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• Federated TinyML on ESP32: A Resource-Constrained Framework for IoT Health Monitoring
  crossref Chandan B Ram, Nirmala. M B, Swathi Papanna Gari 2026-01-22T20:58:23Z 置信度 0.66
• A Comprehensive Survey of TinyML Applications in Environmental Monitoring and Their Technical Challenges
  Environmental monitoring is essential for safeguarding ecosystems, ensuring public health, and supporting climate resilience. Traditional machine learning methods, while effective, often depend on cloud-based processing, resulting in high latency, increased en…
  crossref Sara Yarham, Mehran Behjati, Rosdiadee Nordin 2026-03-03T20:51:04Z 置信度 0.82 sustainabilitycomputer sciencecloud computingsoftware deploymentbusiness
• TinyML-based intrusion detection systems for sustainable and energy-constrained IoT devices
  • TinyML for IoT Security : Explores using Tiny Machine Learning (TinyML) for lightweight, energy-efficient intrusion detection on low-power IoT devices. • GraBoost-AAGT Model : Proposes a novel Gradient Boosting-based Adaptive Artificial Gorilla Troops (GraBo…
  crossref Amuthadevi C, Venkatesan R, Mythily M, Aroul Canessane R 2025-11-01T07:45:01Z 置信度 0.82 computer sciencecomputer and information sciencesmachine learningartificial intelligencecomputer security
• Efficient TinyML Inference on a Fault-Tolerant RISC-V SoC with Vector Extension
  Tiny machine learning (TinyML) enables low-power microcontrollers to run neural network inference locally, allowing real-time classification near the sensor with reduced latency and no reliance on external infrastructure. This is especially relevant in constra…
  crossref Carolina Imianosky, Douglas A. Santos, Luigi Dilillo 2025-08-19T18:08:08Z 置信度 0.82 artificial intelligencecomputer and information scienceselectrical engineering, electronic engineering, information engineeringmachine learningcs.lg
• Development of a Smart Classroom Monitoring System for Responsive and Adaptive Learning Using TinyML
  crossref Halleluyah Oluwatobi Aworinde, Abidemi Emmanuel Adeniyi, Joshua O. Opaleke, Aderonke B. Sakpere 等 2026-08-21T10:24:49Z 置信度 0.66
• EPC-TinyAD: An Energy- and Privacy-Aware Compressed TinyML Framework for Reliable Industrial Anomaly Detection on Resource-Constrained Edge Devices
  Real-time industrial anomaly detection is increasingly shifting from cloud-based diagnosis to edge intelligence deployed close to machines. However, practical industrial scenarios are constrained by scarce fault samples, unknown anomaly types, cross-machine di…
  crossref Yu Sun, Yihang Qin, Wenhao Chen, Wenhui Zhao 等 2026-07-01T10:41:01Z 置信度 0.82 computer and information sciencescomputer sciencemachine learningelectrical engineering, electronic engineering, information engineeringartificial intelligence
• TinyAP: A Smart Access Point to detect KRACK on WPA2 Handshake in Wi-Fi using TinyML
  Wi-Fi Protected Access 2 (WPA2) security protocol suite has been challenged by a recently discovered Key Reinstallation Attack (KRACK) that forces a supplicant to use an all zero-key for encryption. This has triggered the proposal of a new security protocol su…
  crossref Anand Agrawal, Rajib Ranjan Maiti 2025-02-20T20:05:58Z 置信度 0.82 computer and information sciencescs.lgcs.aicomputer scienceelectrical engineering, electronic engineering, information engineering
• Tinyml Models for Soh Estimation of Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy
  crossref Spyridon Giazitzis, Abdisamad ahmed Isse, Nicola Blasuttigh, Susheel Badha 等 2025-03-14T20:24:17Z 置信度 0.66
• A Novel One-Versus-All Approach for Multiclass Classification in TinyML Systems
  The recent progress in TinyML technologies triggers the need to address the challenge of balancing inference time and recognition quality. TinyML systems are defined by specific constraints in computation, memory and energy. These constraints emphasize the nee…
  crossref Tobiasz Puślecki, Krzysztof Walkowiak 2024-10-16T17:57:54Z 置信度 0.82 computer scienceartificial intelligencecs.lgcomputer and information sciencescryptography and security
• FERMI-ML: A Flexible and Resource-Efficient Memory-In-Situ SRAM Macro for TinyML Acceleration
  The growing demand for low-power and areaefficient TinyML inference on AIoT devices necessitates memory architectures that minimise data movement while sustaining high computational efficiency. This paper presents FERMI-ML, a Flexible and Resource-Efficient Me…
  crossref Mukul Lokhande, Akash Sankhe, S. V. Jaya Chand, Shivangi Mishra 等 2026-01-12T18:21:00Z 置信度 0.82 computer and information scienceselectrical engineering, electronic engineering, information engineeringcomputer sciencecryptography and securityinformation theory
• A TinyML Framework for Systolic Heart Murmur Classification Using Digital Phonocardiograms
  Early detection of abnormalities like heart murmurs is crucial because cardiovascular diseases are a major cause of death worldwide. Although automated murmur detection systems are available, they frequently lack the granularity necessary to distinguish betwee…
  crossref Adrian A. C. Alanes, Felipe A. P. de Figueiredo, Samuel B. Mafra 2026-04-16T19:50:24Z 置信度 0.82 artificial intelligencecomputer sciencemedicinecs.lgcs.ai
• TinyML-Powered Tack Weld Detection for Robotic Welding
  crossref Hizza Waseem, Di Wu, Eric Coatanéa, Joe David 2025-10-15T06:16:05Z 置信度 0.66
• Review for "<scp>TinyML</scp>‐Based Adaptive Pulse Shaping for Edge Intelligence in <scp>IoT</scp>/<scp>IIoT</scp>"
  crossref 2025-09-30T22:59:00Z 置信度 0.66
• Application of a temporal convolutional network algorithm fused with channel attention module for UWB indoor positioning.
