Kutluhan Aktar / AI-assisted Air Quality Monitor
This is your Edge Impulse project. From here you acquire new training data, design impulses and train models.
About this project
This model detects air pollution levels (classes) based on ambient nitrogen dioxide concentration, ozone concentration, temperature, humidity, and wind speed:
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.