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Information technology platform for monitoring infectious diseases
| Назва | Information technology platform for monitoring infectious diseases |
| Назва англійською | Information technology platform for monitoring infectious diseases |
| Автори | Andrii Stanko |
| Принадлежність | Ternopil Ivan Puluj National Technical University, Ternopil, Ukraine |
| Бібліографічний опис | Information technology platform for monitoring infectious diseases / Andrii Stanko // Scientific Journal of TNTU. — Tern.: TNTU, 2023. — Vol 110. — No 2. — P. 98–110. |
| Bibliographic description: | Stanko A. (2023) Information technology platform for monitoring infectious diseases. Scientific Journal of TNTU (Tern.), vol 110, no 2, pp. 98–110. |
| DOI: | https://doi.org/10.33108/visnyk_tntu2023.02.098 |
| УДК |
004.9 |
| Ключові слова |
internet of things, information technology platform, remote monitoring devices, artificial intelligence, data analytics, contact tracing, viral diseases. |
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Research conducted to curb the spread of infectious diseases in cities confirms that technology is making a significant contribution. A significant number of scientific studies analyze the impact of technology on the covid-19 pandemic in various aspects. However, the problems associated with the implementation of monitoring systems based on the Internet of Things are not studied in depth, they are related to the design of systems, their implementation in everyday life. This research provides an up-to-date analysis of how technology is helping to fight infectious diseases. Along with this, we consider the main challenges faced by users of such technologies, namely: privacy, security, scalability, etc. As a result, we can say that related technologies have a significant impact on the detection, tracking and containment of viruses. The organization and movement of a person has a great influence on the frequency of contacts, which, as a result, affects the transmission, spread and persistence of disease-causing pathogens. The search for contact structures of infectious diseases in view of human mobility requires a clear consideration of the spatial and temporal dimensions of pathogen transmission, which depend on the type of pathogen and the method of its transmission, the number of contacts and location. A platform that can help collect and analyze data mainly depends on having access to accurate details about various factors. Therefore, obtaining information is of prime importance for the development of this kind of technological platform. Using advanced technologies and tools such as IoT, remote monitoring devices, GPS, artificial intelligence and data analytics, contact tracing programs can provide an extra layer of protection when it
comes to monitoring and controlling people's lives and health. The proposed approach to ensure the effective implementation of the IT platform for monitoring infectious diseases, as well as the formed group of roles. This approach makes it easier to launch the platform, distributing work between assigned roles and reducing the burden on health care resources and other city services. |
| ISSN: | 2522-4433 |
| Перелік літератури |
1. Santiago-Alarcon, D., & MacGregor-Fors, I. Cities and pandemics: urban areas are ground zero for the transmission of emerging human infectious diseases - Journal of Urban Ecology, 2020, no. 6(1), pp. 1-3.
2. Yusuf P., Kashiful H., Firoj P., Mumdouh M. The internet of things (IoT) and its application domains - Int. J. Comput. Appl., 2019, no.182, pp. 36–49.
3. Qi J., Yang P., Min G., Amft O., Dong F., Xu L. Advanced internet of things for personalised healthcare systems: A survey - Pervasive Mob. Comput., 2017, Vol.41, pp. 132–149
4. Chamola V., Hassija V., Gupta V., Guizani M. A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5g in managing its impact - IEEE Access, 2020, Vol.8, pp. 90225–90265.
5. Dudhe P.V., Kadam N.V., Hushangabade R.M. and Deshmukh M. S. Internet of Things (IOT): An overview and its applications. In: 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), Chennai, 2017, pp. 2650-2653, doi: 10.1109/ICECDS.2017.8389935.
6. Tang H., Shi J. and Lei K. A smart low-consumption IoT framework for location tracking and its real application. In: 2016 6th International Conference on Electronics Information and Emergency Communication (ICEIEC), Beijing, 2016, pp. 306-309, doi: 10.1109/ICEIEC.2016.7589744.
7. Bahuguna Y., Verma A. and Raj K. Smart learning based on augmented reality with android platform and its applicability. In: 2018 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU), Bhimtal, 2018, pp. 1-5, doi: 10.1109/IoT-SIU.2018.8519853.
8. Hu F., Xie D. and Shen S. On the Application of the Internet of Things in the Field of Medical and Health Care. In: 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, Beijing, 2013, pp. 2053-2058, doi: 10.1109/GreenCom-iThings-CPSCom.2013.384.
9. Goswami S.A., Padhya B.P. and Patel K.D. Internet of Things: Applications, Challenges and Research Issues. In: 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, 2019, pp. 47-50, doi: 10.1109/I-SMAC47947.2019.9032474.
