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[null,"1.","Record Nr.",null,"UNINA990000054630403321"]
[null,null,"Autore",null,"Royce, Michael"]
[null,null,"Titolo",null,"Studies for student pilots / Michael Royce"]
[null,null,"Pubbl/distr/stampa",null,"London : I. Pitman, 1955"]
[null,null,"Descrizione fisica",null,"IX, 282 p. : ill. ; 19 cm"]
[null,null,"Disciplina",null,"629.13"]
[null,null,"Locazione",null,"FINBC"]
[null,null,"Collocazione",null,"13 F 01 08"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9911018917703321"]
[null,null,"Autore",null,"Mishra Brojo Kishore"]
[null,null,"Titolo",null,"Smart Sensors for Industry 4. 0 : Fundamentals, Fabrication and IIoT Applications"]
[null,null,"Pubbl/distr/stampa",null,"Newark : , : John Wiley & Sons, Incorporated, , 2024"]
[{"$nulls":4},"©2024"]
[null,null,"ISBN",null,"9781394214723"]
[{"$nulls":4},"1394214723"]
[{"$nulls":4},"9781394214716"]
[{"$nulls":4},"1394214715"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (247 pages)"]
[null,null,"Collana",null,"Advances in Learning Analytics for Intelligent Cloud-IoT Systems Series"]
[null,null,"Disciplina",null,"681.2"]
[null,null,"Soggetti",null,"Detectors"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"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 "]
[{"$nulls":4},"Overview of Smart Sensors and Their Applications in Industry 4.0 -- 3.1.3 Challenges in Smart Sensor Design and Implementation for Environmental Monitoring in Industry 4.0 -- 3.2 State-of-the-Art of Smart Sensors for Environmental Monitoring in Industry 4.0 and Real-World Applications -- 3.2.1 Types of Smart Sensors for Environmental Monitoring in Industry 4.0."]
[{"$nulls":4},"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."]
[{"$nulls":4},"7.1 Introduction -- 7.2 Literature Review -- 7.2.1 Psychology -- 7.2.2 Chess and Academic and Non-Academic Skills -- 7.2.3 Insights -- 7.2.4 Impacts of Tangible Interfaces in Gaming -- 7.2.5 Related Work -- 7.2.6 Competitive Analysis -- 7.3 Methodology -- 7.4 Design Intervention -- 7.5 Proposed Solution: IoT Integrated Tangible Chessboard -- 7.5.1 Experimental Setup -- 7.5.2 Algorithm -- 7.6 User Testing and Validation -- 7.7 Conclusion -- References -- 8 Intelligent Systems and Robotics for Wastewater Management Across India: A Study and Analysis -- 8.1 Introduction -- 8.2 Relevant Work -- 8.3 Theoretical Framework -- 8.3.1 Intelligent Systems -- 8.3.2 Artificial Neural Network -- 8.3.3 Genetic Algorithm -- 8.3.4 Fuzzy Logic -- 8.3.5 Machine Learning -- 8.3.6 Deep Learning -- 8.3.7 Data Analytics -- 8.4 Proposed Methodology -- 8.5 Industrial Waste -- 8.6 Robot Design Using Intelligent Systems -- 8.7 Conclusion -- References -- Chapter 9 Text-Based Prediction and Classification Model of Stress, Anxiety and Depression Among Indians -- 9.1 Introduction -- 9.2 Relevant Work -- 9.3 Discussion and Results -- 9.4 Conclusion -- References -- Chapter 10 Industry 4.0: Security Challenges and Opportunities of the IIoT -- 10.1 Introduction -- 10.2 Industry 4.0 Landscape -- 10.3 Literature Survey -- 10.4 Security Requirements in IIoT -- 10.5 Measures for Implementing Cybersecurity -- 10.5.1 Category 1: Smart Factories and Supply Chains -- 10.5.2 Category 2: Stakeholders -- 10.5.3 Category 3: Internet -- 10.5.4 Fog and Edge Computing -- 10.6 Conclusion -- References -- Chapter 11 "]
[{"$nulls":4},"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."]
[{"$nulls":4},"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."]
[null,null,null,"Sommario/riassunto","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 digital era. Over the last decade, technologies like the Internet of Things (IoT), big data, cloud computing, blockchain, artificial intelligence (AI), machine learning, device automation, smart sensors, etc., have become highly developed fundamental supports of Industry 4.0, replacing the conventional production systems with advanced methods, and thereby endorsing the smart industry vision. Industry 4.0 is more flexible and agile in dealing with several risk factors, further enabling improved productivity and efficiency, distribution, increased profitability, data integrity, and enhancing customer experience in the current commercial environment. For understanding and analyzing the environment, sensors play a major role in performing the measurements based on computation-produced results from the surrounding environment. Sensors have a wide range of applications for smart industrial operations. The evolution of flexible, low-cost, and multipurpose sensors and their system integration has been examined to develop advanced devices with applications in numerous fields of technology. With the development of both the Internet of Things (IoT) and the Industrial IoT (IIoT), advanced sensors and their associated applications are developing, resulting in the necessity for IoT sensors to be used for several industrial applications. Beneficial aspects of this book include: "]
[{"$nulls":4},"The latest research in materials and methodology for the fabrication of intelligent sensors, its IoT system integration, and IIoT applications are brought together; Promotes a vision towards making sensor-based monitoring and control of smart industry; Recent advances and challenges of smart sensors are discussed with an emphasis on unmet challenges and future directions of a roadmap to Industry 4.0. Audience This book is highly recommended to a wide range of researchers and industry engineers working in the area of fabrication and integration of industrial smart sensors for IIoT applications, advanced materials for sensor technology, fabrication and characterization of IoT sensors, development of low-cost sensors, sensor system design and integration, and its industrial applications. Post-graduate students from different streams like computer science, electronics and electrical engineering, information technology, electronic communication, etc. will benefit from reading this book."]