This project integrates air quality monitoring using an ESP32 sensor with a real-time mask detection application using a webcam, OpenCV, and deep learning. The system also provides visual and audio alerts based on environmental conditions and mask compliance.
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ESP32 Sensor Monitoring:
- Measures temperature and humidity using DHT11 sensor.
- Measures air pollution level using MQ135 sensor.
- Sends sensor data periodically to a Flask backend API.
- Controls an LED indicator based on environmental thresholds.
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Real-Time Mask Detection:
- Uses webcam for live video streaming.
- Detects faces and predicts mask usage with a MobileNetV2-based model.
- Combines sensor data with mask detection results.
- Provides audio and visual alerts if masks are not worn when pollution or temperature is unsafe.
- User interface built with Streamlit for easy monitoring and control.
- Temperature: 23°C to 35°C
- Humidity: 50% to 88%
- Air Quality Index (from MQ135): Good if below 50 If any sensor reading is out of the ideal range, the LED on the ESP32 blinks, and alerts are shown in the app.
- Python 3.x
- TensorFlow / Keras
- OpenCV
- Streamlit
- Flask
- requests
- playsound
- imutils
Just let me know if you want it saved as a file or if you want me to add or modify anything!