Preface xv List of Contributors xvii 1 An Overview of the Intelligent Green Technologies for Sustainable Smart Cities 1Tanya Srivastava, Sahil Virk and Souvik Ganguli 1.1 Introduction 2 1.2 Case Study 1: Oslo—A Smart City 5 1.3 Case Study 2: Chandigarh—A Smart City 5 1.4 Features of the Smart Cities 6 1.5 Well-Planned Public Spaces and Streets 6 1.5.1 Waste Management 6 1.5.2 Energy Management 7 1.5.3 Good Connectivity 7 1.5.4 Urban Residence 8 1.5.5 Smart Grids 8 1.5.6 Smart Governance 8 1.6 Intelligent Green Technologies 9 1.7 Global and National Acceptance Scenarios 13 1.8 Conclusions 15 References 15 2 Artificial Intelligence for Green Energy Technology 19Shanthi Jayaraj and Meena Chinniah 2.1 Introduction 19 2.2 Solar Energy and AI 20 2.3 AI Transforms Renewable Energy 23 2.4 IBM Solution Using AI 24 2.5 Hydrogen Vehicles 24 2.6 Wind Energy and AI 25 2.7 Renewable Energy Industry in India 29 2.8 Conclusion 30 References 30 Website Reference 31 Abbreviations 31 3 Effective Waste Management System for Smart Cities 33G. Boopathi Raja 3.1 Introduction 34 3.2 Literature Survey 36 3.3 Waste Management in India 37 3.4 Existing Methodology 40 3.4.1 IoT-Based Smart Waste Bin Monitoring and Municipal Solid Waste Management System 40 3.4.2 IoT Enabled Solid Waste Management System 41 3.4.3 Smart Garbage Management System 41 3.5 Proposed Framework 42 3.5.1 System Description 42 3.6 Functionality of the Proposed System 44 3.6.1 Sensing Module 44 3.6.2 Storage Module 46 3.6.3 User Module 47 3.7 Workflow of the Proposed Framework 48 3.8 Conclusion and Future Scope 49 References 50 4 Municipal Solid Waste Energy: An Option for Green Technology for Smart Cities 53Soumitra Mukhopadhyay 4.1 Unavoidable Impacts of Nonrenewable Energy 53 4.2 Municipal Solid Waste Energy as Clean Energy for Smart Cities 55 4.2.1 Renewable Energy Options 55 4.2.2 Municipal Solid Waste as Renewable Energy Option for Smart Cities 56 4.2.3 Why Is MSW Energy Renewable? 58 4.2.4 Various Waste to Energy Technologies 58 4.3 Waste to Energy Technologies (WTE-T) 59 4.3.1 Incineration 59 4.3.2 Pyrolysis 61 4.3.3 Gasification 63 4.3.4 Anaerobic Digestion 65 4.3.5 Landfill with Gas Capture 66 4.3.6 Microbial Fuel Cell (MFC) 68 4.4 Integrated Solid Waste Management Systems (ISWM-S) for Smart Cities 69 4.5 Conclusion 70 References 70 5 E-Waste Management and Recycling Issues: An Overview 73Simran Srivastava, Sahil Virk, Saumyadip Hazra and Souvik Ganguli 5.1 Introduction 73 5.2 Global Status of E-Waste Management 75 5.3 Industrial Practices in E-Waste Management 77 5.4 Recycling of E-Waste 79 5.5 E-Waste Management Benchmarking 81 5.6 Future of E-Waste Management 82 5.7 Conclusions 83 References 84 6 Energy Audit and Management for Green Energy 89Arjyadhara Pradhan and Babita Panda 6.1 Introduction 89 6.2 Types of Renewable Energy 91 6.2.1 Solar Energy 91 6.2.2 Wind Energy 91 6.2.3 Biomass 92 6.2.4 Geothermal Energy 92 6.2.5 Ocean Energy 93 6.3 Energy Management 93 6.3.1 Types of Energy Management 94 6.3.1.1 Demand Side Management 94 6.3.1.2 Implementation of DSM 95 6.3.1.3 Supply Side Management 96 