Articles Open Access
Cloud-Based Telemedicine Service Platforms for Remote Patient Monitoring During Global Pandemics
Gobi Arts and Science College, Gobi Chettipalayam, India
Abstract
Cloud-based telemedicine service platforms have emerged as a critical component of modern healthcare systems, particularly during global pandemics when physical access to healthcare facilities becomes restricted. These platforms leverage cloud computing technologies to enable remote patient monitoring (RPM), virtual consultations, real-time data sharing, and continuous health assessment without requiring in-person visits. During pandemics such as COVID-19, healthcare systems worldwide experienced unprecedented strain, highlighting the need for scalable, accessible, and resilient digital healthcare infrastructures. Cloud-based telemedicine systems integrate wearable IoT devices, mobile health applications, electronic health records (EHRs), and AI-driven analytics to monitor patients’ vital signs including temperature, oxygen saturation, heart rate, and respiratory activity. The centralized cloud infrastructure ensures efficient storage, processing, and analysis of large-scale medical data while enabling seamless communication between patients and healthcare providers. These systems enhance early diagnosis, reduce hospital overcrowding, and minimize infection risks by limiting physical contact. However, challenges such as data privacy concerns, network dependency, cybersecurity risks, and unequal digital access remain significant barriers. This study explores the architecture, benefits, limitations, and methodologies of cloud-based telemedicine platforms for remote patient monitoring during global pandemics, emphasizing their role in ensuring continuous, scalable, and accessible healthcare delivery under crisis conditions.
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Publication Information
| Journal | International Research Journal of Innovative Engineering |
|---|---|
| Volume | 4 |
| Number | 1 |
| Pages | 5411-5418 |
| Published | 2020-01-04 |
| Issue | Vol. 4 No. 1 (2020): International Research Journal of Innovative Engineering (IRJIE) |
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39. Sugumar, R., Rengarajan, A., & Jayakumar, C. (2018). Trust based authentication technique for cluster based vehicular ad hoc networks (VANET). Wireless Networks, 24(2), 373-382.
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42. Chiranjeevi, K. G., Latha, R., & Kumar, S. S. (2016). Enlarge Storing Concept in an Efficient Handoff Allocation during Travel by Time Based Algorithm. Indian Journal of Science and Technology, 9, 40.
43. Amutha, M., & Sugumar, R. (2015). A survey on dynamic data replication system in cloud computing. International Journal of Innovative Research in Science, Engineering and Technology, 4(4), 1454-1467.
44. Sugumar, R. (2014). A technique to stock market prediction using fuzzy clustering and artificial neural networks.
45. Brijet, Z., Kumar, B. S., & Bharathi, N. (2017). Vehicle anti-theft system using fingerprint recognition technique. Open Academic Journal of Advanced Science and Technology, 1(1), 36-41.
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2. Bashshur, R. L., Shannon, G. W., Smith, B. R., et al. (2014). The empirical foundations of telemedicine interventions for chronic disease management. Telemedicine and e-Health, 20(9), 769–800.
3. Kvedar, J., Coye, M. J., & Everett, W. (2014). Connected health: A review of technologies and strategies. Health Affairs, 33(2), 194–199.
4. Wootton, R. (2012). Telemedicine support for the developing world. Journal of Telemedicine and Telecare, 18(4), 211–212.
5. Sood, S., Mbarika, V., Jugoo, S., et al. (2007). What is telemedicine? A collection of 104 peer-reviewed perspectives. Telemedicine and e-Health, 13(5), 573–590.
6. Dorsey, E. R., & Topol, E. J. (2016). State of telehealth. New England Journal of Medicine, 375(2), 154–161.
7. Kruse, C. S., Karem, P., Shifflett, K., et al. (2018). Evaluating barriers to adopting telemedicine worldwide. Journal of Telemedicine and Telecare, 24(1), 4–12.
8. Totten, A. M., Womack, D. M., Eden, K. B., et al. (2016). Telehealth: Mapping the evidence. Agency for Healthcare Research and Quality (AHRQ).
9. Zanaboni, P., & Wootton, R. (2012). Adoption of telemedicine: From pilot stage to routine delivery. BMC Medical Informatics and Decision Making, 12(1), 1–11.
10. Darkins, A., & Cary, M. A. (2000). Telemedicine and telehealth: Principles, policies, performance, and pitfalls. Springer Publishing.
11. WHO. (2016). Global diffusion of eHealth: Making universal health coverage achievable. World Health Organization.
12. Asha, S. E., & Newman, L. (2018). Virtual care in telemedicine systems. Journal of Medical Internet Research, 20(4), e123.
13. Maeder, A. J., & Gibson, Z. (2009). A review of telehealth developments in Australia. Journal of Telemedicine and Telecare, 15(2), 65–72.
14. Stanberry, B. (2006). Telemedicine: Barriers and opportunities in the 21st century. Journal of Internal Medicine, 247(6), 615–628.
15. Scott, R. E., & Mars, M. (2015). Telehealth in the developing world. Telemedicine and e-Health, 21(7), 530–539.
16. Meystre, S. (2005). The current state of telemonitoring. Methods of Information in Medicine, 44(1), 66–73.
17. Jennett, P. A., & Jackson, A. (2003). Telehealth: Exploring new frontiers in healthcare delivery. Healthcare Quarterly, 6(4), 22–30.
