PREDICTION OF AIR POLLUTION BY USING MACHINE LEARNING
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Abstract
Defensive and in charge Nowadays, in many developing and urban areas, the greater air quality has become one of the most important factors in everything. The magnificence of the air is negatively affecting collectibles due to the many tainting methods caused by power consumption, transportation, and other factors. Population growth is a major issue in our nation as it is happening at a rapid pace. This, along with economic expansion, is causing environmental issues in cities, such as water and air pollution. in a portion of the air.
Air pollution and pollutants have a direct effect on human health. As is well known, the main sources of pollution include carbon monoxide, nitrogen oxide, particulate matter (PM), so2; etc. A propellant such as gasoline, petroleum, etc. that has not been properly oxidized is producing carbon monoxide. The burning of thermal fuel releases nitrogen oxide (NO), but sulfur dioxide (So2), one of the main air pollutants, is more prevalent and has a greater impact on human health. Multidimensional collisions with location, time, and imprecise boundaries augment the air's dominance. To examine AI-based approaches for air quality prediction is the aim of this enhancement. In this research, we will use a machine learning system to forecast air pollution.
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