Edited by
Muhammad A. Imran, Sajjad Hussain and Qammer H. Abbasi
James Watt School of Engineering
University of Glasgow
UK
This edition first published 2020
© 2020 John Wiley & Sons Ltd
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.
The right of Muhammad A. Imran, Sajjad Hussain and Qammer H. Abbasi to be identified as the authors of the editorial material in this work has been asserted in accordance with law.
Registered Office(s)
John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA
John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester,West Sussex, PO19 8SQ, UK
Editorial Office
The Atrium, Southern Gate, Chichester,West Sussex, PO19 8SQ, UK
For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.
Wiley also publishes its books in a variety of electronic formats and by print-on-demand. Some content that appears in standard print versions of this book may not be available in other formats.
Limit of Liability/Disclaimer of Warranty
MATLAB® is a trademark of The MathWorks, Inc. and is used with permission. The MathWorks does not warrant the accuracy of the text or exercises in this book. This work's use or discussion of MATLAB® software or related products does not constitute endorsement or sponsorship by The MathWorks of a particular pedagogical approach or particular use of the MATLAB® software.
In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of experimental reagents, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each chemical, piece of equipment, reagent, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions.While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
Library of Congress Cataloging‐in‐Publication data applied for
HB ISBN: 9781119552611
Cover Design: Wiley
Cover Images: © Guryanov Andrey/Shutterstock
Hasan T. Abbas
James Watt School of Engineering
University of Glasgow
UK
Muhammad Mahtab Alam
Thomas Johann Seebeck
Department of Electronics
Tallinn University of Technology
Estonia
Akram Alomainy
School of Electronic Engineering and Computer Science
Queen Mary University of
London
UK
Ramy Amer
CONNECT Centre for Future
Networks
Trinity College Dublin
Ireland
Anas Amjad
Staffordshire University
UK
Gennaro Boggia
Department of Electrical and
Information Engineering
Politecnico di Bari
Italy
M. Majid Butt
Nokia Bell Labs
France
and
CONNECT Centre for Future
Networks
Trinity College Dublin
Ireland
Luigi Alfredo Grieco
Department of Electrical and
Information Engineering
Politecnico di Bari
Italy
Mona Jaber
School of Electronic Engineering
and Computer Science
Queen Mary University of
London
UK
Alar Kuusik
Thomas Johann Seebeck
Department of Electronics
Tallinn University of Technology
Estonia
Yannick Le Moullec
Thomas Johann Seebeck
Department of Electronics
Tallinn University of Technology
Estonia
Hassan Malik
Thomas Johann Seebeck
Department of Electronics
Tallinn University of Technology
Estonia
Nicola Marchetti
CONNECT Centre for Future
Networks
Trinity College Dublin
Ireland
Zhen Meng
James Watt School of Engineering
University of Glasgow
UK
Sven Pärand
Telia Estonia Ltd.
Estonia
João Pedro Battistella Nadas
James Watt School of Engineering
University of Glasgow
UK
Metin Ozturk
James Watt School of Engineering
University of Glasgow
UK
Mohsin Raza
Faculty of Science and
Technology
Middlesex University
UK
Aifeng Ren
James Watt School of Engineering
University of Glasgow
UK
Huan X. Nguyen
Faculty of Science and
Technology
Middlesex University
UK
Hafiz Husnain Raza Sherazi
Department of Electrical and
Information Engineering
Politecnico di Bari
Italy
Richard Demo Souza
Universidade Federal de Santa
Catarina‐Florianópolis
Brazil
Adnan Zahid
James Watt School of Engineering
University of Glasgow
UK
Guodong Zhao
James Watt School of Engineering
University of Glasgow
UK
Ahmed Zoha
James Watt School of Engineering
University of Glasgow
UK
Over the past three centuries, industrial processes have evolved from steam operated mechanical looms (industry 1.0), electrically run machines (industry 2.0) to programmable logic controller (PLC) based manufacturing (industry 3.0). However, in the 21st century, we are talking about the industrial revolution through to industry 4.0. Industry 4.0 is about digitizing all industrial processes and making them intelligent, efficient and autonomous through sensing, connectivity, big data analytics, and control. With advancements in enabling technologies, industrial processes are likely to build further on industry 4.0, resulting in even smarter manufacturing solutions.
Besides the technical challenges, the industrial revolution will face challenges like overhauling of company culture, and hiring and training people with appropriate skills to run the digital processes. Moreover, the companies will need to develop new business models in order to maximize their outputs and take full advantage of the industrial revolution.
With regards to the technical challenges, cybersecurity is an extremely important issue since any sort of cyber attack could result in financial as well as human loss. Interoperability is another important aspect that has to be ensured in the form of the use of open source software and solutions, privacy and accessibility.
The key enablers for industrial revolution are advanced electronics and information and communication technologies (ICT), e.g. energy‐efficient sensing, cloud and mobile‐edge computing, reliable and low latency communication, big data analytics through machine learning and artificial intelligence, and the Industrial Internet of Things (IIoT).
To enable flexible and scalable connectivity solutions for industry 4.0, the role of wireless automation is pivotal. To achieve industrial wireless automation there are stringent requirements of low latency and high reliability in the presence of harsh industrial environments. Specifically, to enable industrial revolution, the end‐to‐end latency should be less than 0.5 ms while the reliability requirements of 10–9 or even less block error ratio (BLER).
To address these issues, the fifth generation of mobile communications (5G) proposes meeting the industrial wireless automation requirements through ultra‐reliable low‐latency communication (URLLC) services.
Integrating 5G URLLC with machine learning and artificial intelligence solutions will result in proactive anomaly detection followed up by self‐healing enabled by a reliable feedback control loop.
This book is presented in a way that it gradually builds on the knowledge introduced in the previous chapters, thus providing a seamless integration of various topics. The book chapters can be broadly divided into the following parts: