Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/31711
Author(s): Leal, D.
Albuquerque, V.
Dias, J.
Ferreira, J.
Editor: Ana Lucia Martins
Joao C. Ferreira
Alexander Kocian
Ulpan Tokkozhina
Date: 2023
Title: Analyzing urban mobility based on smartphone data: The Lisbon case study
Book title/volume: 6th EAI International Conference on Intelligent Transport Systems, INTSYS 2022, Proceedings
Pages: 40 - 54
Reference: 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
Keywords: CRISP-DM
DBSCAN
Point of interest
PRISMA Programa Comunitário Relativo à Preparação das Empresas com Vista ao Mercado Único
Smartphone data
Urban mobility
Visualisation
Abstract: 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
Peerreviewed: yes
Access type: Open Access
Appears in Collections:ISTAR-CRI - Comunicações a conferências internacionais

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