AIR QUALITY INDEX MONITORING AND PREDICTION

This study presents a Flask-based web application designed to deliver real-time and forecasted air quality information using OpenWeatherMap APIs.The system retrieves and analyzes Air Quality Index (AQI) data, pollutant levels, and weather conditions for any user-specified city.The application uses geolocation to obtain coordinates, fetches current pollution and weather data, and interprets AQI values into qualitative health categories.A basic predictive model adjusts AQI based on environmental factors such as wind speed and humidity to anticipate near-future air quality conditions.The system returns structured JSON data for developers and displays key insights through a user-friendly interface.Designed with a modular architecture, this application enables scalability and easy integration of advanced predictive models.The results demonstrate a functional, lightweight platform capable of supporting informed environmental decisions, particularly for health-sensitive populations.Future enhancements may incorporate machine learning for more accurate AQI forecasting.