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<p><b>1 Analysis and Clustering of Sensor Recorded Data to Determine Sensors Consuming the Least Energy<br /></b><i>Prashant Abbi, Khushi Arora, Praveen Kumar Gupta, K.B. Ashwini, V. Chayapathy, and M.J. Vidya</i></p> <p>1.1 Importance of Low Energy Consumption Sensors</p> <p>1.2 Methodology: Clustering Using K Means and Classification Using KNN</p> <p>1.3 Objective Realization and Result of Analysis</p> <p>1.4 Introduction</p> <p>1.5 Working of WSNs and Sensor Nodes</p> <p>1.6 Classification of WSNs</p> <p>1.6.1 Benefits and Drawbacks of Centralized Techniques</p> <p>1.6.2 Benefits and Drawbacks of Distributed Techniques</p> <p>1.7 Security Issues</p> <p>1.7.1 Layering of Level Based Security</p> <p>1.8 Energy Consumption Issues</p> <p>1.9 Commonly Used Standards and Protocols for WSNs</p> <p>1.9.1 Slotted Protocols</p> <p>1.9.1.1 Time Division Multiple Access</p> <p>1.9.1.2 Zig Bee/801.15.4</p> <p>1.9.1.3 Sensor Medium Access Control</p> <p>1.10 Effects of Temperature and Humidity on the Energy of WSNs</p> <p>1.10.1 Effects of Temperature on Signal Strength</p> <p>1.10.2 Effects of Humidity on Signal Strength</p> <p>1.10.3 Temperature Vs. Humidity</p> <p>1.11 Proposed Methodology</p> <p>1.11.1 Information Gathering and Analysis</p> <p>1.11.2 System Design and Implementation</p> <p>1.11.3 Testing and Evaluation</p> <p>1.12 Conclusion</p> <p>References</p> <p><b>2 Impact of Artificial Intelligence in Designing of 5G<br /></b><i>K. Maheswari, Mohankumar, and Banuroopa</i></p> <p>2.1 5G – An Introduction</p> <p>2.1.1 Industry Applications</p> <p>2.1.2 Healthcare</p> <p>2.1.3 Retail</p> <p>2.1.4 Agriculture</p> <p>2.1.5 Manufacturing</p> <p>2.1.6 Logistics</p> <p>2.1.7 Sustainability of 5G Networks</p> <p>2.1.8 Implementation of 5G</p> <p>2.1.9 Architecture of 5G Technology</p> <p>2.2 5G and AI</p> <p>2.2.1 Gaming and Virtual Reality</p> <p>2.3 AI and 5G</p> <p>2.3.1 Continuous Learning AI Model</p> <p>2.4 Challenges and Roadmap</p> <p>2.4.1 Technical Issues</p> <p>2.4.2 Technology Roadmap</p> <p>2.4.3 Deployment Roadmap</p> <p>2.5 Mathematical Models</p> <p>2.5.1 The Insights of Mathematical Modeling in 5G Networks</p> <p>2.6 Conclusion</p> <p>References</p> <p><b>3 Sustainable Paradigm for Computing the Security of Wireless Internet of Things: Blockchain Technology<br /></b><i>Sana Zeba, Mohammed Amjad, and Danish Raza Rizvi</i></p> <p>3.1 Introduction</p> <p>3.2 Research Background</p> <p>3.2.1 The Internet of Things</p> <p>3.2.1.1 Security Requirements in Wireless IoT</p> <p>3.2.1.2 Layered Architecture of Wireless IoT</p> <p>3.2.2 Blockchain Technology</p> <p>3.2.2.1 Types of Blockchain</p> <p>3.2.2.2 Integration of Blockchain with Wireless Internet of Things</p> <p>3.3 Related Work</p> <p>3.3.1 Security Issues in Wireless IoT System</p> <p>3.3.2 Solutions of Wireless IoT Security Problem</p> <p>3.4 Research Methodology</p> <p>3.5 Comparison of Various Existing Solutions</p> <p>3.6 Discussion of Research Questions</p> <p>3.7 Future Scope of Blockchain in IoT</p> <p>3.8 Conclusion</p> <p>References</p> <p><b>4 Cognitive IoT Based Health Monitoring Scheme Using Non-Orthogonal MultipleAccess<br /></b><i>Ashiqur Rahman Rahul, Saifur Rahman