A Deep Learning-Based Prediction and Simulator of Harmful Air Pollutants: A Case from the Philippines
Lloyd H. Macatangay, Rowell Hernandez
Abstract
Harmful air pollution threatens the life of many people due to massive industrialization. Life expectancy, as we know it, is affected due to unmindfully inhaling polluted air in our surrounding environment. This study aims to predict AQI health-level-of-concern using the recorded Total Suspended Particulate (TSP), Sulfur dioxide (SO2), and Nitrogen dioxide (NO2) that used to calculate Air Quality Index (AQI) by employing Deep Neural Network. The model used in the study shows a remarkable result in accuracy when predicting the AQI health category. The air pollutant simulator can be used as a baseline for decision making and policy-driven objectives in monitoring and preventing air pollution in the different areas in Region IV-A, especially in the Province of Batangas.