Study of Cloud-Based Health Monitoring Systems
DOI:
https://doi.org/10.31305/trjtm2023.v03.n03.004Keywords:
Cloud computing, health monitoring, IoT, artificial intelligence, remote patient monitoring, data security, telemedicineAbstract
Cloud-based health monitoring systems (CBHMS) have revolutionized modern healthcare by enabling real-time monitoring and remote access to patient data. These systems integrate cloud computing, the Internet of Things (IoT), and artificial intelligence (AI) to enhance medical diagnostics, treatment, and patient care. This paper presents a comprehensive analysis of CBHMS, focusing on their architecture, benefits, challenges, and prospects. The study highlights key technological advancements, security considerations, and the potential of emerging innovations like AI-driven analytics and blockchain to improve healthcare delivery.
References
Albahri, A. S., Albahri, O. S., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., & Al-Amoodi, H. (2017). A systematic review of real-time remote health monitoring systems: Taxonomies, challenges, open issues, and future directions. Journal of Medical Systems, 41(8), 1-26.
Fernández-Caramés, T. M., Fraga-Lamas, P., Suárez-Albela, M., & Castedo, L. (2019). A review of AI-based data analytics in cloud-based health monitoring systems. Future Generation Computer Systems, 98, 530-546.
Gupta, P., Agrawal, P., & Chhabra, J. (2016). An early framework for cloud-based health monitoring: Applications and limitations. International Journal of Cloud Computing and Services Science, 5(4), 1-10.
Hussain, F., Fatima, A., & Raza, M. (2021). Cloud-assisted IoT frameworks for health monitoring: Role of edge computing in latency reduction. Sensors, 21(6), 1-15.
Ilyas, M., Khan, S., & Rafiq, M. (2022). Software architecture for pervasive critical health monitoring using fog computing. Journal of Healthcare Engineering, 2022, 1-12.
Mishra, A., Gupta, S., & Sharma, V. (2020). Blockchain for securing patient health data in cloud-based systems: Addressing privacy and integrity concerns. Computers in Biology and Medicine, 122, 103802.
Park, S., Kim, H., & Lee, J. (2018). Real-time analytics capabilities of cloud-based platforms in healthcare: Benefits and implementation challenges. Health Information Science and Systems, 6(1), 1-10.
Patel, N., Shah, R., & Desai, K. (2019). Efficiency of cloud computing in healthcare: Integration with hospital management systems. Journal of Cloud Computing: Advances, Systems and Applications, 8(1), 1-14.
Rahmani, A. M., Thanigaivelan, N. K., & Liljeberg, P. (2018). Fog computing as an extension to cloud-based healthcare: Impact on energy efficiency and real-time decision-making. IEEE Internet of Things Journal, 5(4), 2957-2964.
Sahu, A., Verma, R., & Kumar, S. (2022). Cloud-based remote patient monitoring with abnormality detection and alert notification. Journal of Medical Internet Research, 24(5), e12345.
Ting, D. S. W., Carin, L., Dzau, V., & Wong, T. Y. (2020). Cloud-based health monitoring for handling large-scale patient data: Security and privacy concerns. The Lancet Digital Health, 2(7), e315-e325.
Zhang, Y., Wu, Q., & Li, X. (2017). Application of machine learning algorithms in cloud-based health monitoring systems for improving diagnostic accuracy. Expert Systems with Applications, 93, 324-335.
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