing for a long time, they are only more recently making their way into the urban environment and present a relatively new concept for the construction industry. The concept of a digital twin—a model of the physical environment that has a real-time two-way link between the physical and the digital, with the virtual model changing over time to reflect changes in the real world—lends itself well to the continually changing environment of a construction project. Predictive capabilities built into a twin also have great potential for construction planning—including in supply chain management and waste disposal as well as in the construction process itself. Underpinning this opportunity is location data, which model where something is happening and when and can be used to solve a wide range of problems. In particular, location (the power of where) can integrate diverse data sources and types into a single system, overcoming interoperability challenges that are known to be a barrier to twin implementation. This paper demonstrates the power of location-enabled digital twins in the context of a highway construction project, documenting and addressing data engineering tasks and functionality development to explore the potential of digital twins in the context of two case studies—health and safety and construction monitoring. We develop two demonstrators using data from an existing construction project (building on data and requirements from industry partner Skanska) to build twins that make use of the powers of 4D data presentation offered by the Unreal Gaming Engine and CesiumJS mapping, while software development expertise is sometimes available to construction firms, we specifically explore to what extent the no-code approach available within Unreal can be deployed in this context. Our findings provide evidence to construction companies as to the benefits of digital twins, as well as an understanding of the data engineering and technical skills required to achieve these benefits. The overall results demonstrate the potential for digital twins to unlock and democratise construction data, taking them beyond the niche use of experts and into the boardroom.","author":[{"family":"Ellul","given":"Claire"},{"family":"Hamilton","given":"Neve"},{"family":"Pieri","given":"Alexandros"},{"family":"Floros","given":"George"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/buildings14072216","URL":"https://doi.org/10.3390/buildings14072216","source":"openalex"},{"id":"oa:W4400930259","type":"article-journal","title":"Increasing acceptance of AI ‐generated digital twins through clinical trial applications","abstract":"Today's approach to medicine requires extensive trial and error to determine the proper treatment path for each patient. While many fields have benefited from technological breakthroughs in computer science, such as artificial intelligence (AI), the task of developing effective treatments is actually getting slower and more costly. With the increased availability of rich historical datasets from previous clinical trials and real-world data sources, one can leverage AI models to create holistic forecasts of future health outcomes for an individual patient in the form of an AI-generated digital twin. This could support the rapid evaluation of intervention strategies in silico and could eventually be implemented in clinical practice to make personalized medicine a reality. In this work, we focus on uses for AI-generated digital twins of clinical trial participants and contend that the regulatory outlook for this technology within drug development makes it an ideal setting for the safe application of AI-generated digital twins in healthcare. With continued research and growing regulatory acceptance, this path will serve to increase trust in this technology and provide momentum for the widespread adoption of AI-generated digital twins in clinical practice.","author":[{"family":"Vidovszky","given":"Anna"},{"family":"Fisher","given":"Charles"},{"family":"Loukianov","given":"Anton"},{"family":"Smith","given":"Aaron"},{"family":"Tramel","given":"Eric"},{"family":"Walsh","given":"Jonathan"},{"family":"Ross","given":"Jessica"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1111/cts.13897","URL":"https://doi.org/10.1111/cts.13897","source":"openalex"},{"id":"oa:W4324367542","type":"article-journal","title":"Digital twins in cyber effects modelling of IoT/CPS points of low resilience","abstract":"The exponential increase of data volume and velocity have necessitated a tighter linkage of physical and cyber components in modern Cyber–physical systems (CPS) to achieve faster response times and autonomous component reconfiguration. To attain this degree of efficiency, the integration of virtual and physical components reinforced by artificial intelligence also promises to improve the resilience of these systems against organised and often skillful adversaries. The ability to visualise, validate, and illustrate the benefits of this integration, while taking into account improvements in cyber modelling and simulation tools and procedures, is critical to that adoption. Using Cyber Modelling and Simulation (M&S) this study evaluates the scale and complexity required to achieve an acceptable level of cyber resilience testing in an IoT-enabled critical national infrastructure (CNI). This research focuses on the benefits and challenges of integrating cyber modelling and simulation (M&S) with digital twins and threat source characterisation methodologies towards a cost-effective security and resilience assessment. Using our dedicated DT environment, we show how adversaries can utilise cyber–physical systems as a point of entry to a broader network in a scenario where they are trying to attack a port.","author":[{"family":"Epiphaniou","given":"Gregory"},{"family":"Hammoudeh","given":"Mohammad"},{"family":"Yuan","given":"Hu"},{"family":"Maple","given":"Carsten"},{"family":"Ani","given":"Uchenna"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.simpat.2023.102744","URL":"https://doi.org/10.1016/j.simpat.2023.102744","source":"openalex"},{"id":"oa:W4316672828","type":"article-journal","title":"The Influence of Digital Transformation and Supply Chain Integration on Overall Sustainable Supply Chain Performance: An Empirical Analysis from Manufacturing Companies in Morocco","abstract":"This study examined the association between digital transformation (DT), supply chain integration (SCI), and overall sustainable supply chain performance (OSSCP). The current literature has preliminarily explored the concepts of DT and SCI and their relationship with sustainable supply chain performance. However, real empirical evidence of the direct impact of DT and SCI on OSSCP has been missing so far. To fill this gap, data were collected from 134 professionals working in international manufacturing companies operating in Morocco through a questionnaire-based survey from August 2022 to November 2022. A conceptual framework was developed based on DT, SCI, and OSSCP and analyzed by partial least squares structural equation modeling (PLS-SEM) with the assistance of SmartPLS 4.0 software. The findings revealed that DT has a significant positive influence on SCI and OSSCP. Furthermore, SCI directly and positively impacts OSSCP with a partial mediation effect on the relationship between DT and OSSCP. Further, this research provides insights for practitioners into enhancing sustainable supply chain performance by adopting digital technologies and integrating SC functions. In particular, this study revealed that DT adoption drives a higher ethical supply chain level from the perspective of sustainability and efficiency in operations. This study is the first to analyze the influence of digital transformation and supply chain integration on sustainable supply chain performance in a manufacturing context.","author":[{"family":"Oubrahim","given":"Imadeddine"},{"family":"Sefiani","given":"Naoufal"},{"family":"Happonen","given":"Ari"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/en16021004","URL":"https://doi.org/10.3390/en16021004","source":"openalex"},{"id":"oa:W4387899164","type":"article-journal","title":"Transfer learning-based multiple digital twin-assisted intelligent mechanical fault diagnosis","abstract":"Abstract