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7th International Conference on Computing, Control and Industrial Engineering (CCIE 2023) : Advances in Computing, Control and Industrial Engineering VII / / edited by Yuriy S. Shmaliy, Anand Nayyar
| 7th International Conference on Computing, Control and Industrial Engineering (CCIE 2023) : Advances in Computing, Control and Industrial Engineering VII / / edited by Yuriy S. Shmaliy, Anand Nayyar |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (1060 pages) |
| Disciplina | 629.8 |
| Collana | Lecture Notes in Electrical Engineering |
| Soggetto topico |
Engineering mathematics
Engineering - Data processing Electrical engineering Industrial engineering Production engineering Control engineering Mathematical and Computational Engineering Applications Electrical and Electronic Engineering Industrial and Production Engineering Control and Systems Theory |
| ISBN | 981-9927-30-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Electrical, Electronic Engineering and Automation -- Artificial Intelligence and its Applications -- Signal Processing and Pattern Recognition -- Communication, Information, and Networking -- Fault Diagnosis, Simulation and Optimization Techniques. |
| Altri titoli varianti | Computing Control and Industrial Engineering (CCIE), 2023 International Conference on |
| Record Nr. | UNINA-9910735780003321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Intelligent System and Smart Technologies : Proceedings of I2ST'23
| Advances in Intelligent System and Smart Technologies : Proceedings of I2ST'23 |
| Autore | Gherabi Noredine |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2024 |
| Descrizione fisica | 1 online resource (417 pages) |
| Altri autori (Persone) |
AwadAli Ismail
NayyarAnand BahajMohamed |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 3-031-47672-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Specific Topics -- Committee -- Keynote Speakers -- About This Book -- Contents -- A New Design of 5G Planar Antenna with Enhancement of the Gain Using Array Antenna -- 1 Introduction -- 2 Design Methodologies -- 2.1 A Conventional Square Patch Antenna's Design -- 2.2 Design of a 1 × 4 Antenna Array Containing 4 Radiation Elements -- 2.3 Design of a 4 × 4 Antenna Array Containing 16 Radiation Elements -- 2.4 Design of a 8 × 4 Antenna Array Containing 32 Radiation Elements -- 3 Conclusion and Perspectives -- References -- Temperature Forecast Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Study Area -- 5 Results and Discussion -- 6 Conclusion -- References -- Digital Twin-Based Approach for Electric Vehicles: E-Mule Project -- 1 Introduction -- 2 Digital Twin: Background and Definitions -- 3 Related Works -- 4 E-Mule Digital Twin -- 4.1 Induction Motor -- 4.2 Lithium-Ion Battery -- 5 Technical Solutions -- 5.1 Data Collection -- 5.2 Data Transmission -- 5.3 3D Modeling -- 6 Conclusion -- References -- Vision-Based Fall Detection Systems Using 3D Skeleton Features for Elderly Security: A Survey -- 1 Introduction -- 2 Fall Detection System: Overview -- 3 Fall Detection Skeleton Datasets -- 3.1 Human Body Representation -- 3.2 Available 3D Skeletal Datasets -- 3.3 Limitation and Challenges -- 4 Vision-Based Fall Detection Approaches -- 5 Conclusion -- References -- Capacity Prediction for Lithium-Ion Batteries Using Different Neural Networks Methods -- 1 Introduction -- 2 Proposed Methods -- 3 Capacity Estimation -- 3.1 Nasa Datasets Prediction -- 4 Comparative Results Analysis -- 5 Conclusion -- References -- Deployment of Deep Learning in BlockChain Technology for Credit Card Fraud Prevention -- 1 Introduction -- 2 Background and Motivation -- 2.1 What is Blockchain?.