  Ultra-wideband (UWB) technology offers considerable advantages for indoor positioning. However, its accuracy significantly decreases in non-line-of-sight environments, particularly in dynamic scenarios with frequent human movements. To address this challenge, …
  europepmc 2026 置信度 0.94 computer and information sciencescomputer scienceelectrical engineering, electronic engineering, information engineeringrobustnesscs.lg
• Graph Convolution Neural Network and Deep Q-Network Optimization-Based Intrusion Detection with Explainability Analysis.
  As networks expand in size and complexity, coupled with an exponential increase in intrusions on network and IoT systems, this leads to traditional models failing to capture increasingly intricate correlations among network components accurately. Graph Convolu…
  europepmc 2026 置信度 0.94 cs.lgcomputer sciencecomputer and information sciencessignal processingconvolutional neural network
• Trustworthy Cyber-Physical Edge-SHM Architecture for Operational Underground Tunnel Crack Monitoring Under Resource-Constrained Conditions.
  This study presents a low-cost edge-IoT-based structural health monitoring (SHM) architecture for crack monitoring in operational underground tunnels. The system integrates crack-displacement sensing, temperature measurement, ESP32-based edge processing, LoRa/…
  europepmc 2026 置信度 0.94 science policyscalabilitycomputer scienceenvironmental sciencecomputer and information sciences
• A multi-dimensional CNN-Bi-GRU for IoT-based brain-computer interface in early epileptic seizure detection.
  The study focuses on seizure detection using EEG data from Mendeley. An early-alert IoT-BCI system is designed to simulate real-time support for patients during seizures. The proposed Multi-Dimensional CNN-Bi-GRU (MDCBG) outperforms hybrid deep learning models…
  europepmc 2026 置信度 0.94 computer scienceartificial intelligenceconvolutional neural networkbrain-computer interfacedeep learning
• Dual-directional CIM-based non-volatile SRAM for instant-on/off energy-constrained edge AI devices.
  Compute-in-Memory (CIM) offers an efficient approach for accelerating DNNs by performing matrix–vector multiplications directly within memory. However, its adoption in edge devices is limited by unstable power supplies and the performance overhead of conventio…
  europepmc 2026 置信度 0.94 computer and information sciencescomputer scienceelectrical engineering, electronic engineering, information engineeringartificial neural networkcs.lg
• A data migration and integration approach for big data management using linked data.
  The growth in volume of heterogeneous data that are being created by web, IoT, and enterprise systems remains a major challenge to Big Data management, specifically, in the integration and migration of structured, semi-structured and unstructured data. Convent…
  europepmc 2026 置信度 0.84 computer sciencebig datadata sciencecloud computinginteroperability
• AI Methods in Sensor Calibration.
  Artificial intelligence (AI)-based methods are rapidly advancing the development of sensor technology, bringing about significant advancements for sensors in structural design/optimization, fabrication, calibration and application. The recent involvement of AI…
  europepmc 2026 置信度 0.94 computer sciencedata sciencecomputer and information sciencesnanotechnologymaterials science
• Explainable Deep Reinforcement Learning for Anomaly Detection in IoT-Enabled Metaverse Healthcare: Toward Trustworthy Cyber Threat Intelligence.
  The dynamic metaverse paradigm integrates emerging technologies and offers transformative opportunities to enhance consumer healthcare applications through immersive, connected experiences. However, this paradigm faces substantial cybersecurity challenges, suc…
  europepmc 2026 置信度 0.94 computer sciencecs.lgcomputer and information sciencescs.aiartificial intelligence
• Dynamic community detection using class preserving time series generation with Fourier Markov diffusion.
  Generating class-consistent time series necessitates the maintenance of both overarching structure and detailed temporal dynamics-an endeavor that current GAN and diffusion models find challenging. We introduce FMD-GAN, a Fourier-Markov diffusion framework tha…
  europepmc 2026 置信度 0.94 cs.aicomputer and information sciencespsychologyphysical sciencesindustry 4.0
• Respiratory Monitoring in Motion: An Overview of Wearable Methods and Algorithmic Approaches for Reliable Assessment.
  Advances in wearable device and sensor technologies progressively shift respiratory monitoring from the clinical setting to real-world conditions. This rapidly developing field allows for more accurate diagnostics. However, reliable monitoring during dynamic a…
  europepmc 2026 置信度 0.94 computer sciencewearable computerengineeringcomputer and information sciencesrobotics
• A Sparsity-Driven Backpropagation-Less Learning Framework Using Populations of Spiking Growth Transform Neurons.
  Growth-transform (GT) neurons and their population models allow for independent control over the spiking statistics and the transient population dynamics while optimizing a physically plausible distributed energy functional involving continuous-valued neural v…
  europepmc 2021 置信度 0.91 computer sciencecs.lgcomputer and information sciencesartificial neural networkcs.ne
• An Evolving TinyML Compression Algorithm for IoT Environments Based on Data Eccentricity.
  Currently, the applications of the Internet of Things (IoT) generate a large amount of sensor data at a very high pace, making it a challenge to collect and store the data. This scenario brings about the need for effective data compression algorithms to make t…
  europepmc Gabriel Signoretti, Marianne Silva, Pedro Andrade, Ivanovitch Silva 等 2021 置信度 0.91 computer sciencecomputer and information sciencesdata scienceelectrical engineering, electronic engineering, information engineeringartificial intelligence
• AI-driven routing and layered architectures for intelligent ICT in nanosensor networked systems.
  This review examines the emerging integration of nanosensor networks with modern information and communication technologies to address critical needs in healthcare, environmental monitoring, and smart infrastructure. It evaluates how machine learning and artif…
  europepmc 2026 置信度 0.94 computer scienceartificial intelligencedata sciencecloud computingsustainability
• The environmentally impacts of digital health.