With the advancement of complex system diagnosis, prediction, and health management technologies, digital twin technology has become a prominent research area in the fields of intelligent manufacturing and system operation and maintenance. However, due to the high complexity of practical systems, the difficulty of data acquisition, and the low accuracy of modeling techniques, current digital twin modeling suffers from low accuracy, and the generalization ability of models is poor when applied in model transfer. To address this issue, a novel fault diagnosis method is proposed, which integrates a digital twin model based on transfer learning. The framework introduces an innovative approach to construct multiple digital twin models using both mechanistic and data-driven models. The mechanism twin constructs a universal simulation model based on physical equipment and updates it with system response measurement data. The data twin consists of a high-dimensional fully connected-generative adversarial network twin for extracting deep features from data and an long- and short-term memory twin for extracting time series features. Subsequently, transfer learning is introduced to achieve deep fusion in the multiple digital twins system. The mechanism twin is used to obtain source domain samples to construct a diagnostic network, and the data twin is used to extract target domain features to correct the diagnostic network, thereby improving the accuracy and reliability of fault diagnosis. Finally, the proposed framework is applied to the fault diagnosis of triplex pump equipment. The accuracy of diagnosis continuously improves as the system is updated and ultimately reaches 89.28%, demonstrating the effectiveness of the algorithm and providing a novel solution for the generalization limitations of current digital twin models.","author":[{"family":"Liu","given":"Sizhe"},{"family":"Qi","given":"Yongsheng"},{"family":"Gao","given":"Xuejin"},{"family":"Liu","given":"Liqiang"},{"family":"Ma","given":"Ran"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1088/1361-6501/ad0683","URL":"https://doi.org/10.1088/1361-6501/ad0683","source":"openalex"},{"id":"oa:W4385757748","type":"article-journal","title":"Digital Twin Robotic System With Continuous Learning for Grasp Detection in Variable Scenes","abstract":"With the emergence of digitalization technology, digital twin bridges the gap between physical and virtual worlds in industrial production with synchronization, reliability, and fidelity. The manufacturing process of complex products needs multiple working procedures, where novel industrial parts occur, causing scenes to be variable for robots to perceive and grasp. Due to the geometric difference among objects in various categories, it is significant to empower robotic systems with the capability of continuous learning for grasp detection in variable scenes. Therefore, a digital twin robotic system is proposed to realize bidirectional real-time data interaction and synchronization in the physical and virtual worlds. In this digital twin robotic system, a synthetic grasp detection dataset composed of industrial parts is built for an industrial grasping task. Besides, a novel deep learning method, adaptive spatial-awareness grasp network with a novel cc, is proposed to realize end-to-end 7-DoF grasp detection for industrial objects. In addition, a continuous learning strategy is proposed for 7-DoF grasp pose detection without catastrophic forgetting in variable scenes. Experiments in both virtual and physical worlds have demonstrated the effectiveness of our method for potential industrial implementation, and the average grasping success rate reaches 91% and 88% for novel objects in the virtual and physical worlds, respectively.","author":[{"family":"Ren","given":"Lei"},{"family":"Dong","given":"Jiabao"},{"family":"Huang","given":"Di"},{"family":"Lü","given":"Jinhu"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/tie.2023.3299049","URL":"https://doi.org/10.1109/tie.2023.3299049","source":"openalex"},{"id":"oa:W4367319198","type":"article-journal","title":"Construction and Maintenance of Building Geometric Digital Twins: State of the Art Review","abstract":"Most of the buildings that exist today were built based on 2D drawings. Building information models that represent design-stage product information have become prevalent in the second decade of the 21st century. Still, it will take many decades before such models become the norm for all existing buildings. In the meantime, the building industry lacks the tools to leverage the benefits of digital information management for construction, operation, and renovation. To this end, this paper reviews the state-of-the-art practice and research for constructing (generating) and maintaining (updating) geometric digital twins. This paper also highlights the key limitations preventing current research from being adopted in practice and derives a new geometry-based object class hierarchy that mainly focuses on the geometric properties of building objects, in contrast to widely used existing object categorisations that are mainly function-oriented. We argue that this new class hierarchy can serve as the main building block for prioritising the automation of the most frequently used object classes for geometric digital twin construction and maintenance. We also draw novel insights into the limitations of current methods and uncover further research directions to tackle these problems. Specifically, we believe that adapting deep learning methods can increase the robustness of object detection and segmentation of various types; involving design intents can achieve a high resolution of model construction and maintenance; using images as a complementary input can help to detect transparent and specular objects; and combining synthetic data for algorithm training can overcome the lack of real labelled datasets.","author":[{"family":"Drobnyi","given":"Viktor"},{"family":"Hu","given":"Zhiqi"},{"family":"Fathy","given":"Yasmin"},{"family":"Brilakis","given":"Ioannis"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/s23094382","URL":"https://doi.org/10.3390/s23094382","source":"openalex"},{"id":"oa:W4380355471","type":"article-journal","title":"Analyzing the Implementation of Digital Twins in the Agri-Food Supply Chain","abstract":"Background: Digital twins have the potential to significantly improve the efficiency and sustainability of the agri-food supply chain by providing visibility, reducing bottlenecks, planning for contingencies, and improving existing processes and resources. Additionally, they can add value to businesses by lowering costs and boosting customer satisfaction. This study is aimed at responding to common scientific questions on the application of digital twins in the agri-food supply chain, focusing on the benefits, types, integration levels, key elements, implementation steps, and challenges. Methods: This article conducts a systematic literature review of recent works on agri-food supply chain digital twins, using a list of peer-reviewed studies to analyze concepts using precise and well-defined criteria. Thus, 50 papers were selected based on inclusion and exclusion criteria, and descriptive and content-wise analysis was conducted to answer the research questions. Conclusions: The implementation of digital twins has shown promising advancements in addressing global challenges in the agri-food supply chain. Despite encouraging signs of progress in the sector, the real-world application of this solution is still in its early stages. This article intends to provide firms, experts, and researchers with insights into future research directions, implications, and challenges on the topic.","author":[{"family":"Melesse","given":"Tsega"},{"family":"Franciosi","given":"Chiara"},{"family":"Pasquale","given":"Valentina"},{"family":"Riemma","given":"Stefano"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/logistics7020033","URL":"https://doi.org/10.3390/logistics7020033","source":"openalex"},{"id":"oa:W4387696937","type":"article-journal","title":"Digital Twin Simulation System for Reconfigurable Manufacturing Systems","abstract":"In order to adapt to the multi-variety and small-batch production mode, reconfigurable