Combination of GIS and SHM in prognosis and diagnosis of bridges in earthquake-prone locations

Malekloo, Arman and Ozer, Ekin and Al-Turjman, Fadi; (2020) Combination of GIS and SHM in prognosis and diagnosis of bridges in earthquake-prone locations. In: Smart Grid in IoT-Enabled Spaces. CRC Press, Boca Raton, F.L., pp. 139-154. ISBN 978-1-003-05523-5

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Bridge infrastructures are essential nodes in the transportation network. In earthquake-prone areas, seismic performance assessment of infrastructure is vital to identify, retrofit, reconstruct, or, if necessary, demolish the structural systems based on optimal decision-making processes. This research proposes the combined use of advanced tools used in the management and monitoring of bridges such as Geographical Information Systems (GIS) and Structural Health Monitoring (SHM) in a synergistic manner that can enable observation of bridges to construct an earthquake damage model. Post-earthquake disaster data can enhance and update this model to mitigate further damages both to the structure and transportation network in the future. Implications of new technologies such as drones and mobile devices in this scheme constitute the next step toward the future of the Cyber-Physical SHM systems. The proposed intelligent and sustainable cloud-based framework of SHM-GIS in this paper lays the core behind more robust impending systems. The synergistic behavior of the offered framework reduces the overall cost in large scale implementation and increases the accuracy of the results leading to a decision-making platform easing the management of bridges.


Malekloo, Arman, Ozer, Ekin ORCID logoORCID: and Al-Turjman, Fadi;