Smart Cities: Data-Driven Solutions to Understand Disruptive Problems in Transportation—The Lisbon Case Study

Vitória Albuquerque, Ana Oliveira, Jorge Lourenço Barbosa, Rui Simão Rodrigues, Francisco Andrade, Miguel Sales Dias and João Carlos Ferreira
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Vitória Albuquerque: NOVA Information Management School (NOVA IMS), Campus de Campolide, Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal
Ana Oliveira: ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal
Jorge Lourenço Barbosa: ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal
Rui Simão Rodrigues: ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal
Francisco Andrade: ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal
Miguel Sales Dias: NOVA Information Management School (NOVA IMS), Campus de Campolide, Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal
João Carlos Ferreira: ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal

Energies, 2021, vol. 14, issue 11, 1-25

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.

Keywords: transportation; traffic; accidents; data-driven; data visualization; smart cities (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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