Air Pollution Prediction Using Regression Models

Air is the most important natural resource for people, animals, and plants to survive on this world. Fuel combustion, exhaust emissions from factories and industries, and mining operations all contribute to air pollution surpassing all other forms of pollution as the deadliest threat humanity has ever faced. This has a variety of health consequences for people, as well as consequences for plants and animals' ability to thrive. As a result, air quality forecasting and evaluation are becoming more essential study topics. For air quality forecasting, a machine learning-based prediction model is developed in this study. This model will assist us in identifying the principal pollutant present in the area, as well as the causes and sources of that pollutant. The value of India's Air Quality Index is used to forecast air quality. The information is gathered from various locations across India and then preprocessed to remove null values, missing values, and duplicate entries. Various machine learning methods are used to train and test the dataset.