6.3.2 Ways to Improve Energy Management 97 6.4 Energy Audit 97 6.4.1 Types of Energy Audit 98 6.4.2 Preliminary Energy Audit 98 6.4.3 Detailed Energy Audit 98 6.4.4 Data Analysis 100 6.4.5 Detailed Steps in Energy Audit 100 6.5 Energy Audit in Solar Plant 101 6.5.1 Technical Inspection Steps of Solar Power Plant 103 6.6 Energy Conservation 104 6.6.1 Energy Conservation Methods 104 6.6.2 Case Study 105 6.7 Conclusion 108 References 108 7 A Smart Energy-Efficient Support System for PV Power Plants 111Salwa Ammach and Saeed Mian Qaisar 7.1 Introduction 112 7.2 Literature Review 118 7.2.1 Solar Tracking System 119 7.2.2 Solar Cleaning Mechanisms 120 7.2.3 Hotspots Detection 123 7.3 Proposed Solution 131 7.3.1 Solar Tracking 131 7.3.2 Cleaning System 136 7.3.3 Hotspots 136 7.3.4 Modeling and Simulation 136 7.3.5 Limitations 137 7.3.6 Hypothesis 137 7.4 Conclusion 138 References 138 8 A New Hybrid Proposition Based on a Cuckoo Search Algorithm for Parameter Estimation of Solar Cells 143Souvik Ganguli, Shilpy Goyal and Parag Nijhawan 8.1 Introduction 144 8.2 Modelling of an Amended Double Diode Model (ADDM) and the Objective Function 145 8.3 Proposed Work 149 8.4 Results and Discussions 149 8.5 Conclusions 161 References 162 9 Supervisory Digital Feedback Control System for An Effective PV Management and Battery Integration 165Amal E. Abdel Gawad, Nehal A. Alyamani and Saeed Mian Qaisar 9.1 Introduction 166 9.2 Literature Review 173 9.2.1 GHI in the Middle East 173 9.2.2 Types of PV Systems 173 9.2.3 Solar Tracking Systems 176 9.2.4 Charger Controller 179 9.2.5 Series Regulator 179 9.2.6 Shunt Regulator 180 9.2.7 Pulse Width Modulation 180 9.2.8 Maximum Power Point Tracker Charger Controller 181 9.2.9 Reducing the Charging Time 182 9.2.10 Dust Remover 183 9.3 Proposed Solution 185 9.3.1 Single Axis Solar Tracking System 186 9.3.2 Supervisory Digital Feedback Solar Tracker Control System 186 9.3.3 Database-Based Digital Solar Tracker Control System 187 9.3.4 Soiling Treatment Module 187 9.3.5 PV-to-Battery Switching Module 187 9.4 Discussion 189 9.5 Conclusion 191 References 191 10 Performance Analysis of Tunnel Field Effect Transistor for Low-Power Applications 195Deepak Kumar, Shiromani Balmukund Rahi and Neha Paras 10.1 Introduction 196 10.1.1 Limitation of Conventional MOSFET 199 10.1.2 Subthreshold Slope Devices 199 10.2 TFET Structure and Simulation Setup 201 10.3 TFET Working Principle 203 10.3.1 Transport Mechanism in TFET 205 10.3.1.1 Band to Band (BTB) Tunneling Transmission 205 10.3.1.2 Kane’s Model 208 10.4 Subthreshold Swing (SS) in Tunnel FETs 209 10.5 Performance of Hetrojunction Tunnel FET 214 10.5.1 Transfer Characteristics Analysis of TFET Devices 214 10.5.2 Frequency Analysis of TFET Devices 219 10.6 Conclusion 221 References 222 11 Low-Power Integrated Circuit Smart Device Design 227Shasanka Sekhar Rout, Salony Mahapatro, Gaurav Jayaswal and Manish Hooda 11.1 Introduction 228 11.2 Need of Low Power 229 11.3 Design Techniques of Low Power 230 11.3.1 Power Optimization by IC System 230 11.3.2 Power Optimization by Algorithm Section 231 11.3.3 