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, João Carlos Ferreira

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number3044
Pages (from-to)1-25
Number of pages25
JournalEnergies
Volume14
Issue number11
DOIs
Publication statusPublished - 1 Jun 2021

Keywords

  • Accidents
  • Data visualization
  • Data‐driven
  • Smart cities
  • Traffic
  • Transportation

UN Sustainable Development Goals (Under maintenance)

  • SDG 11 - Sustainable Cities and Communities

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