TinyML for edge intelligence in IoT and LPWAN networks /
This book, 'TinyML for Edge Intelligence in IoT and LPWAN Networks', explores the integration of Tiny Machine Learning (TinyML) with Edge Intelligence in the context of the Internet of Things (IoT) and Low-Power Wide-Area Networks (LPWAN). Edited by Bharat S. Chaudhari, Sheetal N. Ghorpade...
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| Autres auteurs: | |
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| Format: | Électronique eBook |
| Langue: | anglais |
| Publié: |
London ; San Diego, CA :
Academic Press, an imprint of Elsevier,
[2024]
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| Sujets: | |
| Accès en ligne: | ScienceDirect |
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| Résumé: | This book, 'TinyML for Edge Intelligence in IoT and LPWAN Networks', explores the integration of Tiny Machine Learning (TinyML) with Edge Intelligence in the context of the Internet of Things (IoT) and Low-Power Wide-Area Networks (LPWAN). Edited by Bharat S. Chaudhari, Sheetal N. Ghorpade, Marco Zennaro, and others, it delves into key topics such as the constraints and requirements of LPWAN, challenges of edge AI, TinyML principles and algorithms, and the application of neural networks in low-power devices. The book also covers reinforcement learning for LoRaWANs, software frameworks, energy modeling, and the role of TinyML in emerging technologies such as 5G and smart cities. It is designed for researchers, professionals, and academics interested in the latest advancements in efficient edge computing and IoT technologies. |
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| Description matérielle: | 1 online resource |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 0443222037 9780443222030 |