• Himanshu Sinha

An indicator of the air's condition, an air quality index (AQI) is a metric. It evaluates an air pollution's immediate health effects. The combustion of fossil fuels (like Wood, coal and natural gas), as well as industrial processes and automobile emissions, are major contributors to air pollution. Among the many air pollutants are NO, CO, and CO2. Air pollution is a leading source of serious health problems, including cancer of the lungs and brain, and in extreme cases, death. After calculate an AQI, machine learning methods are useful. The AQI's mission is to inform people about the dangers of breathing polluted air in their area. The study summarises the, including its main points. This study delves into a growing issue of air pollution and a crucial need for efficient air quality monitoring and evaluation, with a focus on cities that are undergoing fast industrialisation and population expansions. The research delves into several methods for forecasting air quality using machine learning algorithms, taking into account aspects like pollution concentrations, spatio-temporal dynamics, and the effects on both human and environmental health. The paper summarises previous research on methods for predicting air quality, with an emphasis on statistical approaches and basic machine-learning models.

Air pollution, Air quality prediction, machine learning

"A Comprehensive Study on Air Quality Detection Using ML Algorithms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 9, page no.b116-b122, September-2024, Available :http://www.jetir.org/papers/JETIR2409115.pdf

"A Comprehensive Study on Air Quality Detection Using ML Algorithms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 9, page no. ppb116-b122, September-2024, Available at : http://www.jetir.org/papers/JETIR2409115.pdf