manufacturing systems have been widely applied in various industries. However, the rapid reconfiguration of these systems poses challenges for workshop managers to grasp the workshop status in a real-time and comprehensive manner. This paper proposes a digital twin modeling and simulation technology for reconfigurable manufacturing systems, enabling concurrent production simulation and reconfiguration simulation of reconfigurable manufacturing systems. Through the use of digital twin technology, real-time simulation and visualization of physical workshops can be achieved, enhancing managerial efficiency.","author":[{"family":"Shan","given":"Qishen"},{"family":"Cui","given":"Wei"},{"family":"Wang","given":"Aimin"},{"family":"Wang","given":"Sheng"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/aicit59054.2023.10278028","URL":"https://doi.org/10.1109/aicit59054.2023.10278028","source":"openalex"},{"id":"oa:W4385259797","type":"article-journal","title":"Enabling Trust and Security in Digital Twin Management: A Blockchain-Based Approach with Ethereum and IPFS","abstract":"The emergence of Industry 5.0 has highlighted the significance of information usage, processing, and data analysis when maintaining physical assets. This has enabled the creation of the Digital Twin (DT). Information about an asset is generated and consumed during its entire life cycle. The main goal of DT is to connect and represent physical assets as close to reality as possible virtually. Unfortunately, the lack of security and trust among DT participants remains a problem as a result of data sharing. This issue cannot be resolved with a central authority when dealing with large organisations. Blockchain technology has been proposed as a solution for DT information sharing and security challenges. This paper proposes a Blockchain-based solution for digital twin using Ethereum blockchain with performance and cost analysis. This solution employs a smart contract for information management and access control for stakeholders of the digital twin, which is secure and tamper-proof. This implementation is based on Ethereum and IPFS. We use IPFS storage servers to store stakeholders' details and manage information. A real-world use-case of a production line of a smartphone, where a conveyor belt is used to carry different parts, is presented to demonstrate the proposed system. The performance evaluation of our proposed system shows that it is secure and achieves performance improvement when compared with other methods. The comparison of results with state-of-the-art methods showed that the proposed system consumed fewer resources in a transaction cost, with an 8% decrease. The execution cost increased by 10%, but the cost of ether was 93% less than the existing methods.","author":[{"family":"Onwubiko","given":"Austine"},{"family":"Singh","given":"Raman"},{"family":"Awan","given":"Shahid"},{"family":"Pervez","given":"Zeeshan"},{"family":"Ramzan","given":"Naeem"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/s23146641","URL":"https://doi.org/10.3390/s23146641","source":"openalex"},{"id":"oa:W4402157315","type":"article-journal","title":"Design of Manufacturing Equipment Digital Twin Interworking Framework Based on REST API for Smart Factory","abstract":"A digital twin, which digitizes facilities within factories and implements them in virtual space, is a useful technology for monitoring and analyzing the performance and status of manufacturing equipment and systems, and the quality of products in smart factories. To implement the digital twin, synchronization between a real object and a virtual object is required. In this paper, we design a REST API-based interface framework for real-virtual object linkage of manufacturing equipment required in the digital twin for smart factories. The proposed framework exchanges information with the virtual factory in connection with the existing automation system.","author":[{"family":"Wee","given":"Jung"},{"family":"Cho","given":"Minju"},{"family":"Lee","given":"Youn"},{"family":"Lee","given":"Kyung"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/icufn61752.2024.10625236","URL":"https://doi.org/10.1109/icufn61752.2024.10625236","source":"openalex"},{"id":"oa:W4406460525","type":"article-journal","title":"Research on Intelligent Manufacturing Production Lines for Automobile Wheel Hubs by Digital Twin Models","abstract":"Due to the complex geometric shapes, high precision design dimensions, and specific material characteristics of automobile wheel hubs, there are stringent requirements for processing procedures, efficiency, and stability. To meet these demands, enterprises commonly adopt intelligent manufacturing production lines. Key challenges include establishing adaptive intelligent capabilities for the \"processing-measurement-compensation-processing\" cycle, constructing digital twin models of wheel hub production lines for real-time synchronization in virtual reality production, optimizing equipment and process interfaces, and improving fixture systems. Integrating discrete CNC machining, inspection, and assembly organically is crucial for smart manufacturing engineers. This article provides targeted discussions on core technologies and development directions in this field.","author":[{"family":"Zhuming","given":"Cao"},{"family":"Huanbo","given":"Dong"},{"family":"Jide","given":"Jia"},{"family":"Shouhua","given":"Yi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/icdacai65086.2024.00155","URL":"https://doi.org/10.1109/icdacai65086.2024.00155","source":"openalex"},{"id":"oa:W4387686379","type":"article-journal","title":"Development and implementation of a roadmapping methodology to foster twin transition at manufacturing plant level","abstract":"Climate change and resource depletion are reshaping economies, compelling governments, society, and businesses to seek solutions that could meet both economic and environmental needs. Due to their relevance to environmental damage, manufacturers are pushed to achieve a sustainable transition in a relatively short time. In this scenario, Industry 4.0 reportedly act as a facilitator of the processes thus leading to the concept of Twin Transition (TT) or digitally-enabled sustainable transition. However, even if literature is aware of the role that I4.0 plays in enhancing sustainability, companies still face a multitude of barriers that hinder the actual implementation of such transition. This paper aims at proposing a new roadmapping methodology to guide manufacturing companies toward TT and link the strategic goals to operations activities. The methodology originates from both an analysis of the barriers faced by manufacturers found in literature and the empirical observations of the authors throughout their research with manufacturing firms. The methodology was implemented in an application case involving 3 independent plants of a multinational company operating in the Food & Beverage sector. The analysis of barriers was performed via a systematic literature review that allowed to identify 39 barriers clustered as Micro (single firm), Meso (network) and Macro (ecosystem). The results show that the methodology applies to single manufacturing plants, and it addresses challenges at micro and meso levels.","author":[{"family":"Spaltini","given":"Marco"},{"family":"Terzi","given":"Sergio"},{"family":"Taisch","given":"Marco"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.compind.2023.104025","URL":"https://doi.org/10.1016/j.compind.2023.104025","source":"openalex"},{"id":"oa:W4390639795","type":"article-journal","title":"Survey on open‐source digital twin frameworks–A case study approach","abstract":"Abstract Digital twin (DT) technology has been a topic with academic and industrial coverage in recent years. DTs are intended to be a virtual high‐fidelity representation of a physical counterpart. Its complex nature requires several components to create and run a DT, and that is why many DT frameworks have been proposed in the literature. There are also many surveys of DTs, but none that is bottom‐up with concrete examples and focused on open‐source software. This survey analyzes 14 open‐source DT frameworks in 10 different dimensions, which are then categorized in six different groups according to their