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http://dx.doi.org/10.5394/KINPR.2022.46.3.243

Real-time Wave Overtopping Detection and Measuring Wave Run-up Heights Based on Convolutional Neural Networks (CNN)  

Seong, Bo-Ram (Marine Information Technology Co.)
Cho, Wan-Hee (Marine Information Technology Co.)
Moon, Jong-Yoon (Marine Information Technology Co.)
Lee, Kwang-Ho (Department of Civil Engineering, Korea Maritime and Ocean University)
Publication Information
Journal of Navigation and Port Research / v.46, no.3, 2022 , pp. 243-250 More about this Journal
Abstract
The purpose of this study was to propose technology to detect the wave in the image in real-time, and calculate the height of the wave-overtopping through image analysis using artificial intelligence. It was confirmed that the proposed wave overtopping detection system proposed in this study could detect the occurring of wave overtopping, even in severe weather and at night in real-time. In particular, a filtering algorithm for determining if the wave overtopping event was used, to improve the accuracy of detecting the occurrence of wave overtopping, based on a convolutional neural networks to catch the wave overtopping in CCTV images in real-time. As a result, the accuracy of the wave overtopping detection through AP50 was reviewed as 59.6%, and the speed of the overtaking detection model was 70fps based on GPU, confirming that accuracy and speed are suitable for real-time wave overtopping detection.
Keywords
artificial intelligence; wave-overtopping detection; convolutional neural networks; filtering algorithm;
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Times Cited By KSCI : 2  (Citation Analysis)
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