Kutluhan Aktar / AI-assisted Air Quality Monitor Public

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.

home_3.jpg

Unhealthy.training.sample_18
Clean.training.sample_4
Unhealthy.training.sample_46
Risky.training.sample_44
Unhealthy.training.sample_44
Risky.training.sample_11
Clean.training.sample_24
Risky.training.sample_27

Run this model

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Dataset summary

Data collected
3m 15s
Sensors
no2, ozone, temperature, humidity, wind_speed @ 1Hz
Labels
Clean, Risky, Unhealthy

Project info

Project ID 192207
Project version 1
License Apache 2.0
No. of views 31,421
No. of clones 9