Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/29818
Author(s): Vital, D.
Mariano, P.
Almeida, S. M.
Santana, P.
Date: 2022
Title: Knowledge-based generation of plausible air quality maps in the absence of sensor data
Journal title: International Journal of Creative Interfaces and Computer Graphics
Volume: 13
Number: 1
Pages: 1 - 17
Reference: Vital, D., Mariano, P., Almeida, S. M., & Santana, P. (2022). Knowledge-based generation of plausible air quality maps in the absence of sensor data. International Journal of Creative Interfaces and Computer Graphics, 13(1), 1-17. https://dx.doi.org/10.4018/IJCICG.311836
ISSN: 1947-3117
DOI (Digital Object Identifier): 10.4018/IJCICG.311836
Keywords: Air pollution
Environmental expert
Graphical tool
Knowledge elicitation
Abstract: Industrialization increased air pollution sources, which is a cause of major health problems. As such, air pollution became a growing concern and there is a need to monitor and easily visualize air pollution data. There are thousands of air quality monitoring stations throughout the world that are used to measure air quality. Moreover, there are plenty of applications that have been developed to visualize air pollution that use information gathered by these air quality monitoring stations as well as other sources of information, such as traffic intensity or weather forecasts. This paper introduces a novel graphical tool that taps on a new source of information: expert knowledge of air pollution sources. This tool allows experts to represent air pollution sources and their dynamics, and to assign them to different map elements. The authors have performed tool's usability and viability tests with 30 participants of which 6 are environmental experts. The obtained results and the provided feedback show that the proposed approach is a promising complement to sensor-based mapping approaches.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica

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