Mining users mobility at public transportation

Detalhes bibliográficos
Autor(a) principal: Baeta, N.
Data de Publicação: 2017
Outros Autores: Fernandes, A., Ferreira, J.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/15901
Resumo: In this research work we propose a new approach to estimate the number of passengers in a public transportation and determinate the users’ route path based on a passive approach without user intervention. The method is based on the probe requests of users mobile device through the collected data in wireless access point. This data is manipulated to extract the information about the numbers of users with mobile devices and track their route path and time. This data can be manipulated to extract useful knowledge related with users’ habits at public transportation and extract user mobility patterns.
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spelling Mining users mobility at public transportationWi-fiMobile deviceTrackingGPSArtificial intelligentKnowledgeIn this research work we propose a new approach to estimate the number of passengers in a public transportation and determinate the users’ route path based on a passive approach without user intervention. The method is based on the probe requests of users mobile device through the collected data in wireless access point. This data is manipulated to extract the information about the numbers of users with mobile devices and track their route path and time. This data can be manipulated to extract useful knowledge related with users’ habits at public transportation and extract user mobility patterns.Asociacion Espanola de Inteligencia Artificial2018-05-24T15:36:53Z2017-01-01T00:00:00Z20172019-04-05T15:03:05Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/15901eng1137-360110.4114/intartif.vol20iss59pp32-41Baeta, N.Fernandes, A.Ferreira, J.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:RCAAP2023-11-09T17:54:31Zoai:repositorio.iscte-iul.pt:10071/15901Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:27:32.702577Repositório 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 Mining users mobility at public transportation
title Mining users mobility at public transportation
spellingShingle Mining users mobility at public transportation
Baeta, N.
Wi-fi
Mobile device
Tracking
GPS
Artificial intelligent
Knowledge
title_short Mining users mobility at public transportation
title_full Mining users mobility at public transportation
title_fullStr Mining users mobility at public transportation
title_full_unstemmed Mining users mobility at public transportation
title_sort Mining users mobility at public transportation
author Baeta, N.
author_facet Baeta, N.
Fernandes, A.
Ferreira, J.
author_role author
author2 Fernandes, A.
Ferreira, J.
author2_role author
author
dc.contributor.author.fl_str_mv Baeta, N.
Fernandes, A.
Ferreira, J.
dc.subject.por.fl_str_mv Wi-fi
Mobile device
Tracking
GPS
Artificial intelligent
Knowledge
topic Wi-fi
Mobile device
Tracking
GPS
Artificial intelligent
Knowledge
description In this research work we propose a new approach to estimate the number of passengers in a public transportation and determinate the users’ route path based on a passive approach without user intervention. The method is based on the probe requests of users mobile device through the collected data in wireless access point. This data is manipulated to extract the information about the numbers of users with mobile devices and track their route path and time. This data can be manipulated to extract useful knowledge related with users’ habits at public transportation and extract user mobility patterns.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01T00:00:00Z
2017
2018-05-24T15:36:53Z
2019-04-05T15:03:05Z
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/10071/15901
url http://hdl.handle.net/10071/15901
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1137-3601
10.4114/intartif.vol20iss59pp32-41
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 Asociacion Espanola de Inteligencia Artificial
publisher.none.fl_str_mv Asociacion Espanola de Inteligencia Artificial
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
repository.mail.fl_str_mv
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