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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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Request a sales quoteCyber-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.
- Offers perspectives on the design, development and commissioning of intelligent applications
- Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of COVID-19
- Puts forth insights on how future illnesses can be supported using intelligent corona virus monitoring techniques
Researchers or senior graduates working in academia; academics, instructors and senior students in colleges and universities, and faculty members working on Mathematics and Computing Technologies
- 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
- No. of pages: 278
- Language: English
- Edition: 1
- Published: October 30, 2021
- Imprint: Academic Press
- Paperback ISBN: 9780128245576
- eBook ISBN: 9780323853576
RP
Ramesh Chandra Poonia
BA
Basant Agarwal
SK
Sandeep Kumar
MK
Mohammad S. Khan
GM
Goncalo Marques
JN