A Roadmap for Enabling Industry 4.0 by Artificial Intelligence

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