IoT-Based Mood Monitoring System
A mobile-first solution that leverages IoT sensors to monitor user well-being and promote mental health, with a focus on accessibility for underserved communities.
SentioTrack is developed as part of VHACK 2025, with the goal of building a mobile application that tracks and supports mental health through IoT-based mood monitoring. The system collects real-time physiological data, giving users meaningful insights and actionable recommendations to support their emotional wellness.
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Health Monitoring
- Tracks heart rate variability, step count, and physical activity using real-time sensor data.
- Future enhancements include sleep detection and snore pattern recognition.
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Mood Tracking
- Users can log daily mood and reflect on emotional patterns.
- Future enhancements include AI-generated insights help users understand triggers and trends.
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Environmental Monitoring
- Captures ambient noise, with planned upgrades to detect lighting and air quality.
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AI-Based Recommendations
- Recommends relaxation techniques, mindfulness exercises, and activity suggestions based on live data and user history.
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Social Support Integration
- Encourages communication with trusted contacts, including friends, family, and mental health professionals.
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Privacy & Security
- Implements end-to-end encryption and user-controlled data sharing, prioritizing mental health safety and privacy.
| Component | Description |
|---|---|
| ESP32 | Microcontroller for sensor integration & data transfer |
| MAX30102 | Measures user heart rate in real-time |
| MPU6050 | Tracks movement for step count and future sleep analysis |
| MAX4466 | Captures noise level, supporting mood/environment analysis |
| OLED Display | Displays live sensor data for immediate feedback |
| Firebase | Handles cloud data storage, sync, and user authentication |
| FlutterFlow | Cross-platform app development (Android/iOS) |