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Use of AI, Robotics and Modelling tools to fight Covid-19 [Kõva köide]

Edited by (UPES,Dehradun, India), Edited by , Edited by (Graphic Era University, Uttarakhand), Edited by (University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.)
  • Formaat: Hardback, 246 pages, kõrgus x laius: 234x156 mm, kaal: 480 g
  • Ilmumisaeg: 31-Mar-2021
  • Kirjastus: River Publishers
  • ISBN-10: 8770224439
  • ISBN-13: 9788770224437
Teised raamatud teemal:
Use of AI, Robotics and Modelling tools to fight Covid-19Suurem pilt
  • Formaat: Hardback, 246 pages, kõrgus x laius: 234x156 mm, kaal: 480 g
  • Ilmumisaeg: 31-Mar-2021
  • Kirjastus: River Publishers
  • ISBN-10: 8770224439
  • ISBN-13: 9788770224437
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9788770224437.html
This book describes the various AI, IoT, robotics, mathematical andcomputational modelling tools that have been used to fight the Covid-19pandemic.

The COVID-19 pandemic has hit the globe at a colossal scale. With worldwide reported cases of 5.34 million it has led to severe impact on humanity. Being a highly contagious disease, it has given global health services their most severe challenge. Various countries are fighting to minimize the losses due to the outbreak, however a common trait is enforcing lockdown, which has become the main defense mechanism. Researchers are working around the clock to find a breakthrough in the diagnostics and treatment of the pandemic.

AI technology is useful for fast drug development and treatment. In the starting phase of the COVID-19 pandemic, the medical fraternity in China diagnosed the virus using computed tomography (CT) and X-ray images due to the limitation of testing kits. Deep learning neural network models have also been used for COVID-19 diagnosis. AI assisted intelligent humanoid robots can be used to reduce the human contact and spread of COVID-19. In Italy robots have been used for measuring blood pressure, oxygen saturation and temperature of patients. Robots have also found applications in disinfecting and sterilizing of public places, COVID-19 testing, food and medicine delivery as well as entertaining patients in hospitals and quarantine centers, thereby reducing the workload of doctors and nurses.

Prediction of the spread of virus and providing the guidelines or prevention measures is another AI application in COVID-19. Kaggle and GitHub are the two websites where the real-time data of COVID-19 are aggregated. This includes confirmed cases, active cases, cured cases and deaths in each country. This data set can be used for predicting the active cases across different regions of the world so that the appropriate amount of health infrastructure can be made available to these places.
Preface xiii
Acknowledgement xvii
List of Contributors
xix
List of Figures
xxiii
List of Tables
xxvii
List of Notations and Abbreviations
xxix
1 The History of Pandemics and Evolution So Far
1(16)
Puneet Joshi
Swati Shukla
1.1 Introduction
2(1)
1.2 Definition Of Pandemics
2(1)
1.3 History Of Pandemics
3(2)
1.3.1 Prehistoric Epidemic
3(1)
1.3.2 Modern Epidemics
4(1)
1.4 Attributes Of A Pandemic
5(1)
1.5 Origin Of The Corona virus Or Covid-19
6(3)
1.5.1 Pathophysiology
7(1)
1.5.2 Signs, Symptoms, and Transmission
7(1)
1.5.3 Diagnosis
8(1)
1.5.4 Prevention
8(1)
1.5.5 Management
9(1)
1.6 Types Of Covid-19
9(2)
1.7 Vaccine
11(1)
1.8 Pandemic Impacts
11(3)
1.9 Conclusion
14(1)
References
14(3)
2 Tracing the Origins of COVID-19
17(12)
Vidushee Nautiyal
Rakhi Pandey
2.1 Introduction
17(2)
2.2 History of the Virus
19(4)
2.2.1 Influenza
20(1)
2.2.2 Seasonal Flu
21(1)
2.2.3 2002--2004: Severe Acute Respiratory Syndrome
21(1)
2.2.4 2009 (H1N1) Flu Pandemic
22(1)
2.2.5 Middle East Respiratory Syndrome Coronavirus (MERS-COV) -- 2012
22(1)
2.2.6 2014--2016 Ebola
23(1)
2.3 Genetic Sequence of Sars-Cov-2
23(1)
2.4 Transmission and Diagnosis
24(2)
2.5 Conclusion
26(1)
2.6 Acknowledgment
26(1)
References
26(3)
3 AI for COVID-19: The Journey So Far
29(16)
Abhinav Sharma
Arpit Jain
Mangey Ram
3.1 Introduction
30(1)
3.2 Artificial Intelligence
31(2)
3.3 Potential Contribution of Ai Against Covid-19
33(6)
3.3.1 Diagnosis of Disease
33(2)
3.3.2 Discovery of Drug and Vaccine
35(1)
3.3.3 Prediction of Mortality and Survival Rate
36(1)
3.3.4 Contact Tracing
36(1)
3.3.5 Robotics and Health Care
37(1)
3.3.6 COVID-19 Chatbots
38(1)
3.3.7 Prevent Further Spread of Disease
39(1)
3.4 Conclusion
39(1)
References
40(5)
4 Technological Opportunities to Fight COVID-19 for Indian Scenario
45(14)
Meera C. S.
