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Submit a ProposalNetworked Sensing Systems
 | Edited by Rajesh Kumar Dhanaraj, Malathy Sathyamoorthy, Balasubramaniam S., and Seifedine Kadry Copyright: 2025 | Status: Published ISBN: 9781394310869 | Hardcover | 402 pages Price: $225 USD  |
One Line Description
Networked Sensing Systems is essential for anyone seeking innovative and sustainable solutions across diverse sectors, as it explores the integration of cutting-edge IoT technologies and digital transformation aimed at enhancing resource efficiency and addressing climate change challenges.
Audience
Faculty members and students, automobile engineers, IT professionals, researchers, business executives, and technical consultants working in the areas of sensing systems, wireless sensor networks, and Internet of Things
Faculty members and students, automobile engineers, IT professionals, researchers, business executives, and technical consultants working in the areas of sensing systems, wireless sensor networks, and Internet of Things
Description
With todays improvements in wireless and mobile connectivity, Internet of Things (IoT) sensor technologies, and digital innovation, sustainability principles have started to reinforce one another. To switch to more resource-efficient solutions, use resources responsibly, and streamline operations, businesses must embrace digital transformation. Energy management, air pollution monitoring, fleet management, water management, and agriculture are a few examples of potential actuation sectors. Simultaneously, the expansion of IoT deployments and their integration into the contexts of 5G and upcoming 6G mobile networking necessitate that the solutions themselves be green and sustainable, incorporating the use of energy- and environmentally-aware technical solutions for communications.
By offering previously unattainable solutions, networking can contribute to a more sustainable society by enabling the collection of data from new and heterogeneous sources in unique ways and from novel sources using novel technology. In addition, the networking-based solution itself needs to be sustainable or environmentally friendly. For instance, changing the network architecture and moving network equipment to key locations can reduce wasteful energy use. These goals drive the search for solutions, for better and novel sensing objects that need to be energy-efficient using mobile sensing devices.
The goal of Networked Sensing Systems for A Sustainable Society is to present and highlight the most recent developments in sustainable networked sensing systems in a variety of contexts with the common goal of enhancing human well-being and halting climate change. Regardless of the area of expertise, the objective is to offer workable solutions that meet the major problems and difficulties in building a sustainable smart society 5.0. This book will serve as a potential platform to discuss networked sensing systems for a sustainable society, namely systems and applications based on mobile computers and wireless networks, while taking into account multidisciplinary approaches that emphasize the human element in resolving these difficulties.
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With todays improvements in wireless and mobile connectivity, Internet of Things (IoT) sensor technologies, and digital innovation, sustainability principles have started to reinforce one another. To switch to more resource-efficient solutions, use resources responsibly, and streamline operations, businesses must embrace digital transformation. Energy management, air pollution monitoring, fleet management, water management, and agriculture are a few examples of potential actuation sectors. Simultaneously, the expansion of IoT deployments and their integration into the contexts of 5G and upcoming 6G mobile networking necessitate that the solutions themselves be green and sustainable, incorporating the use of energy- and environmentally-aware technical solutions for communications.
By offering previously unattainable solutions, networking can contribute to a more sustainable society by enabling the collection of data from new and heterogeneous sources in unique ways and from novel sources using novel technology. In addition, the networking-based solution itself needs to be sustainable or environmentally friendly. For instance, changing the network architecture and moving network equipment to key locations can reduce wasteful energy use. These goals drive the search for solutions, for better and novel sensing objects that need to be energy-efficient using mobile sensing devices.
The goal of Networked Sensing Systems for A Sustainable Society is to present and highlight the most recent developments in sustainable networked sensing systems in a variety of contexts with the common goal of enhancing human well-being and halting climate change. Regardless of the area of expertise, the objective is to offer workable solutions that meet the major problems and difficulties in building a sustainable smart society 5.0. This book will serve as a potential platform to discuss networked sensing systems for a sustainable society, namely systems and applications based on mobile computers and wireless networks, while taking into account multidisciplinary approaches that emphasize the human element in resolving these difficulties.
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Author / Editor Details
Rajesh Kumar Dhanaraj, PhD is a distinguished professor at Symbiosis International University in Pune, India. He has authored and edited over 50 books on various cutting-edge technologies and holds 21 patents. Furthermore, he has contributed over 100 articles and papers to esteemed refereed journals and international conferences, as well as chapters for several influential books and has shared his insights with the academic community by delivering numerous tech talks on disruptive technologies. He is a senior member of the Institute of Electrical and Electronics Engineers and a member of the Computer Science Teacher Association and the International Association of Engineers.
Rajesh Kumar Dhanaraj, PhD is a distinguished professor at Symbiosis International University in Pune, India. He has authored and edited over 50 books on various cutting-edge technologies and holds 21 patents. Furthermore, he has contributed over 100 articles and papers to esteemed refereed journals and international conferences, as well as chapters for several influential books and has shared his insights with the academic community by delivering numerous tech talks on disruptive technologies. He is a senior member of the Institute of Electrical and Electronics Engineers and a member of the Computer Science Teacher Association and the International Association of Engineers.
Malathy Sathyamoorthy, PhD is an assistant professor in the Department of Information Technology, KPR Institute of Engineering and Technology, Tamil Nadu, India. She is a life member of the Indian Society for Technical Education and International Association of Engineers. She has published a number of works, including more than 25 research papers in SCI, Scopus, and ESCI indexed journals, 22 papers in international conferences, two patents, one book, and eight book chapters.
