A Literature Review of Air Quality Detection using Neural Networks

The escalation of the social economy and urbanization, along with the rapid growth of industrialization, has worsened the issue of ambient air pollution. Air pollution has detrimental effects on public health in both developing and developed countries. Air quality predictors are necessary to control human activities in a particular geographical area and reduce pollution’s harmful impacts. A new deep learning technique that combines neural networks can be used for detecting anomalies in air quality data. Numerous neural network models can be employed for air quality prediction. This review concentrates on earlier research works by various authors who have utilized neural networks in detecting air quality