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Digital cities roadmap : IoT-based architecture and sustainable buildings / / edited by Arun Solanki, Adarsh Kumar and Anand Nayyar
| Digital cities roadmap : IoT-based architecture and sustainable buildings / / edited by Arun Solanki, Adarsh Kumar and Anand Nayyar |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2021] |
| Descrizione fisica | 1 online resource (xxiv, 515 pages) : illustrations |
| Disciplina | 307.760285 |
| Collana | Advances in Learning Analytics for Intelligent Cloud-IoT Systems Ser. |
| Soggetto topico | Smart cities |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-5231-4333-9
1-119-79205-3 1-119-79206-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. |
| Record Nr. | UNINA-9910555178403321 |
| Hoboken, New Jersey : , : Wiley, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Digital cities roadmap : IoT-based architecture and sustainable buildings / / edited by Arun Solanki, Adarsh Kumar and Anand Nayyar
| Digital cities roadmap : IoT-based architecture and sustainable buildings / / edited by Arun Solanki, Adarsh Kumar and Anand Nayyar |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2021] |
| Descrizione fisica | 1 online resource (xxiv, 515 pages) : illustrations |
| Disciplina | 307.760285 |
| Collana | Advances in Learning Analytics for Intelligent Cloud-IoT Systems |
| Soggetto topico | Smart cities |
| ISBN |
1-5231-4333-9
1-119-79205-3 1-119-79206-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. |
| Record Nr. | UNINA-9910830865903321 |
| Hoboken, New Jersey : , : Wiley, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Quantum and blockchain for modern computing systems, vision and advancements : quantum and blockchain technologies : current trends and challenges / / edited by Adarsh Kumar, Sukhpal Singh Gill, and Ajith Abraham
| Quantum and blockchain for modern computing systems, vision and advancements : quantum and blockchain technologies : current trends and challenges / / edited by Adarsh Kumar, Sukhpal Singh Gill, and Ajith Abraham |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (371 pages) |
| Disciplina | 006.3843 |
| Collana | Lecture Notes on Data Engineering and Communications Technologies |
| Soggetto topico |
Quantum computing
Blockchains (Databases) |
| ISBN | 3-031-04613-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Quantum Technologies I: Information, Communication, and Computation -- 1 Quantum Information -- 1.1 Postulates of Quantum Mechanics -- 1.2 Classical and Quantum Information -- 1.3 Quantum Information Science-Applications -- 1.4 Quantum Block Chains -- 2 Multiple Controlled Toffoli -- 2.1 Background -- 2.2 Notation -- 2.3 Definitions -- 2.4 Sleator-Weinfurter Construction -- 2.5 Optimal CNOT Toffoli Circuit -- 2.6 Recursive Relative Phase Toffoli -- 2.7 V-Chain Decomposition -- 2.8 Quadratic Decomposition -- 2.9 Summary -- 3 Quantum Error Correction -- 3.1 Noise Origin -- 3.2 Error Types -- 3.3 Classical Error Correction -- 3.4 From Classical to Quantum -- 3.5 Detecting Bit Flip Errors -- 3.6 Correcting Bit Flip Errors -- 3.7 Three-Qubit Code for Phase Errors -- 3.8 General Error Correcting Codes -- 4 Conclusions and Notes on Blockchain -- References -- Quantum Technologies II: Cryptography, Blockchains, and Sensing -- 1 Quantum Communication -- 1.1 Introduction -- 1.2 Quantum Cryptography -- 1.3 Quantum Blockchain -- 1.4 Quantum Algorithms for Quantum Blockchain -- 1.5 Quantum Advantage -- 1.6 Conclusion -- 2 Quantum Sensing -- 2.1 Introduction -- 2.2 Need for Quantum Sensing -- 2.3 Implementation -- 2.4 Challenges and Limitations -- 2.5 Applications -- 2.6 Outlook -- References -- Empirical Analysis of Security Enabled Quantum Computing for Cloud Environment -- 1 Introduction -- 2 Introduction to Quantum Computing and Quantum Mechanics -- 2.1 Classification of Quantum Computing -- 2.2 Advantages of QC -- 2.3 Disadvantages of QC -- 3 Introduction to Cloud Infrastructure -- 3.1 Cloud Security Issues -- 3.2 Recent Advancements and Trends in Cloud Infrastructure -- 3.3 Timeline of Cloud Computing Paradigms -- 4 Recent Advancements and Trends in Quantum Computing, Mechanics, and Information Processing.
