Artigo em revista científica Q1
Smart cities: Data-driven solutions to understand disruptive problems in transportation—The Lisbon case study
Vitória Albuquerque (Albuquerque, V.); Ana Oliveira (Oliveira, A.); Jorge Lourenço Barbosa (Barbosa, J. L.); Rui Simão Rodrigues (Rodrigues, R. S.); Francisco Andrade (Andrade, F.); Miguel Sales Dias (Dias, J.); Joao C Ferreira or Joao Ferreira (Ferreira, J.); et al.
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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.
Transportation,Traffic,Accidents,Data-driven,Data visualization,Smart cities
  • Ciências da Computação e da Informação - Ciências Naturais
  • Engenharia Eletrotécnica, Eletrónica e Informática - Engenharia e Tecnologia
Registos de financiamentos
Referência de financiamento Entidade Financiadora
UIDB/04466/2020 Fundação para a Ciência e a Tecnologia
UIDP/04466/2020 Fundação para a Ciência e a Tecnologia