Green internet of things and machine learning : towards a smart sustainable world /
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...
Saved in:
Other Authors: | |
---|---|
Format: | Electronic eBook |
Language: | English |
Published: |
Hoboken, NJ : Beverly, MA :
Wiley ; Scrivener Publishing,
2022.
|
Subjects: | |
Online Access: | CONNECT |
MARC
LEADER | 00000nam a2200000 a 4500 | ||
---|---|---|---|
001 | in00006303579 | ||
006 | m o d | ||
007 | cr |n||||||||| | ||
008 | 220114s2022 nju ob 001 0 eng d | ||
005 | 20240124155037.0 | ||
020 | |a 9781119793144 | ||
020 | |a 1119793149 |q (electronic bk. : oBook) | ||
020 | |a 9781119793120 |q (electronic bk.) | ||
020 | |a 1119793122 |q (electronic bk.) | ||
020 | |z 1119792037 | ||
020 | |z 9781119792031 | ||
024 | 7 | |a 10.1002/9781119793144 |2 doi | |
035 | |a (NhCcYBP)e80fa363d91f485b9a695405a0a7a4bb9781119793144 | ||
035 | |a 1wileyeba9781119793144 | ||
040 | |a NhCcYBP |b eng |c NhCcYBP | ||
050 | 4 | |a TK5105.8857 |b .G74 2022 | |
082 | 0 | 4 | |a 004.67/8 |2 23 |
245 | 0 | 0 | |a Green internet of things and machine learning : |b towards a smart sustainable world / |c edited by Roshani Raut [and more]. |
260 | |a Hoboken, NJ : |b Wiley ; |a Beverly, MA : |b Scrivener Publishing, |c 2022. | ||
300 | |a 1 online resource | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
500 | |a Wiley EBA |5 TMurS | ||
505 | 0 | |a Front Matter -- G-IoT and ML for Smart Computing / Karunendra Verma, Vineet Raj Singh Kushwah, Nilesh -- Machine Learning-Enabled Techniques for Reducing Energy Consumption of IoT Devices / Yogini Dilip Borole, Jaya Dofe, C G Dethe -- Energy-Efficient Routing Infrastructure for Green IoT Network / Pradeep Bedi, S B Goyal, Jugnesh Kumar, Shailesh Kumar -- Green IoT Towards Environmentally Friendly, Sustainable and Revolutionized Farming / Ravi Manne, Sneha Chowdary Kantheti -- CIoT: Internet of Green Things for Enhancement of Crop Data Using Analytics and Machine Learning / Sahana Shetty, Narayana Swamy Ramaiah -- Smart Farming Through Deep Learning / Sandeep Mathur, Disha Vaid, Ajay Rana -- Green IoT and Machine Learning for Agricultural Applications / Keshavi Nalla, Seshu Vardhan Pothabathula -- IoT-Enabled AI-Based Model to Assess Land Suitability for Crop Production / Aneesha Gudavalli, G JayaLakshmi, Suneetha Manne -- Green Internet of Things (GIoT): Agriculture and Healthcare Application System (GIoT-AHAS) / Anil L Wanare, Sahebrao N Patil -- Green IoT for Smart Transportation: Challenges, Issues, and Case Study / Pradnya Borkar, Vijaya Balpande, Ujjwala Aher, Roshani Raut, M Sulas Borkar -- Green Internet of Things (IoT) and Machine Learning (ML): The Combinatory Approach and Synthesis in the Banking Industry / Prakashkumar Hasmukhbhai Patel, Chetan K Rathod, Karan Zaveri -- Green Internet of Things (G-IoT) Technologies, Application, and Future Challenges / Saxena Komal, Basit Abdul, Vinod Kumar Shukla -- Index | |
504 | |a Includes bibliographical references and index. | ||
588 | 0 | |a Online resource; title from PDF title page (John Wiley, viewed February 10, 2022). | |
520 | |a 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 Learning lays 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. | ||
650 | 0 | |a Internet of things. | |
650 | 0 | |a Machine learning. | |
700 | 1 | |a Raut, Roshani, |d 1981- |e editor. | |
730 | 0 | |a WILEYEBA | |
776 | 0 | 8 | |c Original |z 1119792037 |z 9781119792031 |
856 | 4 | 0 | |u https://ezproxy.mtsu.edu/login?url=https://onlinelibrary.wiley.com/book/10.1002/9781119793144 |z CONNECT |3 Wiley |t 0 |
949 | |a ho0 | ||
975 | |p Wiley UBCM Online Book All Titles thru 2023 | ||
976 | |a 6006612 | ||
998 | |a wi |d z | ||
999 | f | f | |s e18e998f-985d-4e14-a2a6-5107232a3ca3 |i 54f2284e-b330-40cc-bd6f-831149da6910 |t 0 |
952 | f | f | |a Middle Tennessee State University |b Main |c James E. Walker Library |d Electronic Resources |t 0 |e TK5105.8857 .G74 2022 |h Library of Congress classification |