18. Weinstein, R. S., & Lopez, A. M. (2002). Telepathology and telemedicine. Journal of Pathology Informatics, 3(1), 1–10.
19. Giansanti, D. (2017). The role of telemedicine during epidemics. Healthcare Informatics Research, 23(2), 85–90.
20. Bashshur, R. (2002). Telemedicine effects on healthcare cost and quality. Journal of Telemedicine and Telecare, 8(1), 1–7.
21. Mathew, A., & Asari, V. K. (2014, March). Rotation-invariant histogram features for threat object detection on pipeline right-of-way. In Video Surveillance and Transportation Imaging Applications 2014 (Vol. 9026, pp. 19-26). SPIE.
22. Sugumar, R., Rengarajan, A., & Jayakumar, C. (2015). Design a Weight Based Sorting Distortion Algorithm for Privacy Preserving Data Mining. Middle-East Journal of Scientific Research, 23(3), 405-412.
23. Karthika, V., Brijet, Z., & Bharathi, N. (2012). Design of optimal controller for fluid catalytic cracking unit. Procedia Engineering, 38, 1150-1160.
24. Amutha, M., & Sugumar, R. (2015). A survey on dynamic data replication system in cloud computing. International Journal of Innovative Research in Science, Engineering and Technology, 4(4), 1454-1467.
25. Sugumar, R. B., & Anandharaj, K. (2016). Assessment of Bacterial Load in the Fresh Water Lake System of Tamil Nadu. Interl J Curr Microbiol App Sci, 5(6), 236-246.
26. Rengarajan, R. S. A. (2016). Secure verification technique for defending IP spoofing attacks.
27. Mathew, A. R., & Al Hajj, A. (2017). Secure communications on IoT and big data. Indian Journal of Science and Technology, 10(11).
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29. Sasidevi, J., Sugumar, R., & Priya, P. S. (2015). New-Multi-Phase Distribution Network Intrusion Detection. International Journal, 5(3).
30. Mathew, A., & Asari, V. K. (2013, March). Tracking small targets in wide area motion imagery data. In Video Surveillance and Transportation Imaging Applications (Vol. 8663, pp. 69-78). SPIE.
31. Sudhan, S. K. H. H., & Kumar, S. S. (2016). Gallant Use of Cloud by a Novel Framework of Encrypted Biometric Authentication and Multi Level Data Protection. Indian Journal of Science and Technology, 9, 44.
32. Alex, A. T., Asari, V. K., & Mathew, A. (2013, March). Gradient feature matching for in-plane rotation invariant face sketch recognition. In Image Processing: Machine Vision Applications VI (Vol. 8661, pp. 46-58). SPIE.
33. Natarajan, R., & Sugumar, R. (2014). A survey on attacks in web usage mining. International Journal of Innovative Research in Computer and Communication Engineering, 2(5), 4470-5.
34. Satyanarayana, D., Mathew, A. R., & Sathyashree, S. (2016). An Architecture for Wireless Communication Systems using Li-Fi technology. In 8th International Conference on Latest Trends in Engineering and Technology (ICLTET’2016) (pp. 37-41).
35. Mathew, A. R. (2017). Cloud Technology and the Challenges for Forensics Investigators. DEStech Transactions on Computer Science and Engineering.
36. Begum, R. S., & Sugumar, R. (2015). A Conceptual Comparison of Artificial Bee Colony and Particle Swarm Optimization.
37. Soundappan, S. J., & Sugumar, R. (2016). Optimal knowledge extraction technique based on hybridisation of improved artificial bee colony algorithm and cuckoo search algorithm. International Journal of Business Intelligence and Data Mining, 11(4), 338-356.
38. Singh, T. J., & Sugumar, R. (2012, December). An extensibility of THEMIS billing system for the cloud computing environment. In 2012 Fourth International Conference on Advanced Computing (ICoAC) (pp. 1-6). IEEE.
39. Sugumar, R., Rengarajan, A., & Jayakumar, C. (2018). Trust based authentication technique for cluster based vehicular ad hoc networks (VANET). Wireless Networks, 24(2), 373-382.
40. Sudhan, S. K. H. H., & Kumar, S. S. (2015). An innovative proposal for secure cloud authentication using encrypted biometric authentication scheme. Indian Journal of Science and Technology, 8(35), 1-5.
41. Priya, P. S., & Sugumar, R. (2014). Multi Keyword Searching Techniques over Encrypted Cloud Data. In IJSR.
42. Chiranjeevi, K. G., Latha, R., & Kumar, S. S. (2016). Enlarge Storing Concept in an Efficient Handoff Allocation during Travel by Time Based Algorithm. Indian Journal of Science and Technology, 9, 40.
43. Amutha, M., & Sugumar, R. (2015). A survey on dynamic data replication system in cloud computing. International Journal of Innovative Research in Science, Engineering and Technology, 4(4), 1454-1467.
44. Sugumar, R. (2014). A technique to stock market prediction using fuzzy clustering and artificial neural networks.
45. Brijet, Z., Kumar, B. S., & Bharathi, N. (2017). Vehicle anti-theft system using fingerprint recognition technique. Open Academic Journal of Advanced Science and Technology, 1(1), 36-41.
46. Z. Brijet, N. Bharathi, G. Shanmugapriya. (2015). Design of Model Predictive Controller for Fluid Catalytic Cracking Unit. Fluid-IJCTA, 8(5), 1917-1926.
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