{"product_id":"edge-intelligence-for-6g-enabled-industrial-internet-of-things-hardback-9781394305384","title":"Edge Intelligence for 6G-Enabled Industrial Internet of Things (Hardback) 9781394305384","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eEdge Intelligence for 6G-Enabled Industrial Internet of Things\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eSita Rani (Edited by), Rani (Author), Pankaj Bhambri (Edited by), Balamurugan Balusamy (Edited by), Rishabha Malviya (Edited by), Seifedine Kadry (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394305384, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 3 June 2026\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e448 pages\u003cbr\u003e22.9 x 15.2 x 2.8 cm, 0.739 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eMaster the shift from centralized clouds to the network’s edge with this essential guide, providing real-world case studies and 6G strategies to build faster, more reliable industrial systems.\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003e6G, the next generation of wireless communication technology, will enable unparalleled connectivity and data transfer speeds with ultra-reliable, low-latency transmission. This means better processing and decision-making in real-time. Instead of storing and processing the user’s data in a centralized cloud, edge intelligence allows users to process data locally, at the network’s periphery. With 6G-enabled IIoT, data from industrial devices and sensors can be handled locally, resulting in lower latency and faster response times for mission-critical applications. This book introduces edge intelligence and the 6G-enabled industrial Internet of Things ecosystem. It offers practical guidance and fosters a deeper understanding of how edge intelligence can be integrated with 6G-enabled IIoT applications and frameworks in a modern industrial environment. Through case studies and real-life examples, it will explore the complexities associated with real-life implementations for industrial applications, making it an invaluable resource in today’s digitally industrial ecosystem. \u003c\/p\u003e\n\u003cp\u003eReaders will find the volume: \u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eProvides a clear overview of edge intelligence and 6G-enabled IIoT integration;\u003c\/li\u003e \u003cli\u003eBridges the gap between theoretical concepts and real-life industrial use cases;\u003c\/li\u003e \u003cli\u003eIncludes real-world case studies to illustrate practical applications;\u003c\/li\u003e \u003cli\u003eOffers strategies to overcome industrial implementation challenges.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003cb\u003eAudience\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eEngineers, data scientists, researchers, and technology professionals who are involved in industrial IoT, edge computing, and emerging 6G technologies.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003eForeword xxi\u003c\/p\u003e \u003cp\u003ePreface xxiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1: Introduction, and Future Prospects to Edge Intelligence for 6G Enabled Industrial Internet of Things 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Unveiling the 6G Landscape in Industrial IoT 3\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSita Rani and Pankaj Bhambri\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 4\u003c\/p\u003e \u003cp\u003e1.1.1 Evolution from 5G to 6G Technology 4\u003c\/p\u003e \u003cp\u003e1.1.2 The Role of IoT in Industry 4.0 4\u003c\/p\u003e \u003cp\u003e1.1.3 Importance of 6G in Enhancing Industrial IoT 6\u003c\/p\u003e \u003cp\u003e1.2 Key Features of 6G Technology 6\u003c\/p\u003e \u003cp\u003e1.2.1 Ultra-High Speeds 7\u003c\/p\u003e \u003cp\u003e1.2.2 Ultra-Low Latency 7\u003c\/p\u003e \u003cp\u003e1.2.3 Massive Connectivity 7\u003c\/p\u003e \u003cp\u003e1.2.4 Advanced AI and Machine Learning Integration 7\u003c\/p\u003e \u003cp\u003e1.2.5 Enhanced Reliability and Security 7\u003c\/p\u003e \u003cp\u003e1.2.6 Energy Efficiency and Sustainability 7\u003c\/p\u003e \u003cp\u003e1.2.7 Holographic Communication and Extended Reality (XR) 7\u003c\/p\u003e \u003cp\u003e1.2.8 Global Coverage and Integration 8\u003c\/p\u003e \u003cp\u003e1.2.9 Network Slicing and Customized Services 8\u003c\/p\u003e \u003cp\u003e1.2.10 Quantum Communication and Computing 8\u003c\/p\u003e \u003cp\u003e1.3 6G Use Cases in Industrial IoT 8\u003c\/p\u003e \u003cp\u003e1.4 Challenges and Considerations in Deploying 6G for IIoT 11\u003c\/p\u003e \u003cp\u003e1.5 Impact of 6G on Industry Standards and Protocols 13\u003c\/p\u003e \u003cp\u003e1.6 Future Directions and Research Opportunities 15\u003c\/p\u003e \u003cp\u003e1.7 Case Studies and Real-World Implementations 17\u003c\/p\u003e \u003cp\u003e1.8 Conclusion 18\u003c\/p\u003e \u003cp\u003eReferences 19\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Foundations of Edge Intelligence