2.2 How Does the Blockchain Work? -- 2.3 Strengths of Blockchain -- 2.4 BlockChain Weaknesses -- 2.5 Chainlink -- 3 Methodology -- 3.1 Deep Learning Model -- 3.2 Blockchain -- 3.3 External Adapter -- 3.4 Cryptocurrency -- 4 Visualization -- 4.1 Normal User -- 4.2 Contract's Owner -- 5 Conclusion -- References -- A Survey on Cybersecurity Techniques Toward Convolutional Neural Network -- 1 Introduction -- 2 The Fundamentals of CNN -- 3 Security Threats Toward CNN -- 4 Detection Techniques of CNN -- 4.1 Malware Classification -- 4.2 Malware Detection -- 5 Conclusion -- References -- Publications and Messages Exchanged in a Chat Room Analysis -- 1 Introduction -- 2 Related Work -- 3 Proposed Model and Algorithms -- 3.1 Centers of Interests -- 3.2 Psychological Profile -- 3.3 Relational Profile -- 4 Results and Discussion -- 4.1 Profiling System Result -- 5 Conclusion -- References -- Detection of Common Risk Factors Leading to the Cardiovascular Illness Using Machine Learning -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 BRFSS Heart Disease Dataset -- 3.2 Datasets Preprocessing -- 3.3 Model Training -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Machine Learning Models for Detection COVID-19 -- 1 Introduction -- 2 State of the Art -- 3 Functional Testing Methods -- 3.1 PCR Test -- 3.2 Chest Radiography Images -- 4 COVID19 Detection Models Using Machine Learning Approaches -- 5 Comparison Study Between Methods -- 6 Conclusion and Discussion -- References -- DoS and DDoS Cyberthreats Detection in Drone Networks -- 1 Introduction -- 2 Context of the Study -- 2.1 Fleet of Drones -- 2.2 DoS and DDoS Cyber-Attacks -- 2.3 Network Intrusion Detection Systems (NIDS) -- 3 Related Work -- 3.1 State of the Art -- 3.2 Discussion -- 4 Proposed Approach -- 4.1 Architecture of the Proposed NIDS. 4.2 Operating Principle of the Proposed Model of NIDS -- 5 Experimentation and Tests -- 5.1 CICIDS2017 Dataset -- 5.2 Algorithms Used to Model Benign Network Traffic and DoS/DDoS Attacks -- 6 Summary of Benign Traffic and Attacks Classification Results -- 7 Conclusion -- References -- Artificial Intelligence in Supply Chain 4.0: Using Machine Learning in Demand Forecasting -- 1 Introduction -- 2 Demand Forecasting in Supply Chain -- 3 Machine Learning Model for Demand Forecasting in Supply Chain -- 3.1 Methodology -- 3.2 Data Visualization -- 3.3 Data Segmentation -- 3.4 Data Modeling -- 3.5 Model Evaluation -- 3.6 Comparison of Classifications Models -- 4 Conclusion -- References -- COVID-19 Prediction Applying Machine Learning and Ontological Language -- 1 Introduction -- 2 Literature Review -- 3 Methodology of Research -- 3.1 Data Preprocessing -- 3.2 Machine Learning Decision Tree Algorithm -- 3.3 Ontology Engineering -- 4 Result and Discussion -- 5 Conclusion -- References -- EEG-Based Drivers Drowsiness Prediction Using Personalized Features Extraction and Classification Methods Under Python -- 1 Introduction -- 2 Method -- 2.1 Acquisition and Preprocessing -- 2.2 Main Processing Method -- 2.3 Classification and Predicting -- 3 Results and Discussion -- 4 Conclusion -- References -- A Systematic Review on Blind and Visually Impaired Navigation Systems -- 1 Introduction -- 2 Literature Review -- 2.1 Research Methodology -- 2.2 State-of-the-Art -- 3 Discussion and Recommendations -- 3.1 Discussion -- 3.2 Recommendations -- 4 Conclusion and Future Work -- References -- Comparison of Deep Learning-Based Channel Estimator and Classical Estimators in VANET -- 1 Introduction -- 2 IEEE 802.11p Standard -- 2.1 Environment and Vehicle-To-Vehicle Channel -- 2.2 Channel Vehicle-to-Vehicle Model -- 3 Estimation and Interpolation of Channel. 