modeling and technological domain, to present the reader different options for creating and managing DT applications, and to understand potential combinations, uses, and limitations of the tools. It also presents a case study with five of the explored DT frameworks, describing the process on how the DT is set up and comparing their capabilities based on the services to be provided by the DT. Finally, it discusses advantages and limitations of the tools according to domain, requirements, and scope, relevant aspects regarding built‐in simulations and data analytics, theory‐to‐practice transition, and advantages/disadvantages of using open‐source software instead of commercial. Main limitations of the study due to its narrow niche, conclusions, and opportunities for future research regarding the potential room for improvement in terms of out‐of‐the‐box features and services for DTs, are also shown.","author":[{"family":"Gil","given":"Santiago"},{"family":"Mikkelsen","given":"Peter"},{"family":"Gomes","given":"Cláudio"},{"family":"Larsen","given":"Peter"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/spe.3305","URL":"https://doi.org/10.1002/spe.3305","source":"openalex"},{"id":"oa:W4385162048","type":"article-journal","title":"A Comprehensive Review of Digital Twin Technology for Grid-Connected Microgrid Systems: State of the Art, Potential and Challenges Faced","abstract":"The concept of the digital twin has been adopted as an important aspect in digital transformation of power systems. Although the notion of the digital twin is not new, its adoption into the energy sector has been recent and has targeted increased operational efficiency. This paper is focused on addressing an important gap in the research literature reviewing the state of the art in utilization of digital twin technology in microgrids, an important component of power systems. A microgrid is a local power network that acts as a dependable island within bigger regional and national electricity networks, providing power without interruption even when the main grid is down. Microgrids are essential components of smart cities that are both resilient and sustainable, providing smart cities the opportunity to develop sustainable energy delivery systems. Due to the complexity of design, development and maintenance of a microgrid, an efficient simulation model with ability to handle the complexity and spatio-temporal nature is important. The digital twin technologies have the potential to address the above-mentioned requirements, providing an exact virtual model of the physical entity of the power system. The paper reviews the application of digital twins in a microgrid at electrical points where the microgrid connects or disconnects from the main distribution grid, that is, points of common coupling. Furthermore, potential applications of the digital twin in microgrids for better control, security and resilient operation and challenges faced are also discussed.","author":[{"family":"Kumari","given":"Namita"},{"family":"Sharma","given":"Ankush"},{"family":"Tran","given":"Binh"},{"family":"Chilamkurti","given":"Naveen"},{"family":"Alahakoon","given":"Damminda"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/en16145525","URL":"https://doi.org/10.3390/en16145525","source":"openalex"},{"id":"oa:W4381572789","type":"article-journal","title":"Collaborative robots in manufacturing and assembly systems: literature review and future research agenda","abstract":"Abstract Nowadays, considering the constant changes in customers’ demands, manufacturing systems tend to move more and more towards customization while ensuring the expected reactivity. In addition, more attention is given to the human factors to, on the one hand, create opportunities for improving the work conditions such as safety and, on the other hand, reduce the risks brought by new technologies such as job cannibalization. Meanwhile, Industry 4.0 offers new ways to facilitate this change by enhancing human–machine interactions using Collaborative Robots (Cobots). Recent research studies have shown that cobots may bring numerous advantages to manufacturing systems, especially by improving their flexibility. This research investigates the impacts of the integration of cobots in the context of assembly and disassembly lines. For this purpose, a Systematic Literature Review (SLR) is performed. The existing contributions are classified on the basis of the subject of study, methodology, methodology, performance criteria, and type of Human-Cobot collaboration. Managerial insights are provided, and research perspectives are discussed.","author":[{"family":"Keshvarparast","given":"Ali"},{"family":"Battini","given":"Daria"},{"family":"Battaïa","given":"Olga"},{"family":"Pirayesh","given":"Amir"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1007/s10845-023-02137-w","URL":"https://doi.org/10.1007/s10845-023-02137-w","source":"openalex"},{"id":"oa:W4383313134","type":"article-journal","title":"Industry 5.0 implications for inclusive sustainable manufacturing: An evidence-knowledge-based strategic roadmap","abstract":"Despite the hype surrounding Industry 5.0 and its importance for sustainability, the micro-mechanisms through which this agenda can lead to socio-environmental values are largely understudied. The present study strived to address this knowledge gap by developing a strategic roadmap that outlines how Industry 5.0 can boost sustainable manufacturing. The study first conducted a content-centric literature review and identified 12 functions through which Industry 5.0 can inclusively boost sustainable manufacturing. The study further developed a strategic roadmap that identified the complex contextual relationships among the functions and explained how they should be synergistically leveraged to maximize their contribution to sustainability. Results reveal that value network integration, sustainable technology governance, sustainable business model innovation, and sustainable skill development are the most driver and tangible implications of Industry 5.0 for sustainable manufacturing. Alternatively, renewable integration and manufacturing resilience are among the most dependent and hard-to-reach sustainable functions of Industry 5.0, and their materialization requires major strategic collaboration among stakeholders. The strategic roadmap outlines how Industry 5.0 stakeholders can leverage the technological and functional constituents of this agenda to promote sustainable manufacturing inclusively.","author":[{"family":"Ghobakhloo","given":"Morteza"},{"family":"Iranmanesh","given":"Mohammad"},{"family":"Foroughi","given":"Behzad"},{"family":"Tırkolaee","given":"Erfan"},{"family":"Asadi","given":"Shahla"},{"family":"Amran","given":"Azlan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.jclepro.2023.138023","URL":"https://doi.org/10.1016/j.jclepro.2023.138023","source":"openalex"},{"id":"oa:W4313891040","type":"article-journal","title":"Digital Technologies in Offsite and Prefabricated Construction: Theories and Applications","abstract":"Due to its similarity to industrialized products, the offsite construction industry is seen as a focus for the transformation of Construction 4.0. Many digital technologies have been applied or have the potential to be applied to realize the integration of design, manufacturing, and assembly. The main objective of this review was to identify the current stage of applying digital technologies in offsite construction. In this review, 171 related papers from the last 10 years (i.e., 2013–2022) were obtained by collecting and filtering them. They were classified and analyzed according to the digital twin concept, application areas, and specific application directions. The results indicated that there are apparent differences in the utilization and development level of different technologies in different years. Meanwhile, the introduction, current stages, and benefits of different digital technologies are also discussed. Finally, this review summarizes the current popular fields and speculates on future research directions by analyzing article publication trends, which sheds light on future