Aslesha Bodavula
Pinisetti Swami Sairam
4.1 Introduction
45(2)
4.2 Technological Interventions
47(9)
4.2.1 Robotic Technologies in COVID-19
47(2)
4.2.2 Smart Surveillance Systems
49(1)
4.2.3 Artificial Intelligence and Machine Learning
50(2)
4.2.4 Computational Fluid Dynamics
52(2)
4.2.5 Unmanned Aerial Vehicles
54(2)
4.3 Conclusion
56(1)
References
56(3)
5 Mobile Robots in COVID-19
59(20)
Prashant Kumar Dwivedi
5.1 Introduction
60(4)
5.1.1 What is Mobile Robot?
60(1)
5.1.2 Components of Mobile Robots
61(2)
5.1.3 Mobile Robots and COVID-19
63(1)
5.2 Requirements of Mobile Robots in Pandemic Situation
64(1)
5.3 Innovation and Classification of Mobile Robots
65(7)
5.4 Future Scope and Challenges
72(3)
5.4.1 Challenges During Development Phase
72(2)
5.4.2 Challenges During Deployment Phase
74(1)
5.5 Conclusion
75(1)
References
75(4)
6 Predictor System for Tracing COVID-19 Spread
79(10)
Kuldeep Panwar
Supriya Pandey
Kamal Rawat
Neeraj Bisht
6.1 Introduction
80(1)
6.2 Various Prediction Methods
80(2)
6.3 Case Study - Prediction of Effective Reproductive Number for India
82(1)
6.4 Results and Discussions
83(3)
6.5 Conclusion
86(1)
References
86(3)
7 Discovery of Robust Distributions of COVID-19 Spread
89(22)
Chhaya Kulkarni
Sandipan Dey
Vandana Janeja
7.1 Introduction
90(1)
7.2 Methodology
91(5)
7.2.1 Data Preprocessing
92(1)
7.2.2 Temporal Analysis
92(1)
7.2.3 Distribution Detection
93(2)
7.2.4 Outlier Detection
95(1)
7.3 Experimental Results
96(12)
7.3.1 Geospatial Context of the Data
96(1)
7.3.2 Results
96(12)
7.4 Conclusion
108(1)
References
108(3)
8 Toward Smart Hospital: An Intelligent Personnel Scheduling Using Evolutionary Algorithms
111(16)
Tan Nhat Pham
Son Vu Truong Dao
8.1 Introduction
111(2)
8.2 Methodology
113(8)
8.2.1 Data Collection
113(1)
8.2.2 Mathematical Model Development
113(2)
8.2.3 Discrete GWO with a Novel Neighborhood Search Operator
115(6)
8.3 Computational Results
121(2)
8.4 Conclusion
123(1)
References
124(3)
9 Role of Artificial Intelligence Based Wireless Sensor Network for Pandemic Control: A Case Study Using CupCarbon
127(14)
Paawan Sharma
Hardik Patel
Mohendra Roy
9.1 Introduction
127(5)
9.2 Proposed Anal y si s
132(1)
9.3 Modeling and Simulation
133(2)
9.4 Results and Discussions
135(1)
9.4.1 Application in Pandemic Control
135(1)
9.5 Conclusion
136(1)
References
137(4)
10 Peculiarities of Technical Measures During the COVID-19 Pandemic
141(20)
Iosif Z. Aronov
Anna M. Rybakova
Nataliia M. Galkina
10.1 Introduction
141(2)
10.2 Application of Tbt Measures By Wto Members
143(5)
10.3 Peculiarities of Application of Standardization Tools During the Pandemic
148(7)
10.3.1 Standard Accessibility in Response to the COVID-19 Pandemic
149(3)
10.3.2 Development of Standardization Documents in Response to the COVID-19 Pandemic
152(3)
10.4 Main Conclusions and Recommendations from the Analysis of TBT Measures During the Covid-19 Pandemic
155(1)
10.5 Acknowledgements
156(1)
References
157(4)
11 Climate Change and COVID-19: An Interplay
161(20)
Vibhu Jately
Jyoti Joshi
Rajendra Kumar Jatley
11.1 Introduction
162(2)
11.2 Comparison of Two Disruptors, The Climate Risk, and Covid-19
164(4)
11.2.1 Short-Term and Long-Term Effects of Climate Change and COVID-19
165(1)
11.2.2 Short-Term Effects of the Current Pandemic
165(1)
11.2.3 Long-Term Effects of the Pandemic
165(1)
11.2.4 Short-Term Effects of Climate Change
166(1)
11.2.5 Long-Term Effects of Climate Change
166(1)
11.2.6 Searching Ways to Mitigate
166(1)
11.2.7 Common Features
166(1)
11.2.8 Features that Make Them Different
167(1)
11.2.9 Mitigating the Risk by Avoiding its Multiplication
167(1)
11.3 Trends in CO2 and GHG Emission Levels
168(4)
11.4 Effect of Covid-19 on Emission Levels and on Energy Demand
172(1)
