A Roadmap for Enabling Industry 4.0 by Artificial Intelligence

The book presents comprehensive and up-to-date technological solutions to the main aspects regarding the applications of artificial intelligence to Industry 4.0.

The industry 4.0 vision has been discussed for quite a while and the enabling technologies are now mature enough to turn this vision into a grand reality sooner rather than later. The fourth industrial revolution, or Industry 4.0, involves the infusion of technology-enabled deeper and decisive automation into manufacturing processes and activities. Several information and communication technologies (ICT) are being integrated and used towards attaining manufacturing process acceleration and augmentation. This book explores and educates the recent advancements in blockchain technology, artificial intelligence, supply chains in manufacturing, cryptocurrencies, and their crucial impact on realizing the Industry 4.0 goals. The book thus provides a conceptual framework and roadmap for decision-makers for implementing this transformation.

Audience

Computer and artificial intelligence scientists, information and communication technology specialists, and engineers in electronics and industrial manufacturing will find this book very useful.

1. Mr. Jyotir Moy Chatterjee is an assistant professor in the Information Technology department at Lord Buddha Education Foundation (LBEF), Kathmandu, Nepal.
2. Harish Garg, PhD, is an associate professor at Thapar Institute of Engineering & Technology, Deemed University, Patiala, Punjab, India. His research interests include soft computing, decision making, aggregation operators, Evolutionary algorithm, Expert systems and decision support systems. He has published more than 300 papers published in refereed international journals.  Dr. Garg is the Editor-in-Chief of Annals of Optimization Theory and Practice.
3. R N Thakur, PhD is a senior lecturer in the Information Technology Department, Lord Buddha Education Foundation (LBEF), Kathmandu, Nepal.

Preface xv

1 Artificial Intelligence—The Driving Force of Industry 4.0 1
Hesham Magd, Henry Jonathan, Shad Ahmad Khan and Mohamed El Geddawy

1.1 Introduction 2

1.2 Methodology 2

1.3 Scope of AI in Global Economy and Industry 4.0 3

1.3.1 Artificial Intelligence—Evolution and Implications 4

1.3.2 Artificial Intelligence and Industry 4.0—Investments and Returns on Economy 5

1.3.3 The Driving Forces for Industry 4.0 7

1.4 Artificial Intelligence—Manufacturing Sector 8

1.4.1 AI Diversity—Applications to Manufacturing Sector 9

1.4.2 Future Roadmap of AI—Prospects to Manufacturing Sector in Industry 4.0 12

1.5 Conclusion 13

References 14

2 Industry 4.0, Intelligent Manufacturing, Internet of Things, Cloud Computing: An Overview 17
Sachi Pandey, Vijay Laxmi and Rajendra Prasad Mahapatra

2.1 Introduction 17

2.2 Industrial Transformation/Value Chain Transformation 18

2.2.1 First Scenario: Reducing Waste and Increasing Productivity Using IIoT 19

2.2.2 Second Scenario: Selling Outcome (User Demand)– Based Services Using IIoT 20

2.3 IIoT Reference Architecture 20

2.4 IIoT Technical Concepts 22

2.5 IIoT and Cloud Computing 26

2.6 IIoT and Security 27

References 29

3 Artificial Intelligence of Things (AIoT) and Industry 4.0– Based Supply Chain (FMCG Industry) 31
Seyyed Esmaeil Najafi, Hamed Nozari and S. A. Edalatpanah

3.1 Introduction 32

3.2 Concepts 33

3.2.1 Internet of Things 33

3.2.2 The Industrial Internet of Things (IIoT) 34

3.2.3 Artificial Intelligence of Things (AIoT) 35

3.3 AIoT-Based Supply Chain 36

3.4 Conclusion 40

References 40

4 Application of Artificial Intelligence in Forecasting the Demand for Supply Chains Considering Industry 4.0 43
Alireza Goli, Amir-Mohammad Golmohammadi and S. A. Edalatpanah

4.1 Introduction 44

4.2 Literature Review 45

4.2.1 Summary of the First Three Industrial Revolutions 45

4.2.2 Emergence of Industry 4.0 45

4.2.3 Some of the Challenges of Industry 4.0 47

4.3 Application of Artificial Intelligence in Supply Chain Demand Forecasting 48

4.4 Proposed Approach 50

4.4.1 Mathematical Model 50

4.4.2 Advantages of the Proposed Model 51

4.5 Discussion and Conclusion 52

References 53

5 Integrating IoT and Deep Learning—The Driving Force of Industry 4.0 57
Muhammad Farrukh Shahid, Tariq Jamil Saifullah Khanzada and Muhammad Hassan Tanveer

