Industrial Internet of Things (IIoT)

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Scrivener Publishing100 Cummings Center, Suite 541J Beverly, MA 01915-6106

Advances in Learning Analytics for Intelligent Cloud-IoT Systems

Series Editors: Dr. Souvik Pal and Dr. Dac-Nhuong Le

Scope:The role of adaptation, learning analytics, computational Intelligence, and data analytics in the field of Cloud-IoT Systems is becoming increasingly essential and intertwined. The capability of an intelligent system depends on various self-decision making algorithms in IoT Devices. IoT based smart systems generate a large amount of data (big data) that cannot be processed by traditional data processing algorithms and applications. Hence, this book series involves different computational methods incorporated within the system with the help of Analytics Reasoning and Sense-making in Big Data, which is centered in the Cloud and IoT-enabled environments.

The series seeks volumes that are empirical studies, theoretical and numerical analysis, and novel research findings. The series encourages cross-fertilization of highlighting research and knowledge of Data Analytics, Machine Learning, Data Science, and IoT sustainable developments.

Please send proposals to:

Dr. Souvik Pal

Department of Computer Science & Engineering

Sister Nivedita University

(Techno India Group)

Kolkata, India

souvikpal22@gmail.com

Dr. Dac-Nhuong Le

Faculty of Information Technology, Haiphong University, Haiphong, Vietnam nhuongld@hus.edu.vn

Publishers at Scrivener Martin Scrivener ( martin@scrivenerpublishing.com) Phillip Carmical ( pcarmical@scrivenerpublishing.com)

Edited by

R. Anandan

Suseendran Gopalakrishnan

Souvik Pal

and

Noor Zaman

This edition first published 2022 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

© 2022 Scrivener Publishing LLC

For more information about Scrivener publications please visit www.scrivenerpublishing.com.

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Library of Congress Cataloging-in-Publication Data

ISBN 978-1-119-76877-7

Cover image: Pixabay.ComCover design by 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

It is with immense pleasure that we introduce this book on intelligent analytics for predictive maintenance through the industrial internet of things (IIoT), with the objective of fostering advancements and disseminating results concerning recent applications in the field.

Since the internet of things (IoT) dominates all sectors of technology, from home to industries, automation through IoT devices is remarkably changing the processes of our daily lives. For example, more and more businesses are adopting and accepting industrial automation on a large scale, with the market for industrial robots expected to reach 73.5 billion US dollars by 2023. The primary reason for adopting IoT industrial automation in businesses is the benefits it provides, including enhanced efficiency, high accuracy, cost-effectiveness, quick process completion, low power consumption, fewer errors, and ease of control. Therefore, every smart entrepreneur undoubtedly has the vision of automating office processes to match the latest technological innovations. However, it is not so easy to use these same innovations to automate industrial processes. Which is why the IIoT, a key element of a smart factory, was created to bring together modern cloud computing, the IoT, and AI to design intelligent, self-optimizing industrial equipment and facilities.

Since engineers, both current and future, need systematic training in industrial automation in order to keep up with and advance the rapidly evolving field of applied control technologies, expert systems with IoT capabilities make for more versatile and innovative handling of problems. However, since security of both physical devices and administration applications is basic to the activity of the IoT and is imperative for its success, this book was designed to provide students with an opportunity to explore knowledge concerning the security frameworks of the IoT that are dependent on new specialized norms. Therefore, new security plans are discussed which highlight these new norms.