Air Quality Index Forecasting for Assessing the Status of Air Quality Using Ann & Lstm Neural network

Abstract

As the impact of air pollutants is increasing drastically on living beings in recent years, it has become very necessary to address the issue of air pollution control by scientists and environmental lists. To ensure the same, it is important to forecast air quality in terms of parameters that cause air pollution directly or indirectly, which generally affects the living population. Environmental Protection Agency (USEPA) has suggested a method to estimate air quality index in a region which constitutes different concentration of criteria air pollutants such as RSPM, SO2, NO2, and SPM. The motive of our research is to model a predicting model for forecasting daily AQI that can be put to use for local and regional air quality management.