| Autore |
Mishra Brojo Kishore
|
| Edizione | [1st ed.] |
| Pubbl/distr/stampa |
Newark : , : John Wiley & Sons, Incorporated, , 2024
|
| Descrizione fisica |
1 online resource (247 pages)
|
| Disciplina |
681.2
|
| Altri autori (Persone) |
MallikSandipan
LeDac-Nhuong
|
| Collana |
Advances in Learning Analytics for Intelligent Cloud-IoT Systems Series
|
| Soggetto topico |
Detectors
|
| ISBN |
9781394214723
1394214723
9781394214716
1394214715
|
| Formato |
Materiale a stampa  |
| Livello bibliografico |
Monografia |
| Lingua di pubblicazione |
eng
|
| Nota di contenuto |
Cover -- Series Page -- Title Page -- Copyright Page -- Dedication Page -- Contents -- List of Figures -- List of Tables -- Foreword -- Preface -- Acknowledgments -- Acronyms -- Chapter 1 IoT-Based Health Monitoring Using a Hybrid Machine Learning Model -- 1.1 Introduction -- 1.2 Related Works -- 1.3 Research Gap -- 1.4 Proposed Model -- 1.4.1 Model Analysis with Result and Discussion -- 1.4.2 Dataset Description -- 1.4.3 Model Description -- 1.5 Conclusion -- References -- 2 Addressing Overcrowding: A Plight for Smart Cities -- 2.1 Introduction -- 2.1.1 Smart Industry 4.0 -- 2.1.2 IoT and IIoT -- 2.1.3 IoT - A Basis of Big Data -- 2.1.4 Smart Cities -- 2.2 Overcrowding -- 2.2.1 Causes -- 2.2.2 Consequences -- 2.2.3 Challenges -- 2.3 Existing Applications -- 2.3.1 Traffic Congestion -- 2.3.2 Tourism Control -- 2.3.3 Sustainable Usage of Resources -- 2.3.4 Housing and Infrastructure -- 2.3.5 Public Safety and Security -- 2.4 Modified PSO for Optimal Path in Crowded Areas -- 2.4.1 Step 1: Modeling the Environment and Obstacles -- 2.4.2 Step 2: Particle Swarm Initialization -- 2.4.3 Step 3: Evaluating the Fitness Function -- 2.4.4 Step 4: Particle Position and Velocity Update -- 2.5 Scope -- 2.6 Conclusion -- References -- Chapter 3 Smart Sensors for Environmental Monitoring in Industry 4.0 -- 3.1 Introduction to Smart Sensors for Environmental Monitoring in Industry 4.0 -- 3.1.1 Basic Concepts of Industry 4.0 and Environmental Monitoring -- 3.1.2 Overview of Smart Sensors and Their Applications in Industry 4.0 -- 3.1.3 Challenges in Smart Sensor Design and Implementation for Environmental Monitoring in Industry 4.0 -- 3.2 State-of-the-Art of Smart Sensors for Environmental Monitoring in Industry 4.0 and Real-World Applications -- 3.2.1 Types of Smart Sensors for Environmental Monitoring in Industry 4.0.
3.2.2 Sensor Networks and Communication Protocols for Smart Sensors in Industry 4.0 -- 3.2.3 Data Processing and Analysis for Smart Sensors in Industry 4.0 -- 3.2.4 Integration of Smart Sensors with Cloud Computing and IoT Platforms for Environmental Monitoring -- 3.2.5 Verification and Validation of Smart Sensors for Environmental Monitoring in Industry 4.0 -- 3.2.6 Energy-Efficient and Sustainable Design of Smart Sensors for Environmental Monitoring in Industry 4.0 -- 3.3 Case Studies and Practical Examples of Smart Sensors for Environmental Monitoring in Industry 4.0 -- 3.4 Regulatory and Compliance Considerations for Smart Sensors in Environmental Monitoring -- 3.5 Future Directions and Research Challenges in Smart Sensors for Environmental Monitoring in Industry 4.0 -- 3.6 Conclusion -- References -- Chapter 4 A Novel Hybrid Smart Appliances Control Framework for Specially Challenged Persons -- 4.1 Introduction -- 4.2 Literature Review -- 4.3 Features of Smart Home Appliances -- 4.4 Materials and Methods -- 4.5 Proposed Hybrid Smart Appliances Approach -- 4.6 Conclusion and Future Scope -- References -- Chapter 5 An IoT-based Framework for PUC Monitoring of 2- or 4-Wheeler Vehicle -- 5.1 Introduction -- 5.2 Literature Review -- 5.3 Indian Regulations to Control Air Pollution -- 5.4 Motivation of Work -- 5.5 Proposed Approach -- 5.5.1 Working Process -- 5.5.2 Establishing Communication with Moving Object: Vehicle and Workstation -- 5.6 Existing Technology and Discussion -- 5.7 Conclusion -- References -- Chapter 6 Farm Shielding: A Shielding Experience That Takes a New Turn -- 6.1 Introduction -- 6.2 Desk Research -- 6.3 User Research -- 6.4 Problem Identification -- 6.5 Ideation and Design -- 6.6 How the Scarecrow Works -- 6.7 Conclusion and Future Scope -- References -- Chapter 7 Checkmate: An IoT Integrated Tangible Chessboard.