  Digital health interventions are widely celebrated due to their low-cost nature and ability to provide tailored person-centred care in communities worldwide. As coronavirus disease-19 has rapidly accelerated their growth and reach, interest in global ethical q…
  europepmc 2021 置信度 0.91 psychological interventiondigital transformationhealth caremental healthsustainability
• From Biosignals to Bedside: A Review of Real-Time Edge Machine Learning for Wearable Health Monitoring.
  Wearable devices increasingly capture biosignals such as electrocardiograms, photoplethysmograms, inertial signals, and electrodermal activity during daily life, enabling earlier detection and continuous monitoring outside the clinic. Real-time edge machine le…
  europepmc 2026 置信度 0.94 computer sciencecomputer and information scienceswearable computerinterpretabilityelectrical engineering, electronic engineering, information engineering
• An Overview of Machine Learning within Embedded and Mobile Devices-Optimizations and Applications.
  Embedded systems technology is undergoing a phase of transformation owing to the novel advancements in computer architecture and the breakthroughs in machine learning applications. The areas of applications of embedded machine learning (EML) include accurate c…
  europepmc 2021 置信度 0.91 computer scienceartificial intelligencemachine learningcs.lgcomputer and information sciences
• A Novel Hybrid Deep Learning Model for Human Activity Recognition Based on Transitional Activities.
  In recent years, a plethora of algorithms have been devised for efficient human activity recognition. Most of these algorithms consider basic human activities and neglect postural transitions because of their subsidiary occurrence and short duration. However, …
  europepmc 2021 置信度 0.86 cs.lgartificial intelligenceconvolutional neural networkcomputer sciencecs.cv
• A Survey of AI-Enabled Predictive Maintenance for Railway Infrastructure: Models, Data Sources, and Research Challenges.
  Rail transport is central to achieving sustainable and energy-efficient mobility, and its digitalization is accelerating the adoption of condition-based maintenance (CBM) strategies. However, existing maintenance practices remain largely reactive or rely on li…
  europepmc 2026 置信度 0.94 engineeringcomputer scienceartificial intelligencedata sciencesustainability
• Toward Smart Railway Infrastructure Predictive and Optimised Maintenance Through Digital Twin (DT) System.
  Digital Twin (DT) technology is increasingly recognised as a promising approach for predictive and optimised railway maintenance; however, its current applications remain fragmented and lack systematic evaluation across railway domains. This study aims to crit…
  europepmc 2026 置信度 0.89 computer scienceengineeringdata scienceinteroperabilitymedicine
• Recent advances in the biosensing platforms for sepsis diagnosis.
  Sepsis is one of the major causes of mortality and organ losses due to the infections caused before or after hospitalization. According to the World Health Organization (WHO), 11 million people died from sepsis in 2020, which accounted for 20% of all deaths re…
  europepmc 2026 置信度 0.94 computer sciencenanotechnologydata sciencematerials sciencewearable computer
• Design Space Exploration of a Multi-Model AI-Based Indoor Localization System.
  In this paper, we present the results of a performance evaluation and optimization process of an indoor positioning system (IPS) designed to operate on portable as well as miniaturized embedded systems. The proposed method uses the Received Signal Strength Ind…
  europepmc 2022 置信度 0.91 cs.lgcs.aicomputer sciencecomputer and information scienceseess.sp
• An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation.
  A lightweight on-device liquid consumption estimation system involving an energy-aware machine learning algorithm is developed in this work. This system consists of two separate on-device neural network models that carry out liquid consumption estimation with …
  europepmc 2022 置信度 0.91 computer sciencecomputer and information scienceselectrical engineering, electronic engineering, information engineeringscalabilitysignal processing
• A Microservices-Based Solution with Hybrid Communication for Energy Management in Smart Grid Environments.
  The increasing variability of residential demand, combined with the expansion of distributed generation and electric vehicles, has introduced new challenges to the stability of Smart Grids (SGs). Centralized management models lack the flexibility required to o…
  europepmc 2026 置信度 0.94 computer sciencecomputer and information sciencesengineeringcomputer securityartificial intelligence
• Lightweight Deep Neural Network Embedded with Stochastic Variational Inference Loss Function for Fast Detection of Human Postures.
  Fusing object detection techniques and stochastic variational inference, we proposed a new scheme for lightweight neural network models, which could simultaneously reduce model sizes and raise the inference speed. This technique was then applied in fast human …
  europepmc 2023 置信度 0.91 cs.lgcomputer and information sciencesartificial neural networkartificial intelligencecs.ai
• Ready, Steady, Go AI: A practical tutorial on fundamentals of artificial intelligence and its applications in phenomics image analysis.
  High-throughput image-based technologies are now widely used in the rapidly developing field of digital phenomics and are generating ever-increasing amounts and diversity of data. Artificial intelligence (AI) is becoming a game changer in turning the vast seas…
  europepmc 2021 置信度 0.91 computer sciencedata sciencebig datafieldworkflow
• Machine Learning for Healthcare Wearable Devices: The Big Picture.
  Using artificial intelligence and machine learning techniques in healthcare applications has been actively researched over the last few years. It holds promising opportunities as it is used to track human activities and vital signs using wearable devices and a…
  europepmc 2022 置信度 0.91 computer sciencenanotechnologywearable computerdata sciencehealth care
• Deep Neural Architectures for Contrast Enhanced Ultrasound (CEUS) Focal Liver Lesions Automated Diagnosis.
  Computer vision, biomedical image processing and deep learning are related fields with a tremendous impact on the interpretation of medical images today. Among biomedical image sensing modalities, ultrasound (US) is one of the most widely used in practice, sin…
  europepmc 2021 置信度 0.91 artificial intelligencecomputer sciencedeep learningconvolutional neural networkcomputer and information sciences
• A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People.