Sabuj, Majumder Fazle Haider, andShakil Ahmed</i></p> <p>4.1 Introduction</p> <p>4.2 Related Work</p> <p>4.3 System Model and Implementation</p> <p>4.3.1 Network Description</p> <p>4.3.2 Sensing and Transmission Analysis</p> <p>4.3.3 Pathloss Model</p> <p>4.3.4 Mathematical Model Evaluation</p> <p>4.3.4.1 Effectual Throughput</p> <p>4.3.4.2 Interference Throughput</p> <p>4.3.4.3 Energy Efficiency</p> <p>4.3.4.4 Optimum Power</p> <p>4.3.4.4.1 Optimum Power Derivation for HRC</p> <p>4.2.3.4.2 Optimum Power Derivation for MRC</p> <p>4.4 Simulation Results</p> <p>4.5 Conclusion</p> <p>4.A Appendices</p> <p>4.A.1 Proof of Optimum Power Transmission for HRC Device at EffectualState (z = 0)</p> <p>4.A.2 Proof of Optimum Power Transmission for HRC Device inInterference State (z = 1)</p> <p>4.A.3 Proof of Optimum Power Transmission for MRC Device at EffectualState (z = 0)</p> <p>4.A.4 Proof of Optimum Power Transmission for MRC Device inInterference State (z = 1)</p> <p>References</p> <p><b>5 Overview of Resource Management for Wireless Adhoc Network<br /></b><i>Mehajabeen Fatima and Afreen Khueaheed</i></p> <p>5.1 Introduction</p> <p>5.1.1 Wired and Wireless Network Design Approach</p> <p>5.1.2 History</p> <p>5.1.3 Spectrum of Wireless Adhoc Network</p> <p>5.1.4 Enabling and Networking Technologies</p> <p>5.1.5 Taxonomy of Wireless Adhoc Network (WANET)</p> <p>5.2 Mobile Adhoc Network (MANET)</p> <p>5.2.1 Introduction to MANET</p> <p>5.2.2 Common Characteristics of MANET</p> <p>5.2.3 Advantages and Disadvantages</p> <p>5.2.4 Applications of MANET</p> <p>5.2.5 Major Issues of MANET</p> <p>5.3 Vehicular Adhoc Network (VANET)</p> <p>5.3.1 Introduction of VANET</p> <p>5.3.2 Common Features of VANET</p> <p>5.3.3 Pros, Cons, Applications</p> <p>5.4 Wireless Mesh Network (WMN)</p> <p>5.4.1 Preface of WMN</p> <p>5.4.2 Common Traits of WMN</p> <p>5.4.3 WMN Has Many Open Issues and Research Challenges</p> <p>5.4.4 Performance Metrics</p> <p>5.4.5 Advantages and Disadvantages</p> <p>5.4.6 Prominent Areas and Challenges of WMN</p> <p>5.5 Wireless Sensor Network (WSN)</p> <p>5.5.1 Overview of WSN</p> <p>5.5.2 Common Properties of WSN</p> <p>5.5.3 Benefits, Harms, and Usage of WSN</p> <p>5.6 Intelligent Management in WANET</p> <p>5.6.1 Major Issues of WANET</p> <p>5.6.2 Challenges of MAC Protocols</p> <p>5.6.3 Routing Protocols</p> <p>5.6.3.1 Challenges of Routing Protocols</p> <p>5.6.3.1.1 Scalability</p> <p>5.6.3.1.2 Quality of Service</p> <p>5.6.3.1.3 Security</p> <p>5.6.4 Energy and Battery Management</p> <p>5.7 Future Research Directions</p> <p>5.8 Conclusion</p> <p>References</p> <p><b>6 Survey: Brain Tumor Detection Using MRI Image with Deep Learning Techniques<br /></b><i>Chalapathiraju Kanumuri and C.H. Renu Madhavi</i></p> <p>6.1 Introduction</p> <p>6.2 Background</p> <p>6.2.1 Types of Medical Imaging</p> <p>6.2.2 M. R. Imaging as a Modality</p> <p>6.2.3 Types of Brain Tumor M. R. Imaging Modalities</p> <p>6.2.4 Suitable Technologies Before Machine Learning</p> <p>6.2.5 MRI Brain Image Segmentation</p> <p>6.3 Related Work</p> <p>6.4 Gaps and Observations</p> <p>6.5 Suggestions</p> <p>6.6 Conclusion</p> <p>References</p> <p><b>7 Challenges, Standards, and Solutions for Secure and Intelligent 5G Internet of