Robust Predictive Model to Forecast Air Quality Index Level

The research on air quality index (AQI) prediction in India utilizing machine learning models, particularly the SARIMAX model, highlights the significance of advanced modeling techniques for accurate AQI forecasting. The study incorporates artificial intelligence in AQI prediction based on air pollution data from major Indian cities like Delhi. The dataset used includes attributes like PM 2.5, PM 10, NO, NO2, CO, SO2, O3, and more, with AQI categorized into six levels from good to severe. The research emphasizes the need for comprehensive assessments in urban areas, addressing computational complexities, and integrating real-time data for enhanced forecasting. Various machine learning algorithms like RF, ANN, SVM, and NN have been employed by researchers to predict AQI, with the SARIMAX model being utilized for AQI prediction in cities like Ahmedabad. The study underscores the critical role of accurate AQI prediction in combating air pollution and its adverse effects on public health and the environment in India.