research.","author":[{"family":"Cheng","given":"Zhuo"},{"family":"Tang","given":"Shengxian"},{"family":"Liu","given":"Hexu"},{"family":"Lei","given":"Zhen"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/buildings13010163","URL":"https://doi.org/10.3390/buildings13010163","source":"openalex"},{"id":"oa:W4402910707","type":"article-journal","title":"Smart Manufacturing with a Digital Twin –Driven Cyber‐physical System: Case Study and Application Scenario","abstract":"In the smart world, smart systems that can communicate with us and offer services as needed are widely available in the market. These use cyber-physical systems for power. Medical monitoring, process control systems, robotic systems, and autonomous pilot avionics are some of the fields already utilizing CPS. It encompasses technology areas of cybernetics, mechatronics, embedded system, artificial intelligence (AI), design, and much more. Likewise, another advanced virtual technology is digital twin (DT). A digital twin is a virtual or digital replica of tangible goods or items. It serves as a link between the real world and the digital one. By combining the virtual and real worlds, it is now possible to analyze data and keep track of systems to see issues before they arise, save downtime, create new opportunities, and even simulate the future to make plans. This chapter is an analysis about the implementation of data twin and cyber-physical systems in smart manufacturing at different sectors like health care, manufacturing, transportation, entertainment, civil infrastructure, aerospace, automotive, chemical processes, energy, and consumer appliances with various case studies and about the Industry4.0, the Fourth Industrial Revolution, and the technology that shift to smart manufacturing.","author":[{"family":"Abinaya","given":"P"},{"family":"Kumar","given":"SP"},{"family":"Sivaprakash","given":"P"},{"family":"Kumar","given":"KA"},{"family":"Shuriya","given":"B"},{"family":"Khan","given":"Surbhi"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1002/9781394195336.ch11","URL":"https://doi.org/10.1002/9781394195336.ch11","source":"openalex"},{"id":"oa:W4404351645","type":"manuscript","title":"PMI-DT: Leveraging Digital Twins and Machine Learning for Predictive Modeling and Inspection in Manufacturing","abstract":"Over the years, Digital Twin (DT) has become popular in Advanced Manufacturing (AM) due to its ability to improve production efficiency and quality. By creating virtual replicas of physical assets, DTs help in real-time monitoring, develop predictive models, and improve operational performance. However, integrating data from physical systems into reliable predictive models, particularly in precision measurement and failure prevention, is often challenging and less explored. This study introduces a Predictive Maintenance and Inspection Digital Twin (PMI-DT) framework with a focus on precision measurement and predictive quality assurance using 3D-printed 1''-4 ACME bolt, CyberGage 360 vision inspection system, SolidWorks, and Microsoft Azure. During this approach, dimensional inspection data is combined with fatigue test results to create a model for detecting failures. Using Machine Learning (ML) -- Random Forest and Decision Tree models -- the proposed approaches were able to predict bolt failure with real-time data 100% accurately. Our preliminary result shows Max Position (30%) and Max Load (24%) are the main factors that contribute to that failure. We expect the PMI-DT framework will reduce inspection time and improve predictive maintenance, ultimately giving manufacturers a practical way to boost product quality and reliability using DT in AM.","author":[{"family":"Hamel","given":"Chas"},{"family":"Ahsan","given":"Md"},{"family":"Raman","given":"Shivakumar"},{"family":"Ahsan","given":"Md"},{"family":"Raman","given":"Shivakumar"}],"issued":{"date-parts":[[2024]]},"DOI":"10.48550/arxiv.2411.01299","URL":"https://doi.org/10.48550/arxiv.2411.01299","source":"openalex"},{"id":"oa:W4403869814","type":"article-journal","title":"Digitalization of urban multi-energy systems – Advances in digital twin applications across life-cycle phases","abstract":"• Urban multi-energy system's digital twins (UMES DTs) are emerging in the energy landscape. • UMES DTs should have a real-time data connection to the physical twin updated at desired intervals. • Adherence to standardized ontologies will facilitate interoperability & scalability. • UMES DT architecture balances interpretability & accuracy with open, semi-open, & closed models. • Planning UMES DTs should accompany and enhance the operation & decommissioning/reuse phase. Urban multi-energy systems (UMES) incorporating distributed energy resources are vital to future low-carbon energy systems. These systems demand complex solutions, including increased integration of renewables, improved efficiency through electrification, and exploitation of synergies via sector coupling across multiple sectors and infrastructures. Digitalization and the Internet of Things bring new opportunities for the design-build-operate workflow of the cyber-physical urban multi-energy systems. In this context, digital twins are expected to play a crucial role in managing the intricate integration of assets, systems, and actors within urban multi-energy systems. This review explores digital twin opportunities for urban multi-energy systems by first considering the challenges of urban multi energy systems. It then reviews recent advancements in digital twin architectures, energy system data categories, semantic ontologies, and data management solutions, addressing the growing data demands and modelling complexities. Digital twins provide an objective and comprehensive information base covering the entire design, operation, decommissioning, and reuse lifecycle phases, enhancing collaborative decision-making among stakeholders. This review also highlights that future research should focus on scaling digital twins to manage the complexities of urban environments. A key challenge remains in identifying standardized ontologies for seamless data exchange and interoperability between energy systems and sectors. As the technology matures, future research is required to explore the socio-economic and regulatory implications of digital twins, ensuring that the transition to smart energy systems is both technologically sound and socially equitable. The paper concludes by making a series of recommendations on how digital twins could be implemented for urban multi energy systems.","author":[{"family":"Koirala","given":"Binod"},{"family":"Cai","given":"Hanmin"},{"family":"Khayatian","given":"F"},{"family":"Muñoz","given":"Edrisi"},{"family":"An","given":"Jonggwan"},{"family":"Mutschler","given":"R"},{"family":"Sulzer","given":"Matthias"},{"family":"Wolf","given":"Charles"},{"family":"Orehounig","given":"Kristina"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.adapen.2024.100196","URL":"https://doi.org/10.1016/j.adapen.2024.100196","source":"openalex"},{"id":"oa:W4377294625","type":"article-journal","title":"Digital Twin for Safety and Security: Perspectives on Building Lifecycle","abstract":"As digital twins are gaining importance in various industries, research on their impact, use cases, and implementation in the field of construction is accelerating. In this study, we examine the impact of digital twins on building safety and security throughout their lifecycle, utilizing two state-of-the-art use cases for fire and anomaly detection. The solution employs advanced sensors, 3D visualizations for detecting safety and security threats, and data analysis to predict potential future threats. Using the data that was collected over a seventeen-month period, we present an implementation architecture for safety and security digital twins in buildings, explore the benefits and shortcomings of such a system, and discuss the learnings applicable to different lifecycle stages of a building. This paper contributes to the creation and study of a digital twin for fire safety, analyzing its performance using two real-world use cases and reporting the implementation results. Additionally, we extrapolate the learnings from the use phase of a facility to other lifecycle phases of buildings and