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Submit a ProposalSmart Sensors for Industry 4.0
 | Fundamentals, Fabrication and IIoT Applications Edited by Brojo Kishore Mishra, Sandipan Mallik and Dac-Nhuong Le Series: Advances in Learning Analytics for Intelligent Cloud-IoT Systems Copyright: 2024 | Expected Pub Date:2024/02/2024 ISBN: 9781394213566 | Hardcover | 242 pages Price: $225 USD  |
One Line Description
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.
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.
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.
Description
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:
•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.
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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:
•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.
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Author / Editor Details
Brojo Kishore Mishra, PhD, is a professor and head in the School of Computer Science and Engineering at NIST Institute of Science and Technology (Autonomous), Berhampur, Odisha, India. He received his doctorate in computer science from Berhampur University, India in 2012. He published more than 50 research papers in peer-reviewed international journals, and more than 40 research papers in proceedings of international conferences, more than 50 book chapters, 18 edited books and 2 authored books, 5 book series, 2 patents published, 3 copyright and 1 trademark(applied). His research interests include data mining, machine learning, soft computing, and security.
Brojo Kishore Mishra, PhD, is a professor and head in the School of Computer Science and Engineering at NIST Institute of Science and Technology (Autonomous), Berhampur, Odisha, India. He received his doctorate in computer science from Berhampur University, India in 2012. He published more than 50 research papers in peer-reviewed international journals, and more than 40 research papers in proceedings of international conferences, more than 50 book chapters, 18 edited books and 2 authored books, 5 book series, 2 patents published, 3 copyright and 1 trademark(applied). His research interests include data mining, machine learning, soft computing, and security.
Sandipan Mallik, PhD, earned his doctorate in engineering from Jadavpur University, Kolkata in 2014 and is currently an associate professor in the Department of ECE, NIST (Autonomous), Berhampur, Odisha, India. He has been involved in teaching and research for more than 2 years and has published 5 Indian patents, and more than 90 research articles in various international and national journals and conferences. His wide area of research includes semiconductor device physics and device fabrication technology, nanotechnology & microelectronics, memristor devices, IoT sensors fabrication, and IoT-based devices for biomedical applications.
Dac-Nhuong Le, PhD, obtained his doctorate in computer science from Vietnam National University, Vietnam in 2015. He is deputy head of the Faculty of Information Technology, Haiphong University, Vietnam. His area of research includes evaluation computing and approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, IoT, and image processing in biomedicine. He has over 50 publications and edited/authored 15 computer science books.
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Table of Contents
List of Figures
List of Tables
Foreword
Preface
Acknowledgments
Acronyms
1. IoT-Based Health Monitoring Using a Hybrid Machine Learning Model
Shiplu Das, Gargi Chakraborty, Debarun Joardar, Subrata Paul, Buddhadeb Pradhan
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
P R Anisha, Rithika Badam, Vijaya Sindhoori Kaza
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
3. Smart Sensors for Environmental Monitoring in Industry 4.0
Nimish Kumar, Himanshu Verma, Yogesh Kumar Sharma
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
4. A Novel Hybrid Smart Appliances Control Framework for Specially Challenged Persons
Suprava Ranjan Laha, Saumendra Pattnaik, Sushil Kumar Mahapatra, Binod Kumar Pattanayak
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
5. An IoT-based Framework for PUC Monitoring of 2- or 4-Wheeler Vehicle
Shivnath Ghosh, Subrata Paul, Liza kazima Karishma, Sudeep Karmakar
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
6. Farm Shielding: A Shielding Experience That Takes a New Turn
Tanvi Vaze, Harshal Vavale, Janvi Agarwal, Vaishnavi Telang, Ravindra Bachate
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
7. Checkmate: An IoT Integrated Tangible Chessboard
Riya Narake, Shruti Wagh, Abhishek Tupe, Ravindra Bachate
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
Kishore Kumar Reddy, P. Yashashwini Reddy, Marlia M. Hanafiah, Srinath Doss
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
9. Text-Based Prediction and Classification Model of Stress, Anxiety and Depression Among Indians
Kishor Kumar Reddy C, Tungana Bhavya, Anisha P R, Marlia Mohd Hanafiah
9.1 Introduction
9.2 Relevant Work
9.3 Discussion and Results
9.4 Conclusion
References
10. Industry 4.0: Security Challenges and Opportunities of the IIoT
Uttara Gogate, Alok Ranjan Prusty, Munesh Singh
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
11. Role of Machine Learning and Deep Learning in Smart Sensors
Arka De, Sameeksha Saraf, Tusar Kanti Mishra, B.K. Tripathy
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
12. Drone-Based Traffic Flow Management for Smart Cities: Problems and Solutions
Nimish Kumar, Himanshu Verma Yogesh, Kumar Sharma
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
Back to Top
List of Figures
List of Tables
Foreword
Preface
Acknowledgments
Acronyms
1. IoT-Based Health Monitoring Using a Hybrid Machine Learning Model
Shiplu Das, Gargi Chakraborty, Debarun Joardar, Subrata Paul, Buddhadeb Pradhan
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
P R Anisha, Rithika Badam, Vijaya Sindhoori Kaza
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
3. Smart Sensors for Environmental Monitoring in Industry 4.0
Nimish Kumar, Himanshu Verma, Yogesh Kumar Sharma
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
4. A Novel Hybrid Smart Appliances Control Framework for Specially Challenged Persons
Suprava Ranjan Laha, Saumendra Pattnaik, Sushil Kumar Mahapatra, Binod Kumar Pattanayak
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
5. An IoT-based Framework for PUC Monitoring of 2- or 4-Wheeler Vehicle
Shivnath Ghosh, Subrata Paul, Liza kazima Karishma, Sudeep Karmakar
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
6. Farm Shielding: A Shielding Experience That Takes a New Turn
Tanvi Vaze, Harshal Vavale, Janvi Agarwal, Vaishnavi Telang, Ravindra Bachate
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
7. Checkmate: An IoT Integrated Tangible Chessboard
Riya Narake, Shruti Wagh, Abhishek Tupe, Ravindra Bachate
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
Kishore Kumar Reddy, P. Yashashwini Reddy, Marlia M. Hanafiah, Srinath Doss
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
9. Text-Based Prediction and Classification Model of Stress, Anxiety and Depression Among Indians
Kishor Kumar Reddy C, Tungana Bhavya, Anisha P R, Marlia Mohd Hanafiah
9.1 Introduction
9.2 Relevant Work
9.3 Discussion and Results
9.4 Conclusion
References
10. Industry 4.0: Security Challenges and Opportunities of the IIoT
Uttara Gogate, Alok Ranjan Prusty, Munesh Singh
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
11. Role of Machine Learning and Deep Learning in Smart Sensors
Arka De, Sameeksha Saraf, Tusar Kanti Mishra, B.K. Tripathy
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
12. Drone-Based Traffic Flow Management for Smart Cities: Problems and Solutions
Nimish Kumar, Himanshu Verma Yogesh, Kumar Sharma
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
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