Cyber-Physical Systems: AI and COVID-19

271 Pages·2021·15.52 MB·English

by  Ramesh Poonia, Basant Agarwal, Sandeep Kumar, Mohammad Khan, Goncalo Marques, Janmenjoy Nayak

Cyber-Physical Systems
AI and COVID-19
Cyber-Physical
Systems
AI and COVID-19
Edited by
Ramesh Chandra Poonia
Department ofComputer Science,CHRIST(Deemed to be University),
Bangalore, India
Basant Agarwal
Department ofComputer Scienceand Engineering,Indian Instituteof
InformationTechnology (IIIT), Kota, India
Sandeep Kumar
Department ofComputer Scienceand Engineering,CHRIST (Deemed to
be University), Bengaluru, India
Mohammad S. Khan
Network ScienceandAnalysis Lab (NSAL), Departmentof Computing,
East Tennessee State University,Johnson City, TN, United States
Gonc¸alo Marques
Polytechnic ofCoimbra,ESTGOH,Rua General Santos Costa, Oliveira
do Hospital, Portugal
Janmenjoy Nayak
Aditya Instituteof Technologyand Management(AITAM)(An
Autonomous Institution),Tekkali, K Kotturu, India
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Contents
Listofcontributors xiii
1. AI-based implementation of decisive technology for
prevention and fight with COVID-19 1
AlokNegiandKrishanKumar
1.1 Introduction 1
1.2 Relatedwork 3
1.3 Proposedwork 5
1.3.1 Facemaskdetection 5
1.3.2 DetectionofCOVIDfromCTimages 7
1.4 Resultsandanalysis 9
1.4.1 Facemaskdetection 9
1.4.2 CTscanimage-basedCOVID-19patientidentification 12
1.5 Conclusion 13
References 13
2. Internet of Things-based smart helmet to detect
possible COVID-19 infections 15
ChanchalAhlawatandRajalakshmiKrishnamurthi
2.1 Introduction 15
2.1.1 Epidemiology 17
2.1.2 Treatment 18
2.1.3 Prevention 19
2.1.4 Symptoms 21
2.1.5 StagesofCOVID-19 21
2.1.6 KeymeritsofIoTforCOVID-19pandemic 23
2.1.7 InternetofThingsprocessrequiredforCOVID-19 23
2.1.8 IoTapplicationsforCOVID-19 24
2.2 Relatedwork 24
2.3 IoT-basedsmarthelmettodetecttheinfectionofCOVID-19 27
2.3.1 Objective 27
2.3.2 Methodology 27
2.4 Conclusion 31
References 31
v
vi Contents
3. Role of mobile health in the situation of COVID-19
pandemics: pros and cons 37
PriyankaBhaskarandSunitaRao
3.1 Introduction 37
3.2 ImplementationofatrainingmoduleforthemHealthcare
worker 39
3.3 Governmentpoliciesforthescale-upofthemHealthservices 40
3.4 PopularmodelsofmHealthservingforpandemicCOVID-19 42
3.5 Ethicalconsideration 42
3.6 SuperiorityofmHealthservicesoverotheravailableservices 46
3.7 Probabilityofconflictofinterestbetweenuserandservice
provider 47
3.8 Legalconsideration 48
3.9 Protectionofprivacyofend-users 49
3.10 Conclusion 50
3.11 Futureprospects 51
References 51
4. Combating COVID-19 using object detection techniques
for next-generation autonomous systems 55
HrishikeshShenai,JayGala,KaustubhKekre,PranjalChitaleand
RuhinaKarani
4.1 Introduction 55
4.2 Needforobjectdetection 56
4.3 Objectdetectiontechniques 56
4.3.1 R-CNNfamily 57
4.3.2 YOLOfamily 62
4.4 ApplicationsofobjectiondetectionduringCOVID-19crisis 66
4.4.1 Moduleforautonomoussystems(potholedetection) 66
4.4.2 Socialdistancingdetector 67