3.1 LS Channel Estimation Algorithm -- 3.2 MMSE Channel Estimation Algorithm -- 3.3 Linear Interpolation -- 3.4 Spline Cubic Interpolation -- 4 Channel Estimators Based on Neural Networks -- 4.1 Estimator and Structure OFDM -- 4.2 Channel Estimator Structure of Basic Neural Network -- 5 Simulation and Resultats -- 5.1 Simulations Parameters -- 5.2 Channel's Coherence Time Effect -- 6 Conclusion -- References -- Decision Support Systems Based on Artificial Intelligence for Supply Chain Management: A Literature Review -- 1 Introduction and Motivation -- 2 Concepts -- 2.1 Supply Chain Management -- 2.2 Decision Support System -- 3 DSS Based IA for SCM: A Literature Review -- 3.1 Research Methodology -- 3.2 Adopted IA Methods in SCM -- 4 Discussion -- 5 Conclusion -- References -- Minimization of Task Offloading Latency for COVID-19 IoT Devices -- 1 Introduction -- 2 Related Work and Motivation -- 2.1 Latency -- 2.2 Energy Consumption -- 3 System Model -- 4 Problem Formulation -- 5 Results and Discussion -- 6 Conclusion and Perspectives -- References -- Machine Learning, Deep Learning, and Computer Vision for Age and Gender Detection -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Methods and Materials -- 4.1 Computer Vision -- 4.2 Machine Learning -- 4.3 Deep Learning -- 4.4 Model Architecture Overview -- 5 Results and Discussion -- 6 Conclusion -- References -- Grape and Apple Plant Diseases Detection Using Enhance DenseNet121 Based Convolutional Neural Network -- 1 Introduction -- 2 Related Work -- 3 Material and Method -- 3.1 Dataset -- 3.2 Image Preprocessing and Data Augmentation -- 3.3 Convolutional-Neural-Network Models -- 3.4 Transfer-Learning Approach -- 3.5 Proposed System -- 4 Experiment Results -- 4.1 Performance Evaluation -- 4.2 Parameters -- 4.3 Results Analysis and Comparison -- 5 Conclusion -- References. Operational Code Based on the Lattice Boltzmann Method for Coastal Flows: Application to Oualidia Lagoon -- 1 Introduction -- 2 Presentation of the Shallow Water Equations -- 3 Lattice Boltzmann Method (LBM) -- 3.1 Lattice Pattern -- 3.2 Boundary Conditions -- 4 Flowchart of the Operational Code -- 5 Numerical Test -- 6 Application to Oualidia Lagoon -- 7 Conclusion -- References -- The Use of Chatbots as Supportive Agents in Air Transportation Systems -- 1 Introduction -- 2 Literature Review -- 3 Chatbots and Artificial Intelligence -- 3.1 Chatbots -- 3.2 Artificial Intelligence and Chatbots -- 3.3 Chatbot Frameworks -- 4 The Proposed Methodology -- 4.1 Case Study -- 4.2 Conception of Chatbot -- 5 Results and Discussion -- 6 Conclusion -- References -- The Conception of a Controlled Trigonometric Phase Locked Loop Working Under Grid Anomalies Conditions -- 1 Introduction -- 2 Methods -- 2.1 A Conventional PLL in the Synchronous dq Frame -- 2.2 Trigonometric Phase Locked Loop -- 3 Results and Discussion -- 3.1 Time Response of the Controlled PLL and Angle Jump Test -- 3.2 Unbalanced Grid Voltage -- 3.3 Non Sinusoidal Grid Voltage -- 4 Conclusion -- References -- A Deep Learning Model for Intrusion Detection with Imbalanced Dataset -- 1 Introduction -- 2 Related Work -- 3 Background -- 4 Deep Learning -- 4.1 Feature Selection -- 5 Our Approach -- 5.1 NSL-KDD -- 5.2 Shap Value, Boruta and Anova f-test -- 6 Experimental Results and Discussion -- 7 Conclusion -- References -- Towards Complex Systems Behavioral Prediction: A Survey of Artificial Intelligence Applications -- 1 Introduction -- 1.1 Complex Systems -- 1.2 Characteristics of Complex Systems -- 1.3 Complex Adaptive Systems -- 2 Flood Prediction -- 3 Fetal Monitoring -- 4 Electrical Systems and Renewable Energies -- 5 Extreme Events and Critical Transitions -- 6 Forest Fire. 7 Financial Markets. |
