Intelligent Green Technologies for Sustainable Smart Cities

Description

Intelligent Green Technologies for Sustainable Smart Cities Presenting the concepts and fundamentals of smart cities and developing “green” technologies, this volume, written and edited by a global team of experts, also goes into the practical applications that can be utilized across multiple disciplines and industries, for both the engineer and the student. Smart cities and green technologies are quickly becoming two of the most important areas of development facing today’s engineers, scientists, students, and other professionals. Written by a team of experts in these fields, this outstanding new volume tackles the problem of detailing advances in smart city development, green technologies, and where the two areas intersect to create innovation and revolutionary solutions. This group of hand-selected and vetted papers deals with the fundamental concepts of adapting artificial intelligence, machine learning techniques with green technologies, and many other advances in concepts related to these key areas. Including the most recent research and developments available, this book is an extraordinary source of knowledge for students, engineers seeking the latest research, and facilities and other professionals working in the area of green technologies and challenges and solutions in urban planning and smart city development. Cover Title Page Copyright Page Contents Preface List of Contributors Chapter 1 An Overview of the Intelligent Green Technologies for Sustainable Smart Cities 1.1 Introduction 1.2 Case Study 1: Oslo—A Smart City 1.3 Case Study 2: Chandigarh—A Smart City 1.4 Features of the Smart Cities 1.5 Well-Planned Public Spaces and Streets 1.5.1 Waste Management 1.5.2 Energy Management 1.5.3 Good Connectivity 1.5.4 Urban Residence 1.5.5 Smart Grids 1.5.6 Smart Governance 1.6 Intelligent Green Technologies 1.7 Global and National Acceptance Scenarios 1.8 Conclusions References Chapter 2 Artificial Intelligence for Green Energy Technology 2.1 Introduction 2.2 Solar Energy and AI 2.3 AI Transforms Renewable Energy 2.4 IBM Solution Using AI 2.5 Hydrogen Vehicles 2.6 Wind Energy and AI 2.7 Renewable Energy Industry in India 2.8 Conclusion References Website Reference Abbreviations Chapter 3 Effective Waste Management System for Smart Cities 3.1 Introduction 3.2 Literature Survey 3.3 Waste Management in India 3.4 Existing Methodology 3.4.1 IoT-Based Smart Waste Bin Monitoring and Municipal Solid Waste Management System 3.4.2 IoT Enabled Solid Waste Management System 3.4.3 Smart Garbage Management System 3.5 Proposed Framework 3.5.1 System Description 3.6 Functionality of the Proposed System 3.6.1 Sensing Module 3.6.2 Storage Module 3.6.3 User Module 3.7 Workflow of the Proposed Framework 3.8 Conclusion and Future Scope References Chapter 4 Municipal Solid Waste Energy: An Option for Green Technology for Smart Cities 4.1 Unavoidable Impacts of Nonrenewable Energy 4.2 Municipal Solid Waste Energy as Clean Energy for Smart Cities 4.2.1 Renewable Energy Options 4.2.2 Municipal Solid Waste as Renewable Energy Option for Smart Cities 4.2.3 Why Is MSW Energy Renewable? 4.2.4 Various Waste to Energy Technologies 4.3 Waste to Energy Technologies (WTE-T) 4.3.1 Incineration 4.3.2 Pyrolysis 4.3.3 Gasification 4.3.4 Anaerobic Digestion 4.3.5 Landfill with Gas Capture 4.3.6 Microbial Fuel Cell (MFC) 4.4 Integrated Solid Waste Management Systems (ISWM-S) for Smart Cities 4.5 Conclusion References Chapter 5 E-Waste Management and Recycling Issues: An Overview 5.1 Introduction 5.2 Global Status of E-Waste Management 5.3 Industrial Practices in E-Waste Management 5.4 Recycling of E-Waste 5.5 E-Waste Management Benchmarking 5.6 Future of E-Waste Management 5.7 Conclusions References Chapter 6 Energy Audit and Management for Green Energy 6.1 Introduction 6.2 Types of Renewable Energy 6.2.1 Solar Energy 6.2.2 Wind Energy 6.2.3 Biomass 6.2.4 Geothermal Energy 6.2.5 Ocean Energy 6.3 Energy Management 