Surveillance médicale connectée basée sur ESP32 et application mobile pour le suivi des personnes âgées

Abstract

This thesis presents the study, design, and implementation of an IoT-based medical monitoring system mainly designed for elderly people. With the aging population and the increasing prevalence of chronic diseases, remote monitoring solutions provide an innovative response to improve patient quality of life while reducing the burden on healthcare facilities. After analysing the state of the art of existing systems and IoT technologies applied to healthcare, a customized architecture was designed integrating an ESP32 board as the central processing unit, biomedical sensors (DS18B20 for temperature, MAX30102 for heart rate and SpO2, MPU6050 for fall detection, and NEO-6M for geolocation), along with a mobile application developed with the Flutter framework for data visualization and alert management. The implemented prototype demonstrates the feasibility of a reliable and accessible telemonitoring system, while highlighting some limitations related to energy consumption, data security, and validation in real environments. This work paves the way for future perspectives such as the integration of artificial intelligence for proactive anomaly detection, the optimization of processing algorithms, and the enhancement of communication security.