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This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.
AI-assisted Air Quality Monitor
About this project
Project Description
This model detects air pollution levels (classes) based on ambient nitrogen dioxide concentration, ozone concentration, temperature, humidity, and wind speed:
- Clean
- Risky
- Unhealthy
After building my neural network model, I deployed my model as an Arduino library and uploaded it to FireBeetle ESP32. Also, I employed FireBeetle ESP32 in combination with its media board to capture real-time surveillance footage for further examination and communicate with the web application I developed to display the model detection results.
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Dataset summary
Data collected
3m 15sSensors
no2, ozone, temperature, humidity, wind_speed @ 1HzLabels
Clean, Risky, UnhealthyProject info
| Project ID | 192207 |
| Project version | 1 |
| License | Apache 2.0 |
| No. of views | 32,930 |
| No. of clones | 9 |