6.3.1 Types of Energy Management 6.3.1.1 Demand Side Management 6.3.1.2 Implementation of DSM 6.3.1.3 Supply Side Management 6.3.2 Ways to Improve Energy Management 6.4 Energy Audit 6.4.1 Types of Energy Audit 6.4.2 Preliminary Energy Audit 6.4.3 Detailed Energy Audit 6.4.4 Data Analysis 6.4.5 Detailed Steps in Energy Audit 6.5 Energy Audit in Solar Plant 6.5.1 Technical Inspection Steps of Solar Power Plant 6.6 Energy Conservation 6.6.1 Energy Conservation Methods 6.6.2 Case Study 6.7 Conclusion References Chapter 7 A Smart Energy-Efficient Support System for PV Power Plants 7.1 Introduction 7.2 Literature Review 7.2.1 Solar Tracking System 7.2.2 Solar Cleaning Mechanisms 7.2.3 Hotspots Detection 7.3 Proposed Solution 7.3.1 Solar Tracking 7.3.2 Cleaning System 7.3.3 Hotspots 7.3.4 Modeling and Simulation 7.3.5 Limitations 7.3.6 Hypothesis 7.4 Conclusion References Chapter 8 A New Hybrid Proposition Based on a Cuckoo Search Algorithm for Parameter Estimation of Solar Cells 8.1 Introduction 8.2 Modelling of an Amended Double Diode Model (ADDM) and the Objective Function 8.3 Proposed Work 8.4 Results and Discussions 8.5 Conclusions References Chapter 9 Supervisory Digital Feedback Control System for An Effective PV Management and Battery Integration 9.1 Introduction 9.2 Literature Review 9.2.1 GHI in the Middle East 9.2.2 Types of PV Systems 9.2.3 Solar Tracking Systems 9.2.4 Charger Controller 9.2.5 Series Regulator 9.2.6 Shunt Regulator 9.2.7 Pulse Width Modulation 9.2.8 Maximum Power Point Tracker Charger Controller 9.2.9 Reducing the Charging Time 9.2.10 Dust Remover 9.3 Proposed Solution 9.3.1 Single Axis Solar Tracking System 9.3.2 Supervisory Digital Feedback Solar Tracker Control System 9.3.3 Database-Based Digital Solar Tracker Control System 9.3.4 Soiling Treatment Module 9.3.5 PV-to-Battery Switching Module 9.4 Discussion 9.5 Conclusion References Chapter 10 Performance Analysis of Tunnel Field Effect Transistor for Low-Power Applications 10.1 Introduction 10.1.1 Limitation of Conventional MOSFET 10.1.2 Subthreshold Slope Devices 10.2 TFET Structure and Simulation Setup 10.3 TFET Working Principle 10.3.1 Transport Mechanism in TFET 10.3.1.1 Band to Band (BTB) Tunneling Transmission 10.3.1.2 Kane’s Model 10.4 Subthreshold Swing (SS) in Tunnel FETs 10.5 Performance of Hetrojunction Tunnel FET 10.5.1 Transfer Characteristics Analysis of TFET Devices 10.5.2 Frequency Analysis of TFET Devices 10.6 Conclusion References Chapter 11 Low-Power Integrated Circuit Smart Device Design 11.1 Introduction 11.2 Need of Low Power 11.3 Design Techniques of Low Power 11.3.1 Power Optimization by IC System 11.3.2 Power Optimization by Algorithm Section 11.3.3 Power Optimization by Architecture Design 11.3.4 Power Optimization by Circuit Level 11.3.5 Power Optimization by Process Technology 11.4 VLSI Circuit Design for Low Power 11.4.1 Power Dissipation of CMOS Inverter 11.4.1.1 Static Power 11.4.1.2 Dynamic Power 11.4.1.3 Short Circuit Power Dissipation 11.4.1.4 Other Power Issue 11.4.2 Capacitance Estimation of CMOS Logic Gate 11.5 Circuit Techniques for Low Power 11.5.1 Static Power Technique 11.5.1.1 Self-Reverse Biasing 11.5.1.2 Multithreshold Voltage Technique 11.5.2 Dynamic Power Technique 11.6 Random Access Memory (RAM) Circuits for Low Power 11.6.1 Low-Power Techniques for SRAM 11.6.2 Low-Power Techniques for DRAM 11.7 VLSI Design Methodologies for Low Power 11.7.1 Low-Power Physical Design 11.7.2 Low-Power Gate Level Design 11.7.2.1 Technology Mapping and Logic Minimization 11.7.2.2 Reduction of Spurious Transitions 11.7.2.3 Power Reduction by Precomputation 11.7.3 Low-Power Architecture Level Design 11.8 Power Reduction by Algorithmic Level 11.8.1 Lowering in Switched Capacitance 11.8.2 Lowering in Switching Activities 11.9 Power Estimation Technique 11.9.1 Circuit Level Tool 11.9.2 Gate Level 11.9.3 Architectural Level 11.9.4 Behavioral Level 11.10 Low-Power Flood Sensor Design 11.11 Low-Power VCO Design 11.12 Low-Power Gilbert Mixer Design 11.13 Conclusion