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<p>Preface xv</p> <p><b>1 Artificial Intelligence—The Driving Force of Industry 4.0 1<br /> </b><i>Hesham Magd, Henry Jonathan, Shad Ahmad Khan and Mohamed El Geddawy</i></p> <p>1.1 Introduction 2</p> <p>1.2 Methodology 2</p> <p>1.3 Scope of AI in Global Economy and Industry 4.0 3</p> <p>1.3.1 Artificial Intelligence—Evolution and Implications 4</p> <p>1.3.2 Artificial Intelligence and Industry 4.0—Investments and Returns on Economy 5</p> <p>1.3.3 The Driving Forces for Industry 4.0 7</p> <p>1.4 Artificial Intelligence—Manufacturing Sector 8</p> <p>1.4.1 AI Diversity—Applications to Manufacturing Sector 9</p> <p>1.4.2 Future Roadmap of AI—Prospects to Manufacturing Sector in Industry 4.0 12</p> <p>1.5 Conclusion 13</p> <p>References 14</p> <p><b>2 Industry 4.0, Intelligent Manufacturing, Internet of Things, Cloud Computing: An Overview 17<br /> </b><i>Sachi Pandey, Vijay Laxmi and Rajendra Prasad Mahapatra</i></p> <p>2.1 Introduction 17</p> <p>2.2 Industrial Transformation/Value Chain Transformation 18</p> <p>2.2.1 First Scenario: Reducing Waste and Increasing Productivity Using IIoT 19</p> <p>2.2.2 Second Scenario: Selling Outcome (User Demand)– Based Services Using IIoT 20</p> <p>2.3 IIoT Reference Architecture 20</p> <p>2.4 IIoT Technical Concepts 22</p> <p>2.5 IIoT and Cloud Computing 26</p> <p>2.6 IIoT and Security 27</p> <p>References 29</p> <p><b>3 Artificial Intelligence of Things (AIoT) and Industry 4.0– Based Supply Chain (FMCG Industry) 31<br /> </b><i>Seyyed Esmaeil Najafi, Hamed Nozari and S. A. Edalatpanah</i></p> <p>3.1 Introduction 32</p> <p>3.2 Concepts 33</p> <p>3.2.1 Internet of Things 33</p> <p>3.2.2 The Industrial Internet of Things (IIoT) 34</p> <p>3.2.3 Artificial Intelligence of Things (AIoT) 35</p> <p>3.3 AIoT-Based Supply Chain 36</p> <p>3.4 Conclusion 40</p> <p>References 40</p> <p><b>4 Application of Artificial Intelligence in Forecasting the Demand for Supply Chains Considering Industry 4.0 43<br /> </b><i>Alireza Goli, Amir-Mohammad Golmohammadi and S. A. Edalatpanah</i></p> <p>4.1 Introduction 44</p> <p>4.2 Literature Review 45</p> <p>4.2.1 Summary of the First Three Industrial Revolutions 45</p> <p>4.2.2 Emergence of Industry 4.0 45</p> <p>4.2.3 Some of the Challenges of Industry 4.0 47</p> <p>4.3 Application of Artificial Intelligence in Supply Chain Demand Forecasting 48</p> <p>4.4 Proposed Approach 50</p> <p>4.4.1 Mathematical Model 50</p> <p>4.4.2 Advantages of the Proposed Model 51</p> <p>4.5 Discussion and Conclusion 52</p> <p>References 53</p> <p><b>5 Integrating IoT and Deep Learning—The Driving Force of Industry 4.0 57<br /> </b><i>Muhammad Farrukh Shahid, Tariq Jamil Saifullah Khanzada and Muhammad Hassan Tanveer</i></p> <p>5.1 Motivation and Background 58</p> <p>5.2 Bringing Intelligence Into IoT Devices 60</p> <p>5.3 The Foundation of CR-IoT Network 62</p> <p>5.3.1 Various AI Technique in CR-IoT Network 63</p> <p>5.3.2 Artificial Neural Network (ANN) 63</p> <p>5.3.3 Metaheuristic Technique 64</p> <p>5.3.4 Rule-Based System 64</p> <p>5.3.5 Ontology-Based System 65</p> <p>5.3.6 Probabilistic Models 