Balasubramaniam S., PhD is a post-doctoral researcher in the Department of Applied Data Science, Noroff University College, Kristiansand, Norway with over 15 years of experience in teaching, research, and industry. He has published over 20 research papers in reputed SCI and Scopus journals, contributed chapters to internationally published books, and has been granted one Australian patent, one Indian patent, and published three Indian patents. He has presented papers at conferences and organized a number of conferences, symposiums, and seminars.
Seifedine Kadry, PhD is a professor of data science at Noroff University College, Norway. He is also an Accreditation Board for Engineering and Technology Program Evaluator for computing engineering technology. He serves as a senior member of the Institute of Electrical and Electronics Engineers. His current research interests include data science, education using technology, system prognostics, stochastic systems, and probability and reliability analysis.
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Table of Contents
Preface
1. Introduction to Network Sensing Systems in Society 5.0: Issues and Challenges
Ankit Kumar, Anurag Kumar Kanojiya and Subitha D
1.1 What is Society 5.0?
1.1.1 Advancements in Society 5.0 Over Society 4.0
1.1.2 Integration and Interconnectivity
1.1.3 Data Utilization and Analysis
1.1.4 Personalization and Customization
1.1.5 Sustainability and Ethical Considerations
1.1.6 Human-Centric Design and Empowerment
1.2 Network Sensing Systems in Society 5.0
1.3 Issues and Challenges
1.3.1 Data Privacy and Security
1.3.2 Importance of Privacy and Security
1.4 Encryption and Decryption Techniques: Safeguarding Data Integrity
1.4.1 Decryption Technology
1.4.2 Challenges and Decisions
1.4.3 Interoperability Challenges in Society 5.0: A Tripping Block on the Road to a Hyperconnected Future
1.5 Understanding Interoperability on Society 5.0
1.5.1 The Smart City Dilemma: A Case Study in Interoperability Woes
1.5.2 Ensuring Integration and Data Exchange
1.5.3 Standardization Challenges and Solutions
1.5.4 Heterogeneity Challenges and Solutions
1.6 Importance of Robust Communication and Power Plans
1.6.1 The Requirement and Imperative of Flexible and Dependable Infrastructure
1.6.2 Infrastructure Resilience
1.6.3 Key Characteristics of Sturdy Infrastructure
1.6.4 Infrastructure Resilience’s Importance in Society 5.0
1.6.5 Infrastructure Resilience Techniques
1.6.6 Reduced Operational Costs
1.6.7 Safeguarding the Digital Age: Security and Privacy in Infrastructure
1.7 Environmental Effects and Energy Efficiency
1.7.1 Supporting Sustainability through Energy-Efficient Approach
1.7.2 Building Automation Systems: Transforming Buildings into Energy-Conscious Entities
1.7.3 Connected Appliances: Transforming Everyday Devices into Energy-Conscious Partners
1.7.4 Benefits of Connected Appliances
1.7.5 Challenges and Considerations
1.7.6 Energy-Efficient Manufacturing: Optimizing Industries for a Sustainable Future in Society 5.0
1.7.7 Benefits of Energy-Efficient Manufacturing
1.8 Utilizing Renewable Energy Sources
1.8.1 Methods of Harnessing Cleaner Energy in Society 5.0
1.9 Conclusion
1.9.1 Future Directions
References
2. Remote and Urban Environmental Area Sensing, Connectivity Issues, and Solutions Based on Emerging Technologies
Abinaya M., Vadivu G., Balasubramaniam S and Sundaravadivazhagan B.
2.1 Introduction
2.1.1 Urban Environment Remote Sensing Overview
2.1.2 Smart Factory
2.1.3 Benefits of Remote Sensing in Cities
2.2 Connectivity Challenges in Urban Remote Sensing
2.2.1 Conventional Remote Sensing Systems’ Technological Limitations
2.2.2 Logistical Obstacles in the Integration and Transmission of Data
2.2.3 Problems Affect Data Analysis and Quality
2.2.4 Cutting Edge Technologies to Handle Connectivity Issues
2.3 Artificial Intelligence for Enhancing Data Processing and Analysis
2.3.1 Artificial Intelligence for Data Insights
2.3.2 Real-Time Monitoring With IoT Sensors
2.3.3 Advanced Imagery and Data Acquisition
2.3.4 Secure Data Management With Blockchain
2.3.5 Immersive Data Visualization With AR/VR
2.4 Case Study
2.4.1 Monitoring Urban Air Quality With IoT Sensors
2.4.2 Analyzing Satellite Images for Urban Development and Planning
2.4.3 Drone Aerial Vehicle-Based Monitoring for Environmental Control