in 6G Networks 23\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eD. Harika, C. Venkataramanan, K. Neelima and Satyam\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 24\u003c\/p\u003e \u003cp\u003e2.2 Key Drivers and Goals of 6G Networks 24\u003c\/p\u003e \u003cp\u003e2.3 Role of Distributed Intelligence in Overcoming Traditional Limitations 26\u003c\/p\u003e \u003cp\u003e2.4 Fundamental Building Blocks of Edge Intelligence in 6G 29\u003c\/p\u003e \u003cp\u003e2.5 Transformative Applications Enabled by Edge Intelligence 30\u003c\/p\u003e \u003cp\u003e2.5.1 R1 - Sample Complexity 31\u003c\/p\u003e \u003cp\u003e2.5.2 R2 - Reliable Prediction 31\u003c\/p\u003e \u003cp\u003e2.5.3 R3 - Perception-Aware Prediction 31\u003c\/p\u003e \u003cp\u003e2.5.4 R4 - Multimodal Fusion 31\u003c\/p\u003e \u003cp\u003e2.5.5 R5 - Beyond Visual Modality 31\u003c\/p\u003e \u003cp\u003e2.5.6 R6 - Non-RF Overhead 32\u003c\/p\u003e \u003cp\u003e2.5.7 R7 - Controller Connectivity 32\u003c\/p\u003e \u003cp\u003e2.5.8 R8 - Stable Control 32\u003c\/p\u003e \u003cp\u003e2.5.9 R9 - Scalable Control 32\u003c\/p\u003e \u003cp\u003e2.6 Challenges and Enablers of Edge Intelligence 33\u003c\/p\u003e \u003cp\u003e2.7 Conclusion 36\u003c\/p\u003e \u003cp\u003eReferences 36\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Advancements in Industrial Connectivity: A 6G Perspective 39\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eKali Charan Rath, Nagavarapu Sowmya, Aditi Sharma and Brojo Kishore Mishra\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 40\u003c\/p\u003e \u003cp\u003e3.2 Smart Manufacturing and Communication 41\u003c\/p\u003e \u003cp\u003e3.2.1 Comparison between 5G and 6G Network 42\u003c\/p\u003e \u003cp\u003e3.2.2 6G Technology and Importance for Implementation 42\u003c\/p\u003e \u003cp\u003e3.2.3 6G Technology and Its Significance 43\u003c\/p\u003e \u003cp\u003e3.3 Manufacturing Processes Enhancement through 6G Networks 45\u003c\/p\u003e \u003cp\u003e3.3.1 Case Study of Smart Manufacturing Technologies with 6G 46\u003c\/p\u003e \u003cp\u003e3.4 Smart Auto Manufacturing Powered by 6G: A Case Study 48\u003c\/p\u003e \u003cp\u003e3.4.1 Integration of 6G Connectivity, AI, IoT, and Edge Computing in Automobile Smart Manufacturing Optimizes Processes 51\u003c\/p\u003e \u003cp\u003e3.4.2 Algorithm for Real-Time Monitoring and Control of Factory Machines and Processes (Predictive Maintenance) with the Application of 6G 54\u003c\/p\u003e \u003cp\u003e3.5 Challenges and Obstacles in the Adoption of 6G Networks in Industrial Connectivity 56\u003c\/p\u003e \u003cp\u003e3.6 Conclusion 63\u003c\/p\u003e \u003cp\u003e3.6.1 Future Scope of Work 63\u003c\/p\u003e \u003cp\u003eReferences 64\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Security Paradigm for 6G-Enabled IIoT Ecosystems 67\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eRachna Rana and Pankaj Bhambri\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 68\u003c\/p\u003e \u003cp\u003e4.2 Therefore, What Exactly is Industrial Internet of Things Security? In What Ways Does It Propel Digital Transformation to Shift Business Models and Boost Organizational Effectiveness? Is this a Way Out? How Can Businesses Make the Most of these Advancements to Achieve Their Goals? What Exactly is Industrial Internet of Things Security (IIoT)? 74\u003c\/p\u003e \u003cp\u003e4.3 Why is Security Relevant to IIoT? 74\u003c\/p\u003e \u003cp\u003e4.3.1 Protection of Systems 75\u003c\/p\u003e \u003cp\u003e4.3.2 Information Protection 75\u003c\/p\u003e \u003cp\u003e4.3.3 Crime Prevention 75\u003c\/p\u003e \u003cp\u003e4.3.4 Cost Savings 75\u003c\/p\u003e \u003cp\u003e4.3.5 Enhanced Productivity 75\u003c\/p\u003e \u003cp\u003e4.4 Which Technologies Underpin IIoT Security? 75\u003c\/p\u003e \u003cp\u003e4.4.1 Devices and Sensors 75\u003c\/p\u003e \u003cp\u003e4.4.2 Encryption of Data 76\u003c\/p\u003e \u003cp\u003e4.4.3 Authentication 76\u003c\/p\u003e \u003cp\u003e4.4.4 These Security Measures Keep an Eye on the Digital World 76\u003c\/p\u003e \u003cp\u003e4.4.5 Updates and Patches 76\u003c\/p\u003e \u003cp\u003e4.4.6 Remote Monitoring 76\u003c\/p\u003e \u003cp\u003e4.4.7 Environmental Response 76\u003c\/p\u003e \u003cp\u003e4.4.8 Behavioral Analysis 76\u003c\/p\u003e \u003cp\u003e4.4.9 Machine Learning 77\u003c\/p\u003e \u003cp\u003e4.4.10 Redundancy 77\u003c\/p\u003e \u003cp\u003e4.4.11 Periodic Audits 77\u003c\/p\u003e \u003cp\u003e4.5 Why are IIoT Security Standards Needed? 77\u003c\/p\u003e \u003cp\u003e4.6 What Steps Can Network Administrators and CISOs Take to Secure Their Networks and Devices? 77\u003c\/p\u003e \u003cp\u003e4.6.1 Byos Secure Gateway Edge has the Following Advantages 78\u003c\/p\u003e \u003cp\u003e4.7 What Makes IIoT Security Different from IoT Security? 