10. Sachin K., Prayag T., Mikhail Z. Internet of things is a revolutionary approach for future technology enhancement: a review. - J Big Data, 2019, Vol.6(111). https://doi.org/10.1186/s40537-019-0268-2
11. Nils R., Coker R., Atun R., McKee M. Health Systems and the Challenge of Communicable Diseases; Experiences from Europe and Latin America. - European Journal of Public Health, 2009, Vol. 19, Iss. 1, p.122, doi.org/10.1093/eurpub/ckn119
12. Nosta J. GPS tracking in the era of COVID-19. Available at: https://www.psychologytoday.com/us/blog/the-digital-self/202004/gps-tracking-in-the-era-covid-19. (accessed 03.01.2023)
13. Choudhary M. How IoT can help fight COVID-19 battle. Available at: https://www.geospatialworld.net/blogs/how-iot-can-help-fight-covid-19-battle/. (accessed 09.02.2023)
14. Doukas C. and Maglogiannis I. Bringing IoT and Cloud Computing towards Pervasive Healthcare. In: Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, Palermo, 2012, pp. 922-926, doi: 10.1109/IMIS.2012.26.
15. Jin J., Gubbi J., Marusic S. and Palaniswami M. An Information Framework for Creating a Smart City Through Internet of Things. In: IEEE Internet of Things Journal, 2014, Vol. 1, No. 2, pp. 112-121, doi: 10.1109/JIOT.2013.2296516.
16. Gomes N., Pato M., Lourenço A.R., Datia N. . A Survey on Wearable Sensors for Mental Health Monitoring. - Sensors, 2023, Vol.23(3), p. 1330.
17. Kaur B., Kumar S., Kaushik B.K. Novel Wearable Optical Sensors for Vital Health Monitoring Systems—A Review. -Biosensors, 2023, Vol. 13(2), p. 181.
18. Narassima M.S., Anbuudayasankar S.P., Vasudevan S., Shriram V., Abhinavaram J. Physicians’ and Users’ PerceptionsTtowards Wearable Health Devices. - Indonesian Journal of Electrical Engineering and Computer Science, 2017, Vol. 5, p. 234., doi: 10.11591/ijeecs.v5.i1.pp234-242.
19. Min S., Kim D.H., Joe D.J., Kim B.W., Jung Y.H., Lee J.H., Lee K. J. Clinical Validation of Wearable Piezoelectric Blood Pressure Sensor for Continuous Health Monitoring - Advanced Materials, 2023, doi:10.1002/adma.202301627.
20. Kabha R., Salameh F., Kamel A., Elbahi M., Mustafa H. M-Health applications use amongst mobile users in Dubai-UAE - International Journal of Innovative Technology and Exploring Engineering, 2019, Vol. 9(2), pp. 5100-5110.
21. Alqrnawi N., MYDERRİZİ I. COVID-19 Quarantine Monitoring Based on Geofencing Technique - International Journal of Engineering Technologies (IJET), 2021, Vol. 7(2), pp. 39-46.
22. Pittoli F., Vianna H. D., Barbosa J., Butzen E., Gaedke M., da Costa J., dos Santos R. An intelligent system for prognosis of noncommunicable diseases’ risk factors. - Telematics and Informatics, 2018, Vol. 35(5), pp. 1222-1236.
23. Boldrini C., Passarella A. HCMM: Modelling spatial and temporal properties of human mobility driven by users’ social relationships. - Computer Communications, 2010, Vol. 33(9), pp. 1056-1074.
24. Song C., Koren T., Wang P., Barabási A. Modelling the scaling properties of human mobility. - Nature physics, 2010, Vol. 6(10), pp. 818-823.
25. Boese M., Moran A., Mallman M. Multi-local settlement mobilities. - Journal of Ethnic and Migration Studies, 2020, Vol. 46(15), pp. 3277-3295.
26. Topol E. High-performance medicine: the convergence of human and artifcial intelligence. - Nat Med. 2019, Vol. 25(1), pp. 44–56.
27. VoPham T., Hart JE., Laden F., Chiang Y. Emerging trends in geospatial artifcial intelligence (geoAI): potential applications for environmental epidemiology. - Environ Health, 2018, Vol. 17(1), pp. 40.
28. Shaban-Nejad A., Michalowski M., Buckeridge D. Health intelligence: how artificial intelligence transforms population and personalized health. - NPJ digital medicine, 2018, Vol. 1(1), pp. 53.
29. Serban O., Thapen N., Maginnis B., Hankin C., Foot V. Real-time processing of social media with SENTINEL: A syndromic surveillance system incorporating deep learning for health classification. - Information Processing & Management, 2019, Vol. 56(3), pp. 1166-1184.