2.4.4 Augmented and Virtual Reality Uses in Planning and Monitoring Urban Environments
2.4.5 Combining Emerging Technologies and Remote Sensing
2.5 Frameworks for Integrating Multiple Data Sources
2.5.1 Platforms for Collaborative Work and Data Sharing
2.5.2 Regulatory Aspects and Policy Implications
2.5.3 Prospective Pathways and Difficulties
2.6 The Possible Effects of Next-Generation Connectivity and 5G
2.6.1 Privacy and Ethical Issues With Urban Remote Sensing
2.6.2 New Technologies’ Scalability and Affordability
2.6.3 AR and VR’s Place in the Future of Urban Environment Management
2.7 Conclusion
2.7.1 Future Gap
References
3. Efficient Network and Communication Technologies for Smart and Sustainable Society 5.0
P. Kanaga Priya, R. Sivaranjani, Malathy Sathyamoorthy, and Rajesh Kumar Dhanaraj
3.1 Introduction
3.1.1 Evolution of Societal Paradigms
3.1.2 Transition from Industry 4.0 to Society 5.0
3.1.3 Definition and Key Characteristics of Society 5.0
3.1.4 Importance of Efficient Network and Communication Technologies
3.1.5 Critical Technologies Shaping Smart and Sustainable Society 5.0
3.2 Literature Survey
3.3 Internet of Things for Smart Connectivity
3.3.1 IoT Applications in Smart Cities, Agriculture, Healthcare, and Industry
3.3.2 Challenges in IoT Implementation
3.3.3 Opportunities in IoT Implementation
3.4 Next-Generation Cutting Edge Communication Technologies: 5G and Beyond
3.4.1 Evolution of Cellular Communication Standards
3.4.2 5G Networks’ Features and Capabilities
3.4.3 Emerging Trends and Technologies Beyond—5G (B5G) and 6G
3.5 Edge Computing: Decentralized Processing for Low Latency
3.5.1 Understanding Edge Computing Architecture
3.5.2 Edge Computing’s Benefits for Analytics and Data Processing
3.5.3 Use Case and Deployment Scenario
3.6 Blockchain Technology: Securing Data Integrity and Trust
3.6.1 Fundamentals of Blockchain Technology
3.6.2 Applications in Secure Data Sharing, Supply Chain Management, and Decentralized Finance
3.6.3 Challenges and Potential Solutions
3.7 Artificial Intelligence in Network Optimization
3.7.1 Role of AI and Machine Learning in Network Management
3.7.2 AI-Driven Approaches for Resource Allocation and Optimization
3.8 Energy-Efficient Networking for Sustainability in Society 5.0
3.8.1 Strategies for Reducing Energy Consumption in Communication Networks
3.8.2 Green Networking Technologies and Practices in Society 5.0
3.9 Challenges and Opportunities in Implementing Efficient Network Technologies
3.10 Future Directions and Recommendations
3.10.1 Research Priorities for Advancing Network and Communication Technologies
3.10.2 Policy Recommendations for Fostering Sustainable Development in Society 5.0
3.10.3 Collaborative Efforts Toward Achieving a Smart and Sustainable Society 5.0
3.11 Conclusion
References
4. Advanced Techniques for Human-Centric Sensing in Environmental Monitoring
S. Aathilakshmi, Visali C., T. Manikandan and Seifedine Kadry
4.1 Introduction
4.2 A Basic Human-Centric Sensing Mechanism
4.3 Types of Advanced HCS Environmental Monitoring System
4.3.1 Multispectral Sensors
4.3.2 Thermal Sensors
4.3.3 LiDAR
4.3.4 Hyperspectral Sensors
4.3.5 Photogrammetry Sensors
4.4 Applications in Environmental Monitoring
4.4.1 Smart Sensor
4.4.2 Wireless Network Technology
4.4.3 Passive Sensing Technology
4.4.4 Activity Recognition Technology
4.4.5 Gesture Recognition Technology
4.5 Conclusion and Future Prospects
References
5. Energy-Aware System for Dynamic Workflow Scheduling in Cloud Data Centers: A Genetic Algorithm with DQN Approach
Hariharan B., Anupama C.G., Ratna Kumari Neerukonda and Rajesh Kumar Dhanaraj
5.1 Introduction
5.2 Related Works
5.3 Dynamic Workflow Scheduling System
5.3.1 System Architecture
5.3.2 Genetic Algorithm for Dynamic Workflow Scheduling
5.3.3 Deep Q-Learning for Dynamic Workflow Scheduling
5.3.4 Energy Consumption for Dynamic Workflow Scheduling
5.4 Problem Formulation and Proposed System Architecture
5.4.1 Hybrid Approach
5.4.2 Implementation of GA
5.5 Simulation Set-Up and Experimental Results
5.5.1 Makespan Computation
5.5.2 Energy Consumption Calculation
5.6 Conclusion
References
6. Efficient Load Balancing and Resource Allocation in Networked Sensing Systems—An Algorithmic Study
Lalitha Krishnasamy, Divya Vetriveeran, Rakoth Kandan Sambandam and Jenefa J.