  Population ageing is a growing global trend. It was estimated that by 2050, people over 60 years of age will represent 35% of the population in industrialised countries. This context demands strategies that incorporate technologies, such as fall detection syst…
  europepmc 2025 置信度 0.94 computer sciencedata sciencehealth caremedicineartificial intelligence
• TinyDevID: TinyML-Driven IoT Devices IDentification Using Network Flow Data
  IoT device identification is often used as the first line of defense. However, it is challenging due to the acquisition of IoT as a business by the existing vendors of traditional computing devices, making it difficult to adopt identifiers based on IP or MAC a…
  crossref Priyanka Rushikesh Chaudhary, Anand Agrawal, Rajib Ranjan Maiti 2025-02-20T20:05:58Z 置信度 0.82 computer and information sciencescomputer scienceartificial intelligencecs.lgcs.cl
• TinyML: Deploying Machine Learning on Microcontrollers for IoT Applications
  The rapid proliferation of Internet of Things (IoT) devices has created an urgent need for intelligent data processing directly on resource-constrained hardware. Tiny Machine Learning (TinyML) addresses this challenge by enabling the deployment of machine lear…
  crossref Ron Wainbuch, Akinniyi James Samuel 2026-02-16T18:17:44Z 置信度 0.82 computer scienceartificial intelligencecomputer and information sciencescloud computinginternet of things
• Dispositivo IoT para prevenir la violencia de género usando TinyML
  El estudio se enmarca en el desarrollo de una solución basada en el Internet de las Cosas (IoT) y el aprendizaje automático para prevenir y detectar situaciones de peligro relacionadas con la Violencia basada en el Género (VBG). El objetivo es proporcionar una…
  crossref Mónica Tamara Avila Rodríguez, Elsa Marina Quizhpe Buñay, Wilson Gustavo Chango Sailema, Stalin Arciniegas 2023-12-21T23:00:31Z 置信度 0.79 philosophypolitical scienceinternet of thingslarge language modelsphysical sciences
• Smart Plant Watering Using TinyML: Water Savings through Predictive Control
  Indoor plant watering is not always effective - people often overwater or underwater plants, wasting water and harming plant health. In view of this, a smart watering system using artificial intelligence that runs on a tiny microcontroller chip has been develo…
  crossref Roman Korostenskyi, Igor Olenych 2025-12-04T16:35:22Z 置信度 0.82 environmental sciencepetroleum engineeringecosystemenvironmental resource managementeess.as
• CycloWatt: An Affordable, TinyML-Enhanced IoT Device Revolutionizing Cycling Power Metrics
  Cycling power measurement is an indispensable metric with profound implications for cyclists' performance and fitness levels. It empowers riders with realtime feedback, supports precise training regimen planning, mitigates injury risks, and enhances muscular d…
  crossref Victor Luder, Sizhen Bian, Michele Magno 2024-06-28T17:53:14Z 置信度 0.82 computer and information sciencescomputer scienceelectrical engineering, electronic engineering, information engineeringcs.aiartificial intelligence
• Redesigning Transportation Cyber-Physical Systems: Enhancing Connectivity and Bolstering Security Using TinyML
  The rapid evolution of Transportation Cyber-Physical Systems (TCPS) necessitates secure, efficient, and real-time data processing capabilities to support autonomous and intelligent transportation networks. However, existing machine learning-based security fram…
  crossref Ankita Sharma, Shalli Rani 2025-07-21T18:10:09Z 置信度 0.82 computer and information sciencescomputer scienceartificial intelligencecs.aielectrical engineering, electronic engineering, information engineering
• Evaluating the performance of TinyML singular and ensemble techniques for intrusion detection in IoT networks
  crossref Abderahmane Hamdouchi, Ali Idri 2025-06-03T11:14:45Z 置信度 0.66
• Context‐Aware <scp>TinyML</scp> Model for Korean Handwriting Recognition Under Online Assisted Learning Scenes
  ABSTRACT Optical character recognition (OCR) based on wearable devices plays an important role in online learning. Although the existing convolutional recurrent neural network (CRNN) has achieved great success in the task of optical character recognition (OCR)…
  crossref Shunji Cui 2025-01-22T00:36:16Z 置信度 0.82 computer sciencecs.lgcomputer and information sciencesartificial intelligenceconvolutional neural network
• Lightweight Onboard AI for Mars Rovers: A TinyML Approach to Environmental Prediction
  The growing sophistication of autonomous Mars operations has necessitated intelligent onboard systems that can respond to the harsh and unpredictable Martian environmental conditions. Remote control and delayed processing are no longer efficient enough for rea…
  crossref Neharika Kotamaraju, Priyashree P., K.R.M. Vijaya Chandrakala 2026-02-23T20:46:45Z 置信度 0.82 computer sciencecomputer and information sciencesroboticscs.lgsoftware deployment
• Intelli-Helmet: An IoT, Edge-AI, and TinyML-Based Real-Time Soldier Health and Threat Monitoring System with Novel Panic Tactile Switch Mechanism
  crossref Fatima Ashraf, Iftiak Ahmed, M. Akhtaruzzaman, Md Rashid Ul Islam 等 2026-06-05T09:02:07Z 置信度 0.66
• Towards Predicting Inference Latency of TinyML Models
  The proliferation of tinyML models in embedded devices demands not only resource-efficient execution but also latency-optimized inference for real-time applications, enabling latency as a critical decision-making factor for Neural Architecture Search (NAS). In…
  crossref Jyotishman Sarkar, Urmi Jana, Barnali Basak, Himadri Sekhar Paul 等 2025-08-13T17:27:03Z 置信度 0.82 computer and information sciencescs.aics.dcsignal processingelectrical engineering, electronic engineering, information engineering
• TinyML for Acoustic Anomaly Detection in IoT Sensor Networks