30. Rajkomar A., Oren E., Chen K., Dai A., Hajaj N., Hardt M., Dean J. Scalable and accurate deep learning with electronic health records. - NPJ digital medicine, 2018, Vol. 1(1), pp. 18.
31. Istepanian R., Al-Anzi T. m-Health 2.0: new perspectives on mobile health, machine learning and big data analytics. - Methods, 2018, Vol. 151, pp. 34-40.
32. Bi W., Hosny A., Schabath M., Giger M., Birkbak, N., Mehrtash A., Aerts H. Artificial intelligence in cancer imaging: clinical challenges and applications. - CA: a cancer journal for clinicians, 2019, Vol. 69(2), pp. 127-157.
33. Lee T., Kakehashi M., Arni S. Network models in epidemiology. - Handbook of Statistics, Elsevier, 2021 , Vol. 44, pp. 235-256, doi: 10.1016/bs.host.2020.09.002.
34. Giannotti F. Mobility, Data Mining and Privacy Understanding Human Movement Patterns from Trajectory Data. - IEEE 12th International Conference on Mobile Data Management, Lulea, 2011, pp. 4-5, doi: 10.1109/MDM.2011.103. |
| References: |
1. Santiago-Alarcon, D., & MacGregor-Fors, I. Cities and pandemics: urban areas are ground zero for the transmission of emerging human infectious diseases - Journal of Urban Ecology, 2020, no. 6(1), pp. 1-3.
2. Yusuf P., Kashiful H., Firoj P., Mumdouh M. The internet of things (IoT) and its application domains - Int. J. Comput. Appl., 2019, no.182, pp. 36–49.
3. Qi J., Yang P., Min G., Amft O., Dong F., Xu L. Advanced internet of things for personalised healthcare systems: A survey - Pervasive Mob. Comput., 2017, Vol.41, pp. 132–149
4. Chamola V., Hassija V., Gupta V., Guizani M. A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5g in managing its impact - IEEE Access, 2020, Vol.8, pp. 90225–90265.
5. Dudhe P.V., Kadam N.V., Hushangabade R.M. and Deshmukh M. S. Internet of Things (IOT): An overview and its applications. In: 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), Chennai, 2017, pp. 2650-2653, doi: 10.1109/ICECDS.2017.8389935.
6. Tang H., Shi J. and Lei K. A smart low-consumption IoT framework for location tracking and its real application. In: 2016 6th International Conference on Electronics Information and Emergency Communication (ICEIEC), Beijing, 2016, pp. 306-309, doi: 10.1109/ICEIEC.2016.7589744.
7. Bahuguna Y., Verma A. and Raj K. Smart learning based on augmented reality with android platform and its applicability. In: 2018 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU), Bhimtal, 2018, pp. 1-5, doi: 10.1109/IoT-SIU.2018.8519853.
8. Hu F., Xie D. and Shen S. On the Application of the Internet of Things in the Field of Medical and Health Care. In: 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, Beijing, 2013, pp. 2053-2058, doi: 10.1109/GreenCom-iThings-CPSCom.2013.384.
9. Goswami S.A., Padhya B.P. and Patel K.D. Internet of Things: Applications, Challenges and Research Issues. In: 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, 2019, pp. 47-50, doi: 10.1109/I-SMAC47947.2019.9032474.
10. Sachin K., Prayag T., Mikhail Z. Internet of things is a revolutionary approach for future technology enhancement: a review. - J Big Data, 2019, Vol.6(111). https://doi.org/10.1186/s40537-019-0268-2
11. Nils R., Coker R., Atun R., McKee M. Health Systems and the Challenge of Communicable Diseases; Experiences from Europe and Latin America. - European Journal of Public Health, 2009, Vol. 19, Iss. 1, p.122, doi.org/10.1093/eurpub/ckn119
12. Nosta J. GPS tracking in the era of COVID-19. Available at: https://www.psychologytoday.com/us/blog/the-digital-self/202004/gps-tracking-in-the-era-covid-19. (accessed 03.01.2023)
13. Choudhary M. How IoT can help fight COVID-19 battle. Available at: https://www.geospatialworld.net/blogs/how-iot-can-help-fight-covid-19-battle/. (accessed 09.02.2023)
14. Doukas C. and Maglogiannis I. Bringing IoT and Cloud Computing towards Pervasive Healthcare. In: Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, Palermo, 2012, pp. 922-926, doi: 10.1109/IMIS.2012.26.
