A new model of air quality prediction using lightweight machine learning

Abstract

Air pollution has become one of the environmental concerns in recent years due to its harmful threats to human health. To inform people about the air quality in their living areas, it is essential to measure the extent of pollution in the atmosphere. Air pollution sensors are assembled at static, fixed-site measurement monitoring stations to acquire data. The data can be processed at the fixed stations or transmitted to the server to predict the Air Quality Index (AQI). Some previous studies applied machine learning algorithms to predict the AQI. Even though those works showed good performance on specific data, the results are not consistent on different datasets