Applying artificial intelligence to improve air pollution

Mohammadreza Moradi¹ Sima Rastegar² Arian Esmaili³ Mohammad Taha Hassanpour⁴ Radmehr Kiani⁵

1) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
2) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
3) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
4) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
5) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran

Publication : 3rd International Conference on Recent Advances in Engineering, Innovation and Technology - Belgium(eitconf.com/3rd)
Abstract :
Air pollution is one of the major environmental challenges that has negative impacts on public health and ecosystems. Traditional air quality monitoring methods, although useful, have limitations such as high cost, limited geographical coverage, and data delay. In this regard, artificial intelligence (AI) has been introduced as an efficient tool for predicting, monitoring, and controlling air pollution. Machine learning and deep learning algorithms can analyze environmental sensor data, satellite images, and meteorological information and provide accurate models for predicting air quality. In addition, AI-based warning systems can provide timely information about increasing pollution and help make better decisions on pollution control policies. This article reviews various applications of AI in monitoring, predicting, and reducing air pollution and discusses the advantages of this technology compared to traditional methods. It has a negative impact on human health and ecosystems. With the advancement of technology, artificial intelligence (AI) has emerged as a new tool for monitoring, predicting, and controlling air pollution. Machine learning algorithms can predict changes in air quality and provide necessary warnings by analyzing data from environmental sensors. In addition, AI-based models can identify the main sources of pollutants and suggest optimization of emission reduction strategies. In this paper, the role of AI in improving air quality through forecasting models, warning systems, and optimization of pollution reduction strategies is examined.
Keywords : artificial intelligence air pollution machine learning air quality prediction environmental modeling remote sensing