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Topics in Artificial Intelligence Applied to Industry 4.0

Langue : Anglais

Coordonnateurs : Ragab AL-Refaey Mahmoud, Tyagi Amit Kumar, AL-Malaise AL-Ghamdi Abdullah Saad, Kukreja Swetta

Couverture de l’ouvrage Topics in Artificial Intelligence Applied to Industry 4.0
Topics in Artificial Intelligence Applied to Industry 4.0

Forward thinking resource discussing emerging AI and IoT technologies and how they are applied to Industry 4.0

Topics in Artificial Intelligence Applied to Industry 4.0 discusses the design principles, technologies, and applications of emerging AI and IoT solutions on Industry 4.0, explaining how to make improvements in infrastructure through emerging technologies. Providing a clear connection with different technologies such as IoT, Big Data, AR and VR, and Blockchain, this book presents security, privacy, trust, and other issues whilst delving into real-world problems and case studies.

The text takes a highly practical approach, with a clear insight on how readers can increase productivity by drastically shortening the time period between the development of a new product and its delivery to customers in the market by 50%. This book also discusses how to save energy across systems to ensure competitiveness in a global market, and become more responsive in how they produce products and services for their consumers, such as by investing in flexible production lines.

Written by highly qualified authors, Topics in Artificial Intelligence Applied to Industry 4.0 explores sample topics such as:

  • Quantum machine learning, neural network implementation, and cloud and data analytics for effective analysis of industrial data
  • Computer vision, emerging networking technologies, industrial data spaces, and an industry vision for 2030 in both developing and developed nations
  • Novel or improved nature-inspired optimization algorithms in enhancing Industry 5.0 and the connectivity of any components for smart environment
  • Future professions in agriculture, medicine, education, fitness, R&D, and transport and communication as a result of new technologies

Aimed at researchers and students in the interdisciplinary fields of Smart Manufacturing and Smart Applications, Topics in Artificial Intelligence Applied to Industry 4.0 provides the perfect overview of technology from the perspective of modern society and operational environment.

About the Editors xv

List of Contributors xvii

Preface xxi

Acknowledgment xxiii

1 Introduction to Industry 4.0 and Its Impacts on Society 1
Shrikant Tiwari, Kanchan Naithani, Arun K. Singh, Virendra K. Verma, Ramesh S. Wadawadagi, and Bireshwar D. Mazumdar

1.1 Introduction 1

1.2 The Technological Advancements of the Fourth Industrial Revolution 3

1.3 Impacts on the Economy 5

1.4 Impacts on Society 9

1.5 Ethics and Governance 11

1.6 Future Directions 13

1.7 Conclusion 15

2 Digital Transformation Using Industry 4.0 and Artificial Intelligence 19
M. Keerthika, M. Pragadeesh, M. Santhiya, G. Belshia Jebamalar, and Harish Venu

2.1 Introduction 19

2.2 Industry 4.0 Technologies 20

2.3 AI Features in Industry 4.0 22

2.4 Industry 4.0 and XAI 24

2.5 Industry 4.0 Integration Using an XAI-Based Methodology with AI 24

2.6 Case Studies for Industry 4.0 29

2.7 Challenges of Industry 4.0 31

2.8 Advantages of Intelligent Factory 31

2.9 Discussion and Emerging Trends 32

2.10 Conclusion 33

3 Industry 4.0: Design Principles, Challenges, and Applications 39
K.K. Girish, Sunil Kumar, and Biswajit R. Bhowmik

3.1 Introduction 39

3.2 Organization of Chapter 40

3.3 Industrial Revolutions 40

3.4 Generations of Industrial Revolutions 40

3.5 Transformation to Industry 4.0 43

3.6 Characteristics of Industry 4.0 43

3.7 Technologies Under Industry 4.0 44

3.8 Design Principles of Industry 4.0 53

3.9 Applications of Industry 4.0 57

3.10 Trends in Industry 4.0 58

3.11 Challenges of Industry 4.0 59

3.12 Related Works 61

3.13 Paradigm Shift Toward Industry 5.0 62

3.14 Future Challenges and Research 63

3.15 Conclusion 64

4 Detection from Chest X-Ray Images Based on Modified Deep Learning Approach 69
Jyoti Dabass, Manju Dabass, and Ananda K. Behera