65</p> <p>5.4 The Principles of Deep Learning and Its Implementation in CR-IoT Network 65</p> <p>5.5 Realization of CR-IoT Network in Daily Life Examples 69</p> <p>5.6 AI-Enabled Agriculture and Smart Irrigation System—Case Study 70</p> <p>5.7 Conclusion 75</p> <p>References 75</p> <p><b>6 A Systematic Review on Blockchain Security Technology and Big Data Employed in Cloud Environment 79<br /> </b><i>Mahendra Prasad Nath, Sushree Bibhuprada B. Priyadarshini, Debahuti Mishra and Brojo Kishore Mishra</i></p> <p>6.1 Introduction 80</p> <p>6.2 Overview of Blockchain 83</p> <p>6.3 Components of Blockchain 85</p> <p>6.3.1 Data Block 85</p> <p>6.3.2 Smart Contracts 87</p> <p>6.3.3 Consensus Algorithms 87</p> <p>6.4 Safety Issues in Blockchain Technology 88</p> <p>6.5 Usage of Big Data Framework in Dynamic Supply Chain System 91</p> <p>6.6 Machine Learning and Big Data 94</p> <p>6.6.1 Overview of Shallow Models 95</p> <p>6.6.1.1 Support Vector Machine (SVM) 95</p> <p>6.6.1.2 Artificial Neural Network (ANN) 95</p> <p>6.6.1.3 K-Nearest Neighbor (KNN) 95</p> <p>6.6.1.4 Clustering 96</p> <p>6.6.1.5 Decision Tree 96</p> <p>6.7 Advantages of Using Big Data for Supply Chain and Blockchain Systems 96</p> <p>6.7.1 Replenishment Planning 96</p> <p>6.7.2 Optimizing Orders 97</p> <p>6.7.3 Arranging and Organizing 97</p> <p>6.7.4 Enhanced Demand Structuring 97</p> <p>6.7.5 Real-Time Management of the Supply Chain 97</p> <p>6.7.6 Enhanced Reaction 98</p> <p>6.7.7 Planning and Growth of Inventories 98</p> <p>6.8 IoT-Enabled Blockchains 98</p> <p>6.8.1 Securing IoT Applications by Utilizing Blockchain 99</p> <p>6.8.2 Blockchain Based on Permission 101</p> <p>6.8.3 Blockchain Improvements in IoT 101</p> <p>6.8.3.1 Blockchain Can Store Information Coming from IoT Devices 101</p> <p>6.8.3.2 Secure Data Storage with Blockchain Distribution 101</p> <p>6.8.3.3 Data Encryption via Hash Key and Tested by the Miners 102</p> <p>6.8.3.4 Spoofing Attacks and Data Loss Prevention 102</p> <p>6.8.3.5 Unauthorized Access Prevention Using Blockchain 103</p> <p>6.8.3.6 Exclusion of Centralized Cloud Servers 103</p> <p>6.9 Conclusions 103</p> <p>References 104</p> <p><b>7 Deep Learning Approach to Industrial Energy Sector and Energy Forecasting with Prophet 111<br /> </b><i>Yash Gupta, Shilpi Sharma, Naveen Rajan P. and Nadia Mohamed Kunhi</i></p> <p>7.1 Introduction 112</p> <p>7.2 Related Work 113</p> <p>7.3 Methodology 114</p> <p>7.3.1 Splitting of Data (Test/Train) 116</p> <p>7.3.2 Prophet Model 116</p> <p>7.3.3 Data Cleaning 119</p> <p>7.3.4 Model Implementation 119</p> <p>7.4 Results 120</p> <p>7.4.1 Comparing Forecast to Actuals 121</p> <p>7.4.2 Adding Holidays 122</p> <p>7.4.3 Comparing Forecast to Actuals with the Cleaned Data 122</p> <p>7.5 Conclusion and Future Scope 122</p> <p>References 125</p> <p><b>8 Application of Novel AI Mechanism for Minimizing Private Data Release in Cyber-Physical Systems 127<br /> </b><i>Manas Kumar Yogi and A.S.N. Chakravarthy</i></p> <p>8.1 Introduction 128</p> <p>8.2 Related Work 131</p> <p>8.3 Proposed Mechanism 133</p> <p>8.4 Experimental Results 135</p> <p>8.5 Future Directions 137</p> <p>8.6 Conclusion 