78\u003c\/p\u003e \u003cp\u003e4.8 Security Benefits of IIoT 78\u003c\/p\u003e \u003cp\u003e4.8.1 Data Security 78\u003c\/p\u003e \u003cp\u003e4.8.2 Stops Interruptions 80\u003c\/p\u003e \u003cp\u003e4.8.3 Guarantees Security 80\u003c\/p\u003e \u003cp\u003e4.8.4 Preserves Credibility 80\u003c\/p\u003e \u003cp\u003e4.8.5 Privacy-Protecting 80\u003c\/p\u003e \u003cp\u003e4.8.6 Stops Unauthorized Entry 81\u003c\/p\u003e \u003cp\u003e4.8.7 Protects Vital Infrastructure 81\u003c\/p\u003e \u003cp\u003e4.8.8 Lowers Danger 81\u003c\/p\u003e \u003cp\u003e4.9 Case Study 1: Agricultural Cost Reduction 81\u003c\/p\u003e \u003cp\u003e4.10 Conclusion and Future Scope 82\u003c\/p\u003e \u003cp\u003e4.10.1 Advanced Threat Protection 82\u003c\/p\u003e \u003cp\u003e4.10.2 Real-Time Monitoring 82\u003c\/p\u003e \u003cp\u003e4.10.3 Advances in Encryption 82\u003c\/p\u003e \u003cp\u003e4.10.4 Scalable Solutions 82\u003c\/p\u003e \u003cp\u003e4.10.5 User-Friendly Interfaces 82\u003c\/p\u003e \u003cp\u003e4.10.6 Combining Machine Learning and Artificial Intelligence 83\u003c\/p\u003e \u003cp\u003e4.10.7 Assurance of Compliance 83\u003c\/p\u003e \u003cp\u003eReferences 83\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Machine Learning Dynamics in 6G Industrial Environments 85\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eNaina Agrawal, J. Jayashree and J. Vijayashree\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 86\u003c\/p\u003e \u003cp\u003e5.2 Foundations of 6G Technology 90\u003c\/p\u003e \u003cp\u003e5.2.1 Overview of 6G Capabilities 90\u003c\/p\u003e \u003cp\u003e5.2.2 Integration of AI and Machine Learning into 6G Networks 90\u003c\/p\u003e \u003cp\u003e5.2.3 Key Features Making 6G Suitable for Industrial Applications 92\u003c\/p\u003e \u003cp\u003e5.3 Machine Learning Algorithms in Industrial Environments 92\u003c\/p\u003e \u003cp\u003e5.3.1 Exploration of Machine Learning Algorithms 92\u003c\/p\u003e \u003cp\u003e5.3.2 Real-World Applications of Machine Learning 93\u003c\/p\u003e \u003cp\u003e5.3.3 Case Studies Illustrating Machine Learning Success Stories 94\u003c\/p\u003e \u003cp\u003e5.4 Real-Time Data Processing and Edge Computing 96\u003c\/p\u003e \u003cp\u003e5.4.1 Significance of Real-Time Data Processing 96\u003c\/p\u003e \u003cp\u003e5.4.2 Role of Edge Computing in Industrial Environments 97\u003c\/p\u003e \u003cp\u003e5.4.3 Diagrams Illustrating 6G-Enabled Industrial System with Edge Computing 98\u003c\/p\u003e \u003cp\u003e5.5 Predictive Maintenance and Fault Detection 102\u003c\/p\u003e \u003cp\u003e5.5.1 Utilizing Machine Learning for Predictive Maintenance 102\u003c\/p\u003e \u003cp\u003e5.5.2 Fault Detection Algorithms for Industrial Processes 103\u003c\/p\u003e \u003cp\u003e5.5.3 Case Studies Showcasing Predictive Maintenance Success Stories 105\u003c\/p\u003e \u003cp\u003e5.6 Autonomous Systems and Robotics 106\u003c\/p\u003e \u003cp\u003e5.6.1 Integration of Machine Learning into Autonomous Systems 106\u003c\/p\u003e \u003cp\u003e5.6.2 Robotics Empowered by 6G Connectivity and Machine Learning 108\u003c\/p\u003e \u003cp\u003e5.6.3 Diagrams Illustrating Communication Network in 6G-Enabled Autonomous Systems 110\u003c\/p\u003e \u003cp\u003e5.7 Security and Privacy Concerns 113\u003c\/p\u003e \u003cp\u003e5.7.1 Addressing Security Challenges in 6G-Enabled Industrial Environments 113\u003c\/p\u003e \u003cp\u003e5.7.2 Privacy Considerations in Machine Learning Applications 114\u003c\/p\u003e \u003cp\u003e5.7.3 Strategies for Ensuring Data Security and Privacy 115\u003c\/p\u003e \u003cp\u003e5.8 Conclusion 116\u003c\/p\u003e \u003cp\u003e5.9 Future Prospects 116\u003c\/p\u003e \u003cp\u003eReferences 117\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Wireless Infrastructure for Robust 6G IIoT Connectivity 121\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eBoudhayan Bhattacharya and Arpan Kisore Sarbadhikari\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 122\u003c\/p\u003e \u003cp\u003e6.2 Key Features and Expectations of 6G Technology 123\u003c\/p\u003e \u003cp\u003e6.3 Unique Requirements of IIoT Applications 124\u003c\/p\u003e \u003cp\u003e6.4 Wireless Infrastructure Components for IIoT 124\u003c\/p\u003e \u003cp\u003e6.4.1 Edge Computing 124\u003c\/p\u003e \u003cp\u003e6.4.1.1 Key Concepts and Architecture 125\u003c\/p\u003e \u003cp\u003e6.4.1.2 Key Benefits 125\u003c\/p\u003e \u003cp\u003e6.4.2 Architecture: Fog Layers and Nodes 127\u003c\/p\u003e \u003cp\u003e6.4.2.1 Key Concepts and Architecture 127\u003c\/p\u003e \u003cp\u003e6.4.2.2 Key Benefits: Key Benefits for IIoT Include 128\u003c\/p\u003e \u003cp\u003e6.5 Advanced Communication Protocols 129\u003c\/p\u003e \u003cp\u003e6.5.1 Edge 5G NR (New Radio) 129\u003c\/p\u003e \u003cp\u003e6.5.1.1 Key Features of 5G NR 129\u003c\/p\u003e \u003cp\u003e6.5.1.2 Deployment and Implementation 130\u003c\/p\u003e \u003cp\u003e6.5.2 Time-Sensitive Networking (TSN) 131\u003c\/p\u003e \u003cp\u003e6.5.2.1 Key Features of TSN 131\u003c\/p\u003e \u003cp\u003e6.5.2.2 Deployment \u0026amp; Implementation 132\u003c\/p\u003e \u003cp\u003e6.5.3 Low Power Wide Area