Digital Cities Roadmap

Cover
Half-Title Page
Series Page
Title Page
Copyright Page
Contents
Preface
1 The Use of Machine Learning for Sustainable and Resilient Buildings
	1.1 Introduction of ML Sustainable Resilient Building
	1.2 Related Works
	1.3 Machine Learning
	1.4 What is Resilience?
		1.4.1 Sustainability and Resiliency Conditions
		1.4.2 Paradigm and Challenges of Sustainability and Resilience
		1.4.3 Perspectives of Local Community
	1.5 Sustainability and Resilience of Engineered System
		1.5.1 Resilience and Sustainable Development Framework for Decision-Making
		1.5.2 Exposures and Disturbance Events
		1.5.3 Quantification of Resilience
		1.5.4 Quantification of Sustainability
	1.6 Community and Quantification Metrics, Resilience and Sustainability Objectives
		1.6.1 Definition of Quantification Metric
		1.6.2 Considering and Community
	1.7 Structure Engineering Dilemmas and Resilient Epcot
		1.7.1 Dilation of Resilience Essence
		1.7.2 Quality of Life
	1.8 Development of Risk Informed Criteria for Building Design Hurricane Resilient on Building
	1.9 Resilient Infrastructures Against Earthquake and Tsunami Multi-Hazard
	1.10 Machine Learning With Smart Building
		1.10.1 Smart Building Appliances
		1.10.2 Intelligent Tools, Cameras and Electronic Controls in a Connected House (SRB)
		1.10.3 Level if Clouds are the IoT Institute Level With SBs
		1.10.4 Component of Smart Buildings (SB)
		1.10.5 Machine Learning Tasks in Smart Building Environment
		1.10.6 ML Tools and Services for Smart Building
		1.10.7 Big Data Research Applications for SBs in Real-Time
		1.10.8 Implementation of the ML Concept in the SB Context
	1.11 Conclusion and Future Research
	References
2 Fire Hazard Detection and Prediction by Machine Learning Techniques in Smart Buildings (SBs) Using Sensors and Unmanned Aerial Vehicles (UAVs)
	2.1 Introduction
		2.1.1 Bluetooth
		2.1.2 Unmanned Aerial Vehicle
		2.1.3 Sensors
		2.1.4 Problem Description
	2.2 Literature Review
	2.3 Experimental Methods
		2.3.1 Univariate Time-Series
		2.3.2 Multivariate Time-Series Prediction
		2.3.3 Hidden Markov Model (HMM)
		Algorithm
		2.3.4 Fuzzy Logic
	2.4 Results
	2.5 Conclusion and Future Work
	References
3 Sustainable Infrastructure Theories and Models
	3.1 Introduction to Data Fusion Approaches in Sustainable Infrastructure
		3.1.1 The Need for Sustainable Infrastructure
		3.1.2 Data Fusion
		3.1.3 Different Types of Data Fusion Architecture
		3.1.4 Smart Cities Application With Sustainable Infrastructures Based on Different Data Fusion Techniques
	3.2 Smart City Infrastructure Approaches
		3.2.1 Smart City Infrastructure
		3.2.2 Smart City IoT Deployments
		3.2.3 Smart City Control and Monitoring Centers
		3.2.4 Theory of Unified City Modeling for Smart Infrastructure
		3.2.5 Smart City Operational Modeling
	3.3 Theories and Models
		3.3.1 Sustainable Infrastructure Theories
		3.3.2 Sustainable Infrastructure Models
	3.4 Case Studies
		3.4.1 Case Studies-1: Web Browsing History Analysis
		3.4.2 Case Study-2: Data Model for Group Construction in Student’s Industrial Placement
	3.5 Conclusion and Future Scope
	References
4 Blockchain for Sustainable Smart Cities
	4.1 Introduction
	4.2 Smart City
		4.2.1 Overview of Smart City
		4.2.2 Evolution
		4.2.3 Smart City’s Sub Systems
		4.2.4 Domains of Smart City
		4.2.5 Challenges