Things (IoT) Scenarios<br /></b><i>Ayasha Malik and Bharat Bhushan</i></p> <p>7.1 Introduction</p> <p>7.2 Safety in Wireless Networks: Since 1G to 4G</p> <p>7.2.1 Safety in Non-IP Networks</p> <p>7.2.2 Safety in 3G</p> <p>7.2.3 Security in 4G</p> <p>7.2.4 Security in 5G</p> <p>7.2.4.1 Flashy System Traffic and Radio Visual Security Keys</p> <p>7.2.4.2 Authorized Network Security and Compliance with Subscriber Level Safety Policies</p> <p>7.2.5 Security in 5G and Beyond</p> <p>7.3 IoT Background and Requirements</p> <p>7.3.1 IoT and Its Characteristics</p> <p>7.3.2 Characteristics of IoT Infrastructure</p> <p>7.3.3 Characteristics of IoT Applications</p> <p>7.3.4 Expected Benefits of IoT Adoption for Organization</p> <p>7.3.4.1 Benefits Correlated to Big Data Created by IoT</p> <p>7.3.4.2 Benefits Interrelated to the Openness of IoT</p> <p>7.3.4.3 BenefitsRelated to the Linked Aspect6 of IoT</p> <p>7.4 Non 5G Standards Supporting IoT</p> <p>7.4.1 Bluetooth Low Energy</p> <p>7.4.2 IEEE 802.15.4</p> <p>7.4.3 LoRa</p> <p>7.4.4 Sigfox</p> <p>7.4.5. WiFi HaLow</p> <p>7.5 5 G Advanced Security Model</p> <p>7.5.1 Confidentiality</p> <p>7.5.2 Integrity</p> <p>7.5.3 Accessibility</p> <p>7.5.4 Integrated Safety Rule</p> <p>7.5.5 Visibility</p> <p>7.6 Safety Challenges and Resolution of Three-Tiers Structure of 5G Networks</p> <p>7.6.1 Heterogeneous Access Networks</p> <p>7.6.1.1 Safety Challengers</p> <p>7.6.1.2 Safety Resolutions</p> <p>7.6.2 Backhaul Networks</p> <p>7.6.2.1 Safety Challenges</p> <p>7.6.2.2 Safety Resolutions</p> <p>7.6.3 Core Network</p> <p>7.6.3.1 Safety Challenges</p> <p>7.6.3.2 Safety Resolutions</p> <p>7.7 Conclusion and Future Research Directions</p> <p>References</p> <p><b>8 Blockchain Assisted Secure Data Sharing in Intelligent Transportation Systems<br /></b><i>Gujkan Madaan, Avinash Kumar, and Bharat Bhushan</i></p> <p>8.1 Introduction</p> <p>8.2 Intelligent Transport System</p> <p>8.2.1 ITS Overview</p> <p>8.2.2 Issues in ITS</p> <p>8.2.3 ITS Role in IoT</p> <p>8.3 Blockchain Technology</p> <p>8.3.1 Overview</p> <p>8.3.2 Types of Blockchain</p> <p>8.3.2.1 Public Blockchain</p> <p>8.3.2.3 Private Blockchain</p> <p>8.2.3.2 Federated Blockchain</p> <p>8.3.3 Consensus Mechanism</p> <p>8.3.3.1 Proof of Work</p> <p>8.3.3.2 Proof of Stake</p> <p>8.3.3.3 Delegated Proof of Stake</p> <p>8.3.3.4 Practical Byzantine Fault Tolerance</p> <p>8.3.3.5 Casper</p> <p>8.3.3.6 Ripple</p> <p>8.3.3.7 Proof of Activity</p> <p>8.3.4 Cryptography</p> <p>8.3.5 Data Management and Its Structure</p> <p>8.4 Blockchain Assisted Intelligent Transportation System</p> <p>8.4.1 Security and Privacy</p> <p>8.4.2 Blockchain and Its Application foe Improving Security and Privacy</p> <p>8.4.3 ITS Based on Blockchain</p> <p>8.4.4 Recent Advancement</p> <p>8.5 Future Research Perspectives</p> <p>8.5.1 Electric Vehicle Recharging</p> <p>8.5.2 Smart City Enabling and Smart Vehicle Security</p> <p>8.5.3 Deferentially-Privacy Preserving Solutions</p> <p>8.5.4 Distribution of Economic Profits and Incentives</p> <p>8.6 Conclusion</p> <p>References</p> <p><b>9 Utilization of Agro Waste for Energy Engineering Applications: Toward the Manufacturing of Batteries and Super Capacitors<br /></b><i>S.N. Kumar, S. Akhil, R.P. Nishita, O. Lijo