A PM2.5 Forewarning Algorithm Using k-Nearest Neighbors Machine Learning at Changpuek, Chiang Mai, Thailand

Abstract

In Chiang Mai, Thailand, the air pollution issue caused by atmospheric particulate matter with a diameter of less than 2.5 μm, or PM2.5, has been identified as an ongoing crisis. PM2.5 not only has a direct impact on people's health and way of life, but it also has a negative impact on the national economy. Residents in such PM2.5-polluted locations are particularly susceptible to respiratory diseases, skin diseases, inflammatory eye diseases, and cardiovascular problems. As a result, this study is going to analyze PM2.5 data using the k-nearest neighbors machine learning algorithm as a guideline to warn people, particularly in Changpuek, Chiang Mai, Thailand, to handle the PM2.5 characterization problem.