Kutluhan Aktar / AI-assisted Air Quality Monitor Public

Kutluhan Aktar / AI-assisted Air Quality Monitor

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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.


Download block output

Title Type Size
CSV Wizard config JSON file 345 Bytes
Raw data training data NPY file 150 windows
Raw data training labels NPY file 150 windows
Raw data testing data NPY file 45 windows
Raw data testing labels NPY file 45 windows
Classifier model TensorFlow Lite (float32) 3 KB
Classifier model TensorFlow Lite (int8 quantized) 2 KB
Classifier model TensorFlow SavedModel 9 KB
Classifier model Keras h5 model 3 KB

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Data collected
3m 15s

Project info

Project ID 192207
Project version 1
License Apache 2.0