Unveiling Hidden Air Quality Patterns: A Data-Driven Predictive Regression Analysis for Sustainable Air Management

The importance of Machine Learning in predicting Air Quality Index (AQI) is increasing day by day. This aids in informed health protection decisions amid air pollution's impacts. The factors that affect air quality and the machine learning model parameters that yield good prediction accuracy are not well covered in the existing literature. This study provides a comprehensive comparison analysis that estimates air quality using multiple regression models. To forecast the Air Quality Index, we utilize data from two distinct places in Chennai City. Manali, an industrial area, and Velachery, a residential suburb, are the two. For the purpose of assisting us or the government authorities in making decisions, the study also focuses on the factors that influence air quality. The main goal is to determine which model performs best by evaluating a variety of factors, including R2 measurements and Mean Absolute Error.