facilities.","author":[{"family":"Khajavi","given":"Siavash"},{"family":"Tetik","given":"Müge"},{"family":"Liu","given":"Zixuan"},{"family":"Korhonen","given":"Pasi"},{"family":"Holmström","given":"Jan"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/access.2023.3278267","URL":"https://doi.org/10.1109/access.2023.3278267","source":"openalex"},{"id":"oa:W4403390730","type":"article-journal","title":"Digital twin in manufacturing: Transient Thermo-Mechanical Simulations","abstract":"The Digital Twin (DT) has received a lot of research attention and discussion in recent years. It contributes significantly to the industry's transition from the conventional era of trial and error to the contemporary industrial mode. Simulation and computer-aided engineering (CAE) are important components of the DT concept. Manufacturing DT is a virtual representation of the actual processes that may be planned for and enhanced. Additionally, DT offers an infinite number of measurement points and variables without using large, expensive sensors during the actual process.Surface mount technology (SMT) components are frequently attached to printed circuit boards (PCB) using reflow soldering. Employing DT in manufacturing, will end up in reduction in production time and cost, and CO2emissions from the production line.In this article, a Digital Twin based multiphysics model is used, powered by the Ansys simulation environment, to conduct a comprehensive virtual analysis of the reflow process from both thermo-fluid dynamic and structural perspectives. Thermo-fluid dynamic results are coupled to a structural analysis tool to simulate the stresses and possible deformations during the reflow process. Thermo-fluid dynamic and structural simulation results were compared against the experimental test results done in the Nokia Factory in Oulu, Finland.","author":[{"family":"Ameli","given":"Alireza"},{"family":"Mäkeläinen","given":"Markus"},{"family":"Huttunen","given":"Jari"},{"family":"Frigerio","given":"Davide"},{"family":"Rydin","given":"Andreas"},{"family":"Qin","given":"Kelvin"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1109/itherm55375.2024.10709618","URL":"https://doi.org/10.1109/itherm55375.2024.10709618","source":"openalex"},{"id":"oa:W4316369089","type":"article-journal","title":"The Digital Twin Paradigm Applied to Soil Quality Assessment: A Systematic Literature Review","abstract":"This article presents the results regarding a systematic literature review procedure on digital twins applied to precision agriculture. In particular, research and development activities aimed at the use of digital twins, in the context of predictive control, with the purpose of improving soil quality. This study was carried out through an exhaustive search of scientific literature on five different databases. A total of 158 articles were extracted as a result of this search. After a first screening process, only 11 articles were considered to be aligned with the current topic. Subsequently, these articles were categorised to extract all relevant information, using the preferred reporting items for systematic reviews and meta-analyses methods. Based on the obtained results, there are two main conclusions to draw: First, when compared with industrial processes, there is only a very slight rising trend regarding the use of digital twins in agriculture. Second, within the time frame in which this work was carried out, it was not possible to find any published paper on the use of digital twins for soil quality improvement within a model predictive control context.","author":[{"family":"Silva","given":"Letícia"},{"family":"Rodríguezsedano","given":"Francisco"},{"family":"Baptista","given":"Paula"},{"family":"Coelho","given":"João"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/s23021007","URL":"https://doi.org/10.3390/s23021007","source":"openalex"},{"id":"oa:W4399433494","type":"article-journal","title":"Future of plasma etching for microelectronics: Challenges and opportunities","abstract":"Plasma etching is an essential semiconductor manufacturing technology required to enable the current microelectronics industry. Along with lithographic patterning, thin-film formation methods, and others, plasma etching has dynamically evolved to meet the exponentially growing demands of the microelectronics industry that enables modern society. At this time, plasma etching faces a period of unprecedented changes owing to numerous factors, including aggressive transition to three-dimensional (3D) device architectures, process precision approaching atomic-scale critical dimensions, introduction of new materials, fundamental silicon device limits, and parallel evolution of post-CMOS approaches. The vast growth of the microelectronics industry has emphasized its role in addressing major societal challenges, including questions on the sustainability of the associated energy use, semiconductor manufacturing related emissions of greenhouse gases, and others. The goal of this article is to help both define the challenges for plasma etching and point out effective plasma etching technology options that may play essential roles in defining microelectronics manufacturing in the future. The challenges are accompanied by significant new opportunities, including integrating experiments with various computational approaches such as machine learning/artificial intelligence and progress in computational approaches, including the realization of digital twins of physical etch chambers through hybrid/coupled models. These prospects can enable innovative solutions to problems that were not available during the past 50 years of plasma etch development in the microelectronics industry. To elaborate on these perspectives, the present article brings together the views of various experts on the different topics that will shape plasma etching for microelectronics manufacturing of the future.","author":[{"family":"Oehrlein","given":"GS"},{"family":"Brandstadter","given":"Stephan"},{"family":"Bruce","given":"Robert"},{"family":"Chang","given":"Jane"},{"family":"Demott","given":"Jessica"},{"family":"Donnelly","given":"Vincent"},{"family":"Dussart","given":"Rémi"},{"family":"Fischer","given":"Andreas"},{"family":"Gottscho","given":"Richard"},{"family":"Hamaguchi","given":"Satoshi"},{"family":"Honda","given":"M"},{"family":"Hori","given":"Masaru"},{"family":"Ishikawa","given":"Kenji"},{"family":"Jaloviar","given":"S"},{"family":"Kanarik","given":"Keren"},{"family":"Karahashi","given":"Kazuhiro"},{"family":"Ko","given":"Akiteru"},{"family":"Kothari","given":"H"},{"family":"Kuboi","given":"Nobuyuki"},{"family":"Kushner","given":"Mark"},{"family":"Lill","given":"Thorsten"},{"family":"Luan","given":"Pingshan"},{"family":"Mesbah","given":"Ali"},{"family":"Miller","given":"Eric"},{"family":"Nath","given":"Shoubhanik"},{"family":"Ohya","given":"Yoshinobu"},{"family":"Omura","given":"Mitsuhiro"},{"family":"Park","given":"Chan"},{"family":"Poulose","given":"John"},{"family":"Rauf","given":"Shahid"},{"family":"Sekine","given":"Makoto"},{"family":"Smith","given":"Taylor"},{"family":"Stafford","given":"Nathan"},{"family":"Standaert","given":"T"},{"family":"Ventzek","given":"Peter"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1116/6.0003579","URL":"https://doi.org/10.1116/6.0003579","source":"openalex"},{"id":"oa:W4391480459","type":"article-journal","title":"Virtual agri-food supply chains: A holistic digital twin for sustainable food ecosystem design, control and transparency","abstract":"The transition of Agri-Food Supply Chains (AFSC) toward sustainable patterns able to secure safe, quality, and affordable food whilst preserving natural and anthropogenic ecosystems is a key challenge of this century. Increasing production and distribution operations' transparency and impact visibility uncovers hidden complexities and the food ecosystem's externalities. To this attempt, this paper introduces a novel Agri-Food Supply Chain digital twin (AFSC-DT) able to virtualize the agricultural, processing, warehousing, and distribution operations holistically from-field-to-consumer and estimate economic, logistic, environmental, safety, and nutritional indicators associated with any food order, assumed as the functional unit. The AFSC-DT behaves as a control tower, providing a multi-dimensional dashboard of indicators and labels to enhance practitioners' and consumers' knowledge