Networks (LPWANs) 134\u003c\/p\u003e \u003cp\u003e6.5.3.1 Key Features of LPWAN 134\u003c\/p\u003e \u003cp\u003e6.5.3.2 Deployment and Implementation 135\u003c\/p\u003e \u003cp\u003e6.5.3.3 Common LPWAN Technologies 138\u003c\/p\u003e \u003cp\u003e6.6 Practical Use Cases and Industry Examples 139\u003c\/p\u003e \u003cp\u003e6.6.1 Predictive Maintenance 139\u003c\/p\u003e \u003cp\u003e6.6.2 Smart Manufacturing 139\u003c\/p\u003e \u003cp\u003e6.6.3 Supply Chain Optimization 139\u003c\/p\u003e \u003cp\u003e6.7 Integration of 6G Capabilities 140\u003c\/p\u003e \u003cp\u003e6.7.1 Faster Data Transmission 140\u003c\/p\u003e \u003cp\u003e6.7.2 Improved Network Reliability 140\u003c\/p\u003e \u003cp\u003e6.7.3 Enhanced Security Measures 140\u003c\/p\u003e \u003cp\u003e6.8 Coexistence and Interoperability 140\u003c\/p\u003e \u003cp\u003e6.8.1 Coexistence of Multiple Wireless Technologies 140\u003c\/p\u003e \u003cp\u003e6.8.2 Interoperability Challenges 140\u003c\/p\u003e \u003cp\u003e6.8.3 Importance of Standardization 141\u003c\/p\u003e \u003cp\u003e6.9 Conclusion 141\u003c\/p\u003e \u003cp\u003eReferences 141\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Future Horizons: Emerging Trends in Edge Intelligence for IIoT 143\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eJ. Vigneshwari, K. Geetha, P. Senthamizh Pavai and L. Maria Suganthi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction- An Outline on IIoT 144\u003c\/p\u003e \u003cp\u003e7.2 Significance of IIoT 145\u003c\/p\u003e \u003cp\u003e7.2.1 IIoT vs IoT 146\u003c\/p\u003e \u003cp\u003e7.3 Future of IIoT 147\u003c\/p\u003e \u003cp\u003e7.4 Edge Intelligence 149\u003c\/p\u003e \u003cp\u003e7.4.1 Edge AI for Autonomous Decision-Making 149\u003c\/p\u003e \u003cp\u003e7.4.2 Artificial Intelligence (AI) and Machine Learning (ML) 151\u003c\/p\u003e \u003cp\u003e7.5 The 4.0 Technology 152\u003c\/p\u003e \u003cp\u003e7.5.1 The 4.0 Solution 152\u003c\/p\u003e \u003cp\u003e7.6 Challenges and Considerations for Adopting IIoT Trends 153\u003c\/p\u003e \u003cp\u003e7.7 6G and Future Horizons 155\u003c\/p\u003e \u003cp\u003e7.8 Benefits of Investing in IIoT 156\u003c\/p\u003e \u003cp\u003e7.8.1 Planning and Implementation of IIoT 157\u003c\/p\u003e \u003cp\u003e7.9 Conclusion 158\u003c\/p\u003e \u003cp\u003eReferences 159\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2: Advances and Applications of Edge Intelligence for 6G Enabled Industrial Internet of Things 163\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Connecting the 6G Autonomous Worlds with Real Time Edge Intelligence (Autonomous Vehicle) 165\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eHemant Kumar Saini\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 166\u003c\/p\u003e \u003cp\u003e8.2 Evolutions 168\u003c\/p\u003e \u003cp\u003e8.2.1 1G Communication 168\u003c\/p\u003e \u003cp\u003e8.2.2 2G Communication 169\u003c\/p\u003e \u003cp\u003e8.2.3 3G Communication 169\u003c\/p\u003e \u003cp\u003e8.2.4 4G Communication 170\u003c\/p\u003e \u003cp\u003e8.2.5 5G Generation 170\u003c\/p\u003e \u003cp\u003e8.2.6 6G Communication 171\u003c\/p\u003e \u003cp\u003e8.3 Issues in 6G Edges 171\u003c\/p\u003e \u003cp\u003e8.4 6G with Edge 173\u003c\/p\u003e \u003cp\u003e8.5 Edge Intelligence with Autonomous Vehicle 175\u003c\/p\u003e \u003cp\u003e8.6 Forthcoming Edge Driven AI Based 6G in Autonomous Vehicular Applications 176\u003c\/p\u003e \u003cp\u003e8.7 Future Perspective of Edge Intelligence in Vehicles 177\u003c\/p\u003e \u003cp\u003eReferences 178\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Performance Improvement of 6G Internet of Things Using Converged Super Hybrid [CPU+GPU] HPC Infrastructure and Edge AI 181\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eB.N. Chandrashekhar and V. Geetha\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 182\u003c\/p\u003e \u003cp\u003e9.1.1 Edge Computing with AI 182\u003c\/p\u003e \u003cp\u003e9.1.2 HPC Infrastructure 183\u003c\/p\u003e \u003cp\u003e9.1.2.1 Multicore Architecture 184\u003c\/p\u003e \u003cp\u003e9.1.2.2 Many-Core Architecture 185\u003c\/p\u003e \u003cp\u003e9.1.2.3 Hybrid [CPU+GPU] Architecture 186\u003c\/p\u003e \u003cp\u003e9.2 Proposed Converged Super Hybrid [CPU+GPU] HPC Infrastructure and Edge AI 187\u003c\/p\u003e \u003cp\u003e9.2.1 Overview of Converged HPC Infrastructure and Edge AI 188\u003c\/p\u003e \u003cp\u003e9.2.2 Proposed Converged Super Hybrid [CPU+GPU] HPC Infrastructure and Edge AI 190\u003c\/p\u003e \u003cp\u003e9.2.3 Innovation in 6G IOT 191\u003c\/p\u003e \u003cp\u003e9.3 Performance Optimization 193\u003c\/p\u003e \u003cp\u003e9.3.1 AI-Based Intra-Node and Internode Communication on CPUs and GPUs-Based HPC Infrastructure 193\u003c\/p\u003e \u003cp\u003e9.3.2 Optimal Workload Distribution 194\u003c\/p\u003e \u003cp\u003e9.3.3 Evaluation of Performance 196\u003c\/p\u003e \u003cp\u003eReferences 196\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Embedding