Scientific journal paper 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.
Journal Title
Energies
Year (definitive publication)
2021
Language
English
Country
Switzerland
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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.
Acknowledgements
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Keywords
Transportation,Traffic,Accidents,Data-driven,Data visualization,Smart cities
  • Computer and Information Sciences - Natural Sciences
  • Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
Funding Records
Funding Reference Funding Entity
UIDB/04466/2020 Fundação para a Ciência e a Tecnologia
UIDP/04466/2020 Fundação para a Ciência e a Tecnologia

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