References Chapter 12 GaN Technology Analysis as a Greater Mobile Semiconductor: An Overview 12.1 Introduction 12.2 Research and Collected Data 12.3 Studies Reviewed and Findings 12.4 Conclusion References Chapter 13 Multilevel Distributed Energy Efficient Clustering Protocol for Relay Node Selection in Three-Tiered Architecture 13.1 Introduction 13.1.1 Overview 13.1.2 Routing Challenges and Design Issues 13.1.3 Heterogeneous Wireless Sensor Networks (HWSNs) 13.1.3.1 Clustering in WSN 13.1.4 Relay Node Selection Scheme 13.1.5 Genetic Algorithm 13.1.6 Problem Definition and Motivation 13.1.7 Proposed Work 13.2 Implementation of Proposed Relay Node Selection Based on GA 13.2.1 Network Model 13.2.2 Heterogenous Network Model 13.2.3 Radio Energy Dissipation Model 13.2.4 GA-Based Relay Node Selection 13.2.5 Steady State Phase or Data Communication Phase 13.3 Results of Simulation For Energy Consumption, Lifetime and Throughput of Network 13.3.1 Simulation Setup 13.3.2 Comparison of Residual Energy Consumption 13.3.3 Comparison of Lifetime of Network 13.3.4 Comparison of Throughput at BS 13.4 Conclusion and Future Scope References Chapter 14 Privacy and Security of Smart Systems 14.1 Smart Systems—An Overview 14.2 Security and Privacy Challenges in Smart Systems 14.2.1 Botnet Activities in Smart Systems 14.2.2 Threats of Nonhuman-Operated Cars 14.2.3 Privacy Issues of Virtual Reality 14.3 Case Studies—Security Breaches in Smart Systems 14.3.1 Breaching Smart Surveillance Cameras 14.3.2 Hacking Smart Televisions 14.3.3 Hacked Smart Bulbs 14.3.4 Vulnerable Smart Homes 14.3.5 Identity Stealing using Smart Coffee Machines 14.4 Existing Security and Privacy Protection Technologies 14.4.1 Cryptography 14.4.2 Biometric 14.4.3 Block Chain Technology 14.5 Machine Learning, Deep Learning, and Artificial Intelligence 14.5.1 Machine Learning in Smart Systems 14.5.2 Genetic Algorithm 14.5.3 Deep Learning in Smart Systems 14.5.4 Artificial Intelligence in Smart Systems 14.6 Security Requirement for Smart Systems 14.6.1 Thwarting of Data Leakage and Falsifications 14.6.2 Identification and Prevention of Device Tampering 14.6.3 Light Weight Encryption Algorithm for Authentication 14.6.4 Access Restrictions to Users 14.6.5 Incident Response for Entire Systems 14.7 Instruction to Build Strong Privacy Policy 14.7.1 Privacy Policy 14.7.2 Definition 14.7.3 Key Reasons Why There Is a Need for Privacy Policy 14.8 Role of Internet in Smart Systems 14.8.1 Home Automation 14.8.2 Agriculture 14.8.3 Industry 14.8.4 Health & Lifestyle 14.9 Frameworks, Algorithms, and Protocols for Security Enhancements 14.9.1 Framework for the Internet of Things by Cryptography 14.9.2 Protocols for Security Enhancements 14.10 Design Principles of Privacy Enhancing Methodologies 14.11 Conclusion References Chapter 15 Artificial Intelligence and Blockchain Technologies for Smart City 15.1 Introduction 15.2 Standard for Designing Smart City and Society 15.2.1 Scalability 15.2.2 Intelligent Health Care 15.2.3 Flexible and Interoperable 15.2.4 Safeguard Infrastructure 15.2.5 Robust Environment 15.2.6 Distribution and Sources of Energy 15.2.7 Intelligent Infrastructure 15.2.8 Choice-Based Backing System 15.2.9 Monitoring of Behavior 15.3 Blockchain and Artificial Intelligence 15.4 Contributions and Literature Study 15.5 Conclusion References Chapter 16 Android Application for School Bus Tracking System 16.1 Introduction 16.2 Application Methods for Access 16.2.1 Driver Portal Screen 16.2.2 Parent Portal Screen 16.2.3 Teachers Portal Screen 16.3 GPS Data Processing Methodology 16.4 GPS Working Process 16.5 System Implementation 16.6 Result and Discussion 16.6.1 Reasons to Utilize Android Application for School Bus Tracking System 16.6.1.1 Perfect Child Security 16.6.1.2 Elaborate Operational Efficiency 16.6.1.3 Valid Timely Maintenance 16.6.1.4 Automating Attendance Management 16.6.1.5 Better Staff Management 16.6.1.6 Addressing Environmental Concerns 16.7 Conclusion References About the Editors Index EULA