5.1 Motivation and Background 58

5.2 Bringing Intelligence Into IoT Devices 60

5.3 The Foundation of CR-IoT Network 62

5.3.1 Various AI Technique in CR-IoT Network 63

5.3.2 Artificial Neural Network (ANN) 63

5.3.3 Metaheuristic Technique 64

5.3.4 Rule-Based System 64

5.3.5 Ontology-Based System 65

5.3.6 Probabilistic Models 65

5.4 The Principles of Deep Learning and Its Implementation in CR-IoT Network 65

5.5 Realization of CR-IoT Network in Daily Life Examples 69

5.6 AI-Enabled Agriculture and Smart Irrigation System—Case Study 70

5.7 Conclusion 75

References 75

6 A Systematic Review on Blockchain Security Technology and Big Data Employed in Cloud Environment 79
Mahendra Prasad Nath, Sushree Bibhuprada B. Priyadarshini, Debahuti Mishra and Brojo Kishore Mishra

6.1 Introduction 80

6.2 Overview of Blockchain 83

6.3 Components of Blockchain 85

6.3.1 Data Block 85

6.3.2 Smart Contracts 87

6.3.3 Consensus Algorithms 87

6.4 Safety Issues in Blockchain Technology 88

6.5 Usage of Big Data Framework in Dynamic Supply Chain System 91

6.6 Machine Learning and Big Data 94

6.6.1 Overview of Shallow Models 95

6.6.1.1 Support Vector Machine (SVM) 95

6.6.1.2 Artificial Neural Network (ANN) 95

6.6.1.3 K-Nearest Neighbor (KNN) 95

6.6.1.4 Clustering 96

6.6.1.5 Decision Tree 96

6.7 Advantages of Using Big Data for Supply Chain and Blockchain Systems 96

6.7.1 Replenishment Planning 96

6.7.2 Optimizing Orders 97

6.7.3 Arranging and Organizing 97

6.7.4 Enhanced Demand Structuring 97

6.7.5 Real-Time Management of the Supply Chain 97

6.7.6 Enhanced Reaction 98

6.7.7 Planning and Growth of Inventories 98

6.8 IoT-Enabled Blockchains 98

6.8.1 Securing IoT Applications by Utilizing Blockchain 99

6.8.2 Blockchain Based on Permission 101

6.8.3 Blockchain Improvements in IoT 101

6.8.3.1 Blockchain Can Store Information Coming from IoT Devices 101

6.8.3.2 Secure Data Storage with Blockchain Distribution 101

6.8.3.3 Data Encryption via Hash Key and Tested by the Miners 102

6.8.3.4 Spoofing Attacks and Data Loss Prevention 102

6.8.3.5 Unauthorized Access Prevention Using Blockchain 103

6.8.3.6 Exclusion of Centralized Cloud Servers 103

6.9 Conclusions 103

References 104

7 Deep Learning Approach to Industrial Energy Sector and Energy Forecasting with Prophet 111
Yash Gupta, Shilpi Sharma, Naveen Rajan P. and Nadia Mohamed Kunhi

7.1 Introduction 112

7.2 Related Work 113

7.3 Methodology 114

7.3.1 Splitting of Data (Test/Train) 116

7.3.2 Prophet Model 116

7.3.3 Data Cleaning 119

7.3.4 Model Implementation 119

7.4 Results 120

7.4.1 Comparing Forecast to Actuals 121

7.4.2 Adding Holidays 122

7.4.3 Comparing Forecast to Actuals with the Cleaned Data 122

7.5 Conclusion and Future Scope 122

References 125

8 Application of Novel AI Mechanism for Minimizing Private Data Release in Cyber-Physical Systems 127
Manas Kumar Yogi and A.S.N. Chakravarthy

8.1 Introduction 128

8.2 Related Work 131

8.3 Proposed Mechanism 133

8.4 Experimental Results 135

8.5 Future Directions 137

8.6 Conclusion 138

References 138

9 Environmental and Industrial Applications Using Internet of Things (IoT) 141
Manal Fawzy, Alaa El Din Mahmoud and Ahmed M. Abdelfatah

