Cities Mobility Management: Mobility prediction model applied to Lisbon marathons

Detalhes bibliográficos
Autor(a) principal: Domingues, Fábio Miguel
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/124338
Resumo: Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
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spelling Cities Mobility Management: Mobility prediction model applied to Lisbon marathonsSmart mobilitySmart CitiesSmart event planningCitizen’s life qualityMassive mobilityProject Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceLisbon, as Portugal capital, is a city that receives a vast number of events every year. These enormous concentrations of people, in the same place, at the same time, requires huge transport services planning and organization. To elevate Lisbon to a state of what is called smart city, smart mobility topic must be improved, in a serious way. To achieve this, Lisbon must be able to stop being reactive and start being proactive. Predicting people’s behavior, concerning to the theme “mobility” is something that can improve drastically population’s life quality. With this study, it is intended to have a better and specific understanding of how CARRIS public transport service is managed in Lisbon, during city’s marathons. The main objective is to implement smarter mobility strategies, during big events, analyze people behavior before, during and after these events and try to predict future population behavior, based on data. CARRIS and other related sources provided data that was integrated into a database system in an automated way. Above this database system a machine learning prediction model was put in place revealing that it is possible to forecast at least 75% of the attendance on this type of transports. This project will end with Power BI self-explanatory reports that can help decision making. By having a better understanding of all problems related to smart mobility during big events, Lisbon may predict and act accordingly. By improving smart mobility, the city is improving life quality, as well.Neto, Miguel de Castro Simões FerreiraSarmento, Pedro Alexandre ReisNascimento, Marcel Motta doRUNDomingues, Fábio Miguel2021-09-10T09:44:31Z2021-07-202021-07-20T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/124338TID:202763579enginfo: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:RCAAP2024-03-11T05:05:48Zoai:run.unl.pt:10362/124338Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:45:28.715645Repositório 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 Cities Mobility Management: Mobility prediction model applied to Lisbon marathons
title Cities Mobility Management: Mobility prediction model applied to Lisbon marathons
spellingShingle Cities Mobility Management: Mobility prediction model applied to Lisbon marathons
Domingues, Fábio Miguel
Smart mobility
Smart Cities
Smart event planning
Citizen’s life quality
Massive mobility
title_short Cities Mobility Management: Mobility prediction model applied to Lisbon marathons
title_full Cities Mobility Management: Mobility prediction model applied to Lisbon marathons
title_fullStr Cities Mobility Management: Mobility prediction model applied to Lisbon marathons
title_full_unstemmed Cities Mobility Management: Mobility prediction model applied to Lisbon marathons
title_sort Cities Mobility Management: Mobility prediction model applied to Lisbon marathons
author Domingues, Fábio Miguel
author_facet Domingues, Fábio Miguel
author_role author
dc.contributor.none.fl_str_mv Neto, Miguel de Castro Simões Ferreira
Sarmento, Pedro Alexandre Reis
Nascimento, Marcel Motta do
RUN
dc.contributor.author.fl_str_mv Domingues, Fábio Miguel
dc.subject.por.fl_str_mv Smart mobility
Smart Cities
Smart event planning
Citizen’s life quality
Massive mobility
topic Smart mobility
Smart Cities
Smart event planning
Citizen’s life quality
Massive mobility
description Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
publishDate 2021
dc.date.none.fl_str_mv 2021-09-10T09:44:31Z
2021-07-20
2021-07-20T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/124338
TID:202763579
url http://hdl.handle.net/10362/124338
identifier_str_mv TID:202763579
dc.language.iso.fl_str_mv eng
language eng
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eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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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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