Privacy into Industrial IoT System 199\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eN. Ambika\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 200\u003c\/p\u003e \u003cp\u003e10.2 Background 206\u003c\/p\u003e \u003cp\u003e10.3 Literature Survey 207\u003c\/p\u003e \u003cp\u003e10.4 Previous System 209\u003c\/p\u003e \u003cp\u003e10.5 Proposed System 210\u003c\/p\u003e \u003cp\u003e10.6 Analysis of the Work 212\u003c\/p\u003e \u003cp\u003e10.7 Simulation 213\u003c\/p\u003e \u003cp\u003e10.8 Future Scope 214\u003c\/p\u003e \u003cp\u003e10.9 Conclusion 214\u003c\/p\u003e \u003cp\u003eReferences 215\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Exploring Novel Directions in Edge Intelligence for Industrial Internet of Things (IIoT) 217\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eT. Thangarasan, R. Keerthana, J. Nagaraj, S. Vani and R.M. Dilip Charaan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction to the Internet of Things 218\u003c\/p\u003e \u003cp\u003e11.1.1 Key Components of IoT 218\u003c\/p\u003e \u003cp\u003e11.1.2 Applications of IoT 218\u003c\/p\u003e \u003cp\u003e11.1.3 Challenges of IoT 219\u003c\/p\u003e \u003cp\u003e11.2 Industrial Internet of Things (IIoT) 219\u003c\/p\u003e \u003cp\u003e11.2.1 Key Components of IIoT 219\u003c\/p\u003e \u003cp\u003e11.2.2 Applications of IIoT 220\u003c\/p\u003e \u003cp\u003e11.2.3 Benefits of IIoT 221\u003c\/p\u003e \u003cp\u003e11.2.4 Challenges of IIoT 221\u003c\/p\u003e \u003cp\u003e11.3 Decentralized Edge Intelligence Ecosystems 221\u003c\/p\u003e \u003cp\u003e11.3.1 Components 222\u003c\/p\u003e \u003cp\u003e11.3.2 Benefits 222\u003c\/p\u003e \u003cp\u003e11.3.3 Real-Time Anomaly Detection and Predictive Maintenance 223\u003c\/p\u003e \u003cp\u003e11.3.3.1 Real-Time Anomaly Detection 223\u003c\/p\u003e \u003cp\u003e11.3.3.2 Technologies Used 223\u003c\/p\u003e \u003cp\u003e11.3.3.3 Predictive Maintenance 224\u003c\/p\u003e \u003cp\u003e11.3.4 Benefits 224\u003c\/p\u003e \u003cp\u003e11.3.5 Challenges 224\u003c\/p\u003e \u003cp\u003e11.3.6 Applications 225\u003c\/p\u003e \u003cp\u003e11.4 Federated Learning for Edge Devices 225\u003c\/p\u003e \u003cp\u003e11.4.1 Key Concepts 225\u003c\/p\u003e \u003cp\u003e11.4.2 Benefits 226\u003c\/p\u003e \u003cp\u003e11.4.3 Challenges 226\u003c\/p\u003e \u003cp\u003e11.4.4 Applications 226\u003c\/p\u003e \u003cp\u003e11.4.5 How it Works 227\u003c\/p\u003e \u003cp\u003e11.4.6 Example Workflow 227\u003c\/p\u003e \u003cp\u003e11.4.7 Key Algorithms 227\u003c\/p\u003e \u003cp\u003e11.4.8 Technical Considerations 227\u003c\/p\u003e \u003cp\u003e11.5 Energy-Efficient Edge Computing 228\u003c\/p\u003e \u003cp\u003e11.5.1 Key Strategies 228\u003c\/p\u003e \u003cp\u003e11.5.2 Technologies and Techniques 229\u003c\/p\u003e \u003cp\u003e11.5.3 Benefits 229\u003c\/p\u003e \u003cp\u003e11.5.4 Challenges 230\u003c\/p\u003e \u003cp\u003e11.5.5 Applications 230\u003c\/p\u003e \u003cp\u003e11.5.6 Example Approaches 231\u003c\/p\u003e \u003cp\u003e11.6 Integration of Augmented Reality (AR) and Virtual Reality (VR) 231\u003c\/p\u003e \u003cp\u003e11.6.1 Key Concepts 231\u003c\/p\u003e \u003cp\u003e11.6.2 Integration of AR and VR 232\u003c\/p\u003e \u003cp\u003e11.6.3 Applications 232\u003c\/p\u003e \u003cp\u003e11.6.4 Benefits 233\u003c\/p\u003e \u003cp\u003e11.6.5 Challenges 233\u003c\/p\u003e \u003cp\u003e11.6.6 Future Trends 234\u003c\/p\u003e \u003cp\u003e11.7 Edge-Based Data Fusion 234\u003c\/p\u003e \u003cp\u003e11.7.1 Key Components 234\u003c\/p\u003e \u003cp\u003e11.7.2 Applications 235\u003c\/p\u003e \u003cp\u003e11.7.3 Benefits 236\u003c\/p\u003e \u003cp\u003e11.7.4 Challenges 236\u003c\/p\u003e \u003cp\u003e11.7.5 Implementation Strategies 237\u003c\/p\u003e \u003cp\u003e11.7.6 Future Trends 237\u003c\/p\u003e \u003cp\u003e11.8 Distributed Edge Intelligence Marketplaces 238\u003c\/p\u003e \u003cp\u003e11.8.1 Key Concepts 238\u003c\/p\u003e \u003cp\u003e11.8.2 Components 238\u003c\/p\u003e \u003cp\u003e11.8.3 Benefits 239\u003c\/p\u003e \u003cp\u003e11.8.4 Challenges 239\u003c\/p\u003e \u003cp\u003e11.8.5 Potential Applications 240\u003c\/p\u003e \u003cp\u003e11.8.6 Implementation Strategies 240\u003c\/p\u003e \u003cp\u003e11.8.7 Future Trends 241\u003c\/p\u003e \u003cp\u003e11.9 Edge-to-Cloud Orchestration 242\u003c\/p\u003e \u003cp\u003e11.9.1 Key Components 242\u003c\/p\u003e \u003cp\u003e11.9.2 Benefits 243\u003c\/p\u003e \u003cp\u003e11.9.3 Challenges 243\u003c\/p\u003e \u003cp\u003e11.9.4 Use Cases 244\u003c\/p\u003e \u003cp\u003e11.9.5 Implementation Strategies 245\u003c\/p\u003e \u003cp\u003e11.9.6 Future Trends 245\u003c\/p\u003e \u003cp\u003e11.10 Conclusion 246\u003c\/p\u003e \u003cp\u003eReferences 247\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 6G Network: Integrating Wireless Networks and Machine Learning for Connected Edge Intelligence 249\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eB. Prabha, V. Praveen and