4.1 Processing and Quantum Cryptography Used for Security Issues -- 4.2 Research Directions in Quantum Cryptography -- 5 Quantum Computing in Cloud Infrastructure -- 6 Research Challenges and Directions in QC-Based Cloud Infrastructure -- 7 Future Prospects: Certain and Uncertain -- 8 Conclusion -- References -- Photonic Quantum Computing -- 1 Introduction -- 1.1 DiVincenzo Criteria -- 2 Facets of Photonic Quantum Computers -- 2.1 Scalability of Photonic Quantum Computing -- 2.2 Fault-Tolerance of Photonic Quantum Computer -- 2.3 Room Temperature Operation for Photonic Quantum Computing -- 2.4 Drawbacks -- 3 Photonic Device Component -- 3.1 Squeezers -- 3.2 Interferometers -- 3.3 Waveguides -- 3.4 Photodetectors -- 4 Applications -- 4.1 Quantum Random Number Generators -- 4.2 Quantum Optical Neural Network -- 4.3 Quantum Cryptography -- 4.4 Quantum Key Distribution -- 5 Future Challenges and Solutions-Blockchain -- References -- A Conceptual Framework for Scaling and Security in Serverless Environments Using Blockchain and Quantum Key Distribution -- 1 Introduction -- 2 Serverless Computing -- 2.1 Going Serverless -- 2.2 Shared Responsibility Model -- 3 Blockchain -- 3.1 Blockchain Architecture -- 3.2 Smart Contracts -- 4 Quantum Computing -- 4.1 Quantum Key Distribution -- 5 Blockchain in Serverless Computing -- 6 Quantum Key Distribution in Serverless Computing -- 6.1 Security in Serverless Domain -- 6.2 Using QKD as a Security Mechanism -- 7 Integrating QKD and Blockchain into Serverless Domain -- 7.1 Deployment of Server Code -- 7.2 Blockchain and Consensus Algorithm -- 7.3 Execution of Smart Contract -- 8 Discussion -- 9 Conclusion -- References -- Implications of Quantum Science on Industry 4.0: Challenges and Opportunities -- 1 Introduction -- 2 Quantum Overview -- 3 Applications of Quantum Based Technologies. 3.1 Quantum in AI Based Technologies -- 3.2 Quantum Computing in Online Security -- 3.3 Quantum Computing in Drug Development -- 3.4 Quantum in Weather Forecasting and Climate Change -- 4 Industrial Developments in Quantum Technologies -- 4.1 Industry 4.0 and Quantum World -- 4.2 Industry 4.0 and Blockchain Usage in Quantum World -- 5 Challenges in Quantum Commercialization -- 5.1 Hardware and Software Issues -- 5.2 Security and Privacy Issues -- 5.3 Energy Issues -- 5.4 Financial Constraints -- 5.5 Unskilled Personnel -- 5.6 Adoption Issue -- 6 Future Research Direction -- 7 Conclusion -- References -- Quantum Generative Modelling and Its Use Cases -- 1 Machine Learning in Classical Computing -- 2 Quantum Machine Learning -- 2.1 The Rise of Quantum Machine Learning -- 2.2 Review of Quantum Information Processing Concepts -- 2.3 Variational Quantum Algorithms (VQAs) -- 2.4 Variational Quantum Eigensolver (VQE) -- 3 Quantum Generative Adversarial Networks -- 3.1 Architecture and Training of GAN's -- 3.2 Architecture and Training of Quantum GAN's -- 4 QGAN's Use Case-Drug Discovery -- 4.1 QGANs for Loading Random Distributions -- 4.2 Option Pricing with QGAN -- 5 Conclusion -- References -- A Comprehensive Overview of Quantum Internet: Architecture, Protocol and Challenges -- 1 Introduction -- 2 Fundamentals of Quantum Computing -- 3 Quantum Internet -- 3.1 Classical Internet Versus Quantum Internet -- 3.2 Current State of Art of Quantum Internet -- 3.3 Quantum Internet Design Challenges -- 3.4 Advantages of Quantum Internet -- 4 Related Works in Quantum Internet -- 5 Challenges in Quantum Internet -- References -- Quantum Solutions to Possible Challenges of Blockchain Technology -- 1 Introduction -- 2 Blockchain and Distributed Ledger Techniques -- 3 Scalability Aspects of Classical Blockchain -- 3.1 Blockchain Scalability from Existing Standpoint. 