of FSC entities and operations. The practitioner's visibility drives top-down operational and tactical feedback controls through real-time monitoring and a-posteriori multi-dimensional performance analysis, whilst consumers, with their informed choices, perform a strategic bottom-up pressure on the food industry toward a sustainable redesign. A what-if simulation analysis conducted over four virtual scenarios within a regional horticultural AFSC proves how the AFSC-DT aids informed decision-making across the AFSC echelons, stimulating a virtuous cycle and favoring a progressive transition toward more sustainable patterns.","author":[{"family":"Guidani","given":"Beatrice"},{"family":"Ronzoni","given":"Michele"},{"family":"Accorsi","given":"Riccardo"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.spc.2024.01.016","URL":"https://doi.org/10.1016/j.spc.2024.01.016","source":"openalex"},{"id":"oa:W4393279079","type":"article-journal","title":"Personalized Diabetes Management with Digital Twins: A Patient-Centric Knowledge Graph Approach","abstract":"Diabetes management requires constant monitoring and individualized adjustments. This study proposes a novel approach that leverages digital twins and personal health knowledge graphs (PHKGs) to revolutionize diabetes care. Our key contribution lies in developing a real-time, patient-centric digital twin framework built on PHKGs. This framework integrates data from diverse sources, adhering to HL7 standards and enabling seamless information access and exchange while ensuring high levels of accuracy in data representation and health insights. PHKGs offer a flexible and efficient format that supports various applications. As new knowledge about the patient becomes available, the PHKG can be easily extended to incorporate it, enhancing the precision and accuracy of the care provided. This dynamic approach fosters continuous improvement and facilitates the development of new applications. As a proof of concept, we have demonstrated the versatility of our digital twins by applying it to different use cases in diabetes management. These include predicting glucose levels, optimizing insulin dosage, providing personalized lifestyle recommendations, and visualizing health data. By enabling real-time, patient-specific care, this research paves the way for more precise and personalized healthcare interventions, potentially improving long-term diabetes management outcomes.","author":[{"family":"Rad","given":"Fatemeh"},{"family":"Hendawi","given":"Rasha"},{"family":"Yang","given":"Xinyi"},{"family":"Li","given":"Juan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.3390/jpm14040359","URL":"https://doi.org/10.3390/jpm14040359","source":"openalex"},{"id":"oa:W4403145082","type":"article-journal","title":"Digital twin-based multi-granularity synchronisation for production-warehousing under batch processing mode","abstract":"Batch production is a cost-effective way that boosts efficiency in manufacturing systems. As customer demands become increasingly customised, there is a growing need to consolidate numerous small-batch orders. However, if batch production exceeds the optimal level, it may lead to the premature completion of customer orders, causing temporary congestion in the finished goods warehouse and prolonged resource occupation. Consequently, an essential focus of this study pertains to coordinating decision-making units like workshops and warehouses within batch production setups to ensure stable system operation amidst dynamic customer demands. The proposed solution encompasses a Digital Twin-based Multi-level Synchronised Control System (DTMCS) framework, featuring the Multi-granularity Synchronised Control Mechanism (MgSCM) and a collaborative optimisation model for batch production and warehouse planning. By examining a practical case study from a paint manufacturing company, the research delves into the effects of four synchronised control patterns on various system performance metrics, such as operating costs, equipment and warehouse utilisation rates, and system stability. Overall, this study provides an adaptable and cost-effective solution for enhancing production-logistics synchronisation.","author":[{"family":"Zhang","given":"Yongheng"},{"family":"Qu","given":"Ting"},{"family":"Li","given":"Mingxing"},{"family":"Zhang","given":"Zhongfei"},{"family":"Zhang","given":"Kai"},{"family":"Hong","given":"Zhicong"},{"family":"Huang","given":"George"},{"family":"Chen","given":"Zefeng"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1080/00207543.2024.2408671","URL":"https://doi.org/10.1080/00207543.2024.2408671","source":"openalex"},{"id":"oa:W4404168577","type":"article-journal","title":"Simulation-based Digital Twin for enhancing human-robot collaboration in assembly systems","abstract":"The advent of new technologies and paradigms such as the Internet of Things (IoTs), Digital Twin (DT), Human-Robot Collaboration (HRC), is offering immense opportunities to improve the performance of manufacturing systems, but also opening new challenges. The current scientific literature highlights the presence of numerous theoretical studies, but limited real-life applications, and the need to address interoperability issues, with the aim of valorizing the data continuously generated by humans, robots, machines. This research presents a novel simulation-based DT, designed for supporting HRC optimization in assembly systems. The proposed approach is tested and validated, through a case study in the automotive sector, specifically focusing on an assembly line for car front doors. The results show that it is possible to achieve HRC improvements through the assessment of different working configurations. Furthermore, it is explained how the simulation-based DT, by leveraging the FIWARE/FIROS paradigm, can effectively and efficiently interact with other systems, to enable real-time data exchange, which is nowadays one of the main open research challenges. • Assembly systems with Human-Robot Collaboration (HRC) and simulation based digital twin. • Simulation based digital twin supporting what-if analysis for HRC improvements. • Semantic and syntactic interoperability to enable real-time data exchange. • FIWARE/FIROS standards for interoperable communication between the real and digital world. • Real-life application belonging to an assembly line within the automotive sector.","author":[{"family":"Cimino","given":"Antonio"},{"family":"Longo","given":"Francesco"},{"family":"Nicoletti","given":"Letizia"},{"family":"Solina","given":"Vittorio"}],"issued":{"date-parts":[[2024]]},"DOI":"10.1016/j.jmsy.2024.10.024","URL":"https://doi.org/10.1016/j.jmsy.2024.10.024","source":"openalex"},{"id":"oa:W4323846877","type":"article-journal","title":"Analysis and Visualization of Production Bottlenecks as Part of a Digital Twin in Industrial IoT","abstract":"In the area of industrial Internet of Things (IIoT), digital twins (DTs) are a powerful means for process improvement. In this paper the concept of a DT is explained and analysis possibilities throughout the life-cycle of a product and its production system are explored. The main part of this paper is focused on an approach to the analysis of manufacturing layouts and their parameters. The approach, which is based on a state of the art bottleneck detection method, allows an intelligent representation of the temporal process characteristics. The presented method is widely applicable for any type of manufacturing layout and time-span. The use of elementary heuristics leads to traceable results that can be used for further analysis or optimization. The results of this analysis method can be integrated in a DT and combined with machine learning and explainable artificial intelligence (XAI). The concept for a self-learning DT is explained and implementation possibilities are elucidated.","author":[{"family":"Arff","given":"Benjamin"},{"family":"Haasis","given":"Julian"},{"family":"Thomas","given":"Jochen"},{"family":"Bonenberger","given":"Christopher"},{"family":"Höpken","given":"Wolfram"},{"family":"Stetter","given":"Ralf"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/app13063525","URL":"https://doi.org/10.3390/app13063525","source":"openalex"},{"id":"oa:W4366609676","type":"article-journal","title":"A