Information System of Air Quality Assessment Using Data Interpolation from Ground Stations
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
CEUR-WS Team, Aachen, Germany
Abstract
ENG: Monitoring ground stations is crucial for creating interactive maps that assist in assessing air quality. A developed information system can aggregate and process the data obtained, which is then transformed into a unified format and used as input data for interpolation methods that create raster imagery. After processing, the data is stored in Amazon Simple Storage Service or database and can be retrieved using application program interfaces (APIs). The proposed architectural solution for creating the system includes a toolkit that can work with different volumes of data with ease. Using Docker during deployment provides additional capabilities for creating a flexible and scalable system. Specific tools such as PostGis and Geospatial Data Abstraction Library (GDAL) simplify the processing of data. For instance, GDAL helps with the interpolation, cropping, and tiling of the air quality raster image. The article describes the structure of the client part and the interface in detail. By using the Mapbox Graphics Library system, the system can easily visualize big data as a vector layer, helping users recognize hazardous zones and find safe places.
Description
B. Molodets: ORCID 0000-0002-7802-389X; Vol. Hnatushenko: ORCID 0000-0003-3140-3788; D. Boldyriev: ORCID 0000-0002-8502-1446; T. Bulana: ORCID 0000-0001-6346-3326
Keywords
information system, air quality monitoring, docker, inverse distance weighting, data visualization, КІТС
Citation
Molodets B., Hnatushenko V., Boldyriev D., Bulana T. Information System of Air Quality Assessment Using Data Interpolation from Ground Stations. CEUR Workshop Proceedings. Vol. 3426 : Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2023), Lviv, Ukraine, June 3, 2023. Lviv, 2023. P. 233–245 DOI: 10.1088/1742-6596/2675/1/012015.