Application of Machine Learning Algorithms for Air Quality Prediction

Since becoming one of the leading causes of respiratory illnesses, heart problems and even death, air pollution has been a major concern globally. Various techniques and technologies have been created to monitor and manage air pollution, but deep learning techniques have shown great promise in their ability to accurately predict pollutant concentrations. Machine learning algorithms have been studied and developed recently with the aim of predicting concentrations of airborne contaminants and implementing preventive actions to protect health. The main objective of this article is to perform an analysis of the results of the concentration of CO in the air with R language using the ARIMA model to predict the air quality in the city of Rabat, Morocco.