Utilization of artificial intelligence techniques in predicting air quality index

Abstract

The air quality index (AQI) serves as a standardized metric that condenses complex information regarding various air pollutants into a single numerical value to provide a clear understanding of current air quality conditions in a particular region. Given divergent factors affecting the AQI, advanced techniques have recently been proposed by the research community. Hence, this research provides insights regarding the use of one of the emerging approaches, namely data-driven applications reinforced with explainable artificial intelligence, to predict AQI values under various criteria, including pollutant concentrations and meteorological variables. Future research directions, such as integration of deep learning algorithms, meta-heuristic optimization rationale, and spatiotemporal evaluations, for accomplishing holistic analysis using such promising techniques are also provided within this study.