| Record Nr. | UNINA-9910841861203321 |
Gherabi Noredine
|
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| Cham : , : Springer International Publishing AG, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Development and future of internet of drones (IoD) : insights, trends and road ahead / / Rajalakshmi Krishnamurthi, Anand Nayyar, Aboul Ella Hassanien, editors
| Development and future of internet of drones (IoD) : insights, trends and road ahead / / Rajalakshmi Krishnamurthi, Anand Nayyar, Aboul Ella Hassanien, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (275 pages) |
| Disciplina | 004.678 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico |
Internet of things
Drone aircraft - Automatic control Aerial surveillance - Automatic control Drons Internet de les coses Aprenentatge automàtic Intel·ligència artificial |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-63339-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483663903321 |
| Cham, Switzerland : , : Springer, , [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 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 | ||
| ||
Emerging technologies for battling Covid-19 : applications and innovations / / Fadi Al-Turjman, Ajantha Devi, Anand Nayyar, editors
| Emerging technologies for battling Covid-19 : applications and innovations / / Fadi Al-Turjman, Ajantha Devi, Anand Nayyar, editors |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XIV, 359 p. 210 illus., 190 illus. in color.) |
| Disciplina | 610.285 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico | Medical informatics |
| ISBN | 3-030-60039-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Drone-based social distancing, sanitizing, inspection, monitoring and control room for covid-19 -- COVID 19 Prediction Models Using Machine Learning Techniques -- Perspective to Definition of Data Visualization: A mapping study and discussion on Coronavirus dataset -- Blockchain based framework to maintain trust among various stakeholders involved in COVID -- Role of Big Data in COVID-19 Pandemic: Opportunities, Challenges and Future Avenues -- Artificial intelligence techniques for resources management during covid-19 -- Applications Of Artificial Intelligence And Internet Of Things For Detection And Future Directions To Fight Against Covid-19 -- Robotics and drone-based solutions for covid 19 using AI and IOT -- A novel framework for Wearable device-based identification, monitoring, collaborating and crowdsourcing for covid -19 -- Effectiveness of Big Data in Early Prediction and Measures for COVID-19 using Data Science -- COVID-19: Creating Paradigm Shift in Education System -- Dynamic Models and Control Techniques for Drone Delivery of Medications and Other Healthcare Items in COVID-19 Hotspots -- Disaster management techniques using AI due to COVID-19 -- COVID-19 Impact on Education Systems -- Mobile Technology Solutions for COVID-19 -- Predictive Analysis of COVID 19 transmission- Mathematical modelling study -- Analyzing the effects of covid 19 using big data analysis -- Intrinsic and Extrinsic Motivation for Online Teaching in COVID-19: Applications, Issues and Solution -- Conclusion. |
| Record Nr. | UNINA-9910485009703321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Emerging technologies for battling Covid-19 : applications and innovations / / Fadi Al-Turjman, Ajantha Devi, Anand Nayyar, editors