138</p> <p>References 138</p> <p><b>9 Environmental and Industrial Applications Using Internet of Things (IoT) 141<br /> </b><i>Manal Fawzy, Alaa El Din Mahmoud and Ahmed M. Abdelfatah</i></p> <p>9.1 Introduction 142</p> <p>9.2 IoT-Based Environmental Applications 146</p> <p>9.3 Smart Environmental Monitoring 147</p> <p>9.3.1 Air Quality Assessment 147</p> <p>9.3.2 Water Quality Assessment 148</p> <p>9.3.3 Soil Quality Assessment 150</p> <p>9.3.4 Environmental Health-Related to COVID- 19</p> <p>Monitoring 150</p> <p>9.4 Applications of Sensors Network in Agro-Industrial System 151</p> <p>9.5 Applications of IoT in Industry 153</p> <p>9.5.1 Application of IoT in the Autonomous Field 153</p> <p>9.5.2 Applications of IoT in Software Industries 155</p> <p>9.5.3 Sensors in Industry 156</p> <p>9.6 Challenges of IoT Applications in Environmental and Industrial Applications 157</p> <p>9.7 Conclusions and Recommendations 159</p> <p>Acknowledgments 159</p> <p>References 159</p> <p><b>10 An Introduction to Security in Internet of Things (IoT) and Big Data 169<br /> </b><i>Sushree Bibhuprada B. Priyadarshini, Suraj Kumar Dash, Amrit Sahani, Brojo Kishore Mishra and Mahendra Prasad Nath</i></p> <p>10.1 Introduction 170</p> <p>10.2 Allusion Design of IoT 172</p> <p>10.2.1 Stage 1—Edge Tool 172</p> <p>10.2.2 Stage 2—Connectivity 172</p> <p>10.2.3 Stage 3—Fog Computing 173</p> <p>10.2.4 Stage 4—Data Collection 173</p> <p>10.2.5 Stage 5—Data Abstraction 173</p> <p>10.2.6 Stage 6—Applications 173</p> <p>10.2.7 Stage 7—Cooperation and Processes 174</p> <p>10.3 Vulnerabilities of IoT 174</p> <p>10.3.1 The Properties and Relationships of Various IoT Networks 174</p> <p>10.3.2 Device Attacks 175</p> <p>10.3.3 Attacks on Network 175</p> <p>10.3.4 Some Other Issues 175</p> <p>10.3.4.1 Customer Delivery Value 175</p> <p>10.3.4.2 Compatibility Problems With Equipment 176</p> <p>10.3.4.3 Compatibility and Maintenance 176</p> <p>10.3.4.4 Connectivity Issues in the Field of Data 176</p> <p>10.3.4.5 Incorrect Data Collection and Difficulties 177</p> <p>10.3.4.6 Security Concern 177</p> <p>10.3.4.7 Problems in Computer Confidentiality 177</p> <p>10.4 Challenges in Technology 178</p> <p>10.4.1 Skepticism of Consumers 178</p> <p>10.5 Analysis of IoT Security 179</p> <p>10.5.1 Sensing Layer Security Threats 180</p> <p>10.5.1.1 Node Capturing 180</p> <p>10.5.1.2 Malicious Attack by Code Injection 180</p> <p>10.5.1.3 Attack by Fake Data Injection 180</p> <p>10.5.1.4 Sidelines Assaults 181</p> <p>10.5.1.5 Attacks During Booting Process 181</p> <p>10.5.2 Network Layer Safety Issues 181</p> <p>10.5.2.1 Attack on Phishing Page 181</p> <p>10.5.2.2 Attacks on Access 182</p> <p>10.5.2.3 Attacks on Data Transmission 182</p> <p>10.5.2.4 Attacks on Routing 182</p> <p>10.5.3 Middleware Layer Safety Issues 182</p> <p>10.5.3.1 Attack by SQL Injection 183</p> <p>10.5.3.2 Attack by Signature Wrapping 183</p> <p>10.5.3.3 Cloud Attack Injection with Malware 183</p> <p>10.5.3.4 Cloud Flooding Attack 183</p> <p>10.5.4 Gateways Safety Issues 184</p> <p>10.5.4.1 On-Boarding Safely 184</p> <p>10.5.4.2 Additional Interfaces 184</p> <p>10.5.4.3 