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Leal, D., Albuquerque, V., Dias, J. & Ferreira, J. (2023). Analyzing urban mobility based on smartphone data: The Lisbon case study. In Ana Lucia Martins, Joao C. Ferreira, Alexander Kocian, Ulpan Tokkozhina (Ed.), 6th EAI International Conference on Intelligent Transport Systems, INTSYS 2022, Proceedings. (pp. 40-54). Lisboa: Springer, Cham.

D. Leal et al.,  "Analyzing urban mobility based on smartphone data: The Lisbon case study", in 6th EAI Int. Conf. on Intelligent Transport Systems, INTSYS 2022, Proc., Ana Lucia Martins, Joao C. Ferreira, Alexander Kocian, Ulpan Tokkozhina, Ed., Lisboa, Springer, Cham, 2023, pp. 40-54

@inproceedings{leal2023_1734918657767,
	author = "Leal, D. and Albuquerque, V. and Dias, J. and Ferreira, J.",
	title = "Analyzing urban mobility based on smartphone data: The Lisbon case study",
	booktitle = "6th EAI International Conference on Intelligent Transport Systems, INTSYS 2022, Proceedings",
	year = "2023",
	editor = "Ana Lucia Martins, Joao C. Ferreira, Alexander Kocian, Ulpan Tokkozhina",
	volume = "",
	number = "",
	series = "",
	doi = "10.1007/978-3-031-30855-0_3",
	pages = "40-54",
	publisher = "Springer, Cham",
	address = "Lisboa",
	organization = "",
	url = "https://link.springer.com/chapter/10.1007/978-3-031-30855-0_3"
}

TY  - CPAPER
TI  - Analyzing urban mobility based on smartphone data: The Lisbon case study
T2  - 6th EAI International Conference on Intelligent Transport Systems, INTSYS 2022, Proceedings
AU  - Leal, D.
AU  - Albuquerque, V.
AU  - Dias, J.
AU  - Ferreira, J.
PY  - 2023
SP  - 40-54
DO  - 10.1007/978-3-031-30855-0_3
CY  - Lisboa
UR  - https://link.springer.com/chapter/10.1007/978-3-031-30855-0_3
AB  - 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
ER  -