Recent Advances in Internet of Things and Machine Learning - Real-World Applications (Hardcover, 1st ed. 2022)

This book covers a domain that is significantly impacted by the growth of soft computing. Internet of Things (IoT)-related applications are gaining much attention with more and more devices which are getting connected, and they become the potential components of some smart applications. Thus, a global enthusiasm has sparked over various domains such as health, agriculture, energy, security, and retail. So, in this book, the main objective is to capture this multifaceted nature of IoT and machine learning in one single place. According to the contribution of each chapter, the book also provides a future direction for IoT and machine learning research. The objectives of this book are to identify different issues, suggest feasible solutions to those identified issues, and enable researchers and practitioners from both academia and industry to interact with each other regarding emerging technologies related to IoT and machine learning. In this book, we look for novel chapters that recommend new methodologies, recent advancement, system architectures, and other solutions to prevail over the limitations of IoT and machine learning.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Intelligent Systems Reference Library, 215
Release date:	February 2022
First published:	2022
Editors:	Valentina E. Balas • Vijender Kumar Solanki • Raghvendra Kumar
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	329
Edition:	1st ed. 2022
ISBN-13:	978-3-03-090118-9
Categories:	Books > Computing & IT > Computer hardware & operating systems > General Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	3-03-090118-1
Barcode:	9783030901189

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