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Title	A Markerless High Resolution Structural Health Monitoring Framework For Smart Cities
ID_Doc	2501
Authors	Chan C.C.K.; Chen C.-C.; Delaney S.; Ferworn A.
Year	2021
Published	2021 IEEE Technology and Engineering Management Conference - Europe, TEMSCON-EUR 2021
DOI	http://dx.doi.org/10.1109/TEMSCON-EUR52034.2021.9488617
Abstract	Our paper introduces a novel structural health monitoring (SHM) framework for preexisting surveillance camera video footage towards an automated structural engineering e-governance system in a smart city. We test our framework on a sample pole structure using a high-resolution camera and an off-the-shelf phone camera. A preliminary study suggests the efficacy of using the framework in monitoring noticeable degradation and aging in large structures in periodically captured images. Our framework is dissimilar to computer vision techniques in which deformation patterns are recognized; instead, our framework is purposed as a long term observation application in which large structures in public video surveillance footage is monitored for changes that may suggest signs of aging or degradation of a structure over a long period of time. We posit that this novel framework, with emerging technology and innovation, can pave the way to combine artificial intelligence and smart structural health monitoring techniques in a widespread, unprecedented way of ensuring safe public structures in smart cities. © 2021 IEEE.
Author Keywords	Convolutional neural network; Fiducial marker; High fidelity image resolution

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