| Emerging technologies for battling Covid-19 : applications and innovations / / Fadi Al-Turjman, Ajantha Devi, Anand Nayyar, editors |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XIV, 359 p. 210 illus., 190 illus. in color.) |
| Disciplina | 610.285 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico | Medical informatics |
| ISBN | 3-030-60039-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Drone-based social distancing, sanitizing, inspection, monitoring and control room for covid-19 -- COVID 19 Prediction Models Using Machine Learning Techniques -- Perspective to Definition of Data Visualization: A mapping study and discussion on Coronavirus dataset -- Blockchain based framework to maintain trust among various stakeholders involved in COVID -- Role of Big Data in COVID-19 Pandemic: Opportunities, Challenges and Future Avenues -- Artificial intelligence techniques for resources management during covid-19 -- Applications Of Artificial Intelligence And Internet Of Things For Detection And Future Directions To Fight Against Covid-19 -- Robotics and drone-based solutions for covid 19 using AI and IOT -- A novel framework for Wearable device-based identification, monitoring, collaborating and crowdsourcing for covid -19 -- Effectiveness of Big Data in Early Prediction and Measures for COVID-19 using Data Science -- COVID-19: Creating Paradigm Shift in Education System -- Dynamic Models and Control Techniques for Drone Delivery of Medications and Other Healthcare Items in COVID-19 Hotspots -- Disaster management techniques using AI due to COVID-19 -- COVID-19 Impact on Education Systems -- Mobile Technology Solutions for COVID-19 -- Predictive Analysis of COVID 19 transmission- Mathematical modelling study -- Analyzing the effects of covid 19 using big data analysis -- Intrinsic and Extrinsic Motivation for Online Teaching in COVID-19: Applications, Issues and Solution -- Conclusion. |
| Record Nr. | UNISA-996464499903316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
The Fifth International Conference on Safety and Security with IoT : SaSeIoT 2021 / / edited by Anand Nayyar, Anand Paul, Sudeep Tanwar
| The Fifth International Conference on Safety and Security with IoT : SaSeIoT 2021 / / edited by Anand Nayyar, Anand Paul, Sudeep Tanwar |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (211 pages) |
| Disciplina | 004.678 |
| Collana | EAI/Springer Innovations in Communication and Computing |
| Soggetto topico |
Cooperating objects (Computer systems)
Telecommunication Internet of things Cyber-Physical Systems Communications Engineering, Networks Internet of Things |
| ISBN | 3-030-94285-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Opportunistic Multi-Modal User Authentication for Health-Tracking IoT Wearables -- 2. On-Phone CNN Model-based Implicit Authentication to Secure IoT Wearables -- 3. A Cybersecurity Guide for Using Fitness Devices -- 4. An efficient algorithm for human abnormal behaviour detection using object detection and pose estimation -- 5. A Secure and Scalable IoT Consensus Protocol -- 6. Session Key Agreement Protocol for Secure D2D Communication -- 7. What Do Your Smart-Home Devices Reveal About You? -- 8. A Quantum-Resistant and Fast Secure Boot for IoT Devices Using Hash-Based Signatures and SRAM PUFs -- 9. On the Analysis of MUD-Files’ Interactions, Conflicts, and Configuration Requirements Before Deployment -- 10. Natural Scenes’ Text Detection and Recognition using CNN and Pytesseract -- 11. Assessing the Resistance of Internet of Things Applications Against Memory Corruption Attacks: A Case Study for Contiki and Tizen -- 12. IoT geography chain: Blockchain based solution for Logistics eco system. |