	4.3 Blockchain
		4.3.1 Motivation
		4.3.2 The Birth of Blockchain
		4.3.3 System of Blockchain
	4.4 Use Cases of Smart City Implementing Blockchain
		4.4.1 Blockchain-Based Smart Economy
		4.4.2 Blockchain for Smart People
		4.4.3 Blockchain-Based Smart Governance
		4.4.4 Blockchain-Based Smart Transport
		4.4.5 Blockchain-Based Smart Environment
		4.4.6 Blockchain-Based Smart Living
	4.5 Conclusion
	References
5 Contextualizing Electronic Governance, Smart City Governance and Sustainable Infrastructure in India: A Study and Framework
	5.1 Introduction
	5.2 Related Works
		5.2.1 Research Questions
	5.3 Related E-Governance Frameworks
		5.3.1 Smart City Features in India
	5.4 Proposed Smart Governance Framework
	5.5 Results Discussion
		5.5.1 Initial Stage
		5.5.2 Design, Development and Delivery Stage
	5.6 Conclusion
	References
6 Revolutionizing Geriatric Design in Developing Countries: IoT-Enabled Smart Home Design for the Elderly
	6.1 Introduction to Geriatric Design
		6.1.1 Aim, Objectives, and Methodology
		6.1.2 Organization of Chapter
	6.2 Background
		6.2.1 Development of Smart Homes
		6.2.2 Development of Smart Homes for Elderly
		6.2.3 Indian Scenario
	6.3 Need for Smart Homes: An Assessment of Requirements for the Elderly-Activity Mapping
		6.3.1 Geriatric Smart Home Design: The Indian Context
		6.3.2 Elderly Activity Mapping
		6.3.3 Framework for Smart Homes for Elderly People
		6.3.4 Architectural Interventions: Spatial Requirements for Daily Activities
		6.3.5 Architectural Interventions to Address Issues Faced by Elderly People
	6.4 Schematic Design for a Nesting Home: IoT-Enabled Smart Home for Elderly People
		6.4.1 IoT-Based Real Time Automation for Nesting Homes
		6.4.2 Technological Components of Elderly Smart Homes
	6.5 Worldwide Elderly Smart Homes
		6.5.1 Challenges in Smart Elderly Homes
	6.6 Conclusion and Future Scope
	References
7 Sustainable E-Infrastructure for Blockchain-Based Voting System
	7.1 Introduction
		7.1.1 E-Voting Challenge
	7.2 Related Works
	7.3 System Design
	7.4 Experimentation
		7.4.1 Software Requirements
		7.4.2 Function Requirements
		7.4.3 Common Functional Requirement for All Users
		7.4.4 Non-Function Requirements
		7.4.5 Implementation Details
	7.5 Findings & Results
		7.5.1 Smart Contract Deployment
	7.6 Conclusion and Future Scope
	Acknowledgement
	References
8 Impact of IoT-Enabled Smart Cities: A Systematic Review and Challenges
	8.1 Introduction
	8.2 Recent Development in IoT Application for Modern City
		8.2.1 IoT Potential Smart City Approach
		8.2.2 Problems and Related Solutions in Modern Smart Cities Application
	8.3 Classification of IoT-Based Smart Cities
		8.3.1 Program Developers
		8.3.2 Network Type
		8.3.3 Activities of Standardization Bodies of Smart City
		8.3.4 Available Services
		8.3.5 Specification
	8.4 Impact of 5G Technology in IT, Big Data Analytics, and Cloud Computing
		8.4.1 IoT Five-Layer Architecture for Smart City Applications
		8.4.2 IoT Computing Paradigm for Smart City Application
	8.5 Research Advancement and Drawback on Smart Cities
		8.5.1 Integration of Cloud Computing in Smart Cities
		8.5.2 Integration of Applications
		8.5.3 System Security
	8.6 Summary of Smart Cities and Future Research Challenges and Their Guidelines
	8.7 Conclusion and Future Direction
	References