3.2 Future Classical Approaches to Solve Scalability -- 4 Quantum-aid to Classical Blockchain -- 4.1 Quantum Offers Unprecedented Growth in Computing -- 4.2 Quantum Advantage in Blockchain Scalability -- 5 Shor's Algorithm-Threats on Classical Public-Key Blockchain Algorithms -- 5.1 RSA (Rivest Shamir Adleman) Algorithm -- 5.2 ECC (Elliptic Curve Cryptography) and ECDSA (Elliptic Curve Digital Signature Algorithm) -- 5.3 ECDH (Elliptic Curve Diffe Hellman) Algorithm -- 5.4 DSA (Digital Signature Algorithm) -- 6 Grover's Algorithm-Threats on Classical Blockchain Techniques -- 6.1 Faster Detection of Hash Collision -- 7 Post-Quantum Initiatives for Quantum-Resistant Cryptography -- 7.1 PQCrypto -- 7.2 SAFEcrypto -- 7.3 CryptoMathCREST -- 7.4 Post Quantum Standardization -- 8 Post Quantum Initiatives on Blockchain -- 8.1 Bitcoin Post-Quantum -- 8.2 Ethereum 3.0 -- 8.3 Abelian -- 8.4 Corda -- 9 Feasibility of Quantum Attack on Blockchain DLTs -- 9.1 Bitcoin -- 9.2 Ethereum -- 9.3 Litecoin -- 9.4 Monero -- 9.5 Zcash -- 10 Realization of Post-Quantum Block and Future Research Direction -- 10.1 Key Size and Signature Size -- 10.2 Key Generation Rate -- 10.3 Blockchain Compliance Issues -- 10.4 Incompatibility Issue with Existing Hardware -- 10.5 Ciphertext Overhead -- 11 Conclusion -- References -- Futuristic Technologies for Supply Chain Management: A Survey -- 1 Introduction -- 2 Internet of Things in Supply Chain Management -- 2.1 Use Cases and Benefits of Using IOT -- 2.2 IoT Sample Reference Model -- 2.3 Challenges of Using IoT in Supply Chain Management -- 2.4 IoT Recent Developments and Future Trends -- 3 Artificial Intelligence and Machine Learning in Supply Chain Management -- 3.1 Use Cases and Benefits of Using Artificial Intelligence and Machine Learning -- 3.2 Implementation of AI in Sub-fields. 3.3 Challenges of Using AI Technology in SCM System -- 3.4 AI and Machine Learning Recent Developments and Future Trends -- 4 Blockchain in Supply Chain Management -- 4.1 Use Cases and Benefits of Using Block Chain -- 4.2 Industrial IoT in Supply Chain Management -- 4.3 Centralized Transaction Systems and Databases -- 4.4 Using Distributed Ledger Technologies -- 5 Conclusion -- References -- Quantum Computing and Quantum Blockchain: Recent Advancements, Analysis and Future Directions -- 1 Introduction -- 1.1 Objectives of Work -- 1.2 Work Organization -- 2 Quantum Computing -- 2.1 Quantum Computer and Blockchain -- 2.2 Quantum Computing-Based Hardware Implementation and Blockchain -- 2.3 Quantum Mechanics and Blockchain -- 2.4 Mathematics of Quantum Computing and Blockchain -- 2.5 Quantum BIT -- 2.6 Qubit Gates and Their Types -- 2.7 Quantum Circuit Modelling -- 3 Case Study: Real-World Life Problem Related to Optimal Stock Combination Selection Using QAOA -- 4 Quantum Blockchain -- 4.1 Research Challenges in Quantum Blockchain -- 5 