Joseph, Aju Matthew George, and I Christina Jane</i></p> <p>9.1 Introduction</p> <p>9.2 Super Capacitors and Electrode Materials</p> <p>9.2.1 Energy Density</p> <p>9.3 Related Works in the Utilization of Agro Waste for Energy EngineeringApplications</p> <p>9.4 Inferences from Work Related with Utilization of Coconut. Rice Husk, andPineapple Waste for Fabrication of Super Capacitor</p> <p>9.5 Factors Contributing in the Fabrication of Super Capacitor from Agro Waste</p> <p>9.6 Conclusion</p> <p>Acknowledgment</p> <p>References</p> <p><b>10 Computational Intelligence Techiques for Optimization in Networks<br /></b><i>Ashu Gautam and Rashima Mahajan</i></p> <p>10.1 Introduction Focussing on Pedagogy of Impending Approach</p> <p>10.1.1 Security Challenge in Networks</p> <p>10.1.2 Attacks Vulnerability in Complex Networks</p> <p>10.2 Relevant Analysis</p> <p>10.3 Broad Area of Research</p> <p>10.3.1 Routing Protocols</p> <p>10.3.2 Hybrid Protocols</p> <p>10.4 Problem Identification</p> <p>10.5 Objectives of the Study</p> <p>10.6 Methodology to be Adopted</p> <p>10.7 Proposed/Expected Outcome of the Research</p> <p>References</p> <p><b>11 R&D Export and ICT Regimes in India<br /><br /></b><i>Zeba, M. Afshar Alam, Harleen Kaur*, Ihtiram Raza Khan, Bhavya Alankar<br />Corresponding Author: Harleen Kaur<br /><br /></i></p> <p>11.1 Introduction</p> <p>11.2 Artificial Intelligence: the Uptake of Infrastructure Development</p> <p>11.3 Future Analysis and Conclusion</p> <p>References</p> <p><b>12 Metaheuristics to Aid Energy-Efficient Path Selection in Route Aggregated Mobile Ad Hoc Networks<br /></b><i>Deepa Mehta, Sherin Zafar, Siddhartha Sankar Biswas, Nida Iftekhar, and Samia Khan</i></p> <p>12.1 Introduction</p> <p>12.2 Framework</p> <p>12.2.1 Route Aggregation</p> <p>12.3 Clustering</p> <p>12.4 Ant Colony Optimization</p> <p>12.4.1 Setting Parameters and Initializing</p> <p>12.4.2 Generating Solutions</p> <p>12.4.3 Pheromone Update</p> <p>12.5 Methodology</p> <p>12.5.1 Energy Efficient ACO Algorithm</p> <p>12.5.2 ACO Aided Cluster and Head Selection</p> <p>12.5.3 ACO Aided Route Aggregation</p> <p>12.5.4 ACO Aided Energy: Efficient Path Selection</p> <p>12.6 Results</p> <p>12.7 Discussion</p> <p>12.8 Conclusion</p> <p>References</p> <p><b>13 Knowledge Analytics in IOMT-MANET Through QoS Optimization for Sustainability<br /></b><i>Neha Sharma, Nida Iftekhar, and Samia Khan</i></p> <p>13.1 Introduction</p> <p>13.2 Related Work</p> <p>13.3 Proposed Neoteric Nature Inspired IWD Algorithm for ZRP</p> <p>13.4 Simulation Results</p> <p>13.5 Conclusion and Future Work</p> <p>References</p> <p><b>14 Appraise Assortment of IOT Security Optimization<br /></b><i>Ayesha Hena Afzal and M. Afshar Alam</i></p> <p>14.1 Introduction</p> <p>14.2 Literature Review</p> <p>14.3 Analysis of Traditional Security Mechanisms in IOT</p> <p>14.4 Conclusion and Future Scope</p> <p>References</p> <p><b>15 Trust Based Hybrid Routing Approach for Securing MANET<br /></b><i>Neha Sharma and Satrupa Biswas</i></p> <p>15.1 Introduction</p> <p>15.2 Literature Review</p> <p>15.3 Gaps and Objectives from the Literature Review</p> <p>15.4 Methodology to be Adopted</p> <p>15.5 Comparison Analysis</p> <p>15.6 Conclusion and