MediSense: Intelligent IoT Based Health Monitoring System for Personalized Care

Abstract

This research project addresses the pressing need for the development of advanced health monitoring systems capable of providing real-time and accurate tracking of vital signs. The primary objective is to design and implement a comprehensive solution that effectively monitors key health parameters such as heart rate, blood oxygen saturation, and body temperature. This project utilizes cutting-edge sensor technology, including the MAX30105 Pulse Oximeter and the MLX90614 Temperature Sensor, integrated with the powerful ESP32 Wroom32s microcontroller. The central focus lies in creating a robust system architecture that seamlessly integrates multiple sensors, ensuring reliable data collection under various conditions. The design process involves meticulous attention to detail in establishing optimal sensor placement, calibration procedures, and signal processing techniques to enhance measurement accuracy. Moreover, the project emphasizes the development of efficient data processing algorithms, leveraging the computational capabilities of the ESP32 microcontroller to analyze sensor data in realtime. Additionally, machine learning algorithms are implemented to detect patterns and anomalies in vital signs, enabling proactive intervention and timely alerts to users or caregivers. The findings of this research highlight the successful implementation of the health monitoring system, demonstrating its effectiveness in providing actionable insights into the user's health status. Through rigorous testing and validation, the system proves to be a valuable tool for early detection of health issues, facilitating personalized healthcare interventions, and ultimately promoting improved health outcomes for individuals.