6.1 Introduction to the Networked Sensing Systems
6.2 Understanding the Load Balancing Challenges
6.2.1 Types of Load Balancing
6.2.2 Load Balancing Technologies
6.3 Importance of Efficient Resource Allocation
6.4 Overview of Existing Approaches
6.4.1 Probabilistic Clustering
6.4.2 Non-Probability Clustering
6.5 Artificial Intelligence for Resource Handing
6.5.1 Naïve Bayes
6.5.2 Multi-Class SVM
6.5.3 AdaBoost
6.5.4 Clustering
6.5.5 Learning-Based Resource Allocation (LB-RA)
6.5.6 Neural Networks for Load Balancing and Resource Allocation
6.5.7 Reinforcement Learning
6.6 Real-World Applications
6.7 Performance Metrics
6.7.1 Throughput
6.7.2 Reaction Time
6.7.3 Latency
6.7.4 Versatility
6.7.5 Asset Use
6.7.6 Optimization
6.7.7 Fairness
6.7.8 MTTF
6.7.9 Cost Effectiveness
6.7.10 Adaptability
6.8 Research Directions
6.8.1 Edge Computing
6.8.2 ML and AI
6.8.3 Autonomous Resource Management
6.8.4 Containerization and Orchestration
6.8.5 Hybrid and Multi-Cloud Environments
6.8.6 Energy-Efficient Computing
6.8.7 Quantum Figuring
6.8.8 Asset the Executives
6.8.9 Security and Protection Contemplations
6.8.10 Cross-Domain Resource Allocation
6.9 Conclusion and Future Work
Acknowledgments
References
7. Sustainable Cities and Communities: Role of Network Sensing System in Action
Hitesh Mohapatra, Soumya Ranjan Mishra, Amiya Kumar Rath and Manjur Kolhar
7.1 Introduction
7.2 Literature Review
7.3 Proposed Study
7.3.1 Star Topology
7.3.2 Mesh Topology
7.3.3 Tree Topology
7.3.4 Clustered Topology
7.4 Performance Analysis
7.5 Mapping of Topology with Smart City’s Applications
7.5.1 Mapping of Star Topology with Smart Parking Application
7.5.2 Mapping of Mesh Topology with Smart Grid Application
7.5.3 Mapping of Tree Topology with Smart Education Model
7.5.4 Mapping of Cluster Topology with Smart Health Care Model
7.6 Conclusion
References
8. Air Pollution Monitoring and Control Via Network Sensing Systems in Smart Cities
S. Sharmila Devi
8.1 Introduction
8.2 Related Works
8.3 Air Quality System
8.4 Air Quality Monitoring Techniques
8.5 Conventional Air Pollution Monitoring
8.5.1 Manual Measurement and Evaluation of Air Quality
8.5.2 Automated Continuous Monitoring Devices
8.5.3 Monitoring Air Quality with Sensing Technology
8.6 Wireless Sensor Network for Air Monitoring
8.6.1 Wireless Sensor Networks
8.6.2 WSN Network Topologies
8.6.3 Zigbee Standard
8.7 Architecture of Wireless Sensor Networks
8.7.1 Fire and Flood Detection
8.7.2 Biocomplexity
8.7.3 Habitat Monitoring
8.7.4 Factors Influencing the Efficacy of Inexpensive Sensors in the Monitoring of Air Pollution
8.8 WSN-Based Air Pollution Monitoring in Smart Cities
8.9 Conclusion
References
9. Interconnected Healthcare 5.0 Ecosystems: Enhancing Patient Care Using Sensor Networks
Ashwini A., Kavitha V. and Balasubramaniam S
9.1 Introduction to Healthcare 5.0
9.1.1 Evolution from Healthcare 4.0 to Healthcare 5.0
9.2 Real-Time Monitoring Using Sensor Networks
9.3 Advancements in Remote Patient Monitoring
9.3.1 Challenges in Healthcare 4.0
9.4 Early Disease Detection Through Sensor Networks
9.5 Leveraging Multisensor Data for Comprehensive Health Insights
9.6 Security Measures for Protected Health Information
9.7 Overcoming Infrastructure and Connectivity Barriers
9.8 Improving Treatment Plans Through Sensor-Generated Insights
9.9 Conclusion
References
10. Farming 4.0: Cultivating the Future with Internet of Things Empowered on Smart Agriculture Solutions
Ashwini A., S.R. Sriram, J. Manoj Prabhakar and Seifedine Kadry
10.1 Introduction to Smart Agriculture and IoT Integration
10.1.1 Evolution of Agriculture: From Traditional to Smart Farming
10.2 IoT Sensor Networks in Farming
10.2.1 IoT Sensors and Their Applications
10.3 Smart Pest and Disease Control in Crop Production
10.3.1 Meticulous Fertilization and Nutrition Control
10.3.2 Accurate Irrigation Techniques and Water Administration
10.4 Automation and Robotics in Agriculture
10.4.1 Agricultural Operations Using Automatic Systems
10.4.2 AI in Farm Automation
10.5 Cloud Computing for Agricultural Data Management
10.6 Big Data Analytics for Predictive Farming
10.7 Sustainable Practices with IoT in Agriculture
10.8 The Future Landscape of Farming 4.0
10.9 Conclusion
References
11. Public Safety Management in Smart Society 5.0: A Blockchain-Based Approach
P.N. Senthil Prakash, S. Karthic and M. Saravanan
11.1 Introduction
11.2 Security Challenges in Society 5.0
11.3 Blockchain in Society 5.0
11.3.1 Blockchain for Refinery Industry
11.3.2 Blockchain in Identity Management
11.3.3 Blockchain and Its Impact in Healthcare
11.3.4 Blockchain for Supply Chain Management
11.3.5 Blockchain in Asset Management
11.3.6 Blockchain in Copyright Management
11.4 Conclusion
References
12. Virtualization of Smart Society 5.0 Using Artificial Intelligence and Virtual Reality
Sakthivel Sankaran, M. Arun and R. Kottaimalai
12.1 Introduction to Smart Society 5.0
12.1.1 Smart Society 5.0 and Its Key Characteristics
12.1.2 Evolution from Previous Smart Society Models
12.2 Foundations of Virtual Reality
12.2.1 Brief History and Development of Virtual Reality
12.2.2 Key Components and Technologies in VR
12.2.3 VR Hardware and Software Ecosystems
12.3 Artificial Intelligence in Smart Societies
