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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62825
Volume:
10 |
5 |
May 2026
Pages:
1-7
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Electronics and communication
Tulsiramji Gaikwad Patil College of Engineering and Technology
Department of Electronics and communication
Tulsiramji Gaikwad Patil College of Engineering and Technology
Department of Electronics and communication
Tulsiramji Gaikwad Patil College of Engineering and Technology
Cardiovascular diseases remain a major global health concern, necessitating continuous and real-time monitoring of vital cardiac parameters. This paper presents an IoT-based wireless system for continuous heart rate and SpO₂ monitoring integrated with cloud storage and emergency alert mechanisms. The proposed system utilizes the MAX30100 pulse oximeter sensor to acquire physiological signals non-invasively using photoplethysmography (PPG). The ESP8266 microcontroller processes the acquired data and transmits it to the Blynk cloud platform via Wi-Fi for remote monitoring through a smartphone application. Real-time data is also displayed locally on an LCD screen for immediate observation. The system incorporates signal preprocessing techniques to minimize noise and improve measurement accuracy under varying conditions. An intelligent alert system is implemented to detect abnormal heart rate thresholds such as tachycardia and bradycardia, triggering both a buzzer and mobile notifications for rapid intervention. Experimental results demonstrate reliable performance under resting conditions with acceptable accuracy compared to standard medical devices. The proposed system is compact, low-cost, and energy-efficient, making it suitable for home healthcare, elderly monitoring, and telemedicine applications. Overall, this work provides a scalable and practical solution for continuous cardiac health monitoring using IoT technologies.
KEYWORDS
The proposed IoT-based wireless system for continuous heart rate and SpO₂ monitoring demonstrates an effective, low-cost solution for real-time healthcare applications. By integrating the MAX30100 sensor with the ESP8266 microcontroller, the system successfully captures physiological signals and transmits them to the cloud for remote monitoring. The results indicate that the system provides reliable performance with acceptable accuracy, particularly under resting and moderate activity conditions. Although slight deviations occur during high-motion scenarios due to motion artifacts and sensor limitations, the overall trend tracking remains consistent and useful for detecting abnormalities. The incorporation of cloud-based monitoring through the Blynk IoT Platform enhances accessibility, allowing users and caregivers to monitor health data anytime and from anywhere. The emergency alert mechanism, including buzzer notifications and mobile alerts, ensures timely intervention during critical conditions, improving patient safety. Furthermore, the system’s portability, energy efficiency, and ease of use make it suitable for home healthcare, elderly monitoring, and telemedicine applications. Future improvements may include advanced signal processing, multi-parameter sensing, and enhanced data security. Overall, this system contributes to the advancement of smart healthcare solutions and supports proactive cardiac health management.
[1] P. H. Charlton, P. A. Kyriacou, et al., “The 2023 wearable photoplethysmography roadmap,” npj Digital Medicine, 2023. [Online]. Available: PMC [2] P. H. Charlton and P. A. Kyriacou, “Wearable Photoplethysmography: Current Status and Future Challenges,” Computing in Cardiology (CinC) Proceedings, 2023. [3] A. Elgendi, et al., “Photoplethysmography—new applications for an old technology,” Journal, 2022. [Online]. Available: PMC [4] S. U. Rehman, I. Sadek, B. Huang, S. Manickam, and L. N. Mahmoud, “IoT-based emergency cardiac death risk rescue alert system,” Procedia Computer Science, ScienceDirect / Elsevier, 2024. [5] A. Hannan, S. M. Cheema, and I. M. Pires, “Machine learning-based smart wearable system for cardiac arrest detection,” Journal of Biomedical Informatics, Elsevier, 2023. [6] J. Hutton, S. Lingawi, J. H. Puyat, C. Kuo, B. Shadgan, J. Christenson, and B. Grunau, “Sensor technologies to detect out-of-hospital cardiac arrest,” BMJ Open, 2022. [Online]. Available: PMC [7] S. Abdulmalek, A. Nasir, W. A. Jabbar, M. A. M. Almuhaya, A. K. Bairagi, M. A.-M. Khan, and S.-H. Kee, “IoT-Based Healthcare-Monitoring System towards Improving Quality of Life,” Sensors, MDPI, 2022. [Online]. Available: PMC [8] P. Macheso and A. Meela, “IoT Based Patient Health Monitoring using ESP8266 and Arduino,” International Journal / Conference, 2021. [Online]. Available: ResearchGate [9] D. R. Reddy, N. Saketh, and D. Vijay Sai, “Design and Development of Pulse Oximeter Using Internet of Things,” ICICCS Conference, 2022. [Online]. Available: ResearchGate [10] K. B. Kim and H. J. Baek, “Photoplethysmography in Wearable Devices,” Electronics, MDPI, 2023
Publication Date
5/8/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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