# Tunisia Air Quality Predictor
A web-based tool to predict the Air Quality Index (AQI) across Tunisia using a machine learning regression model trained on environmental and meteorological data.
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## Overview
Tunisia Air Quality Predictor is a React application that allows users to estimate air quality based on input parameters such as particulate matter concentration (PM1), temperature, humidity, and time of day.
The app connects to a regression-based machine learning model hosted on Hugging Face Spaces, which outputs a predicted AQI value and corresponding air quality category.
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## Features
- Predicts Tunisia’s Air Quality Index (AQI) using environmental factors.
- Interactive and responsive interface built with React and Tailwind CSS.
- Provides visual AQI category feedback (Good, Moderate, Unhealthy, etc.).
- Includes dynamic gradients and smooth animations for better user experience.
- Input validation and error handling for missing fields or connection issues.
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## The Machine Learning Model
The model behind this application is a regression-based predictive model trained on Tunisian air quality and weather data.
It estimates AQI from several input variables:
| Feature | Description |
|----------|-------------|
| pm1 | Particulate matter (PM1) concentration (µg/m³) |
| relativehumidity | Relative humidity (%) |
| temperature | Ambient temperature (°C) |
| hour | Hour of the day (0–23) |
| month | Month of the year (1–12) |
| dayofweek | Day of the week (0–6) |
**Example API Response:**
```json
{
"predicted_aqi": 42.6,
"category": "Moderate"
}