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El. knyga: Smart Health Technologies for the COVID-19 Pandemic: Internet of medical things perspectives

Edited by (Birla Institute of Technology, Department of Electronics and Communication Engineering, Mesra, India), Edited by (Senac Faculty of Cearį, Fortaleza - CE, Brazil)
  • Formatas: EPUB+DRM
  • Serija: Healthcare Technologies
  • Išleidimo metai: 23-Jun-2022
  • Leidėjas: Institution of Engineering and Technology
  • Kalba: eng
  • ISBN-13: 9781839535192
Kitos knygos pagal šią temą:
Smart Health Technologies for the COVID-19 Pandemic: Internet of medical things perspectivesDidesnis paveikslėlis
  • Formatas: EPUB+DRM
  • Serija: Healthcare Technologies
  • Išleidimo metai: 23-Jun-2022
  • Leidėjas: Institution of Engineering and Technology
  • Kalba: eng
  • ISBN-13: 9781839535192
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This edited book looks at the role technology has played to monitor, map and fight the COVID-19 global pandemic. The vital role that intelligent advanced healthcare informatics has played during this crucial time are explored, as well as e-healthcare, telemedicine, and life support systems.



Smart Health Technologies for the COVID-19 Pandemic: Internet of medical things perspectives looks at the role technology has played to monitor, map and fight the global COVID-19 pandemic. Chapters outline risk assessment methodologies and social distancing and infection control technologies in the face of this disease outbreak.

The applications of Big Data and artificial intelligence in the fight against the spread of COVID-19 are explored in this edited book, as well as advances in early diagnostic testing and remote monitoring systems, and blockchain-based solutions for secure data handling. The implementation of machine learning for reviewing and analysing biomedical data and assisting with drug design is also discussed.

Emphasising the vital role that intelligent advanced healthcare informatics has played during this crucial time, this book is a valuable resource for researchers in the fields of biomedical engineering, bioengineering, electronics engineering, health informatics, wireless body area networks (WBAN), data analytics, telemedicine, and those in related fields.

About the editors xv
Preface xvii
1 Internet of Things (IoT) and blockchain-based solutions to confront COVID-19 pandemic
1(32)
Abu Hasnat Md Rhydwan
Md Mashrur Sakib Choyon
A.S.M. Mehedi Hasan Sad
Kazi Ahmed Asif Fuad
Kawshik Shikder
Chowdhury Akram Hossain
M. Shamim Kaiser
1.1 Introduction
2(1)
1.2 Internet of Things (IoT) and blockchain overview
3(6)
1.2.1 Internet of Things
4(2)
1.2.2 Blockchain
6(3)
1.3 IoT technologies to confront COVID-19
9(5)
1.3.1 Health monitoring systems
10(2)
1.3.2 Tracking and detecting possible patients
12(1)
1.3.3 Disinfecting area
13(1)
1.3.4 Telemedicine
14(1)
1.3.5 Logistics delivery
14(1)
1.4 Blockchain technologies to confront COVID-19
14(4)
1.4.1 Contact tracing
15(1)
1.4.2 Database security
16(1)
1.4.3 Information sharing
16(1)
1.4.4 Prevention of data fabrication
17(1)
1.4.5 Internet of Medical Things
18(1)
1.5 Challenges, solutions, and deliverables
18(2)
1.5.1 Challenges of IoT and blockchain technology
18(1)
1.5.2 Possible solutions and deliverables
19(1)
1.6 Key findings and discussion
20(1)
1.7 Conclusion and future scopes
21(12)
References
22(11)
2 Application of big data and computational intelligence in fighting COVID-19 epidemic
33(28)
Joseph Bamidele Awotunde
Chinmay Chakraborty
Gbemisola Janet Ajamu
2.1 Introduction
34(2)
