Air Quality Prediction using Machine Learning for Environmental Health

This project aims to predict air quality conditions using machine learning to improve public health responses. The system predicts concentrations of particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), and ozone levels based on weather data, helping health organizations issue warnings and provide advice to the public when air quality deteriorates.