  Tiny Machine Learning enables real-time, energyefficient data processing directly on microcontrollers, making it ideal for Internet of Things sensor networks. This paper presents a compact TinyML pipeline for detecting anomalies in environmental sound within I…
  crossref Amar Almaini, Jakob Folz, Ghadeer Ashour 2025-12-15T18:36:10Z 置信度 0.82 computer sciencecomputer and information sciencescs.lgelectrical engineering, electronic engineering, information engineeringartificial intelligence
• Real-Time Fault Detection in Induction Motors Using TinyML: An Evaluation of the Edge Impulse Platform
  This article evaluates the Edge Impulse platform for developing TinyML-based fault detection models in induction motors, focusing on identifying broken rotor bars using vibration data collected from the motor casing. The study aims to assess the platform’s cap…
  crossref João Pedro B Lima 2025-08-19T18:07:54Z 置信度 0.82 computer scienceedge computingartificial intelligenceartificial neural networkcomputer and information sciences
• HAC-M-DNN: Hardware Aware Compression of Sustainable Multimodal Deep Neural Networks for Efficient TinyML Deployment
  The increasing complexity and energy consumption of advanced artificial intelligence algorithms pose a significant challenge to environmental sustainability. This paper addresses this issue by introducing HAC-M-DNN, a system designed for energy-efficient tinyM…
  crossref Hasib-Al Rashid, Eiman Kanjo, Tinoosh Mohsenin 2025-06-12T17:39:36Z 置信度 0.82 computer and information sciencescomputer scienceartificial intelligencecs.aics.lg
• On-device Deep Learning for Recognizing 3D Geometric Shapes in an Educational App Using the TinyML Paradigm
  Currently, deep learning (DL) algorithms perform best in image classification and object detection tasks. Consequently, they are frequently used to address most problems involving computer vision. In this sense, the pervasive presence of smartphones and IoT de…
  crossref André Ramos, Roberto Oliveira, Manoel Campos Neto 2026-01-21T13:43:30Z 置信度 0.82 computer scienceartificial intelligencecs.lgcomputer and information sciencescs.ai
• Neck Health Detection System with TinyML MCU
  This study investigates the impact of prolonged forward head posture on cervical spine health due to excessive use of 3C products (computer, communication, and consumer electronics). This paper proposed a wearable device integrating AI edge computing to monito…
  crossref Chun-Hung Yang, Zheng-Huan Jiang, Ming-Wei Hsu, Jiun-Fan Chen 2025-10-27T17:53:54Z 置信度 0.82 electrical engineering, electronic engineering, information engineeringsignal processingcomputer and information scienceswearable computeredge computing
• <scp>TinyML</scp> ‐Driven On‐Device Sports Command Recognition in Mobile and Dynamic Environments
  ABSTRACT In this article, we propose a novel TinyML‐based framework for real‐time sports command recognition under mobile conditions. Unlike conventional Human Activity Recognition (HAR) systems that rely on cloud‐based processing or heavy on‐device models, ou…
  crossref Jiali Zang 2025-07-15T05:04:51Z 置信度 0.82 computer and information sciencescs.lgelectrical engineering, electronic engineering, information engineeringcomputer sciencecs.ai
• Low‐Power Physiological Fatigue Monitoring via <scp>TinyML</scp> ‐Enabled Wearables for Sports Evaluation
  ABSTRACT In the context of the growing integration of Internet of Things (IoT) and edge intelligence into sports technology, the ability to accurately monitor athlete fatigue in real time has become increasingly important for performance optimization and injur…
  crossref Yuqiu Zhang 2025-07-22T11:25:14Z 置信度 0.82 computer sciencecomputer and information sciencescloud computinginternet of thingselectrical engineering, electronic engineering, information engineering
• Edge Computing Enables Assessment of Student Community Building: An Emotion Recognition Method Based on <scp>TinyML</scp>
  ABSTRACT Deep network‐based video sentiment analysis is crucial for online evaluation tasks. However, these deep models are difficult to run on intelligent edge devices with limited computing resources. In addition, video data are susceptible to lighting inter…
  crossref Shuo Liu 2025-02-26T09:30:02Z 置信度 0.82 computer scienceartificial intelligencecomputer and information sciencescs.lgcs.cv
• A Survey of the First TinyML@ICCAD Contest for Ventricular Arrhythmia Detection by Artificial Intelligence on Low-power Microprocessor
  Artificial intelligence has achieved remarkable success in various real-world applications. However, the challenge lies in its implementation on hardware platforms with constrained resources and low power while maintaining real-time capabilities. Edge artifici…
  crossref Guoqing Li, Jingwei Zhang, Meng Zhang, Tinghuan Chen 等 2026-05-18T11:04:05Z 置信度 0.82 computer sciencecs.masystems engineeringcloud computingkey
• TinyML: Accelerometer-Based Processing for Seismic Detection in Buildings
  During emergencies, fast and accurate situational awareness of building collapses supports critical decisions that can save human lives. To tackle this problem, we develop a compact on-device learning model (TinyML) that infers seismic activity from accelerome…
  crossref Marwane Rezzouki, Kaoutar El Hina, Guillaume Terrasson 2026-03-24T19:45:47Z 置信度 0.82 computer and information sciencescs.lgcomputer scienceartificial intelligencecs.cl
• Edge-Intelligent Wearable IoT for Real-Time Stress Monitoring and Indoor Localization: A TinyML-Enabled Adaptive RPL Approach
  The growing demand for digital health solutions, continuous monitoring, and indoor location awareness has accelerated the growth of wearable IoT systems. However, real-time analytics and low-latency communication operations are still challenging in resource-co…
  crossref Hariprasath Madhalingam, Naganathan Meyyappan Ramesh, Aadhil Ahamed Jaffarullah, Bharath Shanmugavel 等 2026-08-06T19:13:39Z 置信度 0.82 computer sciencecomputer and information scienceselectrical engineering, electronic engineering, information engineeringcloud computingwearable computer
