Emerging Extended Reality Technologies for Industry 4.0: Experiences with Conception, Design, Implementation, Evaluation and Deployment

257 Pages·2020·13.01 MB·English

by  Jolanda G. Tromp (editor), Dac-Nhuong Le (editor), Chung Van Le (editor)

Emerging Extended Reality
Technologies For Industry 4.0
Scrivener Publishing
100 Cummings Center, Suite 541J
Beverly, MA 01915-6106
Publishers at Scrivener
Martin Scrivener ([email protected])
Phillip Carmical ([email protected])
Emerging Extended Reality
Technologies For Industry 4.0
Early Experiences with Conception, Design,
Implementation, Evaluation and Deployment
Jolanda G. Tromp
State University of New York, Oswego, New York, USA
Dac-Nhuong Le
Haiphong University, Haiphong, Vietnam
Chung Van Le
Duy Tan University, Danang, Vietnam
This edition first published 2020 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
© 2020 Scrivener Publishing LLC
For more information about Scrivener publications please visit www.scrivenerpublishing.com.
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 other-
wise, 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.
Wiley Global Headquarters
111 River Street, Hoboken, NJ 07030, USA
For details of our global editorial offices, customer services, and more information about Wiley prod-
ucts visit us at www.wiley.com.
Limit of Liability/Disclaimer of Warranty
While the publisher and authors have used their best efforts in preparing this work, they make no rep-
resentations 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 merchant-
ability or fitness for a particular purpose. No warranty may be created or extended by sales representa-
tives, 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 informa-
tion does not mean that the publisher and authors endorse the information or services the organiza-
tion, 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. 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.
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.
Library of Congress Cataloging-in-Publication Data
ISBN 978-1-119-65463-6
Cover image: Pixabay.Com
Cover 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
Contents
List of Figures xi
List of Tables xv
Foreword xvii
Introduction xix
Preface xxiii
Acknowledgments xxv
Acronyms xxvii
Part I Extended Reality Education
1 Mixed Reality Use in Higher Education: Results from an International Survey 3
J. Riman, N. Winters, J. Zelenak, I. Yucel, J. G. Tromp
1.1 Introduction 4
1.2 Organizational Framework 4
1.3 Online Survey About MR Usage 5
1.4 Results 6
1.4.1 Use in Classrooms 8
1.4.2 Challenges 9
1.4.3 Examples of Research in Action 10
1.4.4 Hardware and Software for Use in Classrooms and Research 10
1.4.5 Challenges Described by Researcher Respondents 12
1.4.6 Anecdotal Responses about Challenges 12
1.5 Conclusion 13
References 15
2 Applying 3D VR Technology for Human Body Simulation to Teaching,
Learning and Studying 17
Le Van Chung, Gia Nhu Nguyen, Tung Sanh Nguyen, Tri Huu Nguyen,
Dac-Nhuong Le
2.1 Introduction 18
2.2 Related Works 18
2.3 3D Human Body Simulation System 19
2.3.1 The Simulated Human Anatomy Systems 19
2.3.2 Simulated Activities and Movements 20
v
vi Contents
2.3.3 Evaluation of the System 23
2.4 Discussion of Future Work 25
2.5 Conclusion 26
References 26
Part II Internet Of Things
3 A Safety Tracking and Sensor System for School Buses in Saudi Arabia 31
Samah Abbas, Hajar Mohammed, Laila Almalki Maryam Hassan,
Maram Meccawy
3.1 Introduction 32
3.2 Related Work 32
3.3 Data Gathering Phase 33
3.3.1 Questionnaire 34
3.3.2 Driver Interviews 35
3.4 The Proposed Safety Tracking and Sensor School Bus System 36
3.4.1 System Analysis and Design 37
3.4.2 User Interface Design 38
3.5 Testing and Results 41
3.6 Discussion and Limitation 42
3.7 Conclusions and Future Work 42
References 42
4 A Lightweight Encryption Algorithm Applied to a Quantized Speech Image
for Secure IoT 45
Mourad Talbi
4.1 Introduction 46
4.2 Applications of IoT 46
4.3 Security Challenges in IoT 47
4.4 Cryptographic Algorithms for IoT 47
4.5 The Proposed Algorithm 48
4.6 Experimental Setup 50
4.7 Results and Discussion 52
4.8 Conclusion 57
References 58
Part III Mobile Technology
5 The Impact of Social Media Adoption on Entrepreneurial Ecosystem 63
Bodor Almotairy, Manal Abdullah, Rabeeh Abbasi
5.1 Introduction 64
5.2 Background 65
5.2.1 Small and Medium-Sized Enterprises (SMEs) 65
5.2.2 Social Media 65
5.2.3 Social Networks and Entrepreneurial Activities 66
5.3 Analysis Methodology 66
5.4 Understanding the Entrepreneurial Ecosystem 67
Contents vii
5.5 Social Media and Entrepreneurial Ecosystem 69
5.5.1 Social Media Platforms and Entrepreneurship 71
5.5.2 The Drivers of Social Media Adoption 71