9 Indoor Air Quality (IAQ) in Green Buildings, a Pre-Requisite to Human Health and Well-Being
	9.1 Introduction
	9.2 Pollutants Responsible for Poor IAQ
		9.2.1 Volatile Organic Compounds (VOCs)
		9.2.2 Particulate Matter (PM)
		9.2.3 Asbestos
		9.2.4 Carbon Monoxide (CO)
		9.2.5 Environmental Tobacco Smoke (ETS)
		9.2.6 Biological Pollutants
		9.2.7 Lead (Pb)
		9.2.8 Nitrogen Dioxide (NO2)
		9.2.9 Ozone (O3)
	9.3 Health Impacts of Poor IAQ
		9.3.1 Sick Building Syndrome (SBS)
		9.3.2 Acute Impacts
		9.3.3 Chronic Impacts
	9.4 Strategies to Maintain a Healthy Indoor Environment in Green Buildings
	9.5 Conclusion and Future Scope
	References
10 An Era of Internet of Things Leads to Smart Cities Initiatives Towards Urbanization
	10.1 Introduction: Emergence of a Smart City Concept
	10.2 Components of Smart City
		1 1 1 ay
		10.2.1 Smart Infrastructure
		10.2.2 Smart Building
		10.2.3 Smart Transportation
		10.2.4 Smart Energy
		10.2.5 Smart Health Care
		10.2.6 Smart Technology
		10.2.7 Smart Citizen
		10.2.8 Smart Governance
		10.2.9 Smart Education
	10.3 Role of IoT in Smart Cities
		10.3.1 Intent of IoT Adoption in Smart Cities
		10.3.2 IoT-Supported Communication Technologies
	10.4 Sectors, Services Related and Principal Issues for IoT Technologies
	10.5 Impact of Smart Cities
		10.5.1 Smart City Impact on Science and Technology
		10.5.2 Smart City Impact on Competitiveness
		10.5.3 Smart City Impact on Society
		10.5.4 Smart City Impact on Optimization and Management
		10.5.5 Smart City for Sustainable Development
	10.6 Key Applications of IoT in Smart Cities
	10.7 Challenges
		10.7.1 Smart City Design Challenges
		10.7.2 Challenges Raised by Smart Cities
		10.7.3 Challenges of IoT Technologies in Smart Cities
	10.8 Conclusion
	Acknowledgements
	References
11 Trip-I-Plan: A Mobile Application for Task Scheduling in Smart City’s Sustainable Infrastructure
	11.1 Introduction
	11.2 Smart City and IoT
	11.3 Mobile Computing for Smart City
	11.4 Smart City and its Applications
		11.4.1 Traffic Monitoring
		11.4.2 Smart Lighting
		11.4.3 Air Quality Monitoring
	11.5 Smart Tourism in Smart City
	11.6 Mobile Computing-Based Smart Tourism
	11.7 Case Study: A Mobile Application for Trip Planner Task Scheduling in Smart City’s Sustainable Infrastructure
		11.7.1 System Interfaces and User Interfaces
	11.8 Experimentation and Results Discussion
	11.9 Conclusion and Future Scope
	References
12 Smart Health Monitoring for Elderly Care in Indoor Environments
	12.1 Introduction
	12.2 Sensors
		12.2.1 Human Traits
		12.2.2 Sensors Description
		12.2.3 Sensing Challenges
	12.3 Internet of Things and Connected Systems
	12.4 Applications
	12.5 Case Study
		12.5.1 Case 1
		12.5.2 Case 2
		12.5.3 Challenges Involved
		12.5.4 Possible Solution
	12.6 Conclusion
	12.7 Discussion
	References
13 A Comprehensive Study of IoT Security Risks in Building a Secure Smart City
	13.1 Introduction
		13.1.1 Organization of the Chapter
	13.2 Related Works
	13.3 Overview of IoT System in Smart Cities
		13.3.1 Physical Devices
		13.3.2 Connectivity
		13.3.3 Middleware
		13.3.4 Human Interaction
	13.4 IoT Security Prerequisite
	13.5 IoT Security Areas
		13.5.1 Anomaly Detection
		13.5.2 Host-Based IDS (HIDS)
		13.5.3 Network-Based IDS (NIDS)
		13.5.4 Malware Detection
		13.5.5 Ransomware Detection
		13.5.6 Intruder Detection
		13.5.7 Botnet Detection
