Applying Computer Vision Technology to Triaxial Deformation Monitoring of Remedial Construction for a Landslide

Author(s): I-Hui Chen*, Shei-Chen Ho, Jun-Yang Chen, Yu-Shu Lin, Miau-Bin Su

Journal Name: International Journal of Sensors, Wireless Communications and Control

Volume 9 , Issue 4 , 2019

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Graphical Abstract:


Background & Objective: The paper explores a new instrument of computer vision to measure three-dimension deformation with an Internet of Things (IoT) system including Raspberry Pi, digital cameras and OpenCV programs in laboratory and field testing so as to monitor the potential deformation of a structure drainage well in a landslide.

Methods: A chessboard pattern is detected in the image by the camera so that pixels of chessboard cornors can be recognized by OpenCV programs. X-direction, Y-direction and Z-distance changes can be casulated by the similar triangles relationship of camera pixels. For laboratory testing, standard deviations of the measurement were approximately 0.01 cm.

Results: For field testing, the study installed four sets of Raspberry Pi in a drainage well within a landslide and employed OpenCV programs to interpret pixel changes of chessboards at four levels of the draiage well.

Conclusion: Overall, the instrument can be employed for triaxial deformation monitoring of the construction in the field effectively and automatically.

Keywords: Computer vision, ground deformation, image recognition, internet of things, landslide monitoring, raspberry pi.

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Article Details

Year: 2019
Published on: 16 September, 2019
Page: [488 - 496]
Pages: 9
DOI: 10.2174/2210327909666190208153757
Price: $25

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