Machine Learning Adoption in Blockchain-Based Intelligent Manufacturing: Theoretical Basics, Applications, and Challenges (Intelligent Manufacturing and Industrial Engineering)

207 Pages·2022·7.924 MB·English

by  Om Prakash Jena (editor), Sabyasachi Pramanik (editor), Ahmed A. Elngar (editor)

Machine Learning
Adoption in Blockchain-
Based Intelligent
Manufacturing
T his book looks at industry change patterns and innovations (such as artif cial
intelligence, machine learning, big data analysis, and blockchain support and
eff ciency technology) that are speeding up industrial transformation, industrial
infrastructure, biodiversity, and productivity.
This book focuses on real-world industrial applications and case studies to
provide for a wider knowledge of intelligent manufacturing. It also offers insights
into manufacturing, logistics, and supply chain, where systems have undergone
an industrial transformation. It discusses current research of machine learning
along with blockchain techniques that can f ll the gap between research and
industrial exposure. It goes on to cover the effects that the Fourth Industrial
Revolution has on industrial infrastructures and looks at the current industry
change patterns and innovations that are accelerating industrial transformation
activities.
R esearchers, scholars, and students from different countries will appreciate this
book for its real-world applications and knowledge acquisition. This book targets
manufacturers, industry owners, product developers, scientists, logistics, and supply
chain engineers.
• F ocuses on real-world industrial applications and case studies to provide
for a wider knowledge of intelligent manufacturing
• O ffers insights into manufacturing, logistics, and supply chain where
systems have undergone an industrial transformation
• D iscusses current research of machine learning along with blockchain
techniques that can f ll the gap between research and industrial exposure
• C overs the effects that the 4th Industrial Revolution has on industrial
infrastructures
• Looks at industry change patterns and innovations that are speeding up
industrial transformation activities
Om Prakash Jena is currently working as an associate professor in the Department
of Computer Science, Ravenshaw University, Cuttack, Odisha, India.
Sabyasachi Pramanik is an assistant professor in the Department of Computer
Science and Engineering, Haldia Institute of Technology, India.
Ahmed A. Elngar is an associate professor in the Faculty of Computers & Artif cial
Intelligence, Beni-Suef University, Egypt. He is also an associate professor in the
College of Computer Information Technology, chair of the Scientif c Innovation
Research Group (SIRG), and director of the Technological and Informatics Studies
Center (TISC), American University in the Emirates, United Arab Emirates.
Mathematical Engineering, Manufacturing, and
Management Sciences
Series Editor: Ahmed A. Elngar, Beni-Suef
Uni. Mohamed Elhoseny, Mansoura University, Egypt
Machine Learning Adoption in Blockchain-Based
Intelligent Manufacturing
Theoretical Basics, Applications, and Challenges
Edited by Om Prakash Jena, Sabyasachi Pramanik,
Ahmed A. Elngar
For more information about this series, please visit: https://www.routledge.com/
Mathematical-Engineering-Manufacturing-and-Management-Sciences/book-series/
CRCIMIE

