Cyber-Physical Systems

AI and COVID-19

1st Edition - October 30, 2021
Editors: Ramesh Chandra Poonia, Basant Agarwal, Sandeep Kumar, Mohammad S. Khan, Goncalo Marques, Janmenjoy Nayak
Language: English
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 2 4 5 5 7 - 6
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 8 5 3 5 7 - 6

Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-phy… Read more

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Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS).

The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture.

Cover image
Title page
Table of Contents
Copyright
List of contributors
Chapter 1. AI-based implementation of decisive technology for prevention and fight with COVID-19
Abstract
1.1 Introduction
1.2 Related work
1.3 Proposed work
1.4 Results and analysis
1.5 Conclusion
References
Chapter 2. Internet of Things-based smart helmet to detect possible COVID-19 infections
Abstract
2.1 Introduction
2.2 Related work
2.3 IoT-based smart helmet to detect the infection of COVID-19
2.4 Conclusion
References
Chapter 3. Role of mobile health in the situation of COVID-19 pandemics: pros and cons
Abstract
3.1 Introduction
3.2 Implementation of a training module for the mHealth care worker
3.3 Government policies for the scale-up of the mHealth services
3.4 Popular models of mHealth serving for pandemic COVID-19
3.5 Ethical consideration
3.6 Superiority of mHealth services over other available services
3.7 Probability of conflict of interest between user and service provider
3.8 Legal consideration
3.9 Protection of privacy of end-users
3.10 Conclusion
3.11 Future prospects
References
Chapter 4. Combating COVID-19 using object detection techniques for next-generation autonomous systems
Abstract
4.1 Introduction
4.2 Need for object detection
4.3 Object detection techniques
4.4 Applications of objection detection during COVID-19 crisis
4.5 Conclusion
References
Chapter 5. Non-contact measurement system for COVID-19 vital signs to aid mass screening—An alternate approach
Abstract
5.1 Introduction
5.2 COVID-19 global scenarios
5.3 Measurement and testing protocols of COVID-19
5.4 Non-contact approaches to physiological measurement
5.5 Conclusion
Acknowledgment
References
Chapter 6. Evolving uncertainty in healthcare service interactions during COVID-19: Artificial Intelligence - a threat or support to value cocreation?
Abstract
6.1 Introduction
6.2 Service dominant logic in marketing
6.3 Service interactions and cocreated wellbeing
6.4 Uncertainty due to pandemic
6.5 Uncertainty in healthcare
6.6 The emerging role of Artificial Intelligence
6.7 AI combating uncertainty and supporting value cocreation in healthcare interactions
6.8 The spill-over effect of Artificial Intelligence
6.9 Conclusion and future work
References
Chapter 7. The COVID-19 outbreak: social media sentiment analysis of public reactions with a multidimensional perspective
Abstract
7.1 Introduction
7.2 Data collection
7.3 Sentiment analysis of the tweets collected worldwide
7.4 Sentiment analysis of Tweets for India
7.5 Analysis of few most trending hashtags
7.6 Conclusion
References
Chapter 8. A new approach to predict COVID-19 using artificial neural networks
Abstract
8.1 Introduction
8.2 Related studies
8.3 Fundamental symptoms and conditions responsible for COVID-19 infection
8.4 Proposed COVID-19 detection methodology
8.5 Brief description of artificial neural networks
8.6 Parameter settings for the proposed ANN model
8.7 Experimental results and discussion
8.8 Performance comparison between ANN and other classification algorithms
8.9 Conclusion
Appendix
References
Chapter 9. Rapid medical guideline systems for COVID-19 using database-centric modeling and validation of cyber-physical systems
Abstract
9.1 Introduction
9.2 Global pandemic of COVID-19
9.3 Database-centric cyber-physical systems for COVID-19
9.4 Modeling and validation of rapid medical guideline systems
9.5 Conclusion
References
Chapter 10. Machine learning and security in Cyber Physical Systems
Abstract
10.1 Introduction
10.2 Related work
10.3 Motivation
10.4 Importance of cyber security and machine learning
10.5 Machine learning for CPS applications
10.6 Future for CPS technology
10.7 Challenges and opportunities in CPS
10.8 Conclusion
References
Chapter 11. Impact analysis of COVID-19 news headlines on global economy
Abstract
11.1 Introduction
11.2 Related work
11.3 Proposed methodology
11.4 Results and experimental framework
11.5 Conclusion
References
Further reading
Chapter 12. Impact of COVID-19: a particular focus on Indian education system
Abstract
12.1 Introduction
12.2 Impact of COVID-19 on education
12.3 Sustaining the education industry during COVID-19
12.4 Conclusion
References
Chapter 13. Designing of Latent Dirichlet Allocation Based Prediction Model to Detect Midlife Crisis of Losing Jobs due to Prolonged Lockdown for COVID-19
Abstract
13.1 Introduction
13.2 Literature survey
13.3 Methodology
13.4 Result and discussion
13.5 Conclusion and future scope
References
Chapter 14. Autonomous robotic system for ultraviolet disinfection
Abstract
14.1 Introduction
14.2 Background
14.3 Implementation
14.4 Model topology
14.5 Conclusion
References
Chapter 15. Emerging health start-ups for economic feasibility: opportunities during COVID-19
Abstract
15.1 Introduction
15.2 Health-tech verticals for start-ups
15.3 Research gap
15.4 Aim of the study
15.5 Research methodology
15.6 Health-tech category I Indian start-ups
15.7 Conclusions
References
Index

