Smart Sensors for Industry 4. 0 : Fundamentals, Fabrication and IIoT Applications

Smart Sensors for Industry 4. 0 Fundamentals, Fabrication and IIoT Applications

Discover the essential guide to harnessing the power of cutting-edge smart sensors in Industry 4.0, offering deep insights into fundamentals, fabrication techniques, and real-world IIoT applications, equipping you with the knowledge to revolutionize your industrial processes and stay ahead in the di...

Descripción completa

Detalles Bibliográficos
Autor principal: Mishra, Brojo Kishore (-)
Otros Autores: Mallik, Sandipan, Le, Dac-Nhuong
Formato: Libro electrónico
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated 2024.
Edición:1st ed
Colección:Advances in Learning Analytics for Intelligent Cloud-IoT Systems Series
Materias:
Detectors.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009843325006719
Tabla de Contenidos:
  • 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.

Ejemplares similares