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Cyber-Physical Systems: AI and COVID-19 [Pehme köide]

Edited by , Edited by , Edited by (Assistant Professor at the Indian Institute of Information Technology Kota (IIIT-Kota), India.), Edited by (Associate Professor, Departm), Edited by (Professor, Department of Computer Science, CHRIST (Deemed to be University), Bangalore, Karnataka, India), Edited by
  • Formaat: Paperback / softback, 278 pages, kõrgus x laius: 229x152 mm, kaal: 430 g
  • Ilmumisaeg: 02-Nov-2021
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128245573
  • ISBN-13: 9780128245576
Teised raamatud teemal:
Cyber-Physical Systems: AI and COVID-19Suurem pilt
  • Formaat: Paperback / softback, 278 pages, kõrgus x laius: 229x152 mm, kaal: 430 g
  • Ilmumisaeg: 02-Nov-2021
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128245573
  • ISBN-13: 9780128245576
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128245576.html
Märksõnad:

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.

  • 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
List of contributors
xiii
1 Al-based implementation of decisive technology for prevention and fight with COV1D-19
1(14)
Alok Negi
Krishan Kumar
1.1 Introduction
1(2)
1.2 Related work
3(2)
1.3 Proposed work
5(4)
1.3.1 Face mask detection
5(2)
1.3.2 Detection of COVID from CT images
7(2)
1.4 Results and analysis
9(4)
1.4.1 Face mask detection
9(3)
1.4.2 CT scan image-based COVID-19 patient identification
12(1)
1.5 Conclusion
13(2)
References
13(2)
2 Internet of Things-based smart helmet to detect possible COVID-19 infections
15(22)
Chanchal Ahlawat
Rajalakshmi Krishnamurthi
2.1 Introduction
15(9)
2.1.1 Epidemiology
17(1)
2.1.2 Treatment
18(1)
2.1.3 Prevention
19(2)
2.1.4 Symptoms
21(1)
2.1.5 Stages of COVID-19
21(2)
2.1.6 Key merits of IoT for COVID-19 pandemic
23(1)
2.1.7 Internet of Things process required for COVID-19
23(1)
2.1.8 IoT applications for COVID-19
24(1)
2.2 Related work
24(3)
2.3 IoT-based smart helmet to detect the infection of COVID-19
27(4)
2.3.1 Objective
27(1)
2.3.2 Methodology
27(4)
2.4 Conclusion
31(6)
References
31(6)
3 Role of mobile health in the situation of COVID-19 pandemics: pros and cons
37(18)
Priyanka Baskar
Sunita Rao
3.1 Introduction
37(2)
3.2 Implementation of a training module for the mHealth care worker
39(1)
3.3 Government policies for the scale-up of the mHealth services
40(2)
3.4 Popular models of mHealth serving for pandemic COVID-19
42(1)
3.5 Ethical consideration
42(4)
3.6 Superiority of mHealth services over other available services
46(1)
3.7 Probability of conflict of interest between user and service provider
47(1)
3.8 Legal consideration
48(1)
3.9 Protection of privacy of end-users
49(1)
3.10 Conclusion
50(1)
3.11 Future prospects
51(4)
References
51(4)
4 Combating COVID-19 using object detection techniques for next-generation autonomous systems
55(20)
Hrishikesh Shenai
Jay Gala
Kaustubh Kekre
Pranjal Chitale
Ruhina Karani
4.1 Introduction
55(1)
4.2 Need for object detection
56(1)
4.3 Object detection techniques
56(10)
4.3.1 R-CNN family
57(5)
4.3.2 YOLO family
62(4)
4.4 Applications of objection detection during COVID-19 crisis
66(5)
4.4.1 Module for autonomous systems (pothole detection)
66(1)
4.4.2 Social distancing detector
67(2)
4.4.3 COVID-19 detector based on X-rays
69(1)
4.4.4 Face mask detector
70(1)
4.5 Conclusion
71(4)
References
72(3)
5 Non-contact measurement system for COVID-19 vital signs to aid mass screening--An alternate approach
75(18)
Vijay Jeyakumar
K. Nirmala
Sachin C. Sarate
5.1 Introduction
75(1)
5.2 COVID-19 global scenarios
76(2)
5.2.1 Infections, recovery and mortality rate
76(1)
5.2.2 Economy and environmental impacts
77(1)
5.3 Measurement and testing protocols of COVID-19
78(3)
5.3.1 Measurement methods
79(1)
5.3.2 COVID-19 innovations
80(1)
5.4 Non-contact approaches to physiological measurement
81(8)
5.4.1 Need for non-contact measurement
82(1)
5.4.2 State of the art to prior work
83(1)
5.4.3 Proposed approach
84(1)
5.4.4 Methodology
85(1)
5.4.5 Preliminary experimental results
85(4)
5.5 Conclusion
89(4)
Acknowledgment
90(1)
References
91(2)
6 Evolving uncertainty in healthcare service interactions during COVID-19: Artificial Intelligence - a threat or support to value cocreation?
