Intelligent Green Technologies for Sustainable Smart Cities
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portes grátis
Intelligent Green Technologies for Sustainable Smart Cities
Tripathi, Suman Lata; Magradze, Tengiz; Kumar, Abhishek; Ganguli, Souvik
John Wiley & Sons Inc
11/2022
368
Dura
Inglês
9781119816065
15 a 20 dias
666
Descrição não disponível.
Preface xv
List of Contributors xvii
1 An Overview of the Intelligent Green Technologies for Sustainable Smart Cities 1
Tanya 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 19
Shanthi 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 33
G. 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 53
Soumitra 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 73
Simran 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 89
Arjyadhara 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 111
Salwa 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 143
Souvik 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 165
Amal 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 195
Deepak 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 227
Shasanka 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 247
Biyyapu 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 269
Deepti 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 291
K. 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 317
Jagendra 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 331
S. 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 339
About the Editors 341
Index 343
List of Contributors xvii
1 An Overview of the Intelligent Green Technologies for Sustainable Smart Cities 1
Tanya 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 19
Shanthi 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 33
G. 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 53
Soumitra 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 73
Simran 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 89
Arjyadhara 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 111
Salwa 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 143
Souvik 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 165
Amal 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 195
Deepak 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 227
Shasanka 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 247
Biyyapu 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 269
Deepti 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 291
K. 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 317
Jagendra 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 331
S. 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 339
About the Editors 341
Index 343
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Green Energy; Smart cities; Renewable resources; AI technique; Machine learning; Solar cells; Biofuels; Power Devices; Energy-efficient systems; Wind energy; Power Electronics; Privacy and security; Waste management; Green technology; Electric vehicle; Smart healthcare; Urban planning; Portable wearables; Low Power; IoT; Internet of Things; Green Energy; Solar cell; Solar panel; Wind power generation ; Energy Management Systems (EMS); Artificial Intelligence; Machine Learning; Energy Model Simulation; Fabrication process of Solar cell; Electric vehicle; Floating Solar Plant; Biofuels; Power Quality; DC; DC converters; Microgrid; Energy Efficiency; Doubly-Fed Induction Generators; Multi-Level Inverters; Li-Ion Batteries; Harris Hawks Optimization; Solar energy; wind energy; nuclear energy; fuel cells; wave energy; biofeedstocks; geothermal energy; oil; gas; clean coal; drilling; process engineering; electrical systems; power systems; power grid
Preface xv
List of Contributors xvii
1 An Overview of the Intelligent Green Technologies for Sustainable Smart Cities 1
Tanya 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 19
Shanthi 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 33
G. 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 53
Soumitra 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 73
Simran 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 89
Arjyadhara 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 111
Salwa 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 143
Souvik 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 165
Amal 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 195
Deepak 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 227
Shasanka 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 247
Biyyapu 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 269
Deepti 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 291
K. 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 317
Jagendra 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 331
S. 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 339
About the Editors 341
Index 343
List of Contributors xvii
1 An Overview of the Intelligent Green Technologies for Sustainable Smart Cities 1
Tanya 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 19
Shanthi 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 33
G. 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 53
Soumitra 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 73
Simran 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 89
Arjyadhara 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 111
Salwa 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 143
Souvik 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 165
Amal 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 195
Deepak 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 227
Shasanka 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 247
Biyyapu 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 269
Deepti 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 291
K. 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 317
Jagendra 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 331
S. 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 339
About the Editors 341
Index 343
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Green Energy; Smart cities; Renewable resources; AI technique; Machine learning; Solar cells; Biofuels; Power Devices; Energy-efficient systems; Wind energy; Power Electronics; Privacy and security; Waste management; Green technology; Electric vehicle; Smart healthcare; Urban planning; Portable wearables; Low Power; IoT; Internet of Things; Green Energy; Solar cell; Solar panel; Wind power generation ; Energy Management Systems (EMS); Artificial Intelligence; Machine Learning; Energy Model Simulation; Fabrication process of Solar cell; Electric vehicle; Floating Solar Plant; Biofuels; Power Quality; DC; DC converters; Microgrid; Energy Efficiency; Doubly-Fed Induction Generators; Multi-Level Inverters; Li-Ion Batteries; Harris Hawks Optimization; Solar energy; wind energy; nuclear energy; fuel cells; wave energy; biofeedstocks; geothermal energy; oil; gas; clean coal; drilling; process engineering; electrical systems; power systems; power grid
