A Comparative Analysis of ML Based Approaches for Identifying AQI Level

Monitoring Air Quality Index (AQI) is a significant research concern within the realm of intelligent urban planning and the sustainable development of cities, with a particular focus on enhancing air quality in Asian nations such as India. Over the recent years, the utilization of machine learning (ML) techniques has experienced a substantial surge in popularity for predicting the AQI. The primary goal of this work is to assess the air quality levels of four metropolitan cities: Ahmedabad, Bengaluru, Chennai, and Delhi, using various ML models and a comparative analysis of the models’ performance is also done. The AQI data for the four metropolitan cities mentioned are collected from CPCB website. Several preprocessing strategies are employed to control the data before it is fed into the classification models. The outcomes of the utilized models are represented in respect of F1-score, recall, precision and accuracy.