An efficient database model for fine dust management and Suggestion of Visualization Techniques

Abstract

Recently, the risk of fine dust (PM10) and ultrafine dust (PM2.5) has been emphasized. In 2016, the World Health Organization reported that more than three million people die early every year due to fine dust. Korea is one of the countries with lower air quality and needs to take measures against increasing fine dust concentrations. The government has provided fine dust concentration data from all regions to solve this problem. On the other hand, it is unclear if the data currently provided reflects the "average" fine dust concentration in each region, and efficient management according to the new database (DB) model is required in the case of vast amounts of data. This study analyzed the concentration of fine dust by region on a monthly average basis. The paper presents a method for managing fine dust data using a new DB model. It also introduces data preprocessing techniques accordingly. Map visualization is performed using preprocessed data, and techniques are introduced. The DB model, fine dust data preprocessing technique, and visualization technique presented in this paper are expected to be useful in providing various fine dust-related services in the future.