Big and Open Data Supporting Sustainable Mobility in Smart Cities – The Case of Thessaloniki

  • Georgia Aifadopoulou
  • Josep-Maria SalanovaEmail author
  • Panagiotis Tzenos
  • Iraklis Stamos
  • Evangelos Mitsakis
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 879)


This paper presents a methodology for estimating traffic conditions and emissions using innovative data sources, illustrated with its application in the city of Thessaloniki in Greece. Two types of datasets are considered: probe data and traffic data collected through conventional methods. The probe dataset is comprised of individual objects’ pulses (smart devices, navigators, etc.) tracked throughout the network at constant and pre-defined locations (“stationary” probe data collection) or during the whole trip of an “object” that continuously generates pulses (“dynamic” probe data collection). The conventionally collected traffic datasets originate from inductive loops, cameras and radars. Finally, the collected data is processed for estimating mobility and emissions indicators in the city.


Big data Floating car data Probe data Emissions 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Georgia Aifadopoulou
    • 1
  • Josep-Maria Salanova
    • 1
    Email author
  • Panagiotis Tzenos
    • 1
  • Iraklis Stamos
    • 2
  • Evangelos Mitsakis
    • 1
  1. 1.Centre for Research and Technology HellasHellenic Institute of TransportThessalonikiGreece
  2. 2.IRU ProjectsBrusselsBelgium

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