12.3.1 Overview of AI Technologies Shaping Smart Societies
12.3.2 Role of AI in Data Analytics, Automation, and Decision Making
12.3.3 AI-Driven Applications in Healthcare, Transportation, and Education
12.4 Integration of AI and VR
12.4.1 How AI and VR Technologies Complement Each Other
12.4.2 Examples of AI-Enhanced Virtual Reality Applications
12.4.3 Possibilities and Obstacles When Fusing AI with VR
12.5 AI and VR in Education
12.5.1 Virtual Classrooms and Immersive Learning Experiences
12.5.2 AI-Enabled Adaptive Learning Systems
12.5.3 Skill Development and Training Using VR and AI
12.6 Smart Society 5.0 Healthcare Innovations
12.6.1 Virtual Healthcare Consultations and Simulations
12.6.2 AI-Driven Diagnostics and Treatment Planning
12.6.3 VR and AI-Based Treatments and Rehab
12.7 Challenges and Future Directions
12.7.1 Current Obstacles to Integrate VR and AI in Smart Communities
12.7.2 Prospective Developments and Emerging Patterns in AI and VR in Smart Societies
12.7.3 Consider the Role of Emerging Technologies
12.8 Conclusion
12.8.1 Summary of AI and VR Technologies in Smart Societies
12.8.2 Vision for the Future of Smart Societies with AI and VR
References
13. Battery Power Management Schemes Integrated with Industrial IoT for Sustainable Industry Development
D. Karthikeyan, A. Geetha, K. Deepa and Malathy Sathyamoorthy
13.1 Introduction
13.2 Current Battery Technologies
13.2.1 Metal–Air Battery
13.2.2 Lithium–Sulfur Battery
13.2.3 Batteries Beyond Lithium
13.3 Battery Energy Storage and Management
13.4 IoT and Cloud Computing Technology in BMS
13.5 Sustainable Developments via BMS
13.5.1 SDG8
13.5.2 SDG9
13.5.3 SDG12
13.5.4 SDG13
13.6 Conclusion
References
14. Trends, Advances, and Applications of Network Sensing Systems
Ashwini A., Shamini G.I. and Balasubramaniam S
14.1 Introduction to Network Sensing Systems
14.1.1 Relevance in Different Sectors
14.2 Real-Time Trends in Sensor Technology
14.2.1 Advanced Sensing Modalities
14.2.2 Power-Efficient Designs
14.3 Advancements in Data Analytics
14.3.1 Big Data Analytics for Sensor-Generated Data
14.4 Applications in Healthcare
14.4.1 Remote Patient Monitoring
14.4.2 Smart Healthcare and Medical Establishments
14.4.3 Fall Detection and Old Care
14.5 Natural Disaster Detection with Response
14.5.1 Early Detection Systems
14.5.2 Satellite Imagery and Tracking
14.5.3 Resilient Communications Networks
14.5.4 Predictive Analysis and Modeling
14.6 Agricultural Sensing Systems
14.6.1 Crop Monitoring and Management
14.6.2 Soil Sensing and Precision Agriculture
14.6.3 Weather Monitoring and Forecasting
14.6.4 Livestock Monitoring and Management
14.6.5 Data Analytics and Decision Support System
14.6.6 Remote Monitoring and Automation
14.7 Intelligent Transportation Systems
14.8 Smart City Applications
14.9 Challenges
14.10 Conclusion
References
About the Editors
Index
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Preface
1. Introduction to Network Sensing Systems in Society 5.0: Issues and Challenges
Ankit Kumar, Anurag Kumar Kanojiya and Subitha D
1.1 What is Society 5.0?
1.1.1 Advancements in Society 5.0 Over Society 4.0
1.1.2 Integration and Interconnectivity
1.1.3 Data Utilization and Analysis
1.1.4 Personalization and Customization
1.1.5 Sustainability and Ethical Considerations
1.1.6 Human-Centric Design and Empowerment
1.2 Network Sensing Systems in Society 5.0
1.3 Issues and Challenges
1.3.1 Data Privacy and Security
1.3.2 Importance of Privacy and Security
1.4 Encryption and Decryption Techniques: Safeguarding Data Integrity
1.4.1 Decryption Technology
1.4.2 Challenges and Decisions
1.4.3 Interoperability Challenges in Society 5.0: A Tripping Block on the Road to a Hyperconnected Future
1.5 Understanding Interoperability on Society 5.0
1.5.1 The Smart City Dilemma: A Case Study in Interoperability Woes
1.5.2 Ensuring Integration and Data Exchange
1.5.3 Standardization Challenges and Solutions
1.5.4 Heterogeneity Challenges and Solutions
1.6 Importance of Robust Communication and Power Plans
1.6.1 The Requirement and Imperative of Flexible and Dependable Infrastructure
1.6.2 Infrastructure Resilience
1.6.3 Key Characteristics of Sturdy Infrastructure
1.6.4 Infrastructure Resilience’s Importance in Society 5.0
1.6.5 Infrastructure Resilience Techniques
1.6.6 Reduced Operational Costs
1.6.7 Safeguarding the Digital Age: Security and Privacy in Infrastructure
1.7 Environmental Effects and Energy Efficiency
1.7.1 Supporting Sustainability through Energy-Efficient Approach
1.7.2 Building Automation Systems: Transforming Buildings into Energy-Conscious Entities
1.7.3 Connected Appliances: Transforming Everyday Devices into Energy-Conscious Partners
1.7.4 Benefits of Connected Appliances
1.7.5 Challenges and Considerations
1.7.6 Energy-Efficient Manufacturing: Optimizing Industries for a Sustainable Future in Society 5.0
1.7.7 Benefits of Energy-Efficient Manufacturing
1.8 Utilizing Renewable Energy Sources
1.8.1 Methods of Harnessing Cleaner Energy in Society 5.0
1.9 Conclusion
1.9.1 Future Directions
References
2. Remote and Urban Environmental Area Sensing, Connectivity Issues, and Solutions Based on Emerging Technologies
Abinaya M., Vadivu G., Balasubramaniam S and Sundaravadivazhagan B.