review of reference architectures for digital manufacturing: Classification, applicability and open issues","abstract":"The industrial application of digital technologies in manufacturing can result in an increased efficiency of processes and an opportunity to integrate production, logistics and maintenance functions. However, increasingly interconnected manufacturing information means progressively more complex systems. Therefore, there is an ever growing need to provide structure in the design and development of such information systems which is the role of a system architecture. So called ‘reference architectures’ guide the design of system architectures used in particular applications. Reference architectures are models of information functions and their connections that provide a structured template with common terminology. Over the last decades, various reference architectures relevant to digital systems in manufacturing have been proposed. However, industrial applications of these reference architectures are scarce and it is difficult to compare and analyse them due to their various levels of application and different uses. In this study, we review and classify reference architectures used to support digital systems in manufacturing. Contributions of the paper include proposing criteria for a model to be referred to as a ‘reference architecture’, an overview and classification of the different perspectives on reference architectures in the literature, and a guideline to support practitioners, developers and academics in selecting a reference architecture.","author":[{"family":"Kaiser","given":"Jan"},{"family":"Mcfarlane","given":"Duncan"},{"family":"Hawkridge","given":"Gregory"},{"family":"André","given":"Pascal"},{"family":"Leitão","given":"Paulo"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1016/j.compind.2023.103923","URL":"https://doi.org/10.1016/j.compind.2023.103923","source":"openalex"},{"id":"oa:W4377968495","type":"article-journal","title":"Semantic Interoperability of Digital Twins: Ontology-based Capability Checking in AAS Modeling Framework","abstract":"Industry 4.0 currently prepares a major shift towards extreme flexibility into production lines management. Digital Twins are one of the key enabling technologies for Industry 4.0. However, the interoperability gap among digital representation of Industry 4.0 assets is still one of the obstacles to the development and adoption of digital twins. If the Asset Administration Shell (AAS), the standard proposed to represent the I4.0 components, caters for syntactic interoperability, a more semantic kind of interoperability is deeply needed to develop flexible and adaptable production lines. In our work, we overcome the limitation of current syntactic-only resource matching algorithms by implementing semantic interoperability based on ontologies i.e., by transforming AAS-based plant models into MaRCO (Manufacturing Resource Capability Ontology) instances and then query the expanded ontology to find the needed resources. This article presents this ontology-based approach as the first step towards the design and implementation of an automated I4.0 flexible plant supervision and control system based on model-driven engineering (MDE) within the “Papyrus for Manufacturing” toolset. We show how an MDE approach can aggregate around digital twin modeling tools from the Papyrus platform both I4.0 technologies and AI (Knowledge Representation and Reasoning) tools. Our platform aligns modeling and ontological elements to get the best of both worlds. This method has two main advantages: (1) to provide semantic descriptions for digital twin models, (2) to complement model-driven engineering tools with automated reasoning. This paper showcases this approach through a robotic cell use case.","author":[{"family":"Huang","given":"Yining"},{"family":"Dhouib","given":"Saadia"},{"family":"Medinacelli","given":"Luis"},{"family":"Malenfant","given":"Jacques"}],"issued":{"date-parts":[[2023]]},"DOI":"10.1109/icps58381.2023.10128003","URL":"https://doi.org/10.1109/icps58381.2023.10128003","source":"openalex"},{"id":"oa:W4380364197","type":"article-journal","title":"Digital Triplet: A Sequential Methodology for Digital Twin Learning","abstract":"A digital twin is a simulator of a physical system, which is built upon a series of models and computer programs with real-time data (from sensors or devices). Digital twins are used in various industries, such as manufacturing, healthcare, and transportation, to understand complex physical systems and make informed decisions. However, predictions and optimizations with digital twins can be time-consuming due to the high computational requirements and complexity of the underlying computer programs. This poses significant challenges in making well-informed and timely decisions using digital twins. This paper proposes a novel methodology, called the “digital triplet”, to facilitate real-time prediction and decision-making. A digital triplet is an efficient representation of a digital twin, constructed using statistical models and effective experimental designs. It offers two noteworthy advantages. Firstly, by leveraging modern statistical models, a digital triplet can effectively capture and represent the complexities of a digital twin, resulting in accurate predictions and reliable decision-making. Secondly, a digital triplet adopts a sequential design and modeling approach, allowing real-time updates in conjunction with its corresponding digital twin. We conduct comprehensive simulation studies to explore the application of various statistical models and designs in constructing a digital triplet. It is shown that Gaussian process regression coupled with sequential MaxPro designs exhibits superior performance compared to other modeling and design techniques in accurately constructing the digital triplet.","author":[{"family":"Zhang","given":"Xueru"},{"family":"Lin","given":"Dennis"},{"family":"Wang","given":"Lin"}],"issued":{"date-parts":[[2023]]},"DOI":"10.3390/math11122661","URL":"https://doi.org/10.3390/math11122661","source":"openalex"},{"id":"doi:10.15480/882.8938","type":"article-journal","title":"Optimizing raw material composition to increase sustainability in porcelain tile production: A simulation-based approach","abstract":"Reducing the environmental impact of porcelain tile production while maintaining cost-effectiveness is challenging. This work introduced a novel modeling approach for optimizing a standard composition range comprising kaolinite (15–38 wt.%), illite (0–20 wt.%), quartz (20–40 wt.%), and feldspar (20–45 wt.%) to establish a robust composition interval for porcelain stoneware tiles. The proposed study considers several factors, such as composition impact on the manufacturing sequence, production costs, and CO2 emission. A flowsheet simulation database was generated by coupling the Dyssol framework with MATLAB. This study investigated the influence of raw material composition within the process sequence, the total CO2 emissions, and production costs within the contexts of Spain and Brazil, two of the top five global producers. Granules with a higher proportion of talc and illite exhibit reduced moisture content after spray drying, and these combinations have lower green body porosity after compaction. The addition of talc allowed for decreased porosity content after compaction reduced firing temperature, and lowered costs and CO2 emissions despite the higher prices associated with talc. The proposed simulation methodology offers a powerful decision-making tool for optimizing raw material composition to minimize cost and CO2 emissions in the porcelain tile production. This methodology represents an early stride toward integrating digital twin methodologies within the ceramic tile sector, facilitating improved process regulation, and promoting the adoption of digital technologies.","author":[{"family":"Lourenco Alves","given":"Carine"},{"family":"Skorych","given":"Vasyl"},{"family":"Noni","given":"Agenor"},{"family":"Hotza","given":"Dachamir"},{"family":"Gómez González","given":"Sergio"},{"family":"Heinrich","given":"Stefan"}],"issued":{"date-parts":[[2024]]},"DOI":"10.15480/882.8938","URL":"https://doi.org/10.15480/882.8938","source":"datacite"}]