Smart Health Monitoring System Using IoT and Deep Learning

A real-time wearable sensor kit designed to monitor vital signs like heart rate, SpO₂, and body temperature. Integrated with a Raspberry Pi or ESP32, the system uses LSTM or CNN-based deep learning models to detect abnormal health events. Alerts and visualizations are managed through a cloud-based dashboard, providing real-time insights for proactive healthcare.

What You’ll Receive with This Project Kit:

All Essential Project Components:
Includes high-quality sensors and hardware for heart rate, SpO₂, and temperature, along with Raspberry Pi or ESP32 modules and cloud integration parts.

Fully Functional Source Code:
Optimized Python/Arduino code with ML model integration and cloud sync features. Ready-to-run with structured documentation.

Step-by-Step Working Methods:
Comprehensive user manual with connection diagrams, setup steps, model training instructions, and troubleshooting guidelines.

100-Page Detailed Project Report (PDF):
Professionally written report with introduction, literature survey, system design, model explanation, results, graphs, screenshots, and enhancement ideas—viva-ready!