4.1 Introduction 69

4.2 Related Works 70

4.3 Research Methodology 71

4.4 Results and Discussions 80

4.5 Conclusions 89

5 Smart Technologies in Manufacturing Industries: A Useful Perspective 93
V.M. Gobinath, A. Kathirvel, S.K. Rajesh Kanna, and K. Annamalai

5.1 Introduction 93

5.2 Literature Review 95

5.3 Materials and Methods 95

5.4 Discussion 104

5.5 Conclusion 105

6 Blockchain Technology for Industry 4.0 107
Rajiv Kumar Berwer, Sanjeev Indora, Dinesh Kumar Atal, and Vivek Yadav

6.1 Introduction 107

6.2 Key Concepts of Blockchain 110

6.3 Blockchain in Data Privacy and Security 114

6.4 Cybersecurity in the Era of Industry 4.0 116

6.5 Supply Chain Management and Traceability 117

6.6 Blockchain-Enabled Smart Manufacturing 118

6.7 Overcoming Challenges in Blockchain Implementation 119

6.8 Real-World Applications of Blockchain in Industry 4.0 119

6.9 Future Trends 120

6.10 Conclusion 120

7 Unifying Technologies in Industry 4.0: Harnessing the Synergy of Internet of Things, Big Data, Augmented Reality/ Virtual Reality, and Blockchain Technologies 127
K. Logeswaran, S. Savitha, P. Suresh, K.R. Prasanna Kumar, M. Gunasekar, R. Rajadevi, M.K. Dharani, and A.S. Jayasurya

7.1 Introduction to Industry 4.0 127

7.2 Internet of Things 134

7.3 Big Data 136

7.4 Augmented Reality and Virtual Reality 138

7.5 Blockchain 140

7.6 Convergence of IoT, Big Data, AR/VR, and Blockchain in Industry 4.0 142

7.7 Conclusion 145

8 Industry 4.0 in Manufacturing, Communication, Transportation, and Health Care 149
Mani D. Choudhry, Jeevanandham Sivaraj, Sundarrajan Munusamy, Parimala D. Muthusamy, and V. Saravanan

8.1 Introduction 149

8.2 Diversified Applications of Industry 4.0 153

8.3 Conclusion 162

9 Transforming Education Management in the Industry 4.0 Era: Harnessing the Power of Cloud-Based Blockchain 167
Sovers Singh Bisht, Garima Jain, Priyanka Chandani, and Vinod M. Kapse

9.1 Introduction 167

9.2 Revolutionizing Education Through Technology: The Power of Innovation and Connectivity 169

9.3 Blockchain Application in Education with Industry 4.0: Revolutionizing Learning, Credentialing, and Collaboration 172

9.4 Blockchain Solution Providers for Education in the Era of Industry 4.0 174

9.5 Navigating the Challenges: Implementing Blockchain in Education Within the Industry 4.0 Landscape 177

9.6 A Vision for the Future 178

9.7 Conclusion 179

References 179

10 Future Professions in Agriculture, Medicine, Education, Fitness, Research and Development, Transport, and Communication 181
Mohan Singh, Manoj Joshi, Kapil D. Tyagi, and Vaibhav B. Tyagi

