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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 and Miau-Bin Su   Pages 1 - 9 ( 9 )

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. 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. 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, Raspberry Pi, deformation monitoring

Affiliation:

Department of Civil Engineering, College of Engineering, National Chung Hsing University, Taichung, Department of Civil Engineering, College of Engineering, National Chung Hsing University, Taichung, Department of Civil Engineering, College of Engineering, National Chung Hsing University, Taichung, Department of Civil Engineering, College of Engineering, National Chung Hsing University, Taichung, Department of Civil Engineering, College of Engineering, National Chung Hsing University, Taichung



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