93(24)
Sumit Saxena
Amritesh
6.1 Introduction
93(3)
6.2 Service dominant logic in marketing
96(1)
6.3 Service interactions and cocreated wellbeing
97(1)
6.4 Uncertainty due to pandemic
98(1)
6.5 Uncertainty in healthcare
98(5)
6.5.1 Impact of pandemic-led uncertainty on a patient's mind
102(1)
6.5.2 Impact of pandemic-led uncertainty on service interactions
102(1)
6.6 The emerging role of Artificial Intelligence
103(1)
6.7 Al combating uncertainty and supporting value cocreation in healthcare interactions
104(3)
6.8 The spill-over effect of Artificial Intelligence
107(2)
6.9 Conclusion and future work
109(8)
References
110(7)
7 The COVID-19 outbreak: social media sentiment analysis of public reactions with a multidimensional perspective
117(22)
Basant Agarwal
Vaishnavi Sharma
Priyanka Harjule
Vinita Tiwari
Ashish Sharma
7.1 Introduction
117(2)
7.2 Data collection
119(1)
7.3 Sentiment analysis of the tweets collected worldwide
120(3)
7.4 Sentiment analysis of Tweets for India
123(7)
7.4.1 COVID-19 analysis for individual city of India--Mumbai
127(3)
7.5 Analysis of few most trending hashtags
130(7)
7.5.1 Opinion analysis for the hashtag #WorkFromHome
131(4)
7.5.2 Sentiment analysis of #MigrantWorkers
135(2)
7.6 Conclusion
137(2)
References
138(1)
8 A new approach to predict COVID-19 using artificial neural networks
139(22)
Soham Cuhathakurata
Sayak Saha
Souvik Kundu
Arpita Chakraborty
Jyoti Sekhar Banerjee
8.1 Introduction
139(1)
8.2 Related studies
140(1)
8.3 Fundamental symptoms and conditions responsible for COVID-19 infection
141(1)
8.4 Proposed COVID-19 detection methodology
142(3)
8.5 Brief description of artificial neural networks
145(4)
8.5.1 Principles of artificial neural network
145(4)
8.6 Parameter settings for the proposed ANN model
149(2)
8.7 Experimental results and discussion
151(2)
8.8 Performance comparison between ANN and other classification algorithms
153(2)
8.9 Conclusion
155(6)
Appendix
156(1)
References
157(4)
9 Rapid medical guideline systems for COVID-19 using database-centric modeling and validation of cyber-physical systems
161(10)
Mani Padmanabhan
9.1 Introduction
161(1)
9.2 Global pandemic of COVID-19
162(2)
9.3 Database-centric cyber-physical systems for COVID-19
164(2)
9.3.1 Cyber-physical systems
164(1)
9.3.2 Flow of rapid database-centric cyber-physical system
165(1)
9.4 Modeling and validation of rapid medical guideline systems
166(2)
9.5 Conclusion
168(3)
References
168(3)
10 Machine learning and security in Cyber Physical Systems
171(18)
Neha V. Sharma
Narendra Singh Yadav
Saurabh Sharma
10.1 Introduction
171(3)
10.2 Related work
174(2)
10.2.1 Phishing
174(1)
10.2.2 Intrusion detection for networks
175(1)
10.2.3 Key stroke elements validation
175(1)
10.2.4 Breaking human collaboration proofs (CAPTHAs)
175(1)
10.2.5 Cryptography
175(1)
10.2.6 Spam detection for social networking
176(1)
10.3 Motivation
176(1)
10.4 Importance of cyber security and machine learning
177(1)
10.5 Machine learning for CPS applications
178(1)
10.6 Future for CPS technology
179(3)
10.6.1 Cyber physical systems and human
181(1)
10.6.2 CPS and artificial intelligence
181(1)
10.6.3 Trustworthy
181(1)
10.6.4 Cyber physical systems of systems
182(1)
10.7 Challenges and opportunities in CPS
182(3)