Power Optimization by Architecture Design 231 11.3.4 Power Optimization by Circuit Level 231 11.3.5 Power Optimization by Process Technology 231 11.4 VLSI Circuit Design for Low Power 232 11.4.1 Power Dissipation of CMOS Inverter 232 11.4.1.1 Static Power 232 11.4.1.2 Dynamic Power 233 11.4.1.3 Short Circuit Power Dissipation 233 11.4.1.4 Other Power Issue 233 11.4.2 Capacitance Estimation of CMOS Logic Gate 234 11.5 Circuit Techniques for Low Power 234 11.5.1 Static Power Technique 234 11.5.1.1 Self-Reverse Biasing 234 11.5.1.2 Multithreshold Voltage Technique 235 11.5.2 Dynamic Power Technique 235 11.6 Random Access Memory (RAM) Circuits for Low Power 236 11.6.1 Low-Power Techniques for SRAM 236 11.6.2 Low-Power Techniques for DRAM 237 11.7 VLSI Design Methodologies for Low Power 237 11.7.1 Low-Power Physical Design 237 11.7.2 Low-Power Gate Level Design 237 11.7.2.1 Technology Mapping and Logic Minimization 238 11.7.2.2 Reduction of Spurious Transitions 238 11.7.2.3 Power Reduction by Precomputation 238 11.7.3 Low-Power Architecture Level Design 238 11.8 Power Reduction by Algorithmic Level 239 11.8.1 Lowering in Switched Capacitance 239 11.8.2 Lowering in Switching Activities 239 11.9 Power Estimation Technique 239 11.9.1 Circuit Level Tool 239 11.9.2 Gate Level 240 11.9.3 Architectural Level 240 11.9.4 Behavioral Level 240 11.10 Low-Power Flood Sensor Design 240 11.11 Low-Power VCO Design 241 11.12 Low-Power Gilbert Mixer Design 241 11.13 Conclusion 243 References 243 12 GaN Technology Analysis as a Greater Mobile Semiconductor: An Overview 247Biyyapu Sai Vamsi, Tarun Chaudhary, Deepti Kakkar, Amit Tiwari and Manish Sharma 12.1 Introduction 248 12.2 Research and Collected Data 250 12.3 Studies Reviewed and Findings 255 12.4 Conclusion 266 References 266 13 Multilevel Distributed Energy Efficient Clustering Protocol for Relay Node Selection in Three-Tiered Architecture 269Deepti Kakkar, Gurjot Kaur and Aradhana Tirkey 13.1 Introduction 270 13.1.1 Overview 270 13.1.2 Routing Challenges and Design Issues 271 13.1.3 Heterogeneous Wireless Sensor Networks (HWSNs) 272 13.1.3.1 Clustering in WSN 273 13.1.4 Relay Node Selection Scheme 274 13.1.5 Genetic Algorithm 275 13.1.6 Problem Definition and Motivation 275 13.1.7 Proposed Work 276 13.2 Implementation of Proposed Relay Node Selection Based on GA 276 13.2.1 Network Model 276 13.2.2 Heterogenous Network Model 277 13.2.3 Radio Energy Dissipation Model 279 13.2.4 GA-Based Relay Node Selection 279 13.2.5 Steady State Phase or Data Communication Phase 282 13.3 Results of Simulation For Energy Consumption, Lifetime and Throughput of Network 282 13.3.1 Simulation Setup 282 13.3.2 Comparison of Residual Energy Consumption 284 13.3.3 Comparison of Lifetime of Network 284 13.3.4 Comparison of Throughput at BS 286 13.4 Conclusion and Future Scope 287 References 288 14 Privacy and Security of Smart Systems 291K. Suresh Kumar, D. Prabakaran, R. Senthil Kumaran and I. Yamuna 14.1 Smart Systems—An Overview 291 14.2 Security and Privacy Challenges in Smart Systems 292 14.2.1 Botnet Activities in Smart Systems 294 14.2.2 