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(Ebook) Green Internet of Things and Machine Learning: Towards a Smart Sustainable World by Roshani Raut (editor), Sandeep Kautish (editor), Zdzislaw Polkowski (editor), Anil Kumar (editor), Chuan-Ming Liu (editor) ISBN 9781119792031, 1119792037

  • SKU: EBN-38381196
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$ 32 $ 40 (-20%)

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4.8

17 reviews
Instant download (eBook) Green Internet of Things and Machine Learning: Towards a Smart Sustainable World after payment.
Authors:Roshani Raut (editor), Sandeep Kautish (editor), Zdzislaw Polkowski (editor), Anil Kumar (editor), Chuan-Ming Liu (editor)
Pages:384 pages.
Year:2022
Editon:1
Publisher:Wiley-Scrivener
Language:english
File Size:8.74 MB
Format:epub
ISBNS:9781119792031, 1119792037
Categories: Ebooks

Product desciption

(Ebook) Green Internet of Things and Machine Learning: Towards a Smart Sustainable World by Roshani Raut (editor), Sandeep Kautish (editor), Zdzislaw Polkowski (editor), Anil Kumar (editor), Chuan-Ming Liu (editor) ISBN 9781119792031, 1119792037

Health Economics and FinancingEncapsulates different case studies where green-IOT and machine learning can be used for making significant progress towards improvising the quality of life and sustainable environment.The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier. Green Internet of Things and Machine Learninglays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare. AudienceThe book will be helpful for research scholars and researchers in the fields of computer science and engineering, information technology, electronics and electrical engineering. Industry experts, particularly in R&D divisions, can use this book as their problem-solving guide.
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