Air Quality Index Prediction using Machine Learning

Air Quality Index Prediction using Machine Learning

Harsh Jaiswal1, Aman Singh2, Akhilesh Chauhan3

1Harsh Jaiswal CSE department ITM Gida Gorakhpur

2Aman Singh CSE department ITM Gida Gorakhpur

3Akhilesh Chauhan CSE department ITM Gida Gorakhpur

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Abstract - This paper presents an approach of employing Machine Learning for Air Quality prediction by utilizing input like temperature and wind speed. Supervised Machine Learning strategies are implemented through Random Forest Regressor algorithms to achieve more accurate output.

The AQI of a particular area is a measure of pollutants mixed in air of the respected region. As per the air quality standard pollutants are indexed in terms of their scale, these air quality indexes indicates the levels of major pollutants mixed in the atmosphere. Today, major cities experience levels of air pollution that are dangerously higher than the government-set air quality index standard. It significantly affects a person's health. The Machine Learning (ML) algorithms are capable of making predictions about air pollution. We are here to check the air quality index of a particular area to find air pollution level in that area.

Key Words:  Machine Learning, Air Quality Index, Random Forest Regressor.