Future Scope</p> <p>References</p> <p><b>16 Study of Security Issues on Open Channel<br /></b><i>Md Mudassir Chaudhary, Siddhartha Sankar Biswas, Md Tabrez Nafis, and Safdar Tenweer</i></p> <p>16.1 Introduction</p> <p>16.2 Wireless Attacks</p> <p>16.2.1 Reconnaissance Attack</p> <p>16.2.2 Access Attacks</p> <p>16.2.3 Man-in-the-Middle Attack</p> <p>16.2.4 Denial of Services (DOS)</p> <p>16.3 Securing Wireless Transmissions</p> <p>16.3.1 Protecting the Confidentiality</p> <p>16.3.2 Protecting the Modification</p> <p>16.3.3 Preventing Interruption of Denial-of-Service Attack</p> <p>16.4 Proposed Model for Securing the Client Over the Channel</p> <p>16.5 Conclusion</p> <p>References</p>

<p><b>Sherin Zafar, PhD, </b>Assistant Professor, Department of Computer Science, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India.</p> <p><b>Mohd Abdul Ahad, PhD,</b> Assistant Professor, Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India. <p><B>Syed Imran Ali, PhD,</b> Lecturer, University of Technology and Applied Sciences, Al Musannah Sultanate of Oman. <p><b>Deepa Mehta, PhD, </b>Senior Data Scientist, Great Learning. <p><b>M. Afshar Alam, PhD,</b> Vice Chancellor Jamia Hamdard, New Delhi, India.

<p><b>Explores the intersection of sustainable growth, green computing and automation, and performance optimization of 5G wireless networks</b></p> <p><i>Smart and Sustainable Approaches for Optimizing Performance of Wireless Networks</i> explores how wireless sensing applications, green computing, and Big Data analytics can increase the energy efficiency and environmental sustainability of real-time applications across areas such as healthcare, agriculture, construction, and manufacturing. <p>Bringing together an international team of expert contributors, this authoritative volume highlights the limitations of conventional technologies and provides methodologies and approaches for addressing Quality of Service (QOS) issues and optimizing network performance. In-depth chapters cover topics including blockchain-assisted secure data sharing, smart 5G Internet of Things (IoT) scenarios, intelligent management of ad hoc networks, and the use of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) techniques in smart healthcare, smart manufacturing, and smart agriculture. <ul><li>Covers design, implementation, optimization, and sustainability of wireless and sensor-based networks</li> <li>Discusses concepts of sustainability and green computing as well as their relevance to society and the environment </li> <li>Addresses green automation applications in various disciplines such as computer science, nanoscience, information technology (IT), and biochemistry</li> <li>Explores various smart and sustainable approaches for current wireless and sensor-based networks</li> <li>Includes detailed case studies of current methodologies, applications, and implementations</li></ul> <p><i>Smart and Sustainable Approaches for Optimizing Performance of Wireless Networks: Real-time Applications</i> is an essential resource for academic researchers and industry professionals working to integrate sustainable development and Information and Communications Technology (ICT).

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