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.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xiii 7. Chapter 1. AI-based implementation of decisive technology for prevention and fight with COVID-19 - p. 1 8. Chapter 2. Internet of Things-based smart helmet to detect possible COVID-19 infections - p. 15 9. Chapter 3. Role of mobile health in the situation of COVID-19 pandemics: pros and cons - p. 37 10. Chapter 4. Combating COVID-19 using object detection techniques for next-generation autonomous systems - p. 55 11. Chapter 5. Non-contact measurement system for COVID-19 vital signs to aid mass screening—An alternate approach - p. 75 12. Chapter 6. Evolving uncertainty in healthcare service interactions during COVID-19: Artificial Intelligence - a threat or support to value cocreation? - p. 93 13. Chapter 7. The COVID-19 outbreak: social media sentiment analysis of public reactions with a multidimensional perspective - p. 117 14. Chapter 8. A new approach to predict COVID-19 using artificial neural networks - p. 139 15. Chapter 9. Rapid medical guideline systems for COVID-19 using database-centric modeling and validation of cyber-physical systems - p. 161 16. Chapter 10. Machine learning and security in Cyber Physical Systems - p. 171 17. Chapter 11. Impact analysis of COVID-19 news headlines on global economy - p. 189 18. Chapter 12. Impact of COVID-19: a particular focus on Indian education system - p. 207 19. Chapter 13. Designing of Latent Dirichlet Allocation Based Prediction Model to Detect Midlife Crisis of Losing Jobs due to Prolonged Lockdown for COVID-19 - p. 219 20. Chapter 14. Autonomous robotic system for ultraviolet disinfection - p. 231 21. Chapter 15. Emerging health start-ups for economic feasibility: opportunities during COVID-19 - p. 241 22. Index - p. 255
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.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xiii 7. Chapter 1. AI-based implementation of decisive technology for prevention and fight with COVID-19 - p. 1 8. Chapter 2. Internet of Things-based smart helmet to detect possible COVID-19 infections - p. 15 9. Chapter 3. Role of mobile health in the situation of COVID-19 pandemics: pros and cons - p. 37 10. Chapter 4. Combating COVID-19 using object detection techniques for next-generation autonomous systems - p. 55 11. Chapter 5. Non-contact measurement system for COVID-19 vital signs to aid mass screening—An alternate approach - p. 75 12. Chapter 6. Evolving uncertainty in healthcare service interactions during COVID-19: Artificial Intelligence - a threat or support to value cocreation? - p. 93 13. Chapter 7. The COVID-19 outbreak: social media sentiment analysis of public reactions with a multidimensional perspective - p. 117 14. Chapter 8. A new approach to predict COVID-19 using artificial neural networks - p. 139 15. Chapter 9. Rapid medical guideline systems for COVID-19 using database-centric modeling and validation of cyber-physical systems - p. 161 16. Chapter 10. Machine learning and security in Cyber Physical Systems - p. 171 17. Chapter 11. Impact analysis of COVID-19 news headlines on global economy - p. 189 18. Chapter 12. Impact of COVID-19: a particular focus on Indian education system - p. 207 19. Chapter 13. Designing of Latent Dirichlet Allocation Based Prediction Model to Detect Midlife Crisis of Losing Jobs due to Prolonged Lockdown for COVID-19 - p. 219 20. Chapter 14. Autonomous robotic system for ultraviolet disinfection - p. 231 21. Chapter 15. Emerging health start-ups for economic feasibility: opportunities during COVID-19 - p. 241 22. Index - p. 255