5.5.3 The Motivations and Benefits for Entrepreneurs to Use Social Media 71
5.5.4 Entrepreneurship Activities Analysis Techniques in Social
Media Networks 71
5.6 Research Gap and Recommended Solution 73
5.6.1 Research Gap 73
5.6.2 Recommended Solution 74
5.7 Conclusion 74
References 75
6 Human Factors for E-Health Training System: UX Testing for XR Anatomy
Training App 81
Zhushun Timothy Cai, Oliver Medonza, Kristen Ray, Chung Van Le,
Damian Schofield, Jolanda Tromp
6.1 Introduction 82
6.2 Mobile Learning Applications 82
6.3 Ease of Use and Usability 82
6.3.1 Effectiveness 83
6.3.2 Efficiency 83
6.3.3 Satisfaction 83
6.4 Methods and Materials 86
6.5 Results 89
6.5.1 Task Completion Rate (TCR) 89
6.5.2 Time-on-Task (TOT) 90
6.5.3 After-Scenario Questionnaire (ASQ) 91
6.5.4 Post-Study System Usability Questionnaire (PSSUQ) 93
6.6 Conclusion 93
References 94
Part IV Towards Digital Twins and Robotics
7 Augmented Reality at Heritage Sites: Technological Advances and
Embodied Spatially Minded Interactions 101
Lesley Johnston, Romy Galloway, Jordan John Trench, Matthieu Poyade,
Jolanda Tromp, Hoang Thi My
7.1 Introduction 102
7.2 Augmented Reality Devices 103
7.3 Detection and Tracking 105
7.4 Environmental Variation 106
7.5 Experiential and Embodied Interactions 109
7.6 User Experience and Presence in AR 114
7.7 Conclusion 115
References 116
viii Contents
8 TELECI Architecture for Machine Learning Algorithms Integration
in an Existing LMS 121
V. Zagorskis, A. Gorbunovs, A. Kapenieks
8.1 Introduction 122
8.2 TELECI Architecture 123
8.2.1 TELECI Interface to a Real LMS 123
8.2.2 First RS Steps in the TELECI System 124
8.2.3 Real Student Data for VS Model 125
8.2.4 TELECI Interface to VS Subsystem 126
8.2.5 TELECI Interface to AI Component 128
8.3 Implementing ML Technique 128
8.3.1 Organizational Activities 128
8.3.2 Data Processing 129
8.3.3 Computing and Networking Resources 130
8.3.4 Introduction to Algorithm 130
8.3.5 Calibration Experiment 132
8.4 Learners’ Activity Issues 133
8.5 Conclusion 136
References 137
Part V Big Data Analytics
9 Enterprise Innovation Management in Industry 4.0: Modeling Aspects 141
V. Babenko
9.1 Introduction 142
9.2 Conceptual Model of Enterprise Innovation Process Management 144
9.3 Formation of Restrictions for Enterprise Innovation Management Processes 147
9.4 Formation of Quality Criteria for Assessing Implementation of Enterprise
Innovation Management Processes 148
9.5 Statement of Optimization Task of Implementation of Enterprise
Innovation Management Processes 148
9.6 Structural and Functional Model for Solving the Task of Dynamic 150
9.7 Formulation of the Task of Minimax Program Management of Innovation
Processes at Enterprises 152
9.8 General Scheme for Solving the Task of Minimax Program Management
of Innovation Processes at the Enterprises 154
9.9 Model of Multicriteria Optimization of Program Management
of Innovation Processes 156
9.10 Conclusion 161
References 162
10 Using Simulation for Development of Automobile Gas Diesel Engine Systems
and their Operational Control 165
Mikhail G. Shatrov, Vladimir V. Sinyavski, Andrey Yu. Dunin,
Ivan G. Shishlov, Sergei D. Skorodelov, Andrey L. Yakovenko
10.1 Introduction 166
10.2 Computer Modeling 167
Contents ix
10.3 Gas Diesel Engine Systems Developed 168
10.3.1 Electronic Engine Control System 168
10.3.2 Modular Gas Feed System 169
10.3.3 Common Rail Fuel System for Supply of the Ignition Portion
of Diesel Fuel 169
10.4 Results and Discussion 172
10.4.1 Results of Diesel Fuel Supply System Simulation 172
10.4.2 Results of Engine Bed Tests 181
10.5 Conclusion 183
References 184
Part VI Towards Cognitive Computing
11 Classification of Concept Drift in Evolving Data Stream 189
Mashail Althabiti and Manal Abdullah
11.1 Introduction 190
11.2 Data Mining 190
11.3 Data Stream Mining 191
11.3.1 Data Stream Challenges 191
11.3.2 Features of Data Stream Methods 193
11.4 Data Stream Sources 193
11.5 Data Stream Mining Components 193
11.5.1 Input 194
11.5.2 Estimators 194
11.6 Data Stream Classification and Concept Drift 194
11.6.1 Data Stream Classification 194
11.6.2 Concept Drift 194
11.6.3 Data Stream Classification Algorithms with Concept Drift 196
11.6.4 Single Classifier 196
11.6.5 Ensemble Classifiers 197
11.6.6 Output 200
11.7 Datasets 200
11.8 Evaluation Measures 200
11.9 Data Stream Mining Tools 201
11.10 Data Stream Mining Applications 202
11.11 Conclusion 202
References 202
12 Dynamical Mass Transfer Systems in Buslaev Contour Networks
with Conflicts 207
Marina Yashina, Alexander Tatashev, Ivan Kuteynikov
12.1 Introduction 208
12.2 Construction of Buslaev Contour Networks 210
12.3 Concept of Spectrum 211
12.4 One-Dimensional Contour Network Binary Chain of Contours 212
12.5 Two-Dimensional Contour Network-Chainmail 214