Threats of Nonhuman-Operated Cars 294 14.2.3 Privacy Issues of Virtual Reality 294 14.3 Case Studies—Security Breaches in Smart Systems 294 14.3.1 Breaching Smart Surveillance Cameras 295 14.3.2 Hacking Smart Televisions 295 14.3.3 Hacked Smart Bulbs 295 14.3.4 Vulnerable Smart Homes 296 14.3.5 Identity Stealing using Smart Coffee Machines 296 14.4 Existing Security and Privacy Protection Technologies 296 14.4.1 Cryptography 297 14.4.2 Biometric 299 14.4.3 Block Chain Technology 301 14.5 Machine Learning, Deep Learning, and Artificial Intelligence 301 14.5.1 Machine Learning in Smart Systems 301 14.5.2 Genetic Algorithm 302 14.5.3 Deep Learning in Smart Systems 303 14.5.4 Artificial Intelligence in Smart Systems 303 14.6 Security Requirement for Smart Systems 303 14.6.1 Thwarting of Data Leakage and Falsifications 304 14.6.2 Identification and Prevention of Device Tampering 304 14.6.3 Light Weight Encryption Algorithm for Authentication 304 14.6.4 Access Restrictions to Users 305 14.6.5 Incident Response for Entire Systems 305 14.7 Instruction to Build Strong Privacy Policy 305 14.7.1 Privacy Policy 305 14.7.2 Definition 306 14.7.3 Key Reasons Why There Is a Need for Privacy Policy 306 14.8 Role of Internet in Smart Systems 306 14.8.1 Home Automation 307 14.8.2 Agriculture 307 14.8.3 Industry 308 14.8.4 Health & Lifestyle 309 14.9 Frameworks, Algorithms, and Protocols for Security Enhancements 310 14.9.1 Framework for the Internet of Things by Cryptography 311 14.9.2 Protocols for Security Enhancements 312 14.10 Design Principles of Privacy Enhancing Methodologies 312 14.11 Conclusion 313 References 314 15 Artificial Intelligence and Blockchain Technologies for Smart City 317Jagendra Singh, Mohammad Sajid, Suneet Kumar Gupta and Raza Abbas Haidri 15.1 Introduction 318 15.2 Standard for Designing Smart City and Society 322 15.2.1 Scalability 322 15.2.2 Intelligent Health Care 322 15.2.3 Flexible and Interoperable 322 15.2.4 Safeguard Infrastructure 322 15.2.5 Robust Environment 323 15.2.6 Distribution and Sources of Energy 323 15.2.7 Intelligent Infrastructure 323 15.2.8 Choice-Based Backing System 323 15.2.9 Monitoring of Behavior 323 15.3 Blockchain and Artificial Intelligence 323 15.4 Contributions and Literature Study 324 15.5 Conclusion 328 References 329 16 Android Application for School Bus Tracking System 331S. Sriram 16.1 Introduction 331 16.2 Application Methods for Access 332 16.2.1 Driver Portal Screen 333 16.2.2 Parent Portal Screen 334 16.2.3 Teachers Portal Screen 334 16.3 GPS Data Processing Methodology 335 16.4 GPS Working Process 336 16.5 System Implementation 336 16.6 Result and Discussion 336 16.6.1 Reasons to Utilize Android Application for School Bus Tracking System 337 16.6.1.1 Perfect Child Security 337 16.6.1.2 Elaborate Operational Efficiency 337 16.6.1.3 Valid Timely Maintenance 338 16.6.1.4 Automating Attendance Management 338 16.6.1.5 Better Staff Management 338 16.6.1.6 Addressing Environmental Concerns 338 16.7 Conclusion 338 References 339About the Editors 341 Index 343

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