4.4.3 COVID-19detectorbasedonX-rays 69
4.4.4 Facemaskdetector 70
4.5 Conclusion 71
References 72
5. Non-contact measurement system for COVID-19 vital
signs to aid mass screening—An alternate approach 75
VijayJeyakumar,K.NirmalaandSachinG.Sarate
5.1 Introduction 75
5.2 COVID-19globalscenarios 76
5.2.1 Infections,recoveryandmortalityrate 76
5.2.2 Economyandenvironmentalimpacts 77
Contents vii
5.3 MeasurementandtestingprotocolsofCOVID-19 78
5.3.1 Measurementmethods 79
5.3.2 COVID-19innovations 80
5.4 Non-contactapproachestophysiologicalmeasurement 81
5.4.1 Needfornon-contactmeasurement 82
5.4.2 Stateofthearttopriorwork 83
5.4.3 Proposedapproach 84
5.4.4 Methodology 85
5.4.5 Preliminaryexperimentalresults 85
5.5 Conclusion 89
Acknowledgment 90
References 91
6. Evolving uncertainty in healthcare service interactions
during COVID-19: Artificial Intelligence - a threat or
support to value cocreation? 93
SumitSaxenaandAmritesh
6.1 Introduction 93
6.2 Servicedominantlogicinmarketing 96
6.3 Serviceinteractionsandcocreatedwellbeing 97
6.4 Uncertaintyduetopandemic 98
6.5 Uncertaintyinhealthcare 98
6.5.1 Impactofpandemic-leduncertaintyonapatient’smind 102
6.5.2 Impactofpandemic-leduncertaintyonservice
interactions 102
6.6 TheemergingroleofArtificialIntelligence 103
6.7 AIcombatinguncertaintyandsupportingvaluecocreationin
healthcareinteractions 104
6.8 Thespill-overeffectofArtificialIntelligence 107
6.9 Conclusionandfuturework 109
References 110
7. The COVID-19 outbreak: social media sentiment
analysis of public reactions with a multidimensional
perspective 117
BasantAgarwal,VaishnaviSharma,PriyankaHarjule,VinitaTiwariand
AshishSharma
7.1 Introduction 117
7.2 Datacollection 119
7.3 Sentimentanalysisofthetweetscollectedworldwide 120
7.4 SentimentanalysisofTweetsforIndia 123
7.4.1 COVID-19analysisforindividualcityofIndia—Mumbai 127
7.5 Analysisoffewmosttrendinghashtags 130
viii Contents
7.5.1 Opinionanalysisforthehashtag#WorkFromHome 131
7.5.2 Sentimentanalysisof#MigrantWorkers 135
7.6 Conclusion 137
References 138
8. A new approach to predict COVID-19 using artificial
neural networks 139
SohamGuhathakurata,SayakSaha,SouvikKundu,
ArpitaChakrabortyandJyotiSekharBanerjee
8.1 Introduction 139
8.2 Relatedstudies 140
8.3 Fundamentalsymptomsandconditionsresponsible
forCOVID-19infection 141
8.4 ProposedCOVID-19detectionmethodology 142
8.5 Briefdescriptionofartificialneuralnetworks 145
8.5.1 Principlesofartificialneuralnetwork 145
8.6 ParametersettingsfortheproposedANNmodel 149
8.7 Experimentalresultsanddiscussion 151
8.8 PerformancecomparisonbetweenANNandother
classificationalgorithms 153
8.9 Conclusion 155
Appendix 156
References 157
9. Rapid medical guideline systems for COVID-19 using
database-centric modeling and validation of
cyber-physical systems 161
ManiPadmanabhan
9.1 Introduction 161
9.2 GlobalpandemicofCOVID-19 162
9.3 Database-centriccyber-physicalsystemsforCOVID-19 164
9.3.1 Cyber-physicalsystems 164
9.3.2 Flowofrapiddatabase-centriccyber-physicalsystem 165
