Akıllı Hastaneler için e-Sağlık İzleme Sistemlerinde Bulut Maliyet Optimizasyonu

Year 2026, Volume: 21 Issue: 1, 15 - 24

Niayesh Gharaei , Ali Hosseingholipourasl , Gülsüm Kayabaşı Koru , Ramin Abbaszadi

https://doi.org/10.55525/tjst.1681334

Abstract

COVID-19 pandemisinin hızlandırdığı e-sağlık izleme sistemlerine yönelik artan talepler doğrultusunda, geleneksel klinisyen odaklı yaklaşımlar ölçeklenebilirlik ve yanıt süresi açısından yetersiz kalmaktadır. Bu sorunlara çözüm olarak, akıllı hastaneler için kenar cihazlara ihtiyaç duymayan yenilikçi bir refakatçi-taraflı e-sağlık izleme sistemi öneriyoruz. Önerilen sistem, cihaz üzerindeki sağlık değerlendiricileri sayesinde gerçek zamanlı sağlık metriklerini hesaplayarak verilerin yerel olarak işlenmesini sağlar ve dış altyapıya olan bağımlılığı azaltır. Bu mimari, veri depolama verimliliğini artırır, uçtan uca gecikmeleri azaltır ve sürekli hasta takibini mümkün kılar. Deneysel sonuçlar, sistemimizin mevcut çözümlerden daha üstün performans gösterdiğini ortaya koymakta ve modern akıllı sağlık ortamlarında uygulanabilirliğini ve ölçeklenebilirliğini doğrulamaktadır.

Keywords

Akıllı hastaneler , nesnelerin interneti , bulut maliyet optimizasyonu

Cloud Cost Optimization in e-Health Monitoring Systems for Smart Hospitals

Abstract

In response to the growing demand for efficient eHealth monitoring systems, particularly accelerated by the COVID-19 pandemic, traditional clinician-centric approaches have shown limitations in scalability and responsiveness. To address these challenges, we propose an innovative companion-side eHealth monitoring system for smart hospitals, leveraging IoT technologies without the need for edge devices. The proposed system utilizes on-device health evaluators to compute real-time health metrics, enabling efficient local processing and minimizing reliance on external infrastructure. This design significantly optimizes data storage, reduces end-to-end delay, and ensures continuous patient monitoring. Experimental results demonstrate that our system outperforms existing solutions, confirming its effectiveness, scalability, and suitability for deployment in modern smart healthcare environments.

Keywords

Smart health hospitals , IoT , cloud cost optimization

References

• Sharma K, Shivandu SK. Integrating artificial intelligence and internet of things (IoT) for enhanced crop monitoring and management in precision agriculture. Sensors International 2024; 100292.
• Karothia R, Chattopadhyay MK. Internet of thing (IoT) enabled smart sensor node (SSN) to measure the soil and environmental parameters for smart farming. CSI Transactions on ICT 2024; 1-17.
• Uddin R, Koo I. Real-time remote patient monitoring: a review of biosensors integrated with multi-hop IoT systems via cloud connectivity. Applied Sciences 2024; 14(5): 1876.
• Pradeep M, Kumari, S, Tyagi AK, Tiwari S. Smart Hospital in Smart Cities. Digital Twin and Blockchain for Smart Cities 2024; 579-603.
• Mahmmod BM, Naser MA, Al-Sudani AHS, Alsabah, M, Mohammed HJ, Alaskar H, Abdulhussain SH. Patient monitoring system based on internet of things: A review and related challenges with open research issues. IEEE Access 2024.
• Al_Zuhairi MH, Al-Bayati MA. Intelligent mobile cloud platform for monitoring patients of COVID-19 in their home-quarantines. Turkish J Comput Math Educ 2021;12:14:4461–4477.
• Alahmadi A, Soh BA. Smart approach towards a mobile e-health monitoring system architecture. in Proc Int Conf Res Innov Inf Syst 2011;1–5.
• Gera S, Mridul M, Sharma S. IoT based automated health care monitoring system for smart city. in Proc 5th Int Conf Comput Methodol Commun (ICCMC) 2021; 364–368.
• Iqbal N, Imran, Ahmad S, Ahmad R, Kim DH. A scheduling mechanism based on optimization using IoT-tasks orchestration for efficient patient health monitoring. Sensors 2021; 21:16:5430.
• Zhou J, Lin X, Dong X, Cao Z. PSMPA: Patient self-controllable and multi-level privacy-preserving cooperative authentication in distributed m-healthcare cloud computing system. IEEE Trans Parallel Distrib Syst 2015; 26:6:1693–1703.
• Zhou J, Cao Z, Dong X, Xiong N, Vasilakos AV. 4S: A secure and privacy-preserving key management scheme for cloud-assisted wireless body area network in m-healthcare social networks. Inf Sci 2015; 314: 255–276.
• Christo MS, Bommi RM, Anandaraj SP, Sankar SMU, Anbarasu V, Ramkumar G. Enhancement of reputation aggregation based dynamic trust protocols for edge computing based E-health care system. 2021.
• Dong P, Ning Z, Obaidat MS, Jiang X, Guo Y, Hu X, Sadoun BP. Edge computing based healthcare systems: Enabling decentralized health monitoring in Internet of Medical Things. IEEE Network 2020; 34:5:254–261.
• Sodhro H, Luo Z, Sangaiah AK, Baik SW. Mobile edge computing based QoS optimization in medical healthcare applications. Int J Inf Manage 2019; 45:308–318.
• Oueida S, Kotb Y, Aloqaily M, Jararweh Y, Baker T. An edge computing based smart healthcare framework for resource management. Sensors 2018;18:12:4307.
• Dong P, Wang X, Wang S, Wang Y, Ning Z, Obaidat MS. Internet of UAVs based remote health monitoring: An online eHealth system. IEEE Wireless Communication 2021; 28:3:15–21.
• Shafi I, Din S, Farooq S, Díez IDLT, Breñosa J, Espinosa JCM, Ashraf I. Design and development of patient health tracking, monitoring and big data storage using Internet of Things and real time cloud computing. Plos one 2024;19(3):e0298582.
• Malathi J, Kusha KR, Isaac S, Ramesh A, Rajendiran M, Boopathi S. IoT-Enabled Remote Patient Monitoring for Chronic Disease Management and Cost Savings: Transforming Healthcare. In Advances in Explainable AI Applications for Smart Cities 2024;371-388.
• Pathak N, Mukherjee A, MisraS. Queue-Based Analytical Modeling for Capacity Estimation of Wearable eHealth Systems. IEEE Transactions on Network Science and Engineering 2025.
• Venkataramanaiah B, Chittimalla SK, Reddy VR, Vani A, Saidmuratova M, Khasanova S, Vinayagam P. An IoT cloud based health monitoring system for remote area using node MCU: e health checker. In 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) 2025; 807-811.
• Zhang Z, Li Z, Lai CS, Wu R, Li X, Lin J, Qiao H. Joint Optimization of Data Urgency and Freshness in Wireless Body Area Networks for Enhanced eHealth Monitoring. IEEE Transactions on Consumer Electronics 2025.