9.1 Introduction 142

9.2 IoT-Based Environmental Applications 146

9.3 Smart Environmental Monitoring 147

9.3.1 Air Quality Assessment 147

9.3.2 Water Quality Assessment 148

9.3.3 Soil Quality Assessment 150

9.3.4 Environmental Health-Related to COVID- 19

Monitoring 150

9.4 Applications of Sensors Network in Agro-Industrial System 151

9.5 Applications of IoT in Industry 153

9.5.1 Application of IoT in the Autonomous Field 153

9.5.2 Applications of IoT in Software Industries 155

9.5.3 Sensors in Industry 156

9.6 Challenges of IoT Applications in Environmental and Industrial Applications 157

9.7 Conclusions and Recommendations 159

Acknowledgments 159

References 159

10 An Introduction to Security in Internet of Things (IoT) and Big Data 169
Sushree Bibhuprada B. Priyadarshini, Suraj Kumar Dash, Amrit Sahani, Brojo Kishore Mishra and Mahendra Prasad Nath

10.1 Introduction 170

10.2 Allusion Design of IoT 172

10.2.1 Stage 1—Edge Tool 172

10.2.2 Stage 2—Connectivity 172

10.2.3 Stage 3—Fog Computing 173

10.2.4 Stage 4—Data Collection 173

10.2.5 Stage 5—Data Abstraction 173

10.2.6 Stage 6—Applications 173

10.2.7 Stage 7—Cooperation and Processes 174

10.3 Vulnerabilities of IoT 174

10.3.1 The Properties and Relationships of Various IoT Networks 174

10.3.2 Device Attacks 175

10.3.3 Attacks on Network 175

10.3.4 Some Other Issues 175

10.3.4.1 Customer Delivery Value 175

10.3.4.2 Compatibility Problems With Equipment 176

10.3.4.3 Compatibility and Maintenance 176

10.3.4.4 Connectivity Issues in the Field of Data 176

10.3.4.5 Incorrect Data Collection and Difficulties 177

10.3.4.6 Security Concern 177

10.3.4.7 Problems in Computer Confidentiality 177

10.4 Challenges in Technology 178

10.4.1 Skepticism of Consumers 178

10.5 Analysis of IoT Security 179

10.5.1 Sensing Layer Security Threats 180

10.5.1.1 Node Capturing 180

10.5.1.2 Malicious Attack by Code Injection 180

10.5.1.3 Attack by Fake Data Injection 180

10.5.1.4 Sidelines Assaults 181

10.5.1.5 Attacks During Booting Process 181

10.5.2 Network Layer Safety Issues 181

10.5.2.1 Attack on Phishing Page 181

10.5.2.2 Attacks on Access 182

10.5.2.3 Attacks on Data Transmission 182

10.5.2.4 Attacks on Routing 182

10.5.3 Middleware Layer Safety Issues 182

10.5.3.1 Attack by SQL Injection 183

10.5.3.2 Attack by Signature Wrapping 183

10.5.3.3 Cloud Attack Injection with Malware 183

10.5.3.4 Cloud Flooding Attack 183

10.5.4 Gateways Safety Issues 184

10.5.4.1 On-Boarding Safely 184

10.5.4.2 Additional Interfaces 184

10.5.4.3 Encrypting End-to-End 184

10.5.5 Application Layer Safety Issues 185

10.5.5.1 Theft of Data 185

10.5.5.2 Attacks at Interruption in Service 185

10.5.5.3 Malicious Code Injection Attack 185

10.6 Improvements and Enhancements Needed for IoT Applications in the Future 186

10.7 Upcoming Future Research Challenges with Intrusion Detection Systems (IDS) 189

10.8 Conclusion 192

References 193

11 Potential, Scope, and Challenges of Industry 4.0 201
Roshan Raman and Aayush Kumar

11.1 Introduction 202

11.2 Key Aspects for a Successful Production 202

11.3 Opportunities with Industry 4.0 204

11.4 Issues in Implementation of Industry 4.0 206

11.5 Potential Tools Utilized in Industry 4.0 207

11.6 Conclusion 210

References 210

12 Industry 4.0 and Manufacturing Techniques: Opportunities and Challenges 215
Roshan Raman and Aditya Ranjan

12.1 Introduction 216

12.2 Changing Market Demands 217

12.2.1 Individualization 218

