Intelligent Bridge Safety Prediction Edge System


KIPS Transactions on Computer and Communication Systems, Vol. 12, No. 12, pp. 357-362, Dec. 2023
https://doi.org/10.3745/KTCCS.2023.12.12.357,   PDF Download:
Keywords: Safety Prediction, Fast Fourier transform, Principal Component Analysis
Abstract

Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.


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Cite this article
[IEEE Style]
J. Park, T. Lee, Y. Hong, J. Youn, "Intelligent Bridge Safety Prediction Edge System," KIPS Transactions on Computer and Communication Systems, vol. 12, no. 12, pp. 357-362, 2023. DOI: https://doi.org/10.3745/KTCCS.2023.12.12.357.

[ACM Style]
Jinhyo Park, Taejin Lee, Yong-Geun Hong, and Joosang Youn. 2023. Intelligent Bridge Safety Prediction Edge System. KIPS Transactions on Computer and Communication Systems, 12, 12, (2023), 357-362. DOI: https://doi.org/10.3745/KTCCS.2023.12.12.357.