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Energy-Efficient Deep Learning Approaches in IoT, Fog, and Green Blockchain Revolution
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Condizione: New. In. Codice articolo ria9798337303000_new
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Energy-Efficient Deep Learning Approaches in IoT, Fog, and Green Blockchain Revolution
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9798337303000
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Energy-Efficient Deep Learning Approaches in IoT, Fog, and Green Blockchain Revolution
Da: PBShop.store US, Wood Dale, IL, U.S.A.
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9798337303000
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Energy-Efficient Deep Learning Approaches in IoT, Fog, and Green Blockchain Revolution
Print on DemandDa: AHA-BUCH GmbH, Einbeck, Germania
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Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The convergence of Internet of Things (IoT), fog computing, and blockchain technology can be used to revolutionize energy efficiency and sustainability. The implementation of deep learning (DL) techniques may optimize the energy consumption of these interconnected systems. Thus, they can be used to create green, energy-efficient solutions for various industries, including smart cities, healthcare, finance, and industrial IoT (IIoT). Focusing on the energy efficiency and environmental impact of these technologies, they provide valuable insights into creating sustainable and scalable systems. Energy-Efficient Deep Learning Approaches in IoT, Fog, and Green Blockchain Revolution bridges the knowledge gap between traditional IoT and blockchain research and the emerging need for energy-efficient and green technologies. It influences future research directions, encourages collaboration across disciplines, and inspires innovations that prioritize sustainability. Covering topics such as software-defined networking (SDN), ecosystem conservation, and monitoring systems, this book is an excellent resource for computer scientists, policymakers, technologists, industry practitioners, engineers, environmentalists, sustainability advocates, professionals, researchers, scholars, academicians, and more. Codice articolo 9798337303000
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