• Optimized TinyML Models based on Efficient Knowledge Distillation for Textures Classification
  Deploying neural networks on embedded tactile sensing systems is constrained by limited computational and memory resources. This work presents a Knowledge Distillation (KD)–based optimization framework to improve deployment efficiency on such platforms. A pret…
  crossref Sara Awada, Hiba Al Youssef, Zeinab Hijazi, Ali Ibrahim 2025-12-09T18:31:34Z 置信度 0.82 computer and information sciencescs.lgcs.aicryptography and securitycomputer science
• Avaliação de Algoritmos de Compressão de Séries Temporais Multivariadas com TinyML em Dispositivos Embarcados
  A transmissão contínua de dados em aplicações automotivas no contexto de Internet das Coisas (IoT) enfrenta desafios relacionados à largura de banda e consumo energético. Neste cenário, o TinyML — a aplicação de modelos de aprendizado de máquina em dispositivo…
  crossref Morsinaldo Medeiros, Hagi Costa, Marianne Silva, Ivanovitch Silva 2025-06-26T13:05:32Z 置信度 0.82 philosophypopulationai safetyai governancemulti-agent systems
• TinyML Empowering Intelligent Edge Devices
  Tiny Machine Learning (TinyML) bridges the gap between artificial intelligence and low-power embedded systems, enabling devices like microcontrollers to process data locally and operate autonomously. This chapter explores the foundational principles of TinyML,…
  crossref Helen K. Joy, Electa Alice Jayarani, R. Sridevi 2025-08-08T19:01:18Z 置信度 0.82 computer sciencetransformative learningdata scienceartificial intelligencebusiness
• Review for "&lt;scp&gt;TinyML&lt;/scp&gt;‐Based Adaptive Pulse Shaping for Edge Intelligence in &lt;scp&gt;IoT&lt;/scp&gt;/&lt;scp&gt;IIoT&lt;/scp&gt;"
  crossref 2025-09-30T22:59:00Z 置信度 0.66
• IoT device for detecting abnormal vibrations in motors using TinyML
  This paper presents an innovative approach to motor bearing fault detection using TinyML on an IoT device. We developed a system that integrates spectral analysis and deep learning on a resource-constrained edge device, enabling real-time monitoring and anomal…
  crossref Stalin Arciniegas, Dulce Rivero, Jefferson Piñan, Elizabeth Diaz 等 2025-04-16T17:36:46Z 置信度 0.82 computer sciencecomputer and information sciencesdata scienceartificial intelligencemachine learning
• A Compact Dual-IMU Fall Detection Model for TinyML Deployment at Low Sampling Rates
  Falls in the elderly pose a significant health risk, necessitating reliable, real-time detection systems suitable for efficient operation on wearable devices. This paper introduces a lightweight fall detection solution employing dual IMUs at the waist and thig…
  crossref Duan Luong-Cong, Minh Nguyen-Ngoc 2025-09-09T17:29:46Z 置信度 0.82 computer and information scienceselectrical engineering, electronic engineering, information engineeringsignal processingroboticsartificial intelligence
• Steganographic Blockchain for Covert Communication: Hashing Tactical Data in Noisy Channels with TinyML
  crossref Divyanshu Kumar, Ranjan Yengkhom, Jitesh Choudhary 2026-03-06T20:58:41Z 置信度 0.66
• Low-Power TinyML CNN Accelerator using Integrated Clock Gating for Edge Devices
  In this work, a compact low-power convolutional neural network (CNN) hardware accelerator is developed for TinyML-based edge AI systems. The design applies integrated clock gating (ICG) using Synopsys EDA tools, where gating decisions are guided by real switch…
  crossref Shashi Kant Dargar, Akash, Antony Fedrick, Avinash Kumar 2026-01-14T20:37:30Z 置信度 0.82 computer and information scienceselectrical engineering, electronic engineering, information engineeringcs.neconvolutional neural networkphysical sciences
• TinyML-Based Hazardous Gas Detection for Intelligent Personal Protective Equipment
  The increasing integration of artificial intelligence (AI) into safety-critical systems has given rise to innovative approaches for real-time monitoring of a variety of dangerous conditions in personal protective equipment (PPE) [1]. In various sectors, such a…
  crossref Celina Kudrin-Gusten, Michael Kuhl, Valentin Barth, Hang Yu 2026-01-23T20:55:09Z 置信度 0.82 computer scienceartificial intelligencecs.lgenvironmental sciencecs.ai
• TinyML for Computation-aware Transformer-based Anomaly Detection in Internal Combustion Systems
  This paper proposes a highly accurate, computation-efficient anomaly detection for an industrial internal combustion engine using a Transformer model. The proposed anomaly detection model enables identifying anomaly occurrences and quan-tifying how far the abn…
  crossref Iman Sharifirad, Jalil Boudjadar, Peter Gorm Larsen 2025-02-19T18:39:17Z 置信度 0.82 computer and information scienceselectrical engineering, electronic engineering, information engineeringcryptography and securitysystems and controleess.sy
• Hardware-efficient tractable probabilistic inference for TinyML Neurosymbolic AI applications
  Neurosymbolic AI (NSAI) has recently emerged to mitigate limitations associated with deep learning (DL) models, e.g. quantifying their uncertainty or reason with explicit rules. Hence, TinyML hardware will need to support these symbolic models to bring NSAI to…
  crossref Jelin Leslin, Martin Trapp, Martin Andraud 2025-08-22T23:57:49Z 置信度 0.82 computer and information sciencesmachine learningcs.lgcs.aielectrical engineering, electronic engineering, information engineering
• Embedded AI: Integrating TinyML in Resource-Constrained IoT Devices
  This paper presents a targeted benchmarking study on model size reduction for deploying Tiny Machine Learning (TinyML) on resource-constrained Internet of Things (IoT) devices. Through systematic experiments on a convolutional neural network, we quantitatively…