9.4 Modelingandvalidationofrapidmedicalguidelinesystems 166
9.5 Conclusion 168
References 168
10. Machine learning and security in Cyber Physical
Systems 171
NehaV.Sharma,NarendraSinghYadavandSaurabhSharma
10.1 Introduction 171
10.2 Relatedwork 174
10.2.1 Phishing 174
Contents ix
10.2.2 Intrusiondetectionfornetworks 175
10.2.3 Keystrokeelementsvalidation 175
10.2.4 Breakinghumancollaborationproofs(CAPTHAs) 175
10.2.5 Cryptography 175
10.2.6 Spamdetectionforsocialnetworking 176
10.3 Motivation 176
10.4 Importanceofcybersecurityandmachinelearning 177
10.5 MachinelearningforCPSapplications 178
10.6 FutureforCPStechnology 179
10.6.1 Cyberphysicalsystemsandhuman 181
10.6.2 CPSandartificialintelligence 181
10.6.3 Trustworthy 181
10.6.4 Cyberphysicalsystemsofsystems 182
10.7 ChallengesandopportunitiesinCPS 182
10.8 Conclusion 185
References 185
11. Impact analysis of COVID-19 news headlines on global
economy 189
AnanyaMalik,YashTejasJaveri,ManavShahandRamchandra
Mangrulkar
11.1 Introduction 189
11.2 Relatedwork 190
11.3 Proposedmethodology 194
11.3.1 Dataanddatapreprocessing 194
11.3.2 Sentimentanalysis 197
11.3.3 PredictionofNiftyscore 199
11.4 Resultsandexperimentalframework 201
11.4.1 Linearregression 201
11.4.2 Polynomialregressionwithdegree3 202
11.4.3 Randomforestregression 202
11.4.4 Gradientboostregressor 203
11.5 Conclusion 205
References 205
Furtherreading 206
12. Impact of COVID-19: a particular focus on Indian
education system 207
PushpaGothwal,BoskyDharmendraSharma,NanditaChaubeand
NadeemLuqman
12.1 Introduction 207
12.2 ImpactofCOVID-19oneducation 208
12.2.1 Effectofhomeconfinementonchildrenandteachers 211
12.2.2 Amultidimensionalimpactofuncertainty 214
x Contents
12.3 SustainingtheeducationindustryduringCOVID-19 214
12.4 Conclusion 216
References 216
13. Designing of Latent Dirichlet Allocation Based Prediction
Model to Detect Midlife Crisis of Losing Jobs due to
Prolonged Lockdown for COVID-19 219
BasabdattaDas,BarshanDas,AvikChatterjeeandAbhijitDas
13.1 Introduction 219
13.2 Literaturesurvey 220
13.3 Methodology 221
13.3.1 Distinguishingmidlifecrisissymptoms 222
13.3.2 Designingofthepredictionmodel 223
13.3.3 ApplicationofLDAandstatisticalcomparison 223
13.4 Resultanddiscussion 225
13.5 Conclusionandfuturescope 227
References 228
14. Autonomous robotic system for ultraviolet
disinfection 231
RikiPatel,HarshalSanghviandAbhijitS.Pandya
14.1 Introduction 231
14.2 Background 232
14.2.1 Ultravioletlightfordisinfection 232
14.2.2 Exposuretimefordeactivationofthebacteria 233
14.2.3 FlowchartofUVbotcontrollogic 233
14.2.4 Calculationsrelatedtothetimefordisinfection 233
14.3 Implementation 234
14.4 Modeltopology 236
14.4.1 UV-Clightroboticvehicle 237
14.5 Conclusion 239
References 240
15. Emerging health start-ups for economic feasibility:
opportunities during COVID-19 241
ShwetaNanda
15.1 Introduction 241
15.2 Health-techverticalsforstart-ups 243
15.3 Researchgap 244
15.4 Aimofthestudy 244
15.5 Researchmethodology 244
15.5.1 Problemstatement 244
15.5.2 Typeofresearch 245