Mehfooz08/AQI_Predictor

🌍 AQI Predictor

A machine learning model that predicts the Air Quality Index (AQI) using pollutant measurements.

The model was trained using air-quality data and uses four pollutant features:

• PM2.5
• PM10
• Carbon Monoxide (CO)
• Nitrogen Oxides (NO)

The trained model is saved as a Python .pkl file using scikit-learn.

🤖 Model

Algorithm: Random Forest Regressor

Task: AQI Regression

Input Features:

Feature	Description
PM2.5	Fine particulate matter
PM10	Particulate matter
CO	Carbon monoxide
NO	Nitrogen oxide

Output:

Predicted AQI value.

📊 Model Performance

The model achieved approximately:

• R²: 0.89
• RMSE: ~22

Performance was evaluated on the project dataset. Results may vary depending on the data split and preprocessing procedure.

🔄 Prediction Pipeline

Pollutant Measurements
        ↓
PM2.5 | PM10 | CO | NO
        ↓
Trained Random Forest Model
        ↓
Predicted AQI