Resilient Community Microgrids

Chapter 1: AI-Based Virtual Advisor for Smart Climate Farming

• • 1.1 Introduction
• • 1.2 Research on Smart Farming Technologies and AI Applications
• • 1.3 AI and IoT in Smart Farming
• • 1.4 Sustainable Agriculture and Climate-Smart Farming
• • 1.5 Conclusion
• • References

Chapter 2: Swappable Battery Pack System for Electric Two-Wheelers: Design, Infrastructure, and Implementation

• • 2.1 Introduction
• • 2.2 Swappable Battery Technology
• • 2.3 Battery Swapping Infrastructure and Optimization
• • 2.4 Battery Management System
• • 2.5 Business Models and Economic Implications
• • 2.6 Conclusion
• • References

Chapter 3: Implementation of High Gain Bidirectional Interleaved DC/DC Converter for Electric Vehicles with Supercapacitors

• • 3.1 Introduction
• • 3.2 Proposed Converter
• • 3.3 Operating Principle of the HGBID Converter
• • 3.4 Design Considerations
• • 3.5 Characteristics of SC
• • 3.6 Simulation Results
• • 3.7 Conclusion
• • References

Chapter 4: Fault Over-Ride and Minimization of Losses in a PV Integrated Transmission Network Using STATCOM

• • 4.1 Introduction
• • 4.2 Problem Statement
• • 4.3 Contingency Analysis and Contingency Selection
• • 4.4 Test System, Software and Components Used
• • 4.4.1 Test System and Software
• • 4.4.2 PV Generators Integration
• • 4.4.3 Static Synchronous Compensator (STATCOM)
• • 4.5 Results and Analysis
• • 4.5.1 Bus Network Integrated with Solar Photo-Voltaic Generators
• • 4.5.2 Test Bus Network with One STATCOM Installed at Bus 6
• • 4.6 IEEE 14 Bus Network with Two STATCOMs Installed at Bus 2 and Bus 6
• • 4.7 Conclusion
• • 4.8 Future Scope
• • References

Chapter 5: Oscillating Water Column as Clean Energy Source for Sustainable Power Generation

• • 5.1 Introduction to Technology
• • 5.2 Hardware Implementation
• • 5.3 Three-Dimensional Design of Hardware Components in Solid Edge Software
• • 5.4 Hardware Implementation Results and Performance Analysis of Oscillating Water Column (OWC)
• • 5.5 Conclusion
• • 5.6 Future Scope
• • References

Chapter 6: Cloud-Based Big Data Architecture and Infrastructure

• • 6.1 Introduction
• • 6.2 Big Data Architecture for the Cloud Fundamentals
• • 6.3 Overview of Methods for Ingesting Data, Including Batch Operations and Live Streaming
• • 6.4 Technologies for Big Data on the Cloud
• • 6.5 Overview of Server Less Computing and Its Benefits for Cost Optimization and Scaling
• • 6.6 Big Data Architectural Models for the Cloud
• • 6.7 Integration of Cloud Services and Big Data
• • 6.7.1 How to Combine Big Data Platforms with Cloud Services Including Analytics, Compute and Storage
• • 6.8 Examining Data Integration and ETL (Extract, Transform, Load) Methods Based on the Cloud
• • 6.9 Overview of Cloud-Based Big Data Environments’ Data Governance and Metadata Management
• • 6.10 Analysis of Cloud-Based Big Data Architectures’ Scalability Issues
• • 6.11 Examining Vertical and Horizontal Scaling Methods to Succeed in Processing Demands and Growing Data Volumes
• • 6.12 Introduction to Cloud-Based Big Data Architectures’ Performance Optimization Strategies
• • 6.13 Big Data Based on the Cloud is Secure and Private
• • 6.14 A Description of the Mechanisms for Data Encryption, Access Regulation and Identity Administration
• • 6.15 Examination of Privacy Issues and Data Protection Laws Compliance
• • 6.16 Case Studies and Real-World Applications
• • 6.17 Future Directions and Trends
• • 6.18 Future Developments Prediction and Scalable and Efficient Data Processing Implications
• • 6.19 Conclusion
• • 6.20 Emphasis on Cloud-Based Big Data Architecture and Infrastructure’s Potential for Transformation
• • 6.21 Motivating Companies to Adopt Cloud-Based Big Data Technologies

Chapter 7: RISC-V Processor Hardware Modelling with Custom Instruction Set for SHA-3 Acceleration

