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http://hdl.handle.net/10071/22704
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Title: Smart cities: Data-driven solutions to understand disruptive problems in transportation—The Lisbon case study
Authors: Albuquerque, V.
Oliveira, A.
Barbosa, J. L.
Rodrigues, R. S.
Andrade, F.
Dias, J.
Ferreira, J.
Keywords: Transportation
Traffic
Accidents
Data-driven
Data visualization
Smart cities
Issue Date: 2021
Publisher: MDPI
Abstract: Transportation data in a smart city environment is increasingly becoming available. This data availability allows building smart solutions that are viewed as meaningful by both city residents and city management authorities. Our research work was based on Lisbon mobility data available through the local municipality, where we integrated and cleaned different data sources and applied a CRISP-DM approach using Python. We focused on mobility problems and interdependence and cascading-effect solutions for the city of Lisbon. We developed data-driven approaches using artificial intelligence and visualization methods to understand traffic and accident problems, providing a big picture to competent authorities and supporting the city in being more prepared, adaptable, and responsive, and better able to recover from such events.
Peer reviewed: yes
URI: http://hdl.handle.net/10071/22704
DOI: 10.3390/en14113044
ISSN: 1996-1073
Ciência-IUL: https://ciencia.iscte-iul.pt/id/ci-pub-81836
Appears in Collections:ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica

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