• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.1
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• pp.18-29
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• 2019

ROV surveys were conducted using 500 meter mini class ROV with HD video camera, 2 LED lights, a simple manipulator and 8 thrusters near the Dokdo and Simheungtaek seamount. Total six dives have been conducted using the ROV "V8 SII" from Sweden and ROV's support ship, "KOSAL V" at 4 stations between 45 and 370 meters with diving time ranged from 30 to 120 minutes. Dense communities of sea anemone (Actinostolidae sp.) and ophiuroids (Ophiuridae sp.) on the surface of rocky bottom and snow crab on the soft bottom with muddy-sand were observed at northwestern part of Simheungtaek seamount. We obtained the following results 1) habitats information for snow crab, one of the major fisheries resources, and deep-sea fauna, 2) observation on the specific topography and sediment conditions, 3) observation of the seabed surface covered with the discarded fishing gears. This study represents the first report of in situ visual observation of deep-sea organisms and their habitats near the Dokdo slopes and flat top of the Simheungtaek seamount in the East Sea. These results indicated that immediate oceanographic survey using the mini class ROV is available in the East Sea.

• The Journal of Bigdata
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• v.8 no.2
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• pp.73-82
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• 2023

With 78% of current fisheries workers being elderly, there's a pressing need to address labor shortages. Consequently, active research on smart aquaculture technologies, centered on object detection and tracking algorithms, is underway. These technologies allow for fish size analysis and behavior pattern forecasting, facilitating the development of real-time monitoring and automated systems. Our study utilized video data from cameras outside aquaculture facilities and implemented fish detection and tracking algorithms. We aimed to tackle high maintenance costs due to underwater conditions and camera corrosion from ammonia and pH levels. We evaluated the performance of a real-time system using YOLOv7 for fish detection and the SORT algorithm for movement tracking. YOLOv7 results demonstrated a trade-off between Recall and Precision, minimizing false detections from lighting, water currents, and shadows. Effective tracking was ascertained through re-identification. This research holds promise for enhancing smart aquaculture's operational efficiency and improving fishery facility management.