• • 7.1 Introduction
• • 7.2 State of the Art
• • 7.3 Keccak Algorithm in SHA- 3
• • 7.4 RISC-V Instruction Set Architecture
• • 7.5 Custom Instructions for SHA-3 Hashing
• • 7.6 Proposed Processor Microarchitecture
• • 7.7 Results and Discussion
• • 7.8 Conclusion
• • References

Chapter 8: SSL Vulnerability Exploitation Analysis Tool to Provide a Secure and Sustainable Network for Smart Cities

• • 8.1 Introduction
• • 8.2 Related Work
• • 8.3 Research Methodology
• • 8.4 Experimental Results
• • 8.5 Conclusion
• • References

Chapter 9: Service-Oriented Smart City Vigilant Data Hub for Social Innovation

• • 9.1 Introduction
• • 9.2 Background and Literature Review
• • 9.3 App Architecture and Technology Stack
• • 9.4 User Registration and Authentication
• • 9.5 Features and Functionality
• • 9.6 User Experience and Interface Design
• • 9.7 Data Privacy and Security
• • 9.8 Real-Time Updates and Push Notifications from the App
• • 9.9 Scalability and Performance Optimization
• • 9.10 User Engagement Analytics
• • 9.11 Impact and User Engagement
• • 9.12 Citizen User Flow and Admin Access User Flow
• • 9.13 Conclusion
• • 9.14 Future Potential
• • References

Chapter 10: A Survey on AI & ML for Autonomous Driving, User Behavior Monitoring, and Intelligent Navigation in EVs

• • 10.1 Introduction
• • 10.2 Survey Overview
• • 10.3 Objectives of this Work
• • 10.4 Methodologies
• • 10.5 Outcome
• • 10.6 Applications of the Proposed Model
• • 10.7 Demonstration of Autonomous Driving Car Using Pygame
• • 10.8 Conclusion
• • References

Chapter 11: Deep Learning in Waste Management and Recycling in Digital Smart City

• • 11.1 Introduction
• • 11.2 Related Work
• • 11.3 Deep Learning Applications in Waste Management
• • 11.4 Methodology and Model Specifications
• • 11.5 Experimental Results and Discussions
• • 11.6 Conclusion
• • References

Chapter 12: Home Automation Using Augmented Reality

• • 12.1 Introduction
• • 12.2 Literature Review
• • 12.3 Hardware Analysis
• • 12.4 Methodology
• • 12.5 Results and Discussion
• • 12.6 Conclusion
• • References

Chapter 13: Detection and Mitigation Techniques for Defending DDoS Attacks in Cloud Environment

• • 13.1 Introduction
• • 13.2 Related Literature Survey
• • 13.3 Related Work
• • 13.4 Conclusion
• • References

Chapter 14: Design and Implementation of Secure MQTT Protocol for Embedded IoT Device

• • 14.1 Introduction
• • 14.2 Need for Security in IoT Device
• • 14.3 Comparison Between Messaging Protocols Used in IoT Environment
• • 14.4 MQTT Architecture
• • 14.5 Proposed System Objective
• • 14.6 Related Work
• • 14.7 Conclusion and Future Scope
• • References

Chapter 15: Internet of Things in Smart Building Management System

• • 15.1 Introduction
• • 15.2 Components of Intelligent Building Management System
• • 15.3 Choosing the Right Building Management System
• • 15.4 Choosing a System
• • 15.5 Conclusion
• • References

Chapter 16: Comparative Study of Solid Waste Management in Rural Homestays and Urban Hotels in Sikkim, India

• • 16.1 Introduction
• • 16.2 Literature Review
• • 16.3 Methodology
• • 16.4 Result
• • 16.5 Discussion
• • 16.6 Conclusion
• • References

Chapter 17: Load Response in the Smart Home Energy Management System

• • 17.1 Introduction
• • 17.2 Active Demand Response
• • 17.3 Modeling the Effects of Reimbursement of Load Response Resources
• • 17.4 Conclusion
• • References

Chapter 18: Sustainable Agriculture Using IoT Based Smart Irrigation and Intelligent Watering System

• • 18.1 Introduction
• • 18.2 Methods and Material
• • 18.3 Problem Statement
• • 18.4 Proposed Methodology
• • 18.5 Simulation Results and Analysis
• • 18.6 Conclusion
• • References

Chapter 19: Assessing the Impact of Green Spaces on Climate, Air Quality and Temperature in Urbanized Areas: A Case Study of Colombo

• • 19.1 Introduction
• • 19.2 Literature Review
• • 19.3 Data and Methods
• • 19.4 Findings of the Study
• • 19.5 Discussion and Conclusion
• • References

Chapter 20: Weed Rate Anal