| Record Nr. | UNINA-9910627236103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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IoT and IoE Driven Smart Cities
| IoT and IoE Driven Smart Cities |
| Autore | Nath Sur Samarendra |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2022 |
| Descrizione fisica | 1 online resource (328 pages) |
| Altri autori (Persone) |
BalasValentina Emilia
BhoiAkash Kumar NayyarAnand |
| Collana | EAI/Springer Innovations in Communication and Computing Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9783030827151
9783030827144 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Editors -- 1 A Comprehensive Review on Physical Layer Design for Smart Cities -- 1.1 Introduction -- 1.2 Backscatter Communication Systems -- 1.3 RIS -- 1.4 Physical Layer Security -- 1.5 A Case Study of Backscatter System -- 1.5.1 Outage Probability Analysis -- 1.5.2 OP of D1 -- 1.5.3 OP of BD -- 1.5.4 OP of D2 -- 1.5.5 Numerical Results -- 1.6 Conclusion -- References -- 2 An Overview of Security and Privacy in Smart Cities -- 2.1 Introduction -- 2.2 Smart City Architecture -- 2.2.1 The IoT in Smart City -- 2.3 Smart City Applications -- 2.4 Smart City Characteristics -- 2.5 Security and Privacy Challenges -- 2.5.1 Privacy Challenges in Smart Cities -- 2.5.2 Countermeasures and Solutions for Securing Smart City -- 2.6 Related Work -- 2.6.1 Summary -- 2.7 Challenges and Future Directions -- 2.8 Conclusion -- References -- 3 Multi-antenna-Enabled Technologies for IoT-Driven Smart Cities -- 3.1 Introduction -- 3.2 Multi-antenna Systems -- 3.2.1 SISO -- 3.2.2 SIMO -- 3.2.3 MISO -- 3.2.4 MIMO -- 3.2.5 Massive MIMO -- 3.2.6 Smart Antenna -- 3.2.7 Signal Processing in Multi-antenna Systems -- 3.3 Benefits of Multi-antenna System in IoT -- 3.4 Multi-antenna-Enabled Technologies -- 3.4.1 5G -- Millimeter-Wave Radio Access Technology in 5G -- 5G Architecture -- 3.4.2 Beyond 5G -- AI and ML in Telecom Networks -- 3.4.3 New Wi-Fi, WiMAX Versions -- 3.4.4 Vehicular Networks -- 3.5 Smart Cities' Case Studies -- 3.5.1 Smart City of Toronto -- 3.5.2 Smart City of Santiago -- 3.6 Conclusion -- 3.7 Future Scope -- References -- 4 Design of Multiple Access Network by Enabling User Grouping and Energy Harvesting in Relaying System for Smart Cities -- 4.1 Introduction -- 4.2 System Model -- 4.3 Outage Probability -- 4.3.1 Outage Probability of U1 -- 4.3.2 Outage Probability of U2 -- 4.3.3 The Imperfect SIC at U1.
4.3.4 The Benchmark: OMA -- 4.4 Numerical and Simulation Results -- 4.5 Conclusion -- Appendix A -- Proof of Proposition 1 -- Appendix B -- Proof of Proposition 2 -- Appendix C -- Proof of Proposition 3 -- Appendix D -- Proof of Proposition 4 -- References -- 5 Examining the Adoption and Application of Internet of Things for Smart Cities -- 5.1 Introduction -- 5.1.1 IoT Technologies for Smart Cities -- 5.2 Concepts of Smart City -- 5.3 Motivations for Smart City Development in the Developing Countries -- 5.4 Requirements of IoT Platform for Smart City -- 5.5 Taxonomy of IoT-Based Smart City -- 5.6 IoT Platform for Smart Cities -- 5.6.1 DIMMER -- 5.6.2 FLEXIMETER -- 5.7 Issues and Challenges -- 5.8 Applications of IoT in Smart Cities -- 5.9 Case Studies -- 5.10 Conclusion -- References -- 6 Internet of Everything (IoE) in Smart City Paradigm Using Advanced Sensors for Handheld Devices and Equipment -- 6.1 Introduction -- 6.1.1 Need for Smart City -- 6.1.2 IoE and the Smart