Encrypting End-to-End 184</p> <p>10.5.5 Application Layer Safety Issues 185</p> <p>10.5.5.1 Theft of Data 185</p> <p>10.5.5.2 Attacks at Interruption in Service 185</p> <p>10.5.5.3 Malicious Code Injection Attack 185</p> <p>10.6 Improvements and Enhancements Needed for IoT Applications in the Future 186</p> <p>10.7 Upcoming Future Research Challenges with Intrusion Detection Systems (IDS) 189</p> <p>10.8 Conclusion 192</p> <p>References 193</p> <p><b>11 Potential, Scope, and Challenges of Industry 4.0 201<br /> </b><i>Roshan Raman and Aayush Kumar</i></p> <p>11.1 Introduction 202</p> <p>11.2 Key Aspects for a Successful Production 202</p> <p>11.3 Opportunities with Industry 4.0 204</p> <p>11.4 Issues in Implementation of Industry 4.0 206</p> <p>11.5 Potential Tools Utilized in Industry 4.0 207</p> <p>11.6 Conclusion 210</p> <p>References 210</p> <p><b>12 Industry 4.0 and Manufacturing Techniques: Opportunities and Challenges 215<br /> </b><i>Roshan Raman and Aditya Ranjan</i></p> <p>12.1 Introduction 216</p> <p>12.2 Changing Market Demands 217</p> <p>12.2.1 Individualization 218</p> <p>12.2.2 Volatility 218</p> <p>12.2.3 Efficiency in Terms of Energy Resources 218</p> <p>12.3 Recent Technological Advancements 219</p> <p>12.4 Industrial Revolution 4.0 221</p> <p>12.5 Challenges to Industry 4.0 224</p> <p>12.6 Conclusion 225</p> <p>References 226</p> <p><b>13 The Role of Multiagent System in Industry 4.0 227<br /> </b><i>Jagjit Singh Dhatterwal, Kuldeep Singh Kaswan and Rudra Pratap Ojha</i></p> <p>13.1 Introduction 228</p> <p>13.2 Characteristics and Goals of Industry 4.0 Conception 228</p> <p>13.3 Artificial Intelligence 231</p> <p>13.3.1 Knowledge-Based Systems 232</p> <p>13.4 Multiagent Systems 234</p> <p>13.4.1 Agent Architectures 234</p> <p>13.4.2 Jade 238</p> <p>13.4.3 System Requirements Definition 239</p> <p>13.4.4 HMI Development 240</p> <p>13.5 Developing Software of Controllers Multiagent Environment Behavior Patterns 240</p> <p>13.5.1 Agent Supervision 240</p> <p>13.5.2 Documents Dispatching Agents 241</p> <p>13.5.3 Agent Rescheduling 242</p> <p>13.5.4 Agent of Executive 242</p> <p>13.5.5 Primary Roles of High-Availability Agent 243</p> <p>13.6 Conclusion 244</p> <p>References 244</p> <p><b>14 An Overview of Enhancing Encryption Standards for Multimedia in Explainable Artificial Intelligence Using Residue Number Systems for Security 247<br /> </b><i>Akeem Femi Kadri, Micheal Olaolu Arowolo, Ayisat Wuraola Yusuf-Asaju, Kafayat Odunayo Tajudeen and Kazeem Alagbe Gbolagade</i></p> <p>14.1 Introduction 248</p> <p>14.2 Reviews of Related Works 250</p> <p>14.3 Materials and Methods 258</p> <p>14.3.1 Multimedia 258</p> <p>14.3.2 Artificial Intelligence and Explainable Artificial Intelligence 261</p> <p>14.3.3 Cryptography 262</p> <p>14.3.4 Encryption and Decryption 265</p> <p>14.3.5 Residue Number System 266</p> <p>14.4 Discussion and Conclusion 268</p> <p>References 268</p> <p><b>15 Market Trends with Cryptocurrency Trading in Industry 4.0 275<br /> </b><i>Varun Khemka, Sagar Bafna, Ayush Gupta, Somya Goyal and Vivek Kumar Verma</i></p> <p>15.1 Introduction 276</p> <p>15.2 Industry Overview 276</p> <p>15.2.1 History (From Barter to Cryptocurrency) 276</p> <p>15.2.2 In the Beginning Was Bitcoin 278</p> <p>15.3 Cryptocurrency Market 279</p> <p>15.3.1 Blockchain 279</p> <p>15.3.1.1 Introduction to Blockchain Technology 279</p> <p>15.3.1.2 Mining 280</p> <p>15.3.1.3 From Blockchain to Cryptocurrency 281</p> <p>15.3.2 Introduction to Cryptocurrency Market 281</p> <p>15.3.2.1 What is a Cryptocurrency? 