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Scrivener Publishing 100 Cummings Center, Suite 541J Beverly, MA 01915-6106
Publishers at Scrivener Martin Scrivener ([email protected]) Phillip Carmical ([email protected])
Machine Learning Approaches for Convergence of IoT and Blockchain
Edited by
Krishna Kant Singh
Faculty of Engineering & Technology, Jain (Deemed-to-be University), Bengaluru, India
Akansha Singh
Amity University Uttar Pradesh, Noida, India
and
Sanjay Sharma
KIET Group of Institutions, Delhi-NCR, Ghaziabad, India
This edition first published 2021 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA
© 2021 Scrivener Publishing LLC
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Library of Congress Cataloging-in-Publication Data
ISBN 978-1-119-76174-7
Cover image: Pixabay.Com
Cover design Russell Richardson
Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines Printed in the USA
10 9 8 7 6 5 4 3 2 1
Preface
Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. And although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning.
A rapidly advancing fourth industrial revolution, brought about by a digital revolution characterized by the convergence of technologies, is blurring the lines between physical, digital and biological objects. The speed of the fourth revolution, which is evolving at an exponential rate, certainly cannot be compared with that of any previous technologies. Some of these technologies include the artificial intelligence (AI) and IoT currently being used in interactions and operations in various fields such as home appliances, autonomous vehicles, nanotechnology, robotics, cognitive systems and wearable devices; and nowadays the potential of blockchain technology is also being realized in many sectors as well, since security is a crucial factor everywhere.
Readers in many domains will be interested in this book as it covers two major areas of the field of machine learning—blockchain technology and the IoT. Also, it will be appealing for those who want to further their research in this area, as the latest topics are covered. Therefore, the target audience of this book is composed of professionals and researchers working in the field of machine learning with IoT and blockchain technology. Moreover, the book will provide insights and support from practitioners and academia in order to highlight the most debated aspects in the field. A detailed description of each topic relevant to machine learning technologies is presented along with the concepts involved in their convergence. In addition, research problems are included to facilitate further research based on the concepts described in the