2.2 Applicability of computational intelligence in combating COVID-19 pandemic
36(4)
2.3 Big data and analytics in battling COVID-19 outbreak
40(4)
2.4 The limitations of using big data and computational intelligence to fight the COVID-19 pandemic
44(4)
2.5 The practical case of using computational intelligence in fighting COVID-19 pandemic
48(3)
2.5.1 Confusion matrix
49(1)
2.5.2 ROC curves
50(1)
2.5.3 Precision-recall curve
50(1)
2.6 Conclusion
51(10)
References
51(10)
3 Cloud-based IoMT for early COVID-19 diagnosis and monitoring
61(24)
G. Boopathi Raja
T. Sathya
V. Gowrishankar
M. Parimala Devi
3.1 Introduction
62(1)
3.2 Overview about COVID-19 treatments
63(3)
3.2.1 Symptoms
63(1)
3.2.2 Methodologies in COVID-19 diagnosis
63(1)
3.2.3 Treatment approaches
64(1)
3.2.4 Available vaccine
65(1)
3.2.5 COVID-19 timeline
66(1)
3.3 Related work
66(6)
3.3.1 Lightweight block encryption-based secure health monitoring system for data management
66(3)
3.3.2 Smart diagnostic/therapeutic framework for COVID-19 patients
69(1)
3.3.3 IoT-based framework for collecting real-time symptom data using machine learning algorithms
70(2)
3.4 Proposed methodology
72(4)
3.4.1 Architecture of proposed IoT framework
73(3)
3.4.2 Data acquisition using wearables devices
76(1)
3.5 Implementation of proposed framework
76(2)
3.6 Results and discussion
78(3)
3.7 Conclusion and future scopes
81(4)
References
82(3)
4 Assessment analysis of COVID-19 on the global economics and trades
85(30)
Hemanta Kumar Bhuyan
Chinmay Chakraborty
4.1 Introduction
86(1)
4.2 Backgrounds
87(1)
4.3 Social impacts on finance
88(1)
4.4 Framework for the international financial system, bionetworks, and maintainability on pandemic
89(11)
4.4.1 Assessment strategy constructions to fight COVID-19
89(1)
4.4.2 Macro-finance impacts
89(1)
4.4.3 Econometric effects: consumer preferences
90(2)
4.4.4 Nonpositive impacts of COVID-19
92(2)
4.4.5 Impact of international commercial trading
94(1)
4.4.6 COVID-19's effect on the aviation industry
94(2)
4.4.7 Significant collision on the travel sector
96(2)
4.4.8 Significant reduction in primary energy usage
98(1)
4.4.9 Record decrease in C02 emissions
98(1)
4.4.10 Rise in digitalization
99(1)
4.5 The role of circular economy
100(4)
4.5.1 The circular economy for slowing the onset of climate collapse
101(1)
4.5.2 Social finance system
102(1)
4.5.3 Hurdles to CE for context of COVID-19
103(1)
4.6 Chances financial support after COVID-19
104(4)
4.6.1 Several solutions to manage hospital medical and general waste
104(2)
4.6.2 Facilities for CE in communication sector
106(1)
4.6.3 Use digitalization after COVID-19
107(1)
4.7 Conclusions
108(7)
References
110(5)
5 Early diagnosis and remote monitoring using cloud-based IoMT for COVID-19
115(26)
Madhura S. Mulimani
Shridhar Allagi
Rashmi R. Rachh
5.1 Introduction
116(1)
5.2 Detection techniques
117(2)
5.3 Internet of Medical Things
119(2)
5.4 IoMT devices for the identification of COVID-19 symptoms and remote monitoring
121(4)
5.4.1 Wearables
122(3)
5.4.2 Smartphone applications
125(1)
5.5 Early diagnosis of COVID-19 and remote monitoring procedures
125(2)
5.6 Machine learning and deep learning in COVID-19 diagnosis
127(2)
5.7 Related works
129(1)
5.8 Experimental case study
129(6)
5.8.1 Dataset description
129(1)
5.8.2 Methodology
130(3)
5.8.3 Training
133(1)
5.8.4 Experimental setup and results
134(1)
5.9 Measures for monitoring and tracking COVID-19
135(1)
5.10 Limitations of using IoMT devices
136(1)
5.11 Conclusion and future scope
137(4)
References
137(4)
6 Blockchain technology for secure COVID-19 pandemic data handling
141(40)
Agbotiname Lucky Imoize
