• 2nd Edition

  • Winter 2021

  • Open Data And Urban Infrastructures

Prediction of metro incidents


We have developed a supervised learning model to predict the main cause of disruption in the Montreal metro network and the delay time after a breakout. Our predictive model supports public transport authorities and operators to prioritize what type of disruptions at what location to focus on to potentially achieve the most significant reduction in disruption exposure. ions.

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Une collaboration entre :

Ville de Montréal

Direction, technologies, architecture, innovation et sécurité

Experts municipaux

Marie-Odette St-Hilaire


CIVI 691 – Big Data Analytics for Smart City Infrastructure (Building, Civil and Environmental Engineering), Concordia University


Mazdak Nik-Bakht

Équipe étudiante

Farbod Lotfalian
Mohammad Vaseghi
Maryam Faham