  crossref Amel A. Triesh, Nuredin Ali Salem Ahmed 2026-04-16T19:51:19Z 置信度 0.82 computer sciencecomputer and information sciencesartificial intelligencecs.lgcs.ai
• Review for "&lt;scp&gt;TinyML&lt;/scp&gt;‐Based Adaptive Pulse Shaping for Edge Intelligence in &lt;scp&gt;IoT&lt;/scp&gt;/&lt;scp&gt;IIoT&lt;/scp&gt;"
  crossref 2025-09-30T22:59:00Z 置信度 0.66
• A Survey of Model Compression Techniques for TinyML Applications
  The convergence of embedded systems and artificial intelligence has led to the rapid growth of TinyML, which enables ML inference on highly resource-constrained devices. However, deploying modern DL models in these environments poses signif-icant challenges du…
  crossref Ismail Lamaakal, Chaymae Yahyati, Ibrahim Ouahbi, Khalid El Makkaoui 等 2025-09-05T18:04:40Z 置信度 0.82 computer sciencecomputer and information sciencesedge computingdata sciencesoftware deployment
• Federated TinyML for Lightweight Anomaly Detection in IoMT Using MQTT-Enabled Edge Deployment
  crossref Vaibhav Gollapalli, Seema G. Aarella, Saraju P. Mohanty, Elias Kougianos 2026-05-01T19:51:31Z 置信度 0.66
• Smart Cattle Behavior Sensing with Embedded Vision and TinyML at the Edge
  Accurate real-time monitoring of cattle behavior is essential for enabling data-driven decision-making in precision livestock farming. However, existing monitoring solutions often rely on cloud-based processing or high-power hardware, which are impractical for…
  crossref Jazzie R. Jao, Edgar A. Vallar, Ibrahim Hameed 2025-12-19T08:45:28Z 置信度 0.82 computer sciencecomputer and information sciencesartificial intelligencecs.lgelectrical engineering, electronic engineering, information engineering
• TinyML vs LLMs: A Survey of Extreme Scales in Machine Learning
  ML now works with an unmatched range of computational scales, from microcontrollers with models that are only a few kilobytes big to cloud infrastructures with Large Language Models (LLMs) that have trillions of parameters. These extremes show how AI has made …
  crossref Ismail Lamaakal, Chaymae Yahyati, Khalid El Makkaoui, Yassine Maleh 等 2025-12-15T18:36:56Z 置信度 0.82 computer scienceartificial intelligencecs.aisoftware deploymentsustainability
• TinyHAR-Net: Design and Implementation of a TinyML-Based Human Activity Recognition Framework on STM32
  Deploying high-performing and resource-efficient human activity recognition (HAR) models on microcontrollers (MCUs) remains a significant challenge due to severe limitations in memory and computational capacity. While methods like quantization and pruning can …
  crossref Imran Hossan, Mst. Nusratul Jannat Mary, Mohammod Abdul Motin 2025-12-03T18:42:29Z 置信度 0.82 computer and information sciencescs.aics.lgelectrical engineering, electronic engineering, information engineeringmachine learning
• Avaliação do Impacto de DP-SGD em Modelos Otimizados com Tinyml
  Os modelos de aprendizado profundo (MAP) são aplicados na detecção de ataques e anomalias em redes IoT. O paradigma tiny machine learning (tinyml) viabiliza a execução local desses modelos com baixo consumo de recursos e maior privacidade. No entanto, MAPs ain…
  crossref Davi Bezerra Yada da Silva, Aldri Luiz dos Santos, Jeandro de M. Bezerra 2025-09-11T13:10:33Z 置信度 0.82 philosophypolitical sciencegeographyenergynatural language processing
• Sensitivity Analysis Exploration of ML Architectures to TinyML Techniques
  TinyML techniques, such as pruning and quantization, enable the deployment of machine learning (ML) models on resource-constrained embedded devices by reducing computational and memory demands. However, the impact of these techniques varies across different ML…
  crossref Iman Sharifirad, Jalil Boudjadar, Manuel Roveri, Peter Gorm Larsen 2025-09-16T17:32:27Z 置信度 0.82 computer and information sciencescomputer sciencemachine learningcryptography and securityelectrical engineering, electronic engineering, information engineering
• TinyML-driven Sensor Nodes for Energy-efficient Acoustic Event Detection in Pervasive Acoustic WSNs
  The process of sensing and transmitting acoustic signals by pervasive acoustic wireless sensor networks (PAWSNs) poses considerable energy challenges. These problems may be mitigated by filtering only relevant acoustic events from the sensor network. By reduci…
  crossref Bibek B. Roy, Sushovan Das, Uttam Kr. Mondal 2025-06-18T06:02:00Z 置信度 0.82 computer and information scienceselectrical engineering, electronic engineering, information engineeringcomputer sciencesignal processingcs.lg
• Arquitetura Embarcada com TinyML e Modelos Linguísticos para Monitoramento Veicular Inteligente
  Resumo-A Internet das Coisas (IoT) no contexto automotivo impulsiona o desenvolvimento de soluções embarcadas que realizam inferência local e comunicação em tempo real.Nesse cenário, técnicas como TinyML, que executa modelos de aprendizado de máquina em dispos…
  crossref Rejanio Moraes, Morsinaldo Medeiros, Fellipe Nogueira, Marianne Silva 等 2025-10-04T21:58:23Z 置信度 0.82 philosophyedge computingworklarge language modelsmulti-agent systems
• A TinyML Approach for the Classification of Bean Crop Diseases
  Modern agriculture has enabled food production for nearly eight billion people, yet plant diseases and climate change continue to threaten food security. Beans, a key nutritional crop worldwide, are vulnerable to diseases such as bean rust and angular leaf spo…
  crossref Mir Hassan, Wamiq Raza, Varvara Fadeeva, Leonardo Lucio Custode 等 2025-09-30T17:36:40Z 置信度 0.82 computer and information sciencescs.lgcs.cvelectrical engineering, electronic engineering, information engineeringcs.ai
• A Literature Review on Model Conversion, Inference, and Learning Strategies in EdgeML with TinyML Deployment
  Edge Machine Learning (EdgeML) and Tiny Machine Learning (TinyML) are fast-growing fields that bring machine learning to resource-constrained devices, allowing real-time data processing and decision-making at the network’s ... | Find, read and cite all the res…