10.1 Introduction 181

10.2 Literature Review 182

10.3 AI Impact on Future Professions 186

10.4 Role Model of AI in Industry 4.0 187

10.5 AI in Agriculture 187

10.6 AI in Medicine 189

10.7 Role of AI in Challenges of Medicine 190

10.8 AI in Education 191

10.9 AI in Fitness 194

10.10 AI in R&D 196

10.11 AI in Transport 197

10.12 AI Market Growth in Future Profession 200

10.13 Conclusion 201

11 Cybersecurity Issues and Challenges in Quantum Computing 203
R. Rahul, S. Geetha, Soniya Priyatharsini, K. Mehata, Ts. Sundaresan Perumal, N. Ethiraj, and S. Sendilvelan

11.1 Introduction 203

11.2 Cybersecurity Issues and Challenges in Quantum Computer 206

11.3 General Solutions 217

11.4 Conclusion 219

12 Security, Privacy, Trust, and Other Issues in Industries 4.0 223
Ambeshwar Kumar, Manikandan Ramachandran, M. Manjula, Monika Agarwal, Pooja, and Utku Köse

12.1 Introduction 223

12.2 Security Fog Computing 226

12.3 IoT Challenges 228

12.4 Security Threats and Solutions of Industrial Internet of Things 232

12.5 Conclusion 236

13 Designing a Quantum Computer to Gear up Artificial Intelligence for Industry 4.0 239
K. Pradheep Kumar, Neha Sharma, and Juergen Seitz

13.1 Introduction 239

13.2 Literature Survey 240

13.3 Proposed Work 241

13.4 Simulation Results 250

13.5 Conclusion and Future Work 254

14 Opportunities in Neural Networks for Industry 4.0 257
Rodrigo de Paula Monteiro, José P.G. de Oliveira, Sérgio C. Oliveira, and Carmelo J.A.B. Filho

14.1 Introduction: Why Is Machine Learning Interesting to Industry 4.0? 257

14.2 Machine Learning 257

14.3 Challenges in Industry 4.0 That Can Benefit from Using Machine Learning 259

14.4 Some Cases of Success Deploying ML in Industry 4.0 262

14.5 Conclusions and Final Remarks 267

15 A Smarter Way to Collect and Store Data: AI and OCR Solutions for Industry 4.0 Systems 271
Ajay R. Nair, Varun D. Tripathy, R. Lalitha Priya, Manigandan Kashimani, Guru Akaash N. Janthalur, Nusrat J. Ansari, and Igor Jurcic

15.1 Introduction 271

15.2 Background 271

15.3 Architecture of Wireless Extraction of Display Panel 273

15.4 ESP32 Cam Module 275

15.5 Wireless LAN Network Setup 277

15.6 Optical Character Recognition for Text Detection and Text Recognition 278

15.7 Working of the Model 282

15.8 Application GUI 284

15.9 Conclusion 287

References 287

Index 289

Mahmoud Ragab AL-Refaey is a Professor of Data Science with the Information Technology Department, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University (KAU), Jeddah, Saudi Arabia and the Mathematics Department, Faculty of Science, Al-Azhar University, Egypt. He obtained his PhD. from the faculty of Mathematics and Natural Sciences of the Christian-Albrechts-University at Kiel (CAU), Germany.

Amit Kumar Tyagi is an Assistant Professor of Department of Fashion Technology, National Institute of Fashion Technology, New Delhi, India. Previously he has worked as Assistant Professor (Grade-2) and Senior Researcher at the School of Computer Science and Engineering, Vellore Institute of Technology (VIT), Chennai, Tamilnadu, India. He received his PhD. Degree in 2018 from Pondicherry Central University, India.

Abdullah Saad AL-Malaise AL-Ghamdi is a Professor of Information Systems Department, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University (KAU), Jeddah, Saudi Arabia and Information Systems Department, School of Engineering, Computing and Design, Dar Al-Hekma University, Jeddah, Saudi Arabia. He is the Secretary General of the Scientific Council at KAU. He received his PhD. degree in Computer Science, George Washington University, USA.

Swetta Kukreja is Associate Professor in the Computer Science and Engineering, Amity University, Mumbai, India. She has more than 10 years of teaching and research experience.

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