• Z. syed ijaz ahamed
• Abdus shakoor. H. H
• Mohammed thahir. A

ABSTRACT Air pollution is contamination of the indoor or outdoor environment by any chemical, physical or biological agent that modifies the natural characteristics of the atmosphere. The foremost cause of air pollution is of two types, one is natural pollution by means of volcanoes, wildfire and wind-blown dust. The other one is of artificial pollution by humans such as burning woods, trashes, excess usages of fossil fuels and industrial emissions which can be reduce by taking certain measures. In order to maintain and reduce the causes, one should measure and monitor the gases and make the people aware of the cause and explain the changes in climate which increase global warming. Air pollution can also cause of acid rain with exchange of sulfuric or nitric acid that fall to the ground from the atmosphere in wet or dry forms. It is important to first be able to identify whether a site is contaminated before determining a solution. This project explores the classification of Air samples at a particular site (Bangalore) to investigate the natural or unnatural contamination of Air. The samples are addressed using Decision tree learning, Random forests, Support vector machines (SVMS), Auto-regressive integrated moving average (ARIMA), Long short-term memory (LSTM), Artificial Neural Networks (ANN) Algorithm. From these evaluations, contamination at the site of interest can be considered. The final prediction is viewed in application developed under Django using Python.

Air quality index prediction

"Air Quality index prediction using machine learning and deep learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.g340-g350, July-2023, Available :http://www.jetir.org/papers/JETIR2307652.pdf

"Air Quality index prediction using machine learning and deep learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppg340-g350, July-2023, Available at : http://www.jetir.org/papers/JETIR2307652.pdf