• Ms. Jyoti Sachin Kamble
• Mrs. Neeta R. Kadam
• Dr. Manisha P. Hajare

The advancement of Internet of Things (IoT) technologies has enabled real-time health monitoring systems to become more efficient and accessible. This paper presents a low-cost, real-time Electrocardiogram (ECG) data monitoring and analysis system using the ESP32 microcontroller and AWS Cloud services. An AD8232 ECG sensor is interfaced with the ESP32 to capture raw ECG signals from the human body. The data is transmitted wirelessly to AWS IoT Core over Wi-Fi, where it is processed and stored. AWS Lambda functions are used to route the data to AWS SageMaker, which hosts a pre-trained machine learning model for signal classification and anomaly detection. The results are visualized through a cloud-based dashboard, enabling remote monitoring of cardiac health. This system demonstrates an effective integration of embedded systems and cloud computing for remote patient care and health diagnostics. The implementation is scalable, energy-efficient, and can be extended to other biomedical signals in the future.

ECG Monitoring, ESP32, AWS IoT Core, Machine Learning.

"Real-Time ECG Signal Monitoring and Cloud-Based Analysis Using ESP32 and AWS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.n449-n452, April-2025, Available :http://www.jetir.org/papers/JETIR2504D55.pdf

"Real-Time ECG Signal Monitoring and Cloud-Based Analysis Using ESP32 and AWS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppn449-n452, April-2025, Available at : http://www.jetir.org/papers/JETIR2504D55.pdf