Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/31711
Autoria: Leal, D.
Albuquerque, V.
Dias, J.
Ferreira, J.
Editor: Ana Lucia Martins
Joao C. Ferreira
Alexander Kocian
Ulpan Tokkozhina
Data: 2023
Título próprio: Analyzing urban mobility based on smartphone data: The Lisbon case study
Título e volume do livro: 6th EAI International Conference on Intelligent Transport Systems, INTSYS 2022, Proceedings
Paginação: 40 - 54
Referência bibliográfica: Leal, D., Albuquerque, V., Dias, J., & Ferreira, J. (2023) Analyzing urban mobility based on smartphone data: The Lisbon case study. In A. L. Martins, J. C. Ferreira, A. Kocian, & U. Tokkozhina (Eds.). 6th EAI International Conference on Intelligent Transport Systems, INTSYS 2022, Proceedings (pp. 40-54). Springer. https://doi.org/10.1007/978-3-031-30855-0_3
ISBN: 978-3-031-30855-0
DOI (Digital Object Identifier): 10.1007/978-3-031-30855-0_3
Palavras-chave: CRISP-DM
DBSCAN
Point of interest
PRISMA Programa Comunitário Relativo à Preparação das Empresas com Vista ao Mercado Único
Smartphone data
Urban mobility
Visualisation
Resumo: Our paper addresses the mobility patterns in Lisbon in the vicinity of historical and transportation points of interest, with a case study conducted in the parish of Santa Maria Maior, a vibrant touristic neighborhood. We propose a data science-based approach to analyze such patterns. Our dataset includes five months of georeferenced mobile phone data, collected during late 2021 and early 2022, provided by the municipality of Lisbon. We performed a systematic literature review, using the PRISMA methodology and adopted the CRISP-DM methodology, to perform data curation, statistical and clustering analysis, and visualization, following the recommendations of the literature. For clustering we used the DBSCAN algorithm. We found eight clusters in Santa Maria Maior, with outstanding clusters along 28-E tram and Lisbon Cruise Terminal, where mobility is high, particularly for non-roaming travelers. This paper contributes to the digital transformation of Lisbon into a smart city, by improving improved understanding of urban mobility patterns
Arbitragem científica: yes
Acesso: Acesso Aberto
Aparece nas coleções:ISTAR-CRI - Comunicações a conferências internacionais

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