	13.6 IoT Security Threats
		13.6.1 Passive Threats
		13.6.2 Active Threats
	13.7 Review of ML/DL Application in IoT Security
		13.7.1 Machine Learning Methods
		13.7.2 Deep Learning Methods
	13.8 Challenges
		13.8.1 IoT Dataset Unavailability
		13.8.2 Computational Complications
		13.8.3 Forensics Challenges
	13.9 Future Prospects
		13.9.1 Implementation of ML/DL With Edge Computing
		13.9.2 Integration of ML/DL With Blockchain
		13.9.3 Integration of ML/DL With Fog Computing
	13.10 Conclusion
	References
14 Role of Smart Buildings in Smart City— Components, Technology, Indicators, Challenges, Future Research Opportunities
	14.1 Introduction
		14.1.1 Chapter Organization
	14.2 Literature Review
	14.3 Components of Smart Cities
		14.3.1 Smart Infrastructure
		14.3.2 Smart Parking Management
		14.3.3 Connected Charging Stations
		14.3.4 Smart Buildings and Properties
		14.3.5 Smart Garden and Sprinkler Systems
		14.3.6 Smart Heating and Ventilation
		14.3.7 Smart Industrial Environment
		14.3.8 Smart City Services
		14.3.9 Smart Energy Management
		14.3.10 Smart Water Management
		14.3.11 Smart Waste Management
	14.4 Characteristics of Smart Buildings
		14.4.1 Minimal Human Control
		14.4.2 Optimization
		14.4.3 Qualities
		14.4.4 Connected Systems
		14.4.5 Use of Sensors
		14.4.6 Automation
		14.4.7 Data
	14.5 Supporting Technology
		14.5.1 Big Data and IoT in Smart Cities
		14.5.2 Sensors
		14.5.3 5G Connectivity
		14.5.4 Geospatial Technology
		14.5.5 Robotics
	14.6 Key Performance Indicators of Smart City
		14.6.1 Smart Economy
		14.6.2 Smart Governance
		14.6.3 Smart Mobility
		14.6.4 Smart Environment
		14.6.5 Smart People
		14.6.6 Smart Living
	14.7 Challenges While Working for Smart City
		14.7.1 Retrofitting Existing Legacy City Infrastructure to Make it Smart
		14.7.2 Financing Smart Cities
		14.7.3 Availability of Master Plan or City Development Plan
		14.7.4 Financial Sustainability of ULBs
		14.7.5 Technical Constraints ULBs
		14.7.6 Three-Tier Governance
		14.7.7 Providing Clearances in a Timely Manner
		14.7.8 Dealing With a Multivendor Environment
		14.7.9 Capacity Building Program
		14.7.10 Reliability of Utility Services
	14.8 Future Research Opportunities in Smart City
		14.8.1 IoT Management
		14.8.2 Data Management
		14.8.3 Smart City Assessment Framework
		14.8.4 VANET Security
		14.8.5 Improving Photovoltaic Cells
		14.8.6 Smart City Enablers
		14.8.7 Information System Risks
	14.9 Conclusion
	References
15 Effects of Green Buildings on the Environment
	15.1 Introduction
	15.2 Sustainability and the Building Industry
		15.2.1 Environmental Benefits
		15.2.2 Social Benefits
		15.2.3 Economic Benefits
	15.3 Goals of Green Buildings
		15.3.1 Green Design
		15.3.2 Energy Efficiency
		15.3.3 Water Efficiency
		15.3.4 Material Efficiency
		15.3.5 Improved Internal Environment and Air Quality
		15.3.6 Minimization of Wastes
		15.3.7 Operations and Maintenance Optimization
	15.4 Impacts of Classical Buildings that Green Buildings Seek to Rectify
		15.4.1 Energy Use in Buildings
		15.4.2 Green House Gas (GHG) Emissions
		15.4.3 Indoor Air Quality
		15.4.4 Building Water Use
		15.4.5 Use of Land and Consumption
		15.4.6 Construction Materials
		15.4.7 Construction and Demolition (C&D) Wastes
	15.5 Green Buildings in India
	15.6 Conclusion
	Acknowledgement
	Acronyms
	References
Index
EULA