Abstract:
Air pollution is a great area of concern all across the world, involving life and the
environment as a whole. All these areas of concern that regard life, the environment,
health, and other different ecosystems need to have the problem addressed. In recent
years, air pollution has become a matter of growing concern all over the world with its
possible impacts on human health and the environment. In the last few years, the
interest has been growing in the engineering of solutions for the prediction of air
pollution levels. Their main intention will be to raise the alerts and to help early
implementation of preventive strategies in reducing the impacts of the pollutant. The
paper goes on to bring in the development of an air pollution prediction system and its
probable advantage in mitigating the new challenges brought by pollution. This paper
is going to introduce how advanced machine learning models are used for accurate
prediction and reporting of air pollution levels. This type of prediction system could
even be more helpful in offering assessed valuable data about the level of air pollution.
Therefore, this prediction system will form yet another among the many tools that will
be of importance in the development of environmental sustainability, protection of
public health, and work on a data-driven approach toward the management of each
type. It will greatly help to upgrade the quality of life in all these areas and even wider