City -- 6.1.3 Organization -- 6.2 Areas of Smart City Applications and Services -- 6.2.1 Smart Buildings -- 6.2.2 City Air Management Tool (CyAM) -- Consequences -- 6.2.3 Traffic Management -- 6.2.4 Smart Parking -- 6.2.5 Smart Waste Management -- 6.3 Big Data, IoT, and Cloud Computing -- 6.4 Smart City Smart Infrastructure (2010-2023*) -- 6.5 Blockchain Technology in IoT -- 6.5.1 Scenario 1 -- 6.5.2 Scenario 2 -- 6.6 Energy-Efficient Wireless Network -- 6.7 WSN in Smart Cities -- 6.8 Areas of WSN Application -- 6.8.1 Touchscreen -- 6.8.2 Motion Sensors -- 6.8.3 Multimedia Sensors -- 6.8.4 Barometer -- 6.8.5 Ambient Light Sensor -- 6.9 Conclusion -- References -- 7 Machine Learning and Deep Learning Algorithms for Smart Cities: A Start-of-the-Art Review -- 7.1 Introduction -- 7.2 Application of Internet of Things (IoT) in Smart Cities -- 7.2.1 IoT Technologies in Smart Cities. 7.3 Machine Learning and Deep Learning Algorithm Technology for Smart Cities -- 7.4 The Relevance of Machine Learning and Deep Learning in Urban Sustainability and Smart Cities -- 7.4.1 Smart City-Supporting Technologies -- 7.5 The Research Challenges of Machine Learning and Deep Learning in Urban Sustainability and Smart Cities -- 7.5.1 The Futuristic Solutions in Using Machine Learning and Deep Learning in Smart City Implementations -- 7.6 Conclusion and Future Directions -- References -- 8 A Framework for the Actualization of Green Cloud-Based Design for Smart Cities -- 8.1 Introduction -- 8.2 The Prospect and Challenges of the Smart Cities -- 8.2.1 The Features of Smart Cities -- 8.2.2 Green Smart IoT-Cloud-Based Smart Cities -- 8.2.3 Prospect and Challenges of Smart Cities -- 8.3 Literature Review -- 8.4 Framework for Green Smart Cities -- 8.4.1 Green IoT/IoE Devices -- 8.4.2 Fog Infrastructure -- 8.4.3 The Cloud Services -- 8.4.4 Smart City -- 8.5 Conclusion and Future Directions -- References -- 9 Design of a Confidentiality Model Using Semantic-Based Information Segmentation (SBIS) and Scattered Storage in Cloud Computing -- 9.1 Introduction -- 9.1.1 Organization -- 9.2 Preface -- 9.3 Genesis -- 9.4 Contributions -- 9.5 Safety Prototypes and System Framework -- 9.6 Safeguarding Information Without Negotiating Confidentiality -- 9.6.1 Illustration 1 (Background Refinement) -- 9.6.2 Illustration 2 ((di, O(di))) Refinement -- 9.7 Subcontracting of Information with Confidentiality Assurance Using Background Refinement and Semantic Data Segmentation -- 9.7.1 Identification of Precarious Words -- 9.7.2 Illustration 3 (Data Hypothesis for Background Refinement) -- 9.7.3 Algorithm: Identification of Precarious Words -- 9.7.4 Semantic-Based Information Segmentation and Scattered Storage -- 9.7.5 Data Segmentation and Scattered Storage. 9.8 Performance Analysis -- 9.8.1 Evaluation Parameters -- 9.9 Results and Discussion -- 9.10 Summary -- 9.11 Conclusion -- 9.12 Future Scope -- References -- 10 Maintaining IoT Healthcare Records Using Cloud Storage -- 10.1 Introduction to Healthcare Records -- 10.2 Introduction to Cloud Storage -- 10.3 Challenges in Storing Healthcare Records on Cloud -- 10.3.1 Technical Challenges -- 10.3.2 Nontechnical Challenges -- 10.4 Challenges in IoT-Cloud-Based Healthcare Innovations -- 10.4.1 Smart Cities' Healthcare Using IoT -- 10.5 Providing Security to Cloud-Stored Healthcare Records -- 10.5.1 Access Control Model -- 10.5.2 Crypt Databases -- 10.6 IoT and Cloud Integration in Medical Healthcare -- 10.7 Integration with AI for Identification of Hidden Patterns -- 10.8 Conclusion -- References -- 11 Use of IoT in Net-Zero Smart City Concept