Ramesh Chandra Poonia

Dr. Ramesh Chandra Poonia is an Associate Professor at the Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India. Recently completed his Postdoctoral Fellowship from CPS Lab, Department of ICT and Natural Sciences, Norwegian University of Science and Technology, Ålesund, Norway. He has received his Ph.D. degree in Computer Science from Banasthali University, Banasthali, India in July 2013. His research interests are Cyber-Physical Systems, Network Protocol Evaluation and Artificial Intelligence. He is Chief Editor of TARU Journal of Sustainable Technologies and Computing (TJSTC) and Associate Editor of the Journal of Sustainable Computing: Informatics and Systems, Elsevier. He also serves in the editorial boards of a few international journals. He is main author and co-author of 06 books and an editor of more than 25 special issue of journals and books including Springer, CRC Press – Taylor and Francis, IGI Global and Elsevier, edited books and Springer conference proceedings and has authored/co-authored over 65 research publications in peer-reviewed reputed journals, book chapters and conference proceedings.

Affiliations and expertise

Associate Professor Department of Computer Science,CHRIST (Deemed to be University), Bangalore, Karnataka, India

Basant Agarwal

Dr. Basant Agarwal works as an Assistant Professor at the Indian Institute of Information Technology Kota (IIIT-Kota), India, which is an Institute of National Importance. He holds a Ph.D. and M.Tech. from the Department of Computer Science and Engineering, Malaviya National Institute of Technology Jaipur, India. He has more than 9 years of experience in research and teaching. He has worked as a Postdoc Research Fellow at the Norwegian University of Science and Technology (NTNU), Norway, under the prestigious ERCIM (European Research Consortium for Informatics and Mathematics) fellowship in 2016. He has also worked as a Research Scientist at Temasek Laboratories, National University of Singapore (NUS), Singapore. His research interest include Artificial Intelligence, Cyber physical systems, Text mining, Natural Language Processing, Machine learning, Deep learning, Intelligent Systems, Expert Systems and related areas.

Affiliations and expertise

Assistant Professor at the Indian Institute of Information Technology Kota (IIIT-Kota), India.