12.2.2 Volatility 218

12.2.3 Efficiency in Terms of Energy Resources 218

12.3 Recent Technological Advancements 219

12.4 Industrial Revolution 4.0 221

12.5 Challenges to Industry 4.0 224

12.6 Conclusion 225

References 226

13 The Role of Multiagent System in Industry 4.0 227
Jagjit Singh Dhatterwal, Kuldeep Singh Kaswan and Rudra Pratap Ojha

13.1 Introduction 228

13.2 Characteristics and Goals of Industry 4.0 Conception 228

13.3 Artificial Intelligence 231

13.3.1 Knowledge-Based Systems 232

13.4 Multiagent Systems 234

13.4.1 Agent Architectures 234

13.4.2 Jade 238

13.4.3 System Requirements Definition 239

13.4.4 HMI Development 240

13.5 Developing Software of Controllers Multiagent Environment Behavior Patterns 240

13.5.1 Agent Supervision 240

13.5.2 Documents Dispatching Agents 241

13.5.3 Agent Rescheduling 242

13.5.4 Agent of Executive 242

13.5.5 Primary Roles of High-Availability Agent 243

13.6 Conclusion 244

References 244

14 An Overview of Enhancing Encryption Standards for Multimedia in Explainable Artificial Intelligence Using Residue Number Systems for Security 247
Akeem Femi Kadri, Micheal Olaolu Arowolo, Ayisat Wuraola Yusuf-Asaju, Kafayat Odunayo Tajudeen and Kazeem Alagbe Gbolagade

14.1 Introduction 248

14.2 Reviews of Related Works 250

14.3 Materials and Methods 258

14.3.1 Multimedia 258

14.3.2 Artificial Intelligence and Explainable Artificial Intelligence 261

14.3.3 Cryptography 262

14.3.4 Encryption and Decryption 265

14.3.5 Residue Number System 266

14.4 Discussion and Conclusion 268

References 268

15 Market Trends with Cryptocurrency Trading in Industry 4.0 275
Varun Khemka, Sagar Bafna, Ayush Gupta, Somya Goyal and Vivek Kumar Verma

15.1 Introduction 276

15.2 Industry Overview 276

15.2.1 History (From Barter to Cryptocurrency) 276

15.2.2 In the Beginning Was Bitcoin 278

15.3 Cryptocurrency Market 279

15.3.1 Blockchain 279

15.3.1.1 Introduction to Blockchain Technology 279

15.3.1.2 Mining 280

15.3.1.3 From Blockchain to Cryptocurrency 281

15.3.2 Introduction to Cryptocurrency Market 281

15.3.2.1 What is a Cryptocurrency? 281

15.3.2.2 Cryptocurrency Exchanges 283

15.4 Cryptocurrency Trading 283

15.4.1 Definition 283

15.4.2 Advantages 283

15.4.3 Disadvantages 284

15.5 In-Depth Analysis of Fee Structures and Carbon Footprint in Blockchain 285

15.5.1 Need for a Fee-Driven System 285

15.5.2 Ethereum Structure 286

15.5.3 How is the Gas Fee Calculated? 287

15.5.3.1 Why are Ethereum Gas Prices so High? 287

15.5.3.2 Carbon Neutrality 287

15.6 Conclusion 291

References 292

16 Blockchain and Its Applications in Industry 4.0 295
Ajay Sudhir Bale, Tarun Praveen Purohit, Muhammed Furqaan Hashim and Suyog Navale

16.1 Introduction 296

16.2 About Cryptocurrency 296

16.3 History of Blockchain and Cryptocurrency 298

16.4 Background of Industrial Revolution 300

16.4.1 The First Industrial Revolution 301

16.4.2 The Second Industrial Revolution 301

16.4.3 The Third Industrial Revolution 302

16.4.4 The Fourth Industrial Revolution 302

16.5 Trends of Blockchain 303

16.6 Applications of Blockchain in Industry 4.0 304

16.6.1 Blockchain and the Government 304

16.6.2 Blockchain in the Healthcare Sector 304

16.6.3 Blockchain in Logistics and Supply Chain 306

16.6.4 Blockchain in the Automotive Sector 307

16.6.5 Blockchain in the Education Sector 308

16.7 Conclusion 309

References 310

Index 315

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