Air Pulse – An Air Quality Status Analysis Model

A global concern is scaling due to the rapid growth of air pollution, particularly the intensified concentration of impurities and pollutants exposing the risk to the health of innumerable species worldwide. Air Pollution is a combination of various gases in the air with the presence of countless solid particles. To protect human life and the deteriorating situation of air quality that is severely affecting the flora and fauna, we aim to design and train a system to predict the quality of the air that surrounds us with the utmost accuracy and reliability. The Air Quality Index (AQI) of India is a standard computation used to specify the extent of impurities (so2, no2, rspm, spm, etc) over an interval. India is impacted severely as it hosts 22 of the world’s 30 extremely populated cities. We have used and contrasted the machine learning algorithms to achieve the prime results. Interjection, feature analysis, and prediction are three major factors in inner-city air computing. Considering this research, multiple processing methods are used to process the data. Our model will have the capacity to predict the status of the air quality in different parts of the Delhi. The model provides almost 85% accuracy by outlining the correct status of the quality of air in different regions of Delhi. This system can be referred to by the Central Pollution Control Board to understand whether the air is safe or unsafe and record the air quality along with the congregation of defiled particles. A user interface will support this model and display the necessary status to the user at their convenience. The user interface will act as a one-stop platform to track and get updates about the air quality of different regions of the national capital, Delhi.