Conclusion and Future Directions -- 5.1 Future Directions -- References -- Secure Blockchain-Based Mental Healthcare Framework:-A Paradigm Shift from Traditional to Advanced Analytics -- 1 Introduction -- 2 Literature Research Study Method -- 2.1 Research Database Sources -- 2.2 Search Query Keyword -- 3 Methodology -- 4 Related Work -- 4.1 Existing Block Chain Technologies for Healthcare -- 5 Technological Overview -- 5.1 The Nature of Data and the Paradigm Shift Towards Secure Value-Based Mental Healthcare -- 6 Blockchain Taxonomy -- 7 Blockchain for Value-Based Mental Healthcare -- 8 Blockchain-Based Mental Healthcare (EHR, Data Sources, Techniques, and Technologies) -- 9 Mental Health Care Data Sources -- 10 Analytical Techniques and Technologies -- 11 Framework for Value-Based Secure Mental Healthcare. 11.1 Mobile Application Architecture. |
| Record Nr. | UNINA-9910585783503321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Sustainable Blended Learning in STEM Education for Students with Additional Needs [[electronic resource] /] / edited by Neelu Jyothi Ahuja, Adarsh Kumar, Anand Nayyar
| Sustainable Blended Learning in STEM Education for Students with Additional Needs [[electronic resource] /] / edited by Neelu Jyothi Ahuja, Adarsh Kumar, Anand Nayyar |
| Autore | Ahuja Neelu Jyothi |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (351 pages) |
| Disciplina | 507.1 |
| Altri autori (Persone) |
KumarAdarsh
NayyarAnand |
| Collana | Contributions to Environmental Sciences & Innovative Business Technology |
| Soggetto topico |
Sustainability
Education - Data processing People with disabilities - Education Science - Study and teaching Computers and Education Education and Disability Science Education |
| ISBN | 981-9934-97-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Roles and Responsibilities of a Virtual Teacher -- Hybrid Learning System: Analysis, Opportunities, Challenges, and Prospects -- COVID-19 Pandemic and changing dynamics in Teaching and Learning Strategies: A study of student-centric blended learning approach -- Blended Learning in COVID-19 Era and Way-Forward -- Blended learning in COVID-19 Era: Pre and Post COVID times, Lessons learned and way forward -- An investigative study of students’ and faculty perspective towards transition to online teaching during COVID-19 pandemic -- Survey of Blended Learning Approaches, Frameworks, Tools and Techniques for Science and Management Students -- Blended Learning and STEM Education for students with special needs and learning disabilities -- Designing Integrative and Collaborative Learning for Students with Special Needs and Learning Disabilities in an Inclusive Classroom -- Maintaining Performance and QoS of Software Tools for Remote-Teaching Environment -- Students’ Learning Outcomes and Emerging Practices of Blended learning: A case study -- Collaborative and Sustainable Blended Learning in UTAS Salalah -- Integration of Blended Mode of Technologies in Teaching and Learning of Engineering Content at Higher Educational Institutions -- Exploring the Scope of Learning Analytics in Blended Learning Environments. |
| Record Nr. | UNINA-9910742491503321 |
Ahuja Neelu Jyothi
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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