M.R. Santhoosh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 250\u003c\/p\u003e \u003cp\u003e12.1.1 Definition and Importance of Edge Intelligence in the 6G Context 250\u003c\/p\u003e \u003cp\u003e12.2 Evolution of Wireless Networks for Edge Intelligence 252\u003c\/p\u003e \u003cp\u003e12.2.1 Historical Perspective: From 1G to 6G and the Evolution of Edge Computing 252\u003c\/p\u003e \u003cp\u003e12.2.2 Key Technological Advancements Enabling Edge Intelligence in 6G Networks 253\u003c\/p\u003e \u003cp\u003e12.3 Challenges in Integrating AI with Wireless Networks 255\u003c\/p\u003e \u003cp\u003e12.3.1 Latency and Real-Time Processing Requirements 255\u003c\/p\u003e \u003cp\u003e12.3.2 Energy Efficiency and Resource Optimization 256\u003c\/p\u003e \u003cp\u003e12.3.3 Privacy and Security Concerns in Edge AI Systems 256\u003c\/p\u003e \u003cp\u003e12.4 Machine Learning Models for Edge Computing 257\u003c\/p\u003e \u003cp\u003e12.4.1 Overview of Decentralized Machine Learning Algorithms 257\u003c\/p\u003e \u003cp\u003e12.4.2 Model Compression and Optimization Techniques for Edge Devices 258\u003c\/p\u003e \u003cp\u003e12.4.3 Federated Learning and Collaborative Intelligence at the Edge 259\u003c\/p\u003e \u003cp\u003e12.5 Design Principles for Edge AI Systems in 6G 260\u003c\/p\u003e \u003cp\u003e12.5.1 Scalable Architecture for Edge AI Deployment 260\u003c\/p\u003e \u003cp\u003e12.5.2 Service-Driven Resource Allocation and Management 261\u003c\/p\u003e \u003cp\u003e12.5.3 Edge-to-Cloud Continuum: Balancing Computation between Edge and Central Servers 263\u003c\/p\u003e \u003cp\u003e12.6 Applications and Use Cases of Edge Intelligence in 6G Networks 263\u003c\/p\u003e \u003cp\u003e12.6.1 Smart Cities and IoT Applications Leveraging Edge AI 264\u003c\/p\u003e \u003cp\u003e12.6.2 Autonomous Vehicles and Intelligent Transportation Systems 264\u003c\/p\u003e \u003cp\u003e12.6.3 Healthcare, Industry 4.0, and Other Verticals Benefiting from Edge Intelligence 265\u003c\/p\u003e \u003cp\u003e12.6.3.1 Healthcare 265\u003c\/p\u003e \u003cp\u003e12.6.3.2 Industry 4.0 266\u003c\/p\u003e \u003cp\u003e12.7 Future Directions and Emerging Trends 266\u003c\/p\u003e \u003cp\u003e12.7.1 Predictions for the Evolution of Edge Intelligence beyond 6G 266\u003c\/p\u003e \u003cp\u003e12.7.2 Integration of Quantum Computing, Blockchain, and Other Emerging Technologies with Edge AI 267\u003c\/p\u003e \u003cp\u003e12.8 Conclusion 267\u003c\/p\u003e \u003cp\u003eReferences 268\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Securing the Hyper-Connected World: Security, Privacy and Research Challenges in IoT 271\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eGagneet Kaur, Komal Singh, Pankaj Bhambri and Sandeep Kumar Singla\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 272\u003c\/p\u003e \u003cp\u003e13.1.1 Security Framework for Privacy \u0026amp; Security in a Hyper-Connected World 273\u003c\/p\u003e \u003cp\u003e13.2 Security Attacks \u0026amp; Open Challenges 274\u003c\/p\u003e \u003cp\u003e13.2.1 Smart Buildings 274\u003c\/p\u003e \u003cp\u003e13.2.2 Healthcare Industry 275\u003c\/p\u003e \u003cp\u003e13.3 Solutions \u0026amp; Security Architecture for Healthcare Industry 277\u003c\/p\u003e \u003cp\u003e13.3.1 Confidentiality Risks 277\u003c\/p\u003e \u003cp\u003e13.3.2 Availability Risks 278\u003c\/p\u003e \u003cp\u003e13.3.3 Integrity Risks 278\u003c\/p\u003e \u003cp\u003e13.4 Automotive IoT 278\u003c\/p\u003e \u003cp\u003e13.4.1 Vulnerabilities 278\u003c\/p\u003e \u003cp\u003e13.4.2 Safety Measures 279\u003c\/p\u003e \u003cp\u003e13.5 Issues of Risks Arise in Key Security Principles of Security Architecture 280\u003c\/p\u003e \u003cp\u003e13.6 Solutions for Issues of Risks Arise in Key Security Principles of Security Architecture 281\u003c\/p\u003e \u003cp\u003eReferences 282\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Edge-to-Cloud Synergy: Enhancing IIoT Capabilities 285\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eCynthia Jayapal, K. Ulagapriya, K.V.M. Shree and A. Poonguzhali\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 286\u003c\/p\u003e \u003cp\u003e14.1.1 Foundations of Industrial IoT 287\u003c\/p\u003e \u003cp\u003e14.1.1.1 Evolution of Industry IoT 288\u003c\/p\u003e \u003cp\u003e14.1.1.2 Components of IIoT Ecosystem 288\u003c\/p\u003e \u003cp\u003e14.1.1.3 Role of IIoT in Industrial Transformation 290\u003c\/p\u003e \u003cp\u003e14.1.2 Understanding Edge Computing 292\u003c\/p\u003e \u003cp\u003e14.1.2.1 Overview of Edge Computing 292\u003c\/p\u003e \u003cp\u003e14.1.2.2 Need of Edge Computing for IIoT Applications 292\u003c\/p\u003e \u003cp\u003e14.1.2.3 Operational Benefits of Edge Computing 293\u003c\/p\u003e \u003cp\u003e14.1.2.4 Edge Computing Architectures 293\u003c\/p\u003e \u003cp\u003e14.1.3 Cloud Computing 294\u003c\/p\u003e \u003cp\u003e14.1.3.1 Overview of Cloud Computing 294\u003c\/p\u003e \u003cp\u003e14.1.3.2 Cloud Services for Industrial Applications and