in the Indian Context: A Bibliographic Analysis of Literature -- 11.1 Introduction -- 11.2 Methodology: Bibliographic Analysis of Literature -- 11.3 Literature Review -- 11.3.1 Planning Factors and Use of IoT -- 11.3.2 Role of Citizen Engagement and Community Participation in Net-Zero City -- 11.3.3 Energy and Transportation and Use of IoT -- 11.4 Findings and Discussions -- 11.4.1 Factorial Analysis -- 11.4.2 Three-Field Plot -- 11.4.3 Thematic Evolution and Thematic Map -- 11.4.4 Tree Mapping Analysis and Word Growth Analysis -- 11.4.5 Country Collaboration Map -- 11.5 Conclusion -- References -- 12 Smart and Innovative Water Conservation and Distribution System for Smart Cities -- 12.1 Introduction -- 12.2 Literature Review -- 12.2.1 Source of Groundwater -- 12.2.2 Community Water Treatment -- 12.2.3 Water Distribution Pattern -- 12.2.4 Water Tanks -- Types of Tanks -- 12.2.5 Water Stress in Smart Cities -- 12.3 Component Details -- 12.3.1 Automated Valve -- 12.3.2 Flow Sensor -- 12.3.3 Types of Flow Sensor. 12.4 NodeMCU -- 12.5 Proposed System -- 12.5.1 Working of Smart Tap -- 12.5.2 Working on Regular Mode -- 12.5.3 Saver Mode -- 12.5.4 Mobile Application -- 12.5.5 Nozzle Selection -- 12.5.6 Conservation Statistics -- 12.6 Conclusion -- References -- 13 IoT Technology-Based Urban Water Management Strategies Using Indian Traditional Knowledge System -- 13.1 Introduction -- 13.2 Research Methodology -- 13.3 Literature Review -- 13.3.1 Importance of Indian Traditional Water Management Knowledge -- 13.3.2 Review of AMRUT Scheme -- 13.3.3 IoT in Water Management -- 13.3.4 Benefits of Using IoT and Traditional Knowledge in Water Management -- 13.3.5 Role of Community in Resource Management and Sustainability -- 13.4 Study Area -- 13.4.1 Water Problems in the Selected Cities -- 13.4.2 Integrating Existing Schemes, Programs, and Policies -- 13.5 Discussion and Strategies -- 13.6 Conclusion -- References -- 14 X-IoT: Architecture and Use Cases for an IoT Platform in the Area of Smart Cities -- 14.1 Introduction -- 14.2 Role of Data and AI Platform in Collecting IoT Information in Smart Cities -- 14.2.1 Literature Overview -- 14.2.2 Practitioner Context -- 14.2.3 Safe, Healthy, and Livable: Smart City Solutions and Problems They Solve -- 14.2.4 Real-Life Implementation Examples -- 14.3 Typical Technological Challenges and Best Practices of Smart City Implementations -- 14.3.1 Data Availability, Open Data, and Data Sharing -- 14.3.2 Data Governance and Life Cycle Management for Smart Cities -- 14.3.3 Operationalization of Analytics and AI for Smart Cities -- 14.3.4 Reference Architecture for Data and AI Platform: X-IoT by Capgemini -- 14.4 Conclusion and Outlook -- References -- Index. |
| Record Nr. | UNINA-9910513580303321 |
|
Nath Sur Samarendra
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| Cham : , : Springer International Publishing AG, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine learning for critical Internet of medical things : applications and use cases / / edited by Fadi Al-Turjman and Anand Nayyar
| Machine learning for critical Internet of medical things : applications and use cases / / edited by Fadi Al-Turjman and Anand Nayyar |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (267 pages) |
| Disciplina | 610.28563 |
| Soggetto topico |
Internet of things
Artificial intelligence - Medical applications Machine learning |
| ISBN | 3-030-80928-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464553703316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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