| description abstract | This paper aims to summarize central findings from a literature review and technical survey on unmanned aerial vehicle (UAV) techniques for bridge inspection and damage quantification. This literature review includes a detailed compilation of different algorithms on high-quality image selection, image-based damage detection and quantification, and various UAV applications for bridge inspections. To gather current bridge inspection practices in the United States, a technical survey referring to UAV-enabled bridge inspections was also conducted for state DOTs and USDA Forest Service (USDA FS) regions. Responses to the survey were assembled from 17 state DOTs (e.g., Nevada DOT, South Dakota DOT, and Texas DOT) and two USDA FS regions such as Region 8 (Southern). From both the review and survey, it was revealed that researchers, state DOTs, and USDA FS regions have interest in using a UAV for bridge inspections, but they have struggled to use it for bridge damage quantification. Specifically, it was found from the review that some recent studies using different algorithms such as deep learning and pattern recognition have been carried out to quantify different types of damage. Key findings from the survey are that over 56% of respondents have used or are planning to use UAVs for bridge inspections, but only 19% of respondents have begun to quantify damage using images captured from UAVs. | |
