Autism Monitoring System Using IOT and Machine Learning

Abstract

The proposed project, “Autism Monitoring System,” aims to develop an intelligent health monitoring platform designed specifically for individuals with autism to ensure continuous observation of their vital health parameters. The system integrates machine learning algorithms with real-time biomedical data to analyze and predict potential health irregularities. Physiological parameters such as ECG, heartbeat, blood pressure (BP), and SpO₂ levels are collected using various sensors interfaced with an ESP32 microcontroller and Arduino. These sensor readings are transmitted to the ThingSpeak cloud platform, enabling real-time monitoring and remote data accessibility. The backend of the system is developed using Python with the Flask framework, which serves as a bridge between the frontend interface and the hardware data streams. On the software side, an interactive and user-friendly web dashboard is designed using HTML, CSS, and JavaScript, allowing caregivers, doctors, or parents to visualize the monitored parameters dynamically.