281</p> <p>15.3.2.2 Cryptocurrency Exchanges 283</p> <p>15.4 Cryptocurrency Trading 283</p> <p>15.4.1 Definition 283</p> <p>15.4.2 Advantages 283</p> <p>15.4.3 Disadvantages 284</p> <p>15.5 In-Depth Analysis of Fee Structures and Carbon Footprint in Blockchain 285</p> <p>15.5.1 Need for a Fee-Driven System 285</p> <p>15.5.2 Ethereum Structure 286</p> <p>15.5.3 How is the Gas Fee Calculated? 287</p> <p>15.5.3.1 Why are Ethereum Gas Prices so High? 287</p> <p>15.5.3.2 Carbon Neutrality 287</p> <p>15.6 Conclusion 291</p> <p>References 292</p> <p><b>16 Blockchain and Its Applications in Industry 4.0 295<br /> </b><i>Ajay Sudhir Bale, Tarun Praveen Purohit, Muhammed Furqaan Hashim and Suyog Navale</i></p> <p>16.1 Introduction 296</p> <p>16.2 About Cryptocurrency 296</p> <p>16.3 History of Blockchain and Cryptocurrency 298</p> <p>16.4 Background of Industrial Revolution 300</p> <p>16.4.1 The First Industrial Revolution 301</p> <p>16.4.2 The Second Industrial Revolution 301</p> <p>16.4.3 The Third Industrial Revolution 302</p> <p>16.4.4 The Fourth Industrial Revolution 302</p> <p>16.5 Trends of Blockchain 303</p> <p>16.6 Applications of Blockchain in Industry 4.0 304</p> <p>16.6.1 Blockchain and the Government 304</p> <p>16.6.2 Blockchain in the Healthcare Sector 304</p> <p>16.6.3 Blockchain in Logistics and Supply Chain 306</p> <p>16.6.4 Blockchain in the Automotive Sector 307</p> <p>16.6.5 Blockchain in the Education Sector 308</p> <p>16.7 Conclusion 309</p> <p>References 310</p> <p>Index 315</p>

<p><b>Jyotir Moy Chatterjee</b> is an assistant professor in the Information Technology department at Lord Buddha Education Foundation (LBEF), Kathmandu, Nepal. He has published more than 60 research papers in international publications, three conference papers, three authored books, 10 edited books, 16 book chapters, two Master’s theses converted into books, and one patent. <p><b>Harish Garg, PhD, </b>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 <i>Annals of Optimization Theory and Practice.</i> <p><b>R N Thakur, PhD,</b> is a senior lecturer in the Information Technology Department, Lord Buddha Education Foundation (LBEF), Kathmandu, Nepal. He has published about 20 research articles in various journals.

<p><b>The book presents comprehensive and up-to-date technological solutions to the main aspects regarding the applications of artificial intelligence to Industry 4.0</b>. <p>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. <p><b>Audience</b> <p>Computer and artificial intelligence scientists, information and communication technology specialists, and engineers in electronics and industrial manufacturing will find this book very useful.

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