10.8 Conclusion
185(4)
References
185(4)
11 Impact analysis of COVID-19 news headlines on global economy
189(18)
Ananya Malik
Yash Tejas Javeri
Manav Shah
Ramchandra Mangrulkar
11.1 Introduction
189(1)
11.2 Related work
190(4)
11.3 Proposed methodology
194(7)
11.3.1 Data and data preprocessing
194(3)
11.3.2 Sentiment analysis
197(2)
11.3.3 Prediction of Nifty score
199(2)
11.4 Results and experimental framework
201(4)
11.4.1 Linear regression
201(1)
11.4.2 Polynomial regression with degree 3
202(1)
11.4.3 Random forest regression
202(1)
11.4.4 Gradient boost regressor
203(2)
11.5 Conclusion
205(2)
References
205(1)
Further reading
206(1)
12 Impact of COVID-19: a particular focus on Indian education system
207(12)
Pushpa Cothwal
Bosky Dharmendra Sharma
Nandita Chaube
Nadeem Luqman
12.1 Introduction
207(1)
12.2 Impact of COVID-19 on education
208(6)
12.2.1 Effect of home confinement on children and teachers
211(3)
12.2.2 A multidimensional impact of uncertainty
214(1)
12.3 Sustaining the education industry during COVID-19
214(2)
12.4 Conclusion
216(3)
References
216(3)
13 Designing of Latent Dirichlet Allocation Based Prediction Model to Detect Midlife Crisis of Losing Jobs due to Prolonged Lockdown for COVID-19
219(12)
Basabdatta Das
Barshan Das
Avik Chatterjee
Abhijit Das
13.1 Introduction
219(1)
13.2 Literature survey
220(1)
13.3 Methodology
221(4)
13.3.1 Distinguishing midlife crisis symptoms
222(1)
13.3.3.2 Designing of the prediction model
223(1)
13.3.3 Application of LDA and statistical comparison
223(2)
13.4 Result and discussion
225(2)
13.5 Conclusion and future scope
227(4)
References
228(3)
14 Autonomous robotic system for ultraviolet disinfection
231(10)
Riki Patel
Harshal Sanghvi
Abhijit S. Pandya
14.1 Introduction
231(1)
14.2 Background
232(2)
14.2.1 Ultraviolet light for disinfection
232(1)
14.2.2 Exposure time for deactivation of the bacteria
233(1)
14.2.3 Flow chart of UV bot control logic
233(1)
14.2.4 Calculations related to the time for disinfection
233(1)
14.3 Implementation
234(2)
14.4 Model topology
236(3)
14.4.1 UV-C light robotic vehicle
237(2)
14.5 Conclusion
239(2)
References
240(1)
15 Emerging health start-ups for economic feasibility: opportunities during COVID-19
241(14)
Shweta Nanda
15.1 Introduction
241(2)
15.2 Health-tech verticals for start-ups
243(1)
15.3 Research gap
244(1)
15.4 Aim of the study
244(1)
15.5 Research methodology
244(2)
15.5.1 Problem statement
244(1)
15.5.2 Type of research
245(1)
15.5.3 Secondary data
245(1)
15.5.4 Data analysis methods
245(1)
15.6 Health-tech category I Indian start-ups
246(5)
15.6.1 Heath-tech category II Indian start-ups
246(1)
15.6.2 Variables gathered from stakeholder interviews
246(1)
15.6.3 Causal loop model
247(4)
15.7 Conclusions
251(4)
References
252(3)
Index 255
Dr. Ramesh Chandra Poonia is a 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. 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. 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 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, Springers 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. 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. 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 201819. 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.