Edge-AI Wearable for Real-Time Health Monitoring, Intelligent Medical Analysis, and Proactive Alert Management

Access to continuous health monitoring remains limited due to high medical infrastructure costs and the restricted capabilities of conventional wearable devices. This work presents an integrated wearable health monitoring system combining on-device processing with cloud-based intelligence. The system is built on an ESP32-S3 platform and incorporates multiple sensors, including MAX30102 for heart rate and SpO?, MLX90614 for non-contact temperature sensing, MPU6050 for motion tracking, and a galvanic skin response sensor for stress detection. A TCA9548A I²C multiplexer ensures reliable communication, while an OLED display provides real-time feedback.The wearable performs local processing using thresholdbased methods to detect anomalies in vital signs and activity patterns, enabling immediate alerts through vibration without requiring network connectivity, thereby ensuring faster response and improved data privacy. Simultaneously, the device connects to a Node.js-based backend using WebSocket communication for real-time data transfer and monitoring. Emergencyalerts are enhanced with location tracking and SMS notifications containing live map links.The system also supports AI-based medical data analysis, allowing users to upload reports such as X-rays or ECGs for structured interpretation and recommendations. A Reactbased interface provides visualization, reminders, and additional services, demonstrating a costeffective and scalable solution for real-time health monitoring.