Sandeep Kumar

Dr. Sandeep Kumar is currently an Associate Professor at CHRIST (Deemed to be University) Bangalore and a Part-time Post-Doctoral research fellow at Imam Muhammad ibn Saud Islamic University Saudi Arabia. Before joining CHRIST, he has worked with ACEIT Jaipur, Jagannath University Jaipur, and Amity University Rajasthan. He is an associate editor for the Human-centric Computing and Information Sciences (HCIS) journal published by Springer. He has published more than sixty research papers in various international journals/conferences and attended several national and international conferences and workshops. He has authored/edited five books in the area of computer science. His research interests include nature-inspired algorithms, swarm intelligence, soft computing, and computational intelligence

Affiliations and expertise

Associate Professor, Department of Computer Science and Engineering, CHRIST (Deemed to be University)

Mohammad S. Khan

Dr. Mohammad S. Khan (SM’ 19) is currently an Assistant Professor of Computing at East Tennessee State University and the director of Network Science and Analysis Lab (NSAL). He received his M.Sc. and Ph.D. in Computer Science and Computer Engineering from the University of Louisville, Kentucky, USA, in 2011 and 2013, respectively. His primary area of research is in ad-hoc networks, wireless sensor networks, network tomography, connected vehicles, and vehicular social networks. He currently serves as an associate editor of IEEE Access, IET ITS, IET WSS, Springer’s Telecommunication Systems and Neural Computing and Applications. He has been on technical program committees of various international conferences and technical reviewer of various international journals in his field. He is a senior member of IEEE.

Affiliations and expertise

Assistant Professor of Computing, East Tennessee State University and Director, Network Science and Analysis Lab (NSAL), Johnson City , Tennessee, USA

Goncalo Marques

Gonçalo Marques holds a PhD in Computer Science Engineering and is member of the Portuguese Engineering Association (Ordem dos Engenheiros). He is currently working as Assistant Professor lecturing courses on programming, multimedia and database systems. His current research interests include Internet of Things, Enhanced Living Environments, machine learning, e-health, telemedicine, medical and healthcare systems, indoor air quality monitoring and assessment, and wireless sensor networks. He has more than 80 publications in international journals and conferences, is a frequent reviewer of journals and international conferences and is also involved in several edited books projects.

Affiliations and expertise

Polytechnic of Coimbra, ESTGOH, Rua General Santos Costa, 3400-124 Oliveira do Hospital, Portugal

Janmenjoy Nayak

Janmenjoy Nayak is an Assistant Professor, P.G. Department of Computer Science, Maharaja Sriram Chandra Bhanja Deo University, Baripada, Odisha, India. He has been a Gold Medallist in Computer Science twice in his career, and has been awarded the “Innovation in Science Pursuit for Inspired Research” (INSPIRE) Research Fellowship from the Department of Science & Technology, Government of India (at both Junior Research Fellow and Senior Research Fellow level) and Best Researcher Award from Jawaharlal Nehru University of Technology, Kakinada, Andhra Pradesh for the academic year 2018–19. He has received many other awards from national and international academic agencies. Dr. Nayak has edited 19 books and 8 special issues on the applications of computational intelligence, soft computing, and pattern recognition, which have been published by Springer and Inderscience. He has published more than 190 refereed articles in various book chapters, conferences, and peer-reviewed journals of Elsevier, Inderscience, Springer, the Institute of Electrical and Electronics Engineers (IEEE), and others. He has also served as a reviewer for more than 100 journals and conferences produced by the IEEE, the Association for Computing Machinery (ACM), Springer, Elsevier, Wiley, and Inderscience. He has 11 years of experience in both teaching and research. Dr. Nayak is a senior member of the IEEE and a life member of societies such as the Soft Computing Research Society (SCRS), the Computer Society of India (CSI India), the Orissa Information Technology Society (OITS), the Orissa Mathematical Society (OMS), and the International Association of Engineers (IAENG), Hong Kong. He has successfully conducted and is associated with 14 internationally renowned series conferences such as ICCIDM, HIS, ARIAM, CIPR, and SCDA. His areas of interest include data mining, nature-inspired algorithms, and soft computing.

Affiliations and expertise

Department of Computer Science, Maharaja Sriram Chandra Bhanja Deo (MSCBD) University, Mayurbhanj, India