Leveraging analytics to monitor and manage urban infrastructure

Pablo Luis Durango-Cohen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We use structural time series models to predict the progression of measurements collected from infrastructure facilities, and statistical process control for model diagnosis/refinement, and to support detection of extraordinary events. The approach contributes tools to interpret the effect of unusual events that exploits the structural times series analysis paradigm, involving decomposition of measurements into unobserved, but meaningful components. As an example, we consider displacement measurements from a highway bridge. The model yields an estimate of the rate at which the bridge's position is drifting, which is useful to plan corrective measures. The model also provides a means to control for environmental factors affecting the accuracy of the measurements. In terms of unusual measurements, large measurement errors appear driven by extraordinary temperature variation, and the interaction of environmental factors with unusually large traffic or wind loads results in movement deviating significantly from the model's predictions.

Original languageEnglish (US)
Title of host publicationTransportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018
EditorsWeihua Gu, Shuaian Wang
PublisherHong Kong Society for Transportation Studies Limited
Pages273-280
Number of pages8
ISBN (Electronic)9789881581471
StatePublished - Jan 1 2018
Event23rd International Conference of Hong Kong Society for Transportation Studies: Transportation Systems in the Connected Era, HKSTS 2018 - Hong Kong, Hong Kong
Duration: Dec 8 2018Dec 10 2018

Publication series

NameTransportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018

Conference

Conference23rd International Conference of Hong Kong Society for Transportation Studies: Transportation Systems in the Connected Era, HKSTS 2018
CountryHong Kong
CityHong Kong
Period12/8/1812/10/18

Keywords

  • Infrastructure Performance Modeling
  • Kalman Filter
  • Statistical Process Control
  • Structural Health Monitoring
  • Structural Time Series Models

ASJC Scopus subject areas

  • Transportation

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  • Cite this

    Durango-Cohen, P. L. (2018). Leveraging analytics to monitor and manage urban infrastructure. In W. Gu, & S. Wang (Eds.), Transportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018 (pp. 273-280). (Transportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018). Hong Kong Society for Transportation Studies Limited.