2.1 Introduction
2.1.1 Urban Environment Remote Sensing Overview
2.1.2 Smart Factory
2.1.3 Benefits of Remote Sensing in Cities
2.2 Connectivity Challenges in Urban Remote Sensing
2.2.1 Conventional Remote Sensing Systems’ Technological Limitations
2.2.2 Logistical Obstacles in the Integration and Transmission of Data
2.2.3 Problems Affect Data Analysis and Quality
2.2.4 Cutting Edge Technologies to Handle Connectivity Issues
2.3 Artificial Intelligence for Enhancing Data Processing and Analysis
2.3.1 Artificial Intelligence for Data Insights
2.3.2 Real-Time Monitoring With IoT Sensors
2.3.3 Advanced Imagery and Data Acquisition
2.3.4 Secure Data Management With Blockchain
2.3.5 Immersive Data Visualization With AR/VR
2.4 Case Study
2.4.1 Monitoring Urban Air Quality With IoT Sensors
2.4.2 Analyzing Satellite Images for Urban Development and Planning
2.4.3 Drone Aerial Vehicle-Based Monitoring for Environmental Control
2.4.4 Augmented and Virtual Reality Uses in Planning and Monitoring Urban Environments
2.4.5 Combining Emerging Technologies and Remote Sensing
2.5 Frameworks for Integrating Multiple Data Sources
2.5.1 Platforms for Collaborative Work and Data Sharing
2.5.2 Regulatory Aspects and Policy Implications
2.5.3 Prospective Pathways and Difficulties
2.6 The Possible Effects of Next-Generation Connectivity and 5G
2.6.1 Privacy and Ethical Issues With Urban Remote Sensing
2.6.2 New Technologies’ Scalability and Affordability
2.6.3 AR and VR’s Place in the Future of Urban Environment Management
2.7 Conclusion
2.7.1 Future Gap
References
3. Efficient Network and Communication Technologies for Smart and Sustainable Society 5.0
P. Kanaga Priya, R. Sivaranjani, Malathy Sathyamoorthy, and Rajesh Kumar Dhanaraj
3.1 Introduction
3.1.1 Evolution of Societal Paradigms
3.1.2 Transition from Industry 4.0 to Society 5.0
3.1.3 Definition and Key Characteristics of Society 5.0
3.1.4 Importance of Efficient Network and Communication Technologies
3.1.5 Critical Technologies Shaping Smart and Sustainable Society 5.0
3.2 Literature Survey
3.3 Internet of Things for Smart Connectivity
3.3.1 IoT Applications in Smart Cities, Agriculture, Healthcare, and Industry
3.3.2 Challenges in IoT Implementation
3.3.3 Opportunities in IoT Implementation
3.4 Next-Generation Cutting Edge Communication Technologies: 5G and Beyond
3.4.1 Evolution of Cellular Communication Standards
3.4.2 5G Networks’ Features and Capabilities
3.4.3 Emerging Trends and Technologies Beyond—5G (B5G) and 6G
3.5 Edge Computing: Decentralized Processing for Low Latency
3.5.1 Understanding Edge Computing Architecture
3.5.2 Edge Computing’s Benefits for Analytics and Data Processing
3.5.3 Use Case and Deployment Scenario
3.6 Blockchain Technology: Securing Data Integrity and Trust
3.6.1 Fundamentals of Blockchain Technology
3.6.2 Applications in Secure Data Sharing, Supply Chain Management, and Decentralized Finance
3.6.3 Challenges and Potential Solutions
3.7 Artificial Intelligence in Network Optimization
3.7.1 Role of AI and Machine Learning in Network Management
3.7.2 AI-Driven Approaches for Resource Allocation and Optimization
3.8 Energy-Efficient Networking for Sustainability in Society 5.0
3.8.1 Strategies for Reducing Energy Consumption in Communication Networks
3.8.2 Green Networking Technologies and Practices in Society 5.0
3.9 Challenges and Opportunities in Implementing Efficient Network Technologies
3.10 Future Directions and Recommendations
3.10.1 Research Priorities for Advancing Network and Communication Technologies
3.10.2 Policy Recommendations for Fostering Sustainable Development in Society 5.0
3.10.3 Collaborative Efforts Toward Achieving a Smart and Sustainable Society 5.0
3.11 Conclusion
References
4. Advanced Techniques for Human-Centric Sensing in Environmental Monitoring
S. Aathilakshmi, Visali C., T. Manikandan and Seifedine Kadry
4.1 Introduction
4.2 A Basic Human-Centric Sensing Mechanism
4.3 Types of Advanced HCS Environmental Monitoring System
4.3.1 Multispectral Sensors
4.3.2 Thermal Sensors
4.3.3 LiDAR
4.3.4 Hyperspectral Sensors
4.3.5 Photogrammetry Sensors
4.4 Applications in Environmental Monitoring
4.4.1 Smart Sensor
4.4.2 Wireless Network Technology
4.4.3 Passive Sensing Technology
4.4.4 Activity Recognition Technology
4.4.5 Gesture Recognition Technology
4.5 Conclusion and Future Prospects
References
5. Energy-Aware System for Dynamic Workflow Scheduling in Cloud Data Centers: A Genetic Algorithm with DQN Approach
Hariharan B., Anupama C.G., Ratna Kumari Neerukonda and Rajesh Kumar Dhanaraj
5.1 Introduction
5.2 Related Works
5.3 Dynamic Workflow Scheduling System
5.3.1 System Architecture
5.3.2 Genetic Algorithm for Dynamic Workflow Scheduling
5.3.3 Deep Q-Learning for Dynamic Workflow Scheduling
5.3.4 Energy Consumption for Dynamic Workflow Scheduling
5.4 Problem Formulation and Proposed System Architecture
5.4.1 Hybrid Approach
5.4.2 Implementation of GA
5.5 Simulation Set-Up and Experimental Results
5.5.1 Makespan Computation
5.5.2 Energy Consumption Calculation
5.6 Conclusion
References
6. Efficient Load Balancing and Resource Allocation in Networked Sensing Systems—An Algorithmic Study
Lalitha Krishnasamy, Divya Vetriveeran, Rakoth Kandan Sambandam and Jenefa J.