15. Jin J., Gubbi J., Marusic S. and Palaniswami M. An Information Framework for Creating a Smart City Through Internet of Things. In: IEEE Internet of Things Journal, 2014, Vol. 1, No. 2, pp. 112-121, doi: 10.1109/JIOT.2013.2296516.
16. Gomes N., Pato M., Lourenço A.R., Datia N. . A Survey on Wearable Sensors for Mental Health Monitoring. - Sensors, 2023, Vol.23(3), p. 1330.
17. Kaur B., Kumar S., Kaushik B.K. Novel Wearable Optical Sensors for Vital Health Monitoring Systems—A Review. -Biosensors, 2023, Vol. 13(2), p. 181.
18. Narassima M.S., Anbuudayasankar S.P., Vasudevan S., Shriram V., Abhinavaram J. Physicians’ and Users’ PerceptionsTtowards Wearable Health Devices. - Indonesian Journal of Electrical Engineering and Computer Science, 2017, Vol. 5, p. 234., doi: 10.11591/ijeecs.v5.i1.pp234-242.
19. Min S., Kim D.H., Joe D.J., Kim B.W., Jung Y.H., Lee J.H., Lee K. J. Clinical Validation of Wearable Piezoelectric Blood Pressure Sensor for Continuous Health Monitoring - Advanced Materials, 2023, doi:10.1002/adma.202301627.
20. Kabha R., Salameh F., Kamel A., Elbahi M., Mustafa H. M-Health applications use amongst mobile users in Dubai-UAE - International Journal of Innovative Technology and Exploring Engineering, 2019, Vol. 9(2), pp. 5100-5110.
21. Alqrnawi N., MYDERRİZİ I. COVID-19 Quarantine Monitoring Based on Geofencing Technique - International Journal of Engineering Technologies (IJET), 2021, Vol. 7(2), pp. 39-46.
22. Pittoli F., Vianna H. D., Barbosa J., Butzen E., Gaedke M., da Costa J., dos Santos R. An intelligent system for prognosis of noncommunicable diseases’ risk factors. - Telematics and Informatics, 2018, Vol. 35(5), pp. 1222-1236.
23. Boldrini C., Passarella A. HCMM: Modelling spatial and temporal properties of human mobility driven by users’ social relationships. - Computer Communications, 2010, Vol. 33(9), pp. 1056-1074.
24. Song C., Koren T., Wang P., Barabási A. Modelling the scaling properties of human mobility. - Nature physics, 2010, Vol. 6(10), pp. 818-823.
25. Boese M., Moran A., Mallman M. Multi-local settlement mobilities. - Journal of Ethnic and Migration Studies, 2020, Vol. 46(15), pp. 3277-3295.
26. Topol E. High-performance medicine: the convergence of human and artifcial intelligence. - Nat Med. 2019, Vol. 25(1), pp. 44–56.
27. VoPham T., Hart JE., Laden F., Chiang Y. Emerging trends in geospatial artifcial intelligence (geoAI): potential applications for environmental epidemiology. - Environ Health, 2018, Vol. 17(1), pp. 40.
28. Shaban-Nejad A., Michalowski M., Buckeridge D. Health intelligence: how artificial intelligence transforms population and personalized health. - NPJ digital medicine, 2018, Vol. 1(1), pp. 53.
29. Serban O., Thapen N., Maginnis B., Hankin C., Foot V. Real-time processing of social media with SENTINEL: A syndromic surveillance system incorporating deep learning for health classification. - Information Processing & Management, 2019, Vol. 56(3), pp. 1166-1184.
30. Rajkomar A., Oren E., Chen K., Dai A., Hajaj N., Hardt M., Dean J. Scalable and accurate deep learning with electronic health records. - NPJ digital medicine, 2018, Vol. 1(1), pp. 18.
31. Istepanian R., Al-Anzi T. m-Health 2.0: new perspectives on mobile health, machine learning and big data analytics. - Methods, 2018, Vol. 151, pp. 34-40.
32. Bi W., Hosny A., Schabath M., Giger M., Birkbak, N., Mehrtash A., Aerts H. Artificial intelligence in cancer imaging: clinical challenges and applications. - CA: a cancer journal for clinicians, 2019, Vol. 69(2), pp. 127-157.
33. Lee T., Kakehashi M., Arni S. Network models in epidemiology. - Handbook of Statistics, Elsevier, 2021 , Vol. 44, pp. 235-256, doi: 10.1016/bs.host.2020.09.002.
34. Giannotti F. Mobility, Data Mining and Privacy Understanding Human Movement Patterns from Trajectory Data. - IEEE 12th International Conference on Mobile Data Management, Lulea, 2011, pp. 4-5, doi: 10.1109/MDM.2011.103. |
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