7.1 Introduction -- 7.2 Literature Review -- 7.2.1 Psychology -- 7.2.2 Chess and Academic and Non-Academic Skills -- 7.2.3 Insights -- 7.2.4 Impacts of Tangible Interfaces in Gaming -- 7.2.5 Related Work -- 7.2.6 Competitive Analysis -- 7.3 Methodology -- 7.4 Design Intervention -- 7.5 Proposed Solution: IoT Integrated Tangible Chessboard -- 7.5.1 Experimental Setup -- 7.5.2 Algorithm -- 7.6 User Testing and Validation -- 7.7 Conclusion -- References -- 8 Intelligent Systems and Robotics for Wastewater Management Across India: A Study and Analysis -- 8.1 Introduction -- 8.2 Relevant Work -- 8.3 Theoretical Framework -- 8.3.1 Intelligent Systems -- 8.3.2 Artificial Neural Network -- 8.3.3 Genetic Algorithm -- 8.3.4 Fuzzy Logic -- 8.3.5 Machine Learning -- 8.3.6 Deep Learning -- 8.3.7 Data Analytics -- 8.4 Proposed Methodology -- 8.5 Industrial Waste -- 8.6 Robot Design Using Intelligent Systems -- 8.7 Conclusion -- References -- Chapter 9 Text-Based Prediction and Classification Model of Stress, Anxiety and Depression Among Indians -- 9.1 Introduction -- 9.2 Relevant Work -- 9.3 Discussion and Results -- 9.4 Conclusion -- References -- Chapter 10 Industry 4.0: Security Challenges and Opportunities of the IIoT -- 10.1 Introduction -- 10.2 Industry 4.0 Landscape -- 10.3 Literature Survey -- 10.4 Security Requirements in IIoT -- 10.5 Measures for Implementing Cybersecurity -- 10.5.1 Category 1: Smart Factories and Supply Chains -- 10.5.2 Category 2: Stakeholders -- 10.5.3 Category 3: Internet -- 10.5.4 Fog and Edge Computing -- 10.6 Conclusion -- References -- Chapter 11 Role of Machine Learning and Deep Learning in Smart Sensors -- 11.1 Introduction -- 11.2 Smart Sensors and Their Technology -- 11.2.1 Smart Sensors and Their Functionalities -- 11.2.2 Micro-Electromechanical Systems -- 11.2.3 Wireless Sensor Networks -- 11.3 Artificial Intelligence.
11.3.1 Machine Learning -- 11.3.2 Origin and Development of Deep Learning -- 11.3.3 Applications of Machine Learning and Deep Learning in Smart Sensors -- 11.4 Challenges and Opportunities in Fields of Smart Sensors -- 11.5 Conclusion -- References -- Chapter 12 Drone-Based Traffic Flow Management for Smart Cities: Problems and Solutions -- 12.1 Introduction -- 12.1.1 Traffic Flow Management in Smart Cities -- 12.1.2 Benefits of Smart Traffic Management Systems -- 12.1.3 Challenges of Smart Cities and Traffic Flow Management -- 12.1.4 Current Research -- 12.2 Limitations and Challenges of Traditional Traffic Management Systems -- 12.3 The Concept of Drone-Based Traffic Flow Management -- 12.3.1 Advanced Traffic Management System -- 12.3.2 Advanced Public Transportation System -- 12.3.3 Commercial Vehicle Operation -- 12.3.4 Benefits of Drone-Based Traffic Flow Management -- 12.3.5 Challenges of Drone-Based Traffic Flow Management -- 12.3.6 Applications of Drone-Based Traffic Flow Management -- 12.4 Applications of Drones in Traffic Flow Management -- 12.5 Types of Drones and Sensor Technologies Used in Traffic Flow Management -- 12.5.1 Types of Drones -- 12.5.2 Sensor Technologies -- 12.6 Integration of Drone Technology into Existing Traffic Management Systems -- 12.6.1 Benefits of Drone Technology in Traffic Management -- 12.6.2 Challenges of Integrating Drone Technology into Traffic Management -- 12.6.3 Integration Strategies -- 12.7 Case Studies and Best Practices of Drone-Based Traffic Flow Management -- 12.8 Future Trends and Directions for Drone-Based Traffic Flow Management in Smart Cities -- 12.9 Role of Emerging Technologies -- 12.10 Conclusion and Recommendations for Researchers, Practitioners, and Policymakers -- References -- Index -- Also of Interest -- EULA.
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| Record Nr. | UNINA-9911018917703321 |
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Future of AI, IoT, and Sustainability
