AI-Based System for Heart Rate and Body Temperature Monitoring

Continuous monitoring of physiological indicators such as heart rate and body temperature is essential for early disease detection and effective health management. However, existing health monitoring systems often lack real-time data analysis and robust Artificial intelligence (AI) integration for timely identification of health risks. This paper addresses these limitations by developing an AI-based health monitoring system with the objective of providing accurate and real-time tracking and analysis of heart rate and body temperature. The system integrates ESP32 microcontrollers, a DS18B20 temperature sensor, and an AD8232 ECG module to acquire physiological data, which is transmitted wirelessly for AI-driven analysis. Processed data and results are displayed on a TFT screen, allowing users to receive immediate feedback and facilitating proactive healthcare management. The research objectives include improving measurement accuracy, real-time processing, and seamless system integration. The project utilized software tools such as Arduino IDE, EasyEDA, and VS Code for hardware programming, circuit design, simulation, and server integration. Simulation and hardware testing validated the system’s performance, confirming reliable data capture, processing, and real-time visualization. The integration of AI enhances early detection of abnormal health trends, contributing to more effective preventive healthcare. Future enhancements will focus on expanding sensor capabilities, refining AI analytics, and supporting remote access for broader healthcare applications.