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Recent advances in Tiny Machine Learning (TinyML) empower low-footprint embedded devices for real-time on-device Machine Learning (ML). While many acknowledge the potential benefits of TinyML, its practical implementation presents unique challenges. This study…
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Vignesh Kumar M, Sathis Kumar N R, Mariyam Jasmine S A, Pathma Sri S 等
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Animal invasion is one of the major threats observed recent times in the agricultural lands. This is due to the extension of farm lands to feed the increasing population. There is a need to control this animal invasion without harming the living animals. Hence…
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A rise in Urbanisation has vastly increased the number of environmental issues related to urban living, including, most significantly, Noise Pollution, which is now seen as a major Public Health Threat to the residents of contemporary urban centres. Numerous s…
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Hamed F. Langroudi, Vedant Karia, Tej Pandit, Becky Mashaido 等
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The rapid expansion of the Internet of Things (IoT) has driven a shift toward distributed intelligence, where interconnected devices generate and process large-scale data in real time. Traditional cloud-centric architectures face limitations including high lat…
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The automatic recognition of animal vocalizations is a valuable tool for monitoring pigs’ behavior, health, and welfare. This study investigates the feasibility of implementing a convolutional neural network (CNN) model for classifying pig vocalizations using …
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This article studies the merits of applying log-gradient input images to convolutional neural networks (CNNs) for tinyML computer vision (CV). We show that log gradients enable: (i) aggressive 1-bit quantization of first-layer inputs, (ii) potential CNN resour…
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Abstract Stroke rehabilitation requires repetitive, consistent physical therapy to restore upper-limb motor function. However, traditional supervised therapy is resource-intensive and often inaccessible for home-based recovery. This paper presents a low-cost, …
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Jan Stenkamp, Mathis Hunke, Cem Karatas, Steffen Kirchhoff 等
2026-05-08T14:20:14Z
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The Internet of Things (IoT) has made it possible to include everyday objects in a connected network, allowing them to intelligently process data and respond to their environment. Thus, it is expected that those objects will gain an intelligent understanding o…
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Precision agriculture and sustainable farming practices require autonomous environmental monitoring systems capable of operating in remote areas with limited energy and connectivity. However, the high cost of existing professional technology remains a signific…
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2023-12-08T02:51:53Z
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2026-02-06T20:52:44Z
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2024-05-07T13:28:30Z
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On-device artificial intelligence has attracted attention globally, and attempts to combine the internet of things and TinyML (machine learning) applications are increasing. Although most edge devices have limited resources, time and energy costs are important…
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Artificial Intelligence (AI) and Machine Learning (ML) have experienced rapid growth in both industry and academia. However, the current ML and AI models demand significant computing and processing power to achieve desired accuracy and results, often restricti…
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Internet of Things devices are frequently used as consumer devices to provide digital solutions, such as smart lighting and digital voice-activated assistants, but they are also employed to alert residents in the instance of an emergency. Given the increasingl…
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TinyML enables the deployment of machine learning models on low-power embedded devices, offering energy-efficient solutions for real-world applications. However, TinyML faces significant challenges due to strict memory, processing, and energy constraints, maki…
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