Intelligent Green Technologies for Sustainable Smart Cities

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