Open AccessDevelopment and Application of Tunnel Apparent Distress Monitoring System Based on Video Image Analysis
Author(s) -
Hongsheng Ang,
Fei Ma,
Junwei Su,
Hongyan Guo,
Ke Li
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/741/1/012094
Subject(s) - computer science , identification (biology) , real time computing , image processing , field (mathematics) , video processing , term (time) , computer vision , artificial intelligence , image (mathematics) , botany , physics , mathematics , quantum mechanics , pure mathematics , biology
With a lack of complete system and hardware equipment for long-term monitoring of distresses in an operating tunnel to address theoretical and technical issues, it is necessary to develop an IoT-based integrated system for long-term monitoring of lining crack, water leakage and spalling in an operating tunnel using video image processing technology and technique in conjunction with computer programming languages. Use of video image processing methods of this monitoring system allows rapid, accurate identification of distresses and the extent thereof. It is concluded that linear array CCD is the best option for engineering surveillance cameras since such CCD is able to accurately capture both static and dynamic targets; the use of higher-definition cameras provides for tiny target identification under remote monitoring conditions and the addition of temporary storage module for field data.