Daisy Osarugue Irabor
Peter Anuoluwapo Gbadega
Chinmay Chakraborty
6.1 Introduction
142(2)
6.2 Recent developments in blockchain technology
144(7)
6.2.1 Healthcare data systems
147(2)
6.2.2 Healthcare data exchanges
149(1)
6.2.3 Healthcare administration
149(1)
6.2.4 Pharmaceuticals
150(1)
6.3 Potential benefits of blockchain technology in data handling
151(3)
6.3.1 Better exchange of healthcare data records
152(1)
6.3.2 Validating trust in medical research and supplies
152(1)
6.3.3 Validating correct billing management
153(1)
6.3.4 Internet of Things (IoT) in healthcare
153(1)
6.3.5 Optimized privacy and data security
154(1)
6.4 Key challenges of blockchain technology in data handling
154(3)
6.4.1 Security
155(1)
6.4.2 Speed
155(1)
6.4.3 Interoperability
155(1)
6.4.4 Stringent data protection regulation
155(1)
6.4.5 Scalability
156(1)
6.4.6 Privacy
156(1)
6.5 Prospects of blockchain technology
157(3)
6.6 Research on blockchain technology in COVID-19 healthcare
160(3)
6.7 Real-time analysis of COVID-19 pandemic data
163(7)
6.7.1 The susceptible recovered infectious (SIR) model
163(1)
6.7.2 Standard logistic regression model
164(1)
6.7.3 Time-to-event analytics model
164(1)
6.7.4 Results of major real-time analysis
165(5)
6.8 Recommendations and future directions
170(2)
6.9 Conclusion and future scopes
172(9)
Acknowledgments
173(1)
References
173(8)
7 Social distancing technologies for COVID-19
181(28)
Aumnat Tongkaw
7.1 Introduction
181(1)
7.2 Methodology
182(1)
7.3 Social distancing technologies for education
182(5)
7.3.1 Learning management system
183(3)
7.3.2 Social networking and conference software for education
186(1)
7.4 Social distancing technology in healthcare
187(6)
7.4.1 Wearable technology
187(1)
7.4.2 Screening system
188(1)
7.4.3 Queue systems
188(1)
7.4.4 Payment system
189(2)
7.4.5 Social distancing notified people in public
191(2)
7.5 Social distancing technology in manufacturing
193(2)
7.5.1 Checking the distance using wearable device
193(1)
7.5.2 Distance monitoring using Wi-Fi
194(1)
7.5.3 Distance monitoring using video analytics
194(1)
7.5.4 Social distancing by replacing some work with a robot
195(1)
7.6 Social-distancing technologies for supporting everyday life
195(7)
7.6.1 Technologies support working at home
196(1)
7.6.2 Applications support work from home (WFH) service
196(4)
7.6.3 Conferencing application
200(2)
7.7 Social distancing and smart city
202(1)
7.7.1 Aland big data
202(1)
7.7.2 Implementation and usability
202(1)
7.7.3 Privacy and security
203(1)
7.7.4 Policy and legislation
203(1)
7.8 Conclusion and future works
203(6)
References
205(4)
8 Social health protection in touristic destinations during COVID-19
209(18)
Zaklina Spalevic
Aleksandra Stojnev Ilic
Milos Ilic
8.1 Introduction
210(2)
8.2 Related work
212(2)
8.3 Proposal of software solution for health protection
214(6)
8.3.1 System architecture
215(2)
8.3.2 Healthcare service
217(1)
8.3.3 Tourist service
218(1)
8.3.4 Local government service
219(1)
8.3.5 Border control
220(1)
8.4 Data protection
220(2)
8.5 Conclusion and future works
222(5)
References
223(4)
9 Analysis of Artificial Intelligence and Internet of Things in biomedical imaging and sequential data for COVID-19
227(34)
Sinthia Roy Banerjee
Saurav Mallik
Tapas Si
Arijit Banerjee
Shan Jiang
Sudip Podder
9.1 Introduction
228(2)
9.2 Definition of biomedical keywords
230(2)
9.2.1 Microarray and RNA-seq data
230(1)
9.2.2 De novo mutation
231(1)
9.2.3 ChiP-seqdata
231(1)
9.2.4 Biomedical imaging
231(1)
9.3 Categories of computational algorithms in biomedical data
232(3)
9.3.1 Biomedical data analysis