Their Impact on IIoT 295\u003c\/p\u003e \u003cp\u003e14.1.3.3 Benefits and Challenges of Cloud Integration 295\u003c\/p\u003e \u003cp\u003e14.1.4 Synergizing Edge and Cloud Technologies 296\u003c\/p\u003e \u003cp\u003e14.1.4.1 Conceptual Framework of Edge-to-Cloud Synergy 296\u003c\/p\u003e \u003cp\u003e14.1.4.2 Integrating Edge and Cloud for Enhanced Performance 297\u003c\/p\u003e \u003cp\u003e14.1.4.3 Achieving Optimal Balance in IoT Operations 298\u003c\/p\u003e \u003cp\u003e14.1.5 Steps in Edge-to-Cloud Integration 299\u003c\/p\u003e \u003cp\u003e14.1.5.1 Data Collection from Edge Devices 299\u003c\/p\u003e \u003cp\u003e14.1.5.2 Data Filtering, Aggregation, and Compression 300\u003c\/p\u003e \u003cp\u003e14.1.5.3 Edge Intelligence with Machine Learning Algorithms 301\u003c\/p\u003e \u003cp\u003e14.1.5.4 Establishing Edge-Cloud Connectivity 302\u003c\/p\u003e \u003cp\u003e14.1.5.5 Real-Time Monitoring and Control 303\u003c\/p\u003e \u003cp\u003e14.1.5.6 Enabling Real-Time Decision-Making 304\u003c\/p\u003e \u003cp\u003e14.1.6 6G Terahertz Communication Revolution 304\u003c\/p\u003e \u003cp\u003e14.1.6.1 Introduction to 6G Terahertz Communication 304\u003c\/p\u003e \u003cp\u003e14.1.6.2 Framework for Using Edge Intelligence in the 6G Industrial Internet of Things (IIoT) 305\u003c\/p\u003e \u003cp\u003e14.1.6.3 Implications and Advantages in IIoT 306\u003c\/p\u003e \u003cp\u003e14.1.6.4 Challenges and Solutions in Implementing Edge Intelligence for 6G IIoT 307\u003c\/p\u003e \u003cp\u003e14.1.7 Digital Twins for Real-Time Monitoring 309\u003c\/p\u003e \u003cp\u003e14.1.7.1 Digital Twins 309\u003c\/p\u003e \u003cp\u003e14.1.7.2 Integration of Digital Twin and IIoT 309\u003c\/p\u003e \u003cp\u003e14.1.7.3 Framework for Digital Twin in IIoT 310\u003c\/p\u003e \u003cp\u003e14.1.8 Blockchain for Data Security and Integrity 312\u003c\/p\u003e \u003cp\u003e14.1.8.1 Blockchain for IIoT Data Security and Integrity 312\u003c\/p\u003e \u003cp\u003e14.1.8.2 Overview of Blockchain Technology 312\u003c\/p\u003e \u003cp\u003e14.1.8.3 Need for Blockchain in IIoT 313\u003c\/p\u003e \u003cp\u003e14.1.8.4 Smart Contract and DApp 313\u003c\/p\u003e \u003cp\u003e14.1.8.5 Benefits of the Use of Blockchain in IIoT 314\u003c\/p\u003e \u003cp\u003e14.1.9 Conclusion 314\u003c\/p\u003e \u003cp\u003e14.1.9.1 Recapitulation of Key Findings 315\u003c\/p\u003e \u003cp\u003e14.1.9.2 Future Trends and Emerging Technologies 315\u003c\/p\u003e \u003cp\u003eReferences 317\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Advancing Industrial Intelligence: Leveraging Optimized Edge Devices With Large Language Model Concepts 321\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eS. Sathishkumar, R. Devi Priya, K. Karthika and A. Menaka\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 322\u003c\/p\u003e \u003cp\u003e15.1.1 The Evolution of Industrial Intelligence 322\u003c\/p\u003e \u003cp\u003e15.1.1.1 From Traditional Manufacturing to Industry 4.0 323\u003c\/p\u003e \u003cp\u003e15.1.2 Understanding Edge Computing 323\u003c\/p\u003e \u003cp\u003e15.1.2.1 Defining Edge Computing 323\u003c\/p\u003e \u003cp\u003e15.1.2.2 The Conceptual Framework 324\u003c\/p\u003e \u003cp\u003e15.1.2.3 Key Components and Architecture 324\u003c\/p\u003e \u003cp\u003e15.1.3 Enabling Technologies 324\u003c\/p\u003e \u003cp\u003e15.1.3.1 Internet of Things (IoT) in Industrial Context 325\u003c\/p\u003e \u003cp\u003e15.1.3.2 Artificial Intelligence (AI) Paradigms 326\u003c\/p\u003e \u003cp\u003e15.1.4 Challenges and Opportunities 328\u003c\/p\u003e \u003cp\u003e15.1.4.1 Computational Resource Constraints 328\u003c\/p\u003e \u003cp\u003e15.1.4.2 Security Considerations 330\u003c\/p\u003e \u003cp\u003e15.1.5 Industrial Applications 331\u003c\/p\u003e \u003cp\u003e15.1.5.1 Predictive Maintenance 331\u003c\/p\u003e \u003cp\u003e15.1.5.2 Quality Control and Assurance 332\u003c\/p\u003e \u003cp\u003e15.1.5.3 Supply Chain Management 332\u003c\/p\u003e \u003cp\u003e15.2 Proposed Architecture\/System for Industrial Edge Computing 333\u003c\/p\u003e \u003cp\u003e15.2.1 Introduction 333\u003c\/p\u003e \u003cp\u003e15.2.2 Key Components and Architecture 333\u003c\/p\u003e \u003cp\u003e15.3 Conclusion 335\u003c\/p\u003e \u003cp\u003eReferences 336\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Advancing Edge Intelligence: The Role and Future in 6G Networks 339\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eL. Maria Suganthi, P. Senthamizh Pavai, K. Geetha and J. Vigneshwari\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 340\u003c\/p\u003e \u003cp\u003e16.2 What is 6G Networks? 340\u003c\/p\u003e \u003cp\u003e16.3 Key Characteristics of 6G Networks 341\u003c\/p\u003e \u003cp\u003e16.4 Technological Innovations Driving 6G 342\u003c\/p\u003e \u003cp\u003e16.5 Challenges and Opportunities in 6G Development 344\u003c\/p\u003e \u003cp\u003e16.6 Applications and Implications of 6G Networks 345\u003c\/p\u003e \u003cp\u003e16.7 The Role of AI in 6G Networks 345\u003c\/p\u003e \u003cp\u003e16.8 Security and Privacy Enhancements in 6G Networks 347\u003c\/p\u003e \u003cp\u003e16.9 What is Edge Intelligence? 