Prediction Of Air Quality Index Affected By Vehicle Emissions Using Machine Learning

Abstract

As a reaction to the increasing population everywhere globally and the rapid process of urbanization, development and manufacturing industries have increased. Growth has, however, increased levels of pollution, thus contributing to vast environmental issues like global warming. Out of all the sources of pollution, car emissions have a crucial role in affecting the condition of the atmosphere, thus making air pollution a primary cause of climate change.

This research tries to examine the effect of vehicle emissions on air pollution in India and forecast the Air Quality Index (AQI) using machine learning methods. This research is interested in learning about the effect of vehicle pollutants on the increase and decrease in AQI. Machine learning algorithms are used to predict AQI from vehicle emissions. Different prediction models are used to compare their efficacy in determining air quality. The research mostly utilizes information regarding vehicle pollution in India and its effect on AQI levels.

The research proves the capability of machine learning to forecast AQI based on vehicle emissions. Varying algorithms yield varying outcomes when it comes to predicting AQI, and this further highlights the importance of data-driven solutions in tracking the environment. Emissions from vehicles are a primary source of air pollution and contribute to significant AQI values. Machine learning methods provide an efficient way to predict AQI, supporting environmental evaluation and decision-making for preventing air pollution impact.