6.1 Introduction to the Networked Sensing Systems
6.2 Understanding the Load Balancing Challenges
6.2.1 Types of Load Balancing
6.2.2 Load Balancing Technologies
6.3 Importance of Efficient Resource Allocation
6.4 Overview of Existing Approaches
6.4.1 Probabilistic Clustering
6.4.2 Non-Probability Clustering
6.5 Artificial Intelligence for Resource Handing
6.5.1 Naïve Bayes
6.5.2 Multi-Class SVM
6.5.3 AdaBoost
6.5.4 Clustering
6.5.5 Learning-Based Resource Allocation (LB-RA)
6.5.6 Neural Networks for Load Balancing and Resource Allocation
6.5.7 Reinforcement Learning
6.6 Real-World Applications
6.7 Performance Metrics
6.7.1 Throughput
6.7.2 Reaction Time
6.7.3 Latency
6.7.4 Versatility
6.7.5 Asset Use
6.7.6 Optimization
6.7.7 Fairness
6.7.8 MTTF
6.7.9 Cost Effectiveness
6.7.10 Adaptability
6.8 Research Directions
6.8.1 Edge Computing
6.8.2 ML and AI
6.8.3 Autonomous Resource Management
6.8.4 Containerization and Orchestration
6.8.5 Hybrid and Multi-Cloud Environments
6.8.6 Energy-Efficient Computing
6.8.7 Quantum Figuring
6.8.8 Asset the Executives
6.8.9 Security and Protection Contemplations
6.8.10 Cross-Domain Resource Allocation
6.9 Conclusion and Future Work
Acknowledgments
References
7. Sustainable Cities and Communities: Role of Network Sensing System in Action
Hitesh Mohapatra, Soumya Ranjan Mishra, Amiya Kumar Rath and Manjur Kolhar
7.1 Introduction
7.2 Literature Review
7.3 Proposed Study
7.3.1 Star Topology
7.3.2 Mesh Topology
7.3.3 Tree Topology
7.3.4 Clustered Topology
7.4 Performance Analysis
7.5 Mapping of Topology with Smart City’s Applications
7.5.1 Mapping of Star Topology with Smart Parking Application
7.5.2 Mapping of Mesh Topology with Smart Grid Application
7.5.3 Mapping of Tree Topology with Smart Education Model
7.5.4 Mapping of Cluster Topology with Smart Health Care Model
7.6 Conclusion
References
8. Air Pollution Monitoring and Control Via Network Sensing Systems in Smart Cities
S. Sharmila Devi
8.1 Introduction
8.2 Related Works
8.3 Air Quality System
8.4 Air Quality Monitoring Techniques
8.5 Conventional Air Pollution Monitoring
8.5.1 Manual Measurement and Evaluation of Air Quality
8.5.2 Automated Continuous Monitoring Devices
8.5.3 Monitoring Air Quality with Sensing Technology
8.6 Wireless Sensor Network for Air Monitoring
8.6.1 Wireless Sensor Networks
8.6.2 WSN Network Topologies
8.6.3 Zigbee Standard
8.7 Architecture of Wireless Sensor Networks
8.7.1 Fire and Flood Detection
8.7.2 Biocomplexity
8.7.3 Habitat Monitoring
8.7.4 Factors Influencing the Efficacy of Inexpensive Sensors in the Monitoring of Air Pollution
8.8 WSN-Based Air Pollution Monitoring in Smart Cities
8.9 Conclusion
References
9. Interconnected Healthcare 5.0 Ecosystems: Enhancing Patient Care Using Sensor Networks
Ashwini A., Kavitha V. and Balasubramaniam S
9.1 Introduction to Healthcare 5.0
9.1.1 Evolution from Healthcare 4.0 to Healthcare 5.0
9.2 Real-Time Monitoring Using Sensor Networks
9.3 Advancements in Remote Patient Monitoring
9.3.1 Challenges in Healthcare 4.0
9.4 Early Disease Detection Through Sensor Networks
9.5 Leveraging Multisensor Data for Comprehensive Health Insights
9.6 Security Measures for Protected Health Information
9.7 Overcoming Infrastructure and Connectivity Barriers
9.8 Improving Treatment Plans Through Sensor-Generated Insights
9.9 Conclusion
References
10. Farming 4.0: Cultivating the Future with Internet of Things Empowered on Smart Agriculture Solutions
Ashwini A., S.R. Sriram, J. Manoj Prabhakar and Seifedine Kadry
10.1 Introduction to Smart Agriculture and IoT Integration
10.1.1 Evolution of Agriculture: From Traditional to Smart Farming
10.2 IoT Sensor Networks in Farming
10.2.1 IoT Sensors and Their Applications
10.3 Smart Pest and Disease Control in Crop Production
10.3.1 Meticulous Fertilization and Nutrition Control
10.3.2 Accurate Irrigation Techniques and Water Administration
10.4 Automation and Robotics in Agriculture
10.4.1 Agricultural Operations Using Automatic Systems
10.4.2 AI in Farm Automation
10.5 Cloud Computing for Agricultural Data Management
