Enhanced Ai-Driven Raspberry Pi–Based -Embedded System For Health Monitoring

Abstract

The Enhanced AI-Driven Raspberry Pi-Based Embedded Health Monitoring System is expected to solve the increasing demand of continuous health monitoring, particularly to individuals with chronic illnesses or limited access to healthcare services. The proposed project is an inexpensive yet effective health monitoring system based on Raspberry Pi and AI to measure such vital health parameters as heart rate, temperature, and SpO2. The system combines the sensors and real-time data processing with Raspberry Pi, which does not require constant cloud reliance. The AI methods categorize the health conditions as normal, warning, and critical and notify the user in case of abnormal readings. The low cost of the system, combined with the popularity of sensors and the flexibility of Raspberry Pi, makes it practical to use in education and small-scale healthcare. This study highlights the importance of the incorporation of AI into embedded health monitoring systems, its potential, and its limitations. This project will start with conceptual planning and then hardware and software integration to ensure it develops a working prototype that can be used to improve real-time health monitoring and early disease detection.