In recent years, there have been substantial breakthroughs in the prediction and analysis of air quality. Previously, our dependence was significant on conventional approaches such as statistical models and simple equations. Nevertheless, these methodologies encountered difficulties in comprehending the intricate and ever-changing characteristics of air pollution. With the advancement of technology, scientists and researchers have utilized AI, machine learning, and big data analytics to enhance air quality predictions.