350\u003c\/p\u003e \u003cp\u003e16.10 AI Chips for Edge Devices - Transforming Localized Processing and Intelligence 350\u003c\/p\u003e \u003cp\u003e16.11 Edge Intelligence in 6G Networks 351\u003c\/p\u003e \u003cp\u003e16.12 Key Components of Edge Intelligence in 6G Networks 352\u003c\/p\u003e \u003cp\u003e16.13 The Role of Edge Intelligence in 6G Networks 353\u003c\/p\u003e \u003cp\u003e16.14 Security and Privacy in Edge Intelligence 354\u003c\/p\u003e \u003cp\u003e16.14.1 Introduction to Security and Privacy in Edge Intelligence 354\u003c\/p\u003e \u003cp\u003e16.14.2 Threat Landscape for Edge Intelligence 354\u003c\/p\u003e \u003cp\u003e16.14.3 AI-Driven Security Solutions for Edge Intelligence 354\u003c\/p\u003e \u003cp\u003e16.14.4 Data Privacy Concerns and Solutions 355\u003c\/p\u003e \u003cp\u003e16.14.5 Secure Edge Device Management 355\u003c\/p\u003e \u003cp\u003e16.14.6 Encryption and Data Integrity 356\u003c\/p\u003e \u003cp\u003e16.14.7 Zero Trust Architecture in Edge Networks 356\u003c\/p\u003e \u003cp\u003e16.14.8 Blockchain for Enhanced Security and Privacy 356\u003c\/p\u003e \u003cp\u003e16.14.9 Federated Learning and Collaborative AI 357\u003c\/p\u003e \u003cp\u003e16.14.10 Case Studies: Security and Privacy Best Practices 357\u003c\/p\u003e \u003cp\u003e16.14.11 Future Directions in Security and Privacy for Edge Intelligence 357\u003c\/p\u003e \u003cp\u003e16.15 The Future of Edge Intelligence in 6G Networks 358\u003c\/p\u003e \u003cp\u003e16.16 Advantages of Edge Intelligence 359\u003c\/p\u003e \u003cp\u003e16.17 Challenges in Edge Intelligence 361\u003c\/p\u003e \u003cp\u003e16.18 Conclusion 361\u003c\/p\u003e \u003cp\u003eReferences 362\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Optimizing Edge Devices for Industrial Intelligence 365\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eTharun Satla, Srikanth Jannu, Pankaj Bhambri and Chaitanya Thuppari\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 366\u003c\/p\u003e \u003cp\u003e17.1.1 Overview of OOA 367\u003c\/p\u003e \u003cp\u003e17.1.2 Organization 368\u003c\/p\u003e \u003cp\u003e17.2 Related Work 368\u003c\/p\u003e \u003cp\u003e17.3 System Models 369\u003c\/p\u003e \u003cp\u003e17.3.1 Network Models 369\u003c\/p\u003e \u003cp\u003e17.3.2 Energy Models 370\u003c\/p\u003e \u003cp\u003e17.4 Proposed Work 370\u003c\/p\u003e \u003cp\u003e17.4.1 OOA Based Cluster Head Selection 371\u003c\/p\u003e \u003cp\u003e17.4.1.1 Initialization 371\u003c\/p\u003e \u003cp\u003e17.4.1.2 Phase 1: Exploration 372\u003c\/p\u003e \u003cp\u003e17.4.1.3 Phase 2: Exploitation 373\u003c\/p\u003e \u003cp\u003e17.4.1.4 OOA Representation 374\u003c\/p\u003e \u003cp\u003e17.4.2 Derivation of Fitness Functions 374\u003c\/p\u003e \u003cp\u003e17.4.2.1 Sink Distance 374\u003c\/p\u003e \u003cp\u003e17.4.2.2 Residual Energy 375\u003c\/p\u003e \u003cp\u003e17.4.2.3 Intra-Cluster Distance 375\u003c\/p\u003e \u003cp\u003e17.4.3 Cluster Formation 376\u003c\/p\u003e \u003cp\u003e17.4.4 An Illustration 376\u003c\/p\u003e \u003cp\u003e17.5 Simulation Results 379\u003c\/p\u003e \u003cp\u003e17.5.1 Residual Energy 380\u003c\/p\u003e \u003cp\u003e17.5.2 Network Lifetime 381\u003c\/p\u003e \u003cp\u003e17.5.3 Number of Alive Nodes 381\u003c\/p\u003e \u003cp\u003e17.6 Conclusion 382\u003c\/p\u003e \u003cp\u003eAcknowledgement 383\u003c\/p\u003e \u003cp\u003eReferences 383\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 6G Enabled Industrial Internet of Medical Things: Prospective, Development and Challenges 387\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMeetali Chauhan and Sita Rani\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 388\u003c\/p\u003e \u003cp\u003e18.2 Literature Survey 390\u003c\/p\u003e \u003cp\u003e18.3 6G Technology 392\u003c\/p\u003e \u003cp\u003e18.4 Role of 6G Technology towards Healthcare 394\u003c\/p\u003e \u003cp\u003e18.5 6G Based IIoMT Applications 396\u003c\/p\u003e \u003cp\u003e18.5.1 Holographic Communication 396\u003c\/p\u003e \u003cp\u003e18.5.2 Augmented Reality and Virtual Reality 397\u003c\/p\u003e \u003cp\u003e18.5.3 Haptic Internet 397\u003c\/p\u003e \u003cp\u003e18.5.4 Sample Reader Sensors 398\u003c\/p\u003e \u003cp\u003e18.5.5 Intelligent Wearable Devices 398\u003c\/p\u003e \u003cp\u003e18.5.6 Hospital to Home Services 398\u003c\/p\u003e \u003cp\u003e18.5.7 Telesurgery 399\u003c\/p\u003e \u003cp\u003e18.6 Challenges and Future Perspective 399\u003c\/p\u003e \u003cp\u003e18.6.1 Challenges for 6G Technology 399\u003c\/p\u003e \u003cp\u003e18.6.2 Future Perspective 400\u003c\/p\u003e \u003cp\u003e18.7 Conclusion 402\u003c\/p\u003e \u003cp\u003eReferences 402\u003c\/p\u003e \u003cp\u003eIndex 407\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand 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