Cloud-Based IoT and AWS Architecture for Real-Time Cardiovascular Patient Monitoring
| International Journal of Electronics and Communication Engineering |
| © 2026 by SSRG - IJECE Journal |
| Volume 13 Issue 2 |
| Year of Publication : 2026 |
| Authors : Dasaraju Chandra Mohan, R.Yogesh Rajkumar |
10.14445/23488549/IJECE-V13I2P121
How to Cite?
Dasaraju Chandra Mohan, R.Yogesh Rajkumar, "Cloud-Based IoT and AWS Architecture for Real-Time Cardiovascular Patient Monitoring," SSRG International Journal of Electronics and Communication Engineering, vol. 13, no. 2, pp. 281-290, 2026. Crossref, https://doi.org/10.14445/23488549/IJECE-V13I2P121
Abstract:
Cardiovascular disease requires continuous and timely monitoring to avert abrupt medical catastrophes, particularly for high-risk patients who cannot stay under continual hospital observation. The Internet of Things (IoT) has been the subject of much research into healthcare monitoring systems, but current solutions have several drawbacks, such as slow cloud updates, no real-time event-driven alerting, poor integration of scalable cloud services, and restricted access for multiple users. In this study, we provide an Internet of Things (IoT) architecture that runs on Amazon Web Services (AWS) to monitor heart patients in real-time. Through the use of wearable medical sensors coupled with an Internet of Things module based on the ESP8266, the system is able to gather physiological characteristics such as heart rate, temperature, and oxygen saturation. By using MQTT and TLS authentication, the collected data is safely sent to AWS IoT Core. It is then processed in real-time by AWS Lambda and saved in DynamoDB for scalable time-series management. Notifications of critical threshold breaches are sent automatically using AWS Simple Notification Service (SNS), allowing for quick action. In addition, two dashboards built on Android are created to provide medical professionals and guardians with access to real-time visualization and monitoring. When compared to traditional cloud-IoT healthcare systems, the suggested system outperforms them in terms of end-to-end latency, alert accuracy, and scalability. The results prove that the suggested event-based monitoring framework powered by AWS is an efficient, practical, and lightweight way to keep an eye on patients’ heart health in real-time.
Keywords:
Internet of Things, Cloud computing, AWS, Cardiovascular diseases.
References:
[1] Shyamal Patel et al., “A Review of Wearable Sensors and Systems with Application in Rehabilitation,” Journal of NeuroEngineering and Rehabilitation, vol. 9, pp. 1-17, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Atif Alamri et al., “A Survey on Sensor-Cloud: Architecture, Applications, and Approaches,” International Journal of Distributed Sensor Networks, vol. 9, no. 2, pp. 1-18, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Alexandros Pantelopoulos, and Nikolaos G. Bourbakis, “A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis,” IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 40, no. 1, pp. 1-12, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Priyan Malarvizhi Kumar et al., “Cloud and IoT-based Disease Prediction and Diagnosis System for Healthcare using Fuzzy Neural Classifier,” Future Generation Computer Systems, vol. 86, pp. 527-534, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Weisong Shi et al., “Edge Computing: Vision and Challenges,” IEEE Internet of Things Journal, vol. 3, no. 5, pp. 637-646, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Amir M. Rahmani et al., “Exploiting Smart e-Health Gateways at the Edge of Healthcare Internet-of-Things: A Fog Computing Approach,” Future Generation Computer Systems, vol. 78, no. 2, pp. 641-658, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Alessio Botta et al., “Integration of Cloud Computing and Internet of Things: A Survey,” Future Generation Computer Systems, vol. 56, pp. 684-700, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Jayavardhana Gubbi et al., “Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions,” Future Generation Computer Systems, vol. 29, no. 7, pp. 1645-1660, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Ala Al-Fuqaha et al., “Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications,” IEEE Communications Surveys & Tutorials, vol. 17, no. 4, pp. 2347-2376, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[10] G. Jaya Lakshmi, Mangesh Ghonge, and Ahmed J. Obaid, “Cloud-based IoT Smart Healthcare System for Remote Patient Monitoring,” EAI Endorsed Transactions on Pervasive Health and Technology, vol. 7, no. 28, pp. 1-11, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Dinesh Thangavel et al., “Performance Evaluation of MQTT and CoAP via a Common Middleware,” 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), Singapore, pp. 1-6, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Adrian Bussone, Simone Stumpf, and Dympna O'Sullivan, “The Role of Explanations on Trust and Reliance in Clinical Decision Support Systems,” 2015 International Conference on Healthcare Informatics, Dallas, TX, USA, pp. 160-169, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Mahadev Satyanarayanan, “The Emergence of Edge Computing,” Computer, vol. 50, no. 1, pp. 30-39, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[14] S.M. Riazul Islam et al., “The Internet of Things for Health Care: A Comprehensive Survey,” IEEE Access, vol. 3, pp. 678-708, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Earlence Fernandes, Jaeyeon Jung, and Atul Prakash, “Security Analysis of Emerging Smart Home Applications,” 2016 IEEE Symposium on Security and Privacy (SP), San Jose, CA, USA, pp. 636-654, 2016.
[CrossRef] [Google Scholar] [Publisher Link]