232(1)
9.3.2 Array-based data analysis
233(2)
9.3.3 Hybrid data analysis
235(1)
9.4 Different techniques for diagnosis using biomedical imaging
235(3)
9.4.1 Brain
235(1)
9.4.2 Breast
236(1)
9.4.3 Kidney
236(1)
9.4.4 Ovary
237(1)
9.4.5 Skin cancer
237(1)
9.4.6 Soft tissue sarcoma
238(1)
9.5 Comparative review of computational algorithms
238(1)
9.6 Role of CT in COVID-19 pandemic
238(13)
9.7 Advent of smart technologies during COVID-19
251(3)
9.7.1 Building ML models to diagnose COVID-19
253(1)
9.7.2 Impact of IoT in healthcare
253(1)
9.8 Conclusion
254(7)
References
255(6)
10 Review of medical imaging with machine learning and deep learning-based approaches for COVID-19
261(34)
Swapnil Singh
Vidhi Vazirani
Deepa Krishnan
10.1 Introduction
262(2)
10.2 Literature review
264(15)
10.2.1 Reviewed work
264(15)
10.3 Comparative analysis of existing work
279(10)
10.4 Research gaps
289(1)
10.4.1 Unavailability of large datasets
289(1)
10.4.2 Imbalanced datasets
289(1)
10.4.3 Multiple image sources
290(1)
10.5 Conclusion
290(5)
References
291(4)
11 Machine-based drug design to inhibit SARS-CoV-2 virus
295(36)
T. Lurthu Pushparaj
E. Francy Irudaya Rani
E. Fantin Irudaya Raj
M. Appadurai
11.1 Introduction
296(2)
11.2 What is SARS-coronavirus-2?
298(1)
11.3 Mechanism of SARS-coronavirus-2 infection in human
299(1)
11.4 How SARS-coronavirus-2 multiplies?
300(2)
11.5 Human antibody generation and role of vaccine
302(1)
11.5.1 Immediate action of human antibody
302(1)
11.5.2 Role of synthetic vaccine on COVID-19
302(1)
11.6 Real-time COVID-19 identification test (RT-PCR)
303(2)
11.6.1 Limitations of RT-PCR tool
304(1)
11.7 Discussion on in silico methods in COVID-19 drug research
305(13)
11.7.1 In silico-assisted anchoring site analysis
305(2)
11.7.2 Machine-assisted designing and evaluation of COVID-19 drug
307(11)
11.8 Machine-integrated advanced techniques for COVID-19
318(4)
11.8.1 Computerized tomography in COVID-19 detection
318(1)
11.8.2 Advanced MRI for COVID-19 treatment
319(3)
11.9 Summary
322(2)
11.10 Conclusion and future scopes
324(7)
11.10.1 Future scope
324(1)
References
325(6)
12 Stress detection for cognitive rehabilitation in COVID-19 scenario
331(28)
Ahona Ghosh
Sima Das
Sriparna Saha
12.1 Introduction
331(2)
12.2 Related works
333(2)
12.3 Proposed framework
335(9)
12.3.1 Introduction to EEG
340(1)
12.3.2 Feature extraction using DWT
341(1)
12.3.3 Feature selection using principal component analysis
342(1)
12.3.4 Classification using support vector machine
343(1)
12.4 Experimental outcomes and discussions
344(7)
12.4.1 Dataset preparation
344(1)
12.4.2 Sloreta-based activated brain region selection
345(1)
12.4.3 Discrete wavelet transform-based feature extraction outcome
345(1)
12.4.4 Principal component analysis-based dimensionality reduction outcome
346(1)
12.4.5 Support vector machine-based classification outcome
346(2)
12.4.6 Performance metrics
348(1)
12.4.7 Performance evaluation
348(2)
12.4.8 Statistical significance using Mest
350(1)
12.5 Conclusion and future works
351(8)
Acknowledgment
351(1)
References
352(7)
13 Arduino-based robot for purification of COVID-19 using far UVC light
359(26)
C.N. Sujatha
B. Sri Charan
K. Himabindu
13.1 Introduction
360(5)
13.1.1 Arduino
360(3)
13.1.2 Far-UVC lamp
363(2)
13.2 Literature survey
365(11)
13.2.1 Improvements and requirements
372(4)
13.3 Working of the proposed robot
376(2)
13.3.1 Value proposition
377(1)
13.4 Results and discussions
378(3)
13.5 Conclusion and future scope
381(4)
References
381(4)
14 Effect of COVID-19 pandemic on waste management system and infection control
385(20)
