Smart Sensors for Industry 4.0
Wiley-Scrivener (Verlag)
978-1-394-21356-6 (ISBN)
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.
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.
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.
List of Figures xii
List of Tables xv
Foreword xvii
Preface xix
Acknowledgments xxi
Acronyms xxiii
1 IoT-Based Health Monitoring Using a Hybrid Machine Learning Model 1
Shiplu Das, Gargi Chakraborty, Debarun Joardar, Subrata Paul, Buddhadeb Pradhan
2 Addressing Overcrowding: A Plight for Smart Cities 15
P R Anisha, Rithika Badam, Vijaya Sindhoori Kaza
3 Smart Sensors for Environmental Monitoring in Industry 4.0 39
Nimish Kumar, Himanshu Verma, Yogesh Kumar Sharma
4 A Novel Hybrid Smart Appliances Control Framework for Specially Challenged Persons 57
Suprava Ranjan Laha, Saumendra Pattnaik, Sushil Kumar Mahapatra, Binod Kumar Pattanayak
5 An IoT-based Framework for PUC Monitoring of 2- or 4-Wheeler Vehicle 71
Shivnath Ghosh, Subrata Paul, Liza kazima Karishma, Sudeep Karmakar
6 Farm Shielding: A Shielding Experience That Takes a New Turn 83
Tanvi Vaze, Harshal Vavale, Janvi Agarwal, Vaishnavi Telang, Ravindra Bachate
7 Checkmate: An IoT Integrated Tangible Chessboard 95
Riya Narake, Shruti Wagh, Abhishek Tupe, Ravindra Bachate
8 Intelligent Systems and Robotics for Wastewater Management Across India: A Study and Analysis 109
Kishore Kumar Reddy, P. Yashashwini Reddy, Marlia M. Hanafiah, Srinath Doss
9 Text-Based Prediction and Classification Model of Stress, Anxiety and Depression Among Indians 131
Kishor Kumar Reddy C, Tungana Bhavya, Anisha P R, Marlia Mohd Hanafiah
10 Industry 4.0: Security Challenges and Opportunities of the IIoT 149
Uttara Gogate, Alok Ranjan Prusty, Munesh Singh 10.1 Introduction 150
11 Role of Machine Learning and Deep Learning in Smart Sensors 161
Arka De, Sameeksha Saraf, Tusar Kanti Mishra, B.K. Tripathy
12 Drone-Based Traffic Flow Management for Smart Cities: Problems and Solutions 177
Nimish Kumar, Himanshu Verma Yogesh, Kumar Sharma
References 199
Index 203
| Erscheinungsdatum | 21.08.2024 |
|---|---|
| Reihe/Serie | Advances in Learning Analytics for Intelligent Cloud-IoT Systems |
| Sprache | englisch |
| Gewicht | 680 g |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| ISBN-10 | 1-394-21356-5 / 1394213565 |
| ISBN-13 | 978-1-394-21356-6 / 9781394213566 |
| Zustand | Neuware |
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