[1F4-GS-10c] AI応用：環境モニタリング

[1F4-GS-10c-03] Proposal of monitoring method for river revetment utilizing deep learning

〇Junichiro Fujii¹, Ryuto Yoshida¹, Masahiro Okano¹, Masazumi Amakata¹ (1. Yachiyo Engineering Co., Ltd.)

Keywords:deep learning, semantic segmentation, structure inspection

The inspection of civil engineering structures such as river revetments has traditionally been carried out visually by engineers. Visual inspection requires a great deal of labor and is subjective to the engineer's judgment, resulting in inconsistent inspection records. In order to solve these problems, an inspection method that applies image recognition technology based on deep learning is being researched. However, for the maintenance and management of structures, image recognition results alone are not sufficient. It is necessary to convert these results into physical quantities that can be used as indicators to determine the health of structures, and to monitor the changes over time.
In this study, we propose a river revetment monitoring method based on the physical quantities of area, width, and length calculated for the crack detection results by deep learning. We also report the results of applying this method to actual rivers.