Automated Prediction of Air Pollution Conditions in Environment Monitoring Systems

This paper aims to explore the problem of air pollution forecasting, especially the particulate matter (PM) concentration in the air. Other quantities such as air temperature, atmospheric pressure, and relative humidity are also considered. Moreover, a large part of the discussion in this paper can be extended and applied to a variety of other quantities which are stored and expressed as data series. The goal is to evaluate different time series forecasting models on a selected air pollution data set. The proposed model is compared with other implemented state-of-the-art methods in order to validate whether it could be a reliable pick for air pollution forecasting problem.