Machine Learning
Adoption in Blockchain-
Based Intelligent
Manufacturing
Theoretical Basics, Applications,
and Challenges
Edited by
Om Prakash Jena, Sabyasachi Pramanik,
and Ahmed A. Elngar
First edition published 2022
by CRC Press
6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487–2742
and by CRC Press
4 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN
CRC Press is an imprint of Taylor & Francis Group, LLC
© 2022 selection and editorial matter, Om Prakash Jena, Sabyasachi Pramanik, Ahmed A.
Elngar; individual chapters, the contributors
All rights reserved. No part of this book may be reprinted or reproduced or utilised
in any form or by any electronic, mechanical, or other means, now known or hereafter
invented, including photocopying and recording, or in any information storage or retrieval
system, without permission in writing from the publishers.
Trademark notice : Product or corporate names may be trademarks or registered trademarks and
are used only for identif cation and explanation without intent to infringe.
I SBN: 978-1-032-17153-1 (hbk)
I SBN: 978-1-032-17154-8 (pbk)
I SBN: 978-1-003-25200-9 (ebk)
DOI: 10.1201/9781003252009
T ypeset in Times
b y Apex CoVantage, LLC
Contents
Preface. ......................................................................................................................ix
Editors .................................................................................................................... xiii
Chapter 1 Integration of Big Data, Machine Learning, and Blockchain
Technology ...........................................................................................1
S adia Showkat and Shaima Qureshi
Chapter 2 Blockchain in Digital Libraries: State of the Art, Trends,
and Challenges ................................................................................... 17
P ramod Kumar Hota, Lopamudra Hota,
and Prasant Kumar Dash
Chapter 3 An Integration of Blockchain and Machine Learning
into the Health Care System ............................................................... 33
M ahita Sri Arza and Sandeep Kumar Panda
Chapter 4 Blockchain for the Industrial Internet of Things ................................59
R oheen Qamar and Fareed Jokhio
Chapter 5 Security Measures for Blockchain Technology ..................................79
S atpal Singh Kushwaha, Amit Kumar Bairwa, Sandeep
Chaurasia, Vineeta Soni, and Venkatesh Gauri Shankar
Chapter 6 An Analysis of Data Management in Industry 4.0
Using Big Data Analytics ...................................................................95
J yoti Khandelwal and Jyoti Anand
Chapter 7 Exploring Role of Industry 4.0 Techniques for Building a
Promising Circular Economy Concept: Manufacturing
Industry Perspective ......................................................................... 111
R . Adimuthu, K. Muduli, M. Ray, S. Singh, and T. S. T. Ahmad
vii
viii Contents
Chapter 8 Comparative Analysis of Blockchain-Based Consensus
Algorithms for Suitability in Critical IoT Infrastructures ................ 125
Sadia Showkat and Shaima Qureshi
Chapter 9 Quantum Machine Learning and Big Data for Real-Time
Applications: A Review .................................................................... 143
Shruti Pophale and Amit Gadekar
Chapter 10 Sensors-Based Automatic Human Body Detection and
Prevention System to Avoid Entrapment Casualties inside
a Vehicle ..................................................................................................157
Suraj Arya, Raman, Sanjay, and Preeti Sharma
Chapter 11 A Mechanism to Protect Decentralized Transaction Using
Blockchain Technology .................................................................... 171
A jay B Gadicha, Vijay B Gadicha, and Om Prakash Jena
I ndex ...................................................................................................................... 187
Preface
The idea of intelligent manufacturing is closely linked to the computerization of
manufacturing and the development of the necessary skills for the new workforce to
benef t from high-paying employment. Several innovations, such as the Internet of
Things (IoT), machine learning, big data analytics, and blockchain technology, are
now considered critical components of industry growth and deployment. Technical
advancements in the ability to effectively collect, transfer, and analyze vast amounts
of data are at the forefront of this trend. Smart manufacturing is a concept that refers
to the use of emerging technology to create smart factories that can quickly adapt
and react to changes in customer demand for high-quality products.
With the IoT, machine learning, data processing, and blockchain technology,
industrial transformation will be more sustainable. These reforms mark the begin-
ning of a movement toward fully integrated and automated growth, management,
and regulatory frameworks. Many businesses tend to be aware of the change and are
focusing on how it will affect their business; many others are changing things and
investing for the future, where their business is escalating through smart machines
with intelligence techniques. Industry transformation using the intelligent manufac-
turing concept is the so-called Fourth Industrial Revolution in manufacturing, logis-
tics, and supply chain management of distinct and structures; the chemical industry;
resource use; transportation; utilities; gas and oil; mining and metals; and other sec-
tors, such as the mineral industries, health care, medical products, sustainable devel-
opment, waste management, and energy optimization.
This book looks at industry change patterns and innovations (such as artif cial
intelligence, machine learning, big data analysis, and blockchain value chain support
and eff ciency technology) that are speeding up industrial transformation, industrial
infrastructure, biodiversity, and productivity.
I ntelligent manufacturing systems are evolving in response to an increasing num-
ber of requests for equipment reliability and quality prediction. To that end, a variety
of machine learning methods are being investigated. Data protection and manage-
ment is another topic that is becoming increasingly relevant in the industry. It entails
the use of cyber-physical devices, facilities, and processes in smart factories to facili-
tate decision-making. It improves f exibility, protection, cost savings, eff ciency, and
prof tability by automating and optimizing operations. Blockchain technology based
on machine learning is groundbreaking in terms of data security, delivery, fault tol-
erance, and transparency.
C hapter 1 describes the integration of blockchain technology and machine learn-
ing to make information and communication technology infrastructures robust,
decentralized, and secure with intelligent data analytics and eff cient network opera-
tion and management. The challenges and main issues are described before imple-
menting the integration.
C hapter 2 explores the concepts, structures, and the applications of blockchain
in digital libraries. The decentralized aspect of blockchain and its data-intensive
ix