Ramkrishna Mondal
Chinmay Chakrabarty
14.1 Introduction
386(1)
14.2 Socioeconomic and environmental impact
387(1)
14.3 Impact of waste generation
388(2)
14.4 Impacts on waste management
390(3)
14.4.1 Waste management adjustments
392(1)
14.5 Challenges in handling waste
393(1)
14.6 Rethinking effective waste management
394(3)
14.6.1 Policy, regulatory, and guidelines
395(1)
14.6.2 Handling of infectious waste
395(1)
14.6.3 Suitable disposal methods
396(1)
14.6.4 Information, education, and communication
396(1)
14.6.5 Data management and learning
396(1)
14.6.6 Monitoring of segregation
396(1)
14.6.7 Basic principles for managing waste
396(1)
14.6.8 Fund raising and national and international collaboration
397(1)
14.7 Conclusion and future scopes
397(8)
References
398(7)
15 Natural adjunctive therapies options other than COVID-19 antiviral therapies
405(16)
Betul Ozdemir
Zeliha Selamoglu
15.1 Introduction
406(1)
15.2 Immune system and inflammatory responds
407(1)
15.3 Proinflammatory cytokines
408(1)
15.4 Immunomodulators and adjunctive therapies
409(6)
15.4.1 Phenolic compounds
409(3)
15.4.2 Melatonin
412(1)
15.4.3 Zinc
413(1)
15.4.4 Ascorbic acid (vitamin C)
413(1)
15.4.5 Vitamin D
413(1)
15.4.6 Vitamin E
414(1)
15.4.7 Selenium
414(1)
15.4.8 Omega-3 fatty acids
414(1)
15.5 Dietary ingredients in immunity
415(1)
15.6 Conclusion and future scope for natural antiviral therapies against COVID-19
415(6)
References
415(6)
16 Risk assessment and spread of COVID-19
421(18)
Challa Sri Gouri
D. Ajitha
Nikhil Mulaguru
Goteti Rithika
16.1 Introduction
422(1)
16.2 Technology and epidemics
422(4)
16.2.1 Healthcare
425(1)
16.2.2 Education
425(1)
16.2.3 Work
425(1)
16.2.4 Others
425(1)
16.3 Prediction techniques
426(1)
16.4 General methods followed for risk assessment
427(4)
16.4.1 What-if analysis
428(1)
16.4.2 Fault-tree analysis
429(1)
16.4.3 Guidelines issued by World Health Organization
430(1)
16.5 Prevention and management of epidemics
431(3)
16.5.1 Strategies proposed
432(1)
16.5.2 Sentimental analysis using machine learning
433(1)
16.6 Protecting the living beings from the impact of epidemics
434(1)
16.6.1 Impact of COVID-19 on agriculture sector
434(1)
16.6.2 Impact of COVID-19 on economy
434(1)
16.6.3 Impact of COVID-19 on educational sector
435(1)
16.7 Our contribution
435(3)
16.7.1 Proposed method and its working
435(1)
16.7.2 Components required
436(1)
16.7.3 Software required and simulation
437(1)
16.8 Conclusion and future scope
438(1)
References 439(4)
Index 443
Chinmay Chakraborty has published more than 70 conference presentations, journal papers, book chapters and books. He has served on the Editorial Boards of more than ten journals, including Future Internet Journal (Wiley), Internet Technology Letters (Springer), and Advances in Smart Healthcare Technologies (CRC Press) and the organizing committees of numerous IEEE international conferences.



Joel J.P.C. Rodrigues is an Highly Cited Researcher has published over 1,000 papers in refereed international journals and conferences, 3 books, 2 patents, and 1 ITU-T Recommendation. He is the editor-in-chief of the International Journal of E-Health and Medical Communications and an editorial board member of several high-reputed journals. He has chaired many international conferences, including IEEE ICC, IEEE GLOBECOM, IEEE HEALTHCOM, and IEEE LatinCom. He has received several Outstanding Leadership and Outstanding Service Awards by IEEE Communications Society. He is a member of the Internet Society, a senior member ACM, and a Fellow of AAIA and IEEE.
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