Data Predictive Model of Thai Air Quality Using Data Visualization Based on National Ambient Air Quality Standards

Abstract

The research objectives are to develop the predictive model with the indicators based on Thai national standard of air quality. The samples are dust particles smaller than 2.5 micron (PM 2.5) which is collected from 1 January 2018 – 31 December 2018. The case study is in the area of Bangkok metropolitan region to analyze amount of dust that can be appalled into the respiratory tract and cause hazard against lives. The research instrument consisted of (1) The predictive model of Thai air quality using data visualization, and (2) The performance evaluation form of predictive model. The findings are the predictive model can create insight data visualization of the dust density occurred over a different period of time. Moreover, some risk areas are indicated a high level of dust particles smaller than 2.5 micron that pollute over the control limit of Ministry of Natural Resources and Environment standard that consequently resulting in organism harm. The benefits of this research can support for dust protection planning for the livings in Thailand.