11.5 How to Move Forward?
173(5)
11.5.1 Responses Helpful in Saving the Environment
174(1)
11.5.2 Pitfalls in Road that Can Blur the Focus of Stakeholders for Reducing Emissions
174(1)
11.5.3 Road Map for the Planners
175(3)
11.6 Conclusion
178(1)
11.7 Acknowledgements
179(1)
References
179(2)
12 COVID-19 Pandemic: A New Era in Higher Education
181(14)
Sriperumbuduru Srilaya
Sirisha Velampalli
12.1 Introduction
182(1)
12.2 Covid-19 Impact on Higher Education
183(1)
12.2.1 All Educational Activities are Disrupted
183(1)
12.2.2 Turndown in Employment Opportunities
183(1)
12.2.3 Impact on Academic Research and Professional Development
184(1)
12.2.4 Attendance of Students May Slow Down
184(1)
12.2.5 National and International Student Mobility for Higher Study May Be Reduced
184(1)
12.3 Challenges of India for Higher Education During Covid-19
184(3)
12.3.1 Virtual Platforms in Higher Education at Times of COVID-19
185(2)
12.4 Challenges Undertaken for Digitalizing Sector in Higher Education
187(1)
12.4.1 Resource and Internet Connectivity
187(1)
12.4.2 Shortage of Trained Teachers
187(1)
12.4.3 Content-Related Challenges
188(1)
12.4.4 Poor Maintenance and Upgradation of Digital Equipment
188(1)
12.4.5 Inadequate Funds
188(1)
12.5 Post-Covid-19 (Digitalization: A New Phenomenon in Higher Education)
188(4)
12.5.1 Urge for Distance Learning and Online Learning May Grow
189(1)
12.5.2 Blending Teaching and Learning with Technology
189(1)
12.5.3 New Design in Assessment System
190(1)
12.5.4 Online Learning Helped Us to Tackle the Crisis
190(2)
12.6 Conclusion
192(1)
12.7 Acknowledgment
192(1)
References
192(3)
13 Virtual Reality: Solution to Reduce the Impact of COVID-19 on Global Economy
195(16)
Sushma Malik
Anamika Rana
13.1 Introduction
196(2)
13.2 Impact of Covid-19 on the Economy
198(2)
13.2.1 Tourism Industry
198(1)
13.2.2 Automobile Industry
198(1)
13.2.3 Agriculture
198(1)
13.2.4 Aviation Industry
199(1)
13.2.5 Oil Industry
199(1)
13.2.6 Construction Industry
199(1)
13.2.7 Food Industry
199(1)
13.2.8 Healthcare and Medical Industry
200(1)
13.3 Domain Moving Toward Virtual Reality for Survival
200(4)
13.3.1 Education
200(2)
13.3.2 Hospital
202(1)
13.3.3 Agriculture
202(1)
13.3.4 Sports
202(1)
13.3.5 Businesses
203(1)
13.3.6 Government
203(1)
13.4 Challenges During Implementation of Virtual Reality
204(2)
13.4.1 Lack of Familiarity
205(1)
13.4.2 Network Load
205(1)
13.4.3 Bottleneck Communication
206(1)
13.4.4 Cost
206(1)
13.4.5 Internet
206(1)
13.4.6 User Experience Issue
206(1)
13.4.7 Security
206(1)
13.4.8 Powerful Computers
206(1)
13.5 Road Map Toward Normal During Covid-19
206(1)
13.6 Implications for Research
207(1)
13.7 Conclusion
208(1)
References
209(2)
Index 211(2)
About the Editors 213
Arpit Jain, Abhinav Sharma, Jianwu Wang, Mangey Ram