http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
IoT-based architecture and sustainable buildings
1 online resource (xxiv, 515 pages) : color illustrations.
"A good management strategy must be expected to mitigate the dangerous consequences of rapid urbanization that modern society, the economy, and the environment may face. Sustainable smart cities include established structures, infrastructures, communities, institutions, and individuals. On the other hand, this book also deals with energy consumption. Such energy consumption leads to a rapid depletion of energy resources, an increased need for building maintenance, an improvised comfortable lifestyle, and an increase in time spent on building construction. A sustainable building mainly explains the renewable sources used for construction, which helps the structure withstand atmospheric changes. Currently, all countries are looking for ecological materials, that is, renewable plant materials such as straw and clay bricks, wood from forests certified for sustainable management, recycled materials, and other non-toxic, reusable and renewable products. For sustainable and durable construction, energy efficiency is an urgent problem, and researchers are currently actively involved in this area. This book will provide an in-depth analysis of design technologies that lay a solid foundation for sustainable buildings. The book also highlights smart automation technologies that help save energy, as well as various performance indicators needed to make construction easier. The book aims to create a strong research community, to have a deep understanding and the latest knowledge in the field of energy and comfort, to offer solid ideas in the nearby future for sustainable and resilient buildings. These buildings will help the city grow as a smart city. The smart city has also focused on low energy consumption, renewable energy, and small carbon footprints. To find the optimal use of energy resources, researchers must study optimization methods."--
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 andamp -- 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.
edited by Arun Solanki, Adarsh Kumar and Anand Nayyar.
Includes bibliographical references and index.
Advances in learning analytics for intelligent cloud-IoT systems