  crossref Muhammad Arif, Muhammad Rashid 2025-03-11T03:12:21Z 置信度 0.80 artificial intelligencemachine learningdeep learningedge computingbig data
• Toward Neuromorphic TinyML for Efficient Visual Perception
  The rapid growth of edge computing applications in robotics, wearable devices, autonomous systems, and IoT has driven a critical demand for energy-efficient and low-latency visual perception capabilities. Traditional deep learning models, though effective, oft…
  crossref Ismail Lamaakal, Chaymae Yahyati, Ibrahim Ouahbi, Khalid El Makkaoui 等 2025-12-09T18:31:34Z 置信度 0.82 computer sciencecomputer and information sciencesartificial intelligenceneuromorphic engineeringcs.lg
• Deep Learning Model for Firearm Detection Based on Tinyml and Edgeia Architectures in Smart Cities
  crossref Sergio Sanchez, Camilo Baldovino, Carlos Arias, Bryan Restrepo 等 2026-01-23T20:55:06Z 置信度 0.66
• Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure
  With the growing need for real-time processing on IoT devices, optimizing machine learning (ML) models' size, latency, and computational efficiency is essential. This paper investigates a pruning method for anomaly detection in resourceconstrained environments…
  crossref Fatemeh Dehrouyeh, Ibrahim Shaer, Soodeh Nikan, Firouz Badrkhani Ajaei 等 2025-09-26T17:34:55Z 置信度 0.82 computer and information sciencesmachine learningelectrical engineering, electronic engineering, information engineeringsignal processingcomputer science
• AirMouse-3D: An On-Device TinyML Inertial Mouse for Table-Free Desktop Interaction
  Humans prefer unconstrained, free-space movement—so why must the mouse stay on a tabletop? This paper presents the design and development of a novel three-dimensional (3D) motion-based mouse that operates without a surface, built around the Arduino Nano 33 BLE…
  crossref Kavya Shah, Priyam Parikh 2025-09-28T07:28:51Z 置信度 0.82 computer and information sciencesroboticselectrical engineering, electronic engineering, information engineeringhuman-computer interactioncomputer science
• AgriSense - smart rain prediction and automated irrigation with TinyML
  crossref J. Chinna Babu, G. Sujatha, M. Upesh Rayudu, C. Yaswanth Krishna 等 2025-11-14T13:05:12Z 置信度 0.66
• TinyML Unleashed: Accelerating TensorFlow Lite Micro Kernels with RISC-V Vector Extension
  The widespread use of machine learning on embedded devices has intensified the demand for efficient inference acceleration. The RISC-V Instruction Set Architecture (ISA) integrates vector extensions that provide advanced data-processing capabilities to address…
  crossref Ahmed Mahmoudi, Christopher Horn, Saleh Mulhem, Rainer Buchty 等 2026-01-02T18:15:33Z 置信度 0.82 cs.lgcomputer and information sciencescryptography and securitynetworking and internet architecturestat.ml
• Enabling Secure Edge Intelligence: TinyML-Based Threat Detection in 5G and Future Networks
  The evolution of 5G networks toward 6G presents an opportunity to shift from centralized security to decentralized, intelligent, and autonomous security. While 5G introduces decentralization through software-based virtualization and edge computing, it also exp…
  crossref Sandeep Pirbhulal, Muhammad Muzammal, Habtamu Abie 2025-12-24T18:47:49Z 置信度 0.82 computer and information sciencescomputer scienceelectrical engineering, electronic engineering, information engineeringcs.aics.lg
• Low-Cost IoT and TinyML for Offline Early Chronic Disease Risk Identification in African Communities
  In Africa, at least 41% deaths are a result of chronic diseases such as Cardiovascular diseases, Diabetes mellitus and Hypertension. Still, early detection is not easy, particularly in poorer communities with scarce resources, laboratories, technology, and som…
  crossref Kayongo Johnson Brian, Marvin Ogore 2026-01-19T20:52:59Z 置信度 0.82 computer sciencecs.lgartificial intelligencecomputer and information sciencesmedicine
• Sistema de Análise Preditiva em Tempo Real para Smart Meters usando Machine Learning Embarcado (TinyML)
  Este trabalho apresenta o desenvolvimento de um protótipo de sistema de análise preditiva em tempo real para medidores inteligentes, utilizando TinyML no ESP32 para prever o consumo de energia e detectar anomalias. Foram coletados dados reais de uma geladeira …
  crossref Jones Nambundo, Otavio Gomes 2026-05-21T17:24:16Z 置信度 0.82 philosophyworkpolitical sciencematerials sciencetaxonomy
• A Low-Power Low-cost System for Disaster Locations Detection using ESP32 CAM and TinyML
  This paper presents a low-cost, low-power solution for real-time natural disaster or calamity location detection using the ESP32 CAM, a GPS module, and TinyML. By overlaying calamity locations on open-source street maps, our system improves user interaction wi…
  crossref Riya Samanta, Bidyut Saha, Soumya K. Ghosh 2025-02-20T15:05:58Z 置信度 0.82 computer and information sciencescs.cvelectrical engineering, electronic engineering, information engineeringcs.lgeess.iv
• TinyML—From Efficient Edge Inference to On-Device Intelligence
  crossref Theocharis Theocharides, Marian Verhelst, Vijay Janapa Reddy, Evgeni Gousev 2025-08-20T18:43:19Z 置信度 0.66
• TinyML Based Biometric Authentication Using PPG Signals for Edge Devices
  crossref Yogeswar Reddy Thota, Jeffrey Scott Nixon, Bhavya Chandran, Tooraj Nikoubin 2025-06-27T09:58:23Z 置信度 0.66
• Tinyml-Empowered Climbing Robots for Real-Time Structural Defect Detection: Case Studies on Bolt and Tile Inspection
  Structural inspection of critical infrastructure presents significant safety challenges when performed manually, particularly for bolt connections in steel structures and exterior wall tiles. This paper presents an innovative approach integrating Tiny Machine …
  crossref Tzu-Hsuan Lin 2025-08-19T18:06:18Z 置信度 0.82 artificial intelligencecomputer sciencecomputer and information sciencesroboticsunderwater