10.6 Big Data Analytics for Predictive Farming
10.7 Sustainable Practices with IoT in Agriculture
10.8 The Future Landscape of Farming 4.0
10.9 Conclusion
References
11. Public Safety Management in Smart Society 5.0: A Blockchain-Based Approach
P.N. Senthil Prakash, S. Karthic and M. Saravanan
11.1 Introduction
11.2 Security Challenges in Society 5.0
11.3 Blockchain in Society 5.0
11.3.1 Blockchain for Refinery Industry
11.3.2 Blockchain in Identity Management
11.3.3 Blockchain and Its Impact in Healthcare
11.3.4 Blockchain for Supply Chain Management
11.3.5 Blockchain in Asset Management
11.3.6 Blockchain in Copyright Management
11.4 Conclusion
References
12. Virtualization of Smart Society 5.0 Using Artificial Intelligence and Virtual Reality
Sakthivel Sankaran, M. Arun and R. Kottaimalai
12.1 Introduction to Smart Society 5.0
12.1.1 Smart Society 5.0 and Its Key Characteristics
12.1.2 Evolution from Previous Smart Society Models
12.2 Foundations of Virtual Reality
12.2.1 Brief History and Development of Virtual Reality
12.2.2 Key Components and Technologies in VR
12.2.3 VR Hardware and Software Ecosystems
12.3 Artificial Intelligence in Smart Societies
12.3.1 Overview of AI Technologies Shaping Smart Societies
12.3.2 Role of AI in Data Analytics, Automation, and Decision Making
12.3.3 AI-Driven Applications in Healthcare, Transportation, and Education
12.4 Integration of AI and VR
12.4.1 How AI and VR Technologies Complement Each Other
12.4.2 Examples of AI-Enhanced Virtual Reality Applications
12.4.3 Possibilities and Obstacles When Fusing AI with VR
12.5 AI and VR in Education
12.5.1 Virtual Classrooms and Immersive Learning Experiences
12.5.2 AI-Enabled Adaptive Learning Systems
12.5.3 Skill Development and Training Using VR and AI
12.6 Smart Society 5.0 Healthcare Innovations
12.6.1 Virtual Healthcare Consultations and Simulations
12.6.2 AI-Driven Diagnostics and Treatment Planning
12.6.3 VR and AI-Based Treatments and Rehab
12.7 Challenges and Future Directions
12.7.1 Current Obstacles to Integrate VR and AI in Smart Communities
12.7.2 Prospective Developments and Emerging Patterns in AI and VR in Smart Societies
12.7.3 Consider the Role of Emerging Technologies
12.8 Conclusion
12.8.1 Summary of AI and VR Technologies in Smart Societies
12.8.2 Vision for the Future of Smart Societies with AI and VR
References
13. Battery Power Management Schemes Integrated with Industrial IoT for Sustainable Industry Development
D. Karthikeyan, A. Geetha, K. Deepa and Malathy Sathyamoorthy
13.1 Introduction
13.2 Current Battery Technologies
13.2.1 Metal–Air Battery
13.2.2 Lithium–Sulfur Battery
13.2.3 Batteries Beyond Lithium
13.3 Battery Energy Storage and Management
13.4 IoT and Cloud Computing Technology in BMS
13.5 Sustainable Developments via BMS
13.5.1 SDG8
13.5.2 SDG9
13.5.3 SDG12
13.5.4 SDG13
13.6 Conclusion
References
14. Trends, Advances, and Applications of Network Sensing Systems
Ashwini A., Shamini G.I. and Balasubramaniam S
14.1 Introduction to Network Sensing Systems
14.1.1 Relevance in Different Sectors
14.2 Real-Time Trends in Sensor Technology
14.2.1 Advanced Sensing Modalities
14.2.2 Power-Efficient Designs
14.3 Advancements in Data Analytics
14.3.1 Big Data Analytics for Sensor-Generated Data
14.4 Applications in Healthcare
14.4.1 Remote Patient Monitoring
14.4.2 Smart Healthcare and Medical Establishments
14.4.3 Fall Detection and Old Care
14.5 Natural Disaster Detection with Response
14.5.1 Early Detection Systems
14.5.2 Satellite Imagery and Tracking
14.5.3 Resilient Communications Networks
14.5.4 Predictive Analysis and Modeling
14.6 Agricultural Sensing Systems
14.6.1 Crop Monitoring and Management
14.6.2 Soil Sensing and Precision Agriculture
14.6.3 Weather Monitoring and Forecasting
14.6.4 Livestock Monitoring and Management
14.6.5 Data Analytics and Decision Support System
14.6.6 Remote Monitoring and Automation
14.7 Intelligent Transportation Systems
14.8 Smart City Applications
14.9 Challenges
14.10 Conclusion
References
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