Knowledge-based generation of plausible air quality maps in the absence of sensor data
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/29818 |
Resumo: | 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. |
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Knowledge-based generation of plausible air quality maps in the absence of sensor dataAir pollutionEnvironmental expertGraphical toolKnowledge elicitationIndustrialization 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.IGI Global2023-11-28T10:45:18Z2022-01-01T00:00:00Z20222023-11-28T10:44:50Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/29818eng1947-311710.4018/IJCICG.311836Vital, D.Mariano, P.Almeida, S. M.Santana, P.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-03T01:19:21Zoai:repositorio.iscte-iul.pt:10071/29818Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:40:44.250795Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Knowledge-based generation of plausible air quality maps in the absence of sensor data |
title |
Knowledge-based generation of plausible air quality maps in the absence of sensor data |
spellingShingle |
Knowledge-based generation of plausible air quality maps in the absence of sensor data Vital, D. Air pollution Environmental expert Graphical tool Knowledge elicitation |
title_short |
Knowledge-based generation of plausible air quality maps in the absence of sensor data |
title_full |
Knowledge-based generation of plausible air quality maps in the absence of sensor data |
title_fullStr |
Knowledge-based generation of plausible air quality maps in the absence of sensor data |
title_full_unstemmed |
Knowledge-based generation of plausible air quality maps in the absence of sensor data |
title_sort |
Knowledge-based generation of plausible air quality maps in the absence of sensor data |
author |
Vital, D. |
author_facet |
Vital, D. Mariano, P. Almeida, S. M. Santana, P. |
author_role |
author |
author2 |
Mariano, P. Almeida, S. M. Santana, P. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Vital, D. Mariano, P. Almeida, S. M. Santana, P. |
dc.subject.por.fl_str_mv |
Air pollution Environmental expert Graphical tool Knowledge elicitation |
topic |
Air pollution Environmental expert Graphical tool Knowledge elicitation |
description |
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. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01T00:00:00Z 2022 2023-11-28T10:45:18Z 2023-11-28T10:44:50Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/29818 |
url |
http://hdl.handle.net/10071/29818 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1947-3117 10.4018/IJCICG.311836 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
IGI Global |
publisher.none.fl_str_mv |
IGI Global |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799136312104583168 |