• Journal of the Korea Computer Graphics Society
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• v.25 no.4
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• pp.9-16
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• 2019

In this paper, we propose a hydrodynamic scene separation method for wave propagation from video imagery using autoencoder. In the coastal area, image analysis methods such as particle tracking and optical flow with video imagery are usually applied to measure ocean waves owing to some difficulties of direct wave observation using sensors. However, external factors such as ambient light and weather conditions considerably hamper accurate wave analysis in coastal video imagery. The proposed method extracts hydrodynamic scenes by separating only the wave motions through minimizing the effect of ambient light during wave propagation. We have visually confirmed that the separation of hydrodynamic scenes is reasonably well extracted from the ambient light and backgrounds in the two videos datasets acquired from real beach and wave flume experiments. In addition, the latent representation of the original video imagery obtained through the latent representation learning by the variational autoencoder was dominantly determined by ambient light and backgrounds, while the hydrodynamic scenes of wave propagation independently expressed well regardless of the external factors.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.1-12
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• 2022

In the event of a maritime distress accident, rapid search and rescue operations using rescue assets are very important to ensure the safety and life of drowning person's at sea. In this paper, we analyzed the surface layer current in the northwest sea area of Ulleungdo by applying machine learning such as multiple linear regression, decision tree, support vector machine, vector autoregression, and LSTM to the meteorological information collected from the maritime observation buoy. And we predicted the drowning person's route at sea based on the predicted current direction and speed information by constructing each prediction model. Comparing the various machine learning models applied in this paper through the performance evaluation measures of MAE and RMSE, the LSTM model is the best. In addition, LSTM model showed superior performance compared to the other models in the view of the difference distance between the actual and predicted movement point of drowning person.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.161-164
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• 2022

부유식 라이다는 해상풍력단지 조성시 필수적으로 수행하고 있는 풍황관측 업무에 새로운 패러다임을 제공하고 있는 시스템으로, 전통적으로 풍황관측을 수행하고 있던 해상기상관측탑을 대체하여 사업 초기의 대규모 공사를 획기적으로 축소하여 시간과 비용을 절약하고, 환경적 영향을 최소화 하며, 지역사회의 반발 요소까지 줄일 수 있어 해당 업계의 표준으로 자리잡고 있는 중이다. 다만 부표식의 동요에 따른 외란적 요소가 관측자료의 신뢰성에 영향을 미치는 만큼 안정적인 플랫폼의 설계 및 검증이 매우 중요한 상황이며, 국내에서는 해당기술에 대한 늦은 진입으로 인해 다수의 외산장비 제조사들이 국내시장까지 선점하고 있는 상황이다. 한국의 서해안은 천해 환경으로 조석차가 매우 커 지역에 따라 강한 조류가 반복적으로 나타나며, 계절별로 상이한 강한 에너지의 파랑이 형성되는 등 플랫폼에 안정도에 많은 영향을 미치는 바다 환경을 갖고 있다. 본 논문에서는 이러한 복잡한 환경적 특성을 갖고 있는 우리나라의 해역에 라이다 운영에 적합한 부표식에 대한 연구를 수행하며, 우선적으로 적용하였던 선박형 부표식의 최적화 설계 및 검증 사례를 소개하고, 향후 다양한 플랫폼 개발에 토대가 되는 중요 개념을 도출하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.76-76
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• 2023

최근 자율주행과 관련한 시장의 관심은 기존 자동차 자율주행에서 선박 자율운항으로 자연스럽게 이동하고 있다. 이에 인공지능 및 빅데이터 등과 같은 최근 기술을 선박 자율주행에 적용하는 자율운항선박(MASS: Maritime Autonomous Surface Ship) 개발이 활발히 진행되고 있으며, 레이더 및 카메라 등과 같은 센서 정보를 선박 자율운항에 적용하여 다양한 선박 운동 및 정보를 획득하는 연구 기술이 집중되고 있다. 이러한 경향에 따라 IMO(International Maritime Organization)과 같은 국제기구에서도 자율운항선박 표준화 본격 논의로 기술표준 선점 경쟁에 참여하고 있다. 이 중 연안 자율운항선박 개발은 IMO에서 주관하는 무인화 핵심기술로 여겨지고 있어, 기존 대양 항해 기술과 함께 연안 항해에 대한 기술 개발의 중요성이 높아지고 있다. 특히 항만 인근 해역에서는 다수의 선박이 입출항함으로 인해 해상에서의 안전과 물류의 효율화가 요구되기 때문에 고도화된 자율운항 기술개발이 필요하다. 하지만 자율운항선박에서의 상황인식 기술은 탑재된 센서의 제한된 시야각 및 기상조건에 따른 인식률이 떨어지는 문제가 생긴다. 이러한 기술적 한계를 극복하기 위해 육상에 설치된 레이더를 활용하여 선박을 탐지할 수 있는 기술이 필요하다. 본 연구에서는 고해상도 육상 레이더를 기반하여 얻어진 레이더 화면상의 물표 정보를 이용해 인공지능 기법에 활용하기 위한 라벨링 자동 생성 방법에 대해 소개한다. 얻어진 물표 정보에 인공지능 기법을 적용하여 선박 길이 정보를 추정하는 기술에 대해 소개한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.206-207
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• 2023

Intelligent maritime traffic information services provide services for maritime traffic safety, but due to the difference in ship specifications and loading condition, the method of determining abnormalities in ship stability has not been generalized. In this study, we established a method for collecting and preprocessing Accelerometer and GPS data for calculating ship stability. In addition, we have researched a model that can determine the real-time ship stability through data science algorithms that can reflect each vessel specifications and external forces, breaking away from approximate calculations that cannot reflect weather factors in the real ocean.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.887-892
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• 2023

Vessel traffic service(VTS) centers are equipped with RADAR, AIS(Automatic Identification System), weather sensors, and VHF(Very High Frequency). VTS operators use this equipment to observe the movement of ships operating in the VTS area and provide information. The VTS data generated by these various devices is highly valuable for analyzing maritime traffic situation. However, owing to a lack of compatibility between system manufacturers or policy issues, they are often not systematically managed. Therefore, we developed the VTS Bigdata Platform that could efficiently collect, store, and manage control data collected by the VTS, and this paper describes its design and implementation. A microservice architecture was applied to secure operational stability that was one of the important issues in the development of the platform. In addition, the performance of the platform could be improved by dualizing the storage for real-time navigation information. The implemented system was tested using real maritime data to check its performance, identify additional improvements, and consider its feasibility in a real VTS environment.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.603-614
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• 2021

Recently, the surface temperature in the seas around Korea has been continuously rising. This temperature rise causes changes in fishery resources and affects leisure activities such as fishing. In particular, high temperatures lead to the occurrence of red tides, causing severe damage to ocean industries such as aquaculture. Meanwhile, changes in sea temperature are closely related to military operation to detect submarines. This is because the degree of diffraction, refraction, or reflection of sound waves used to detect submarines varies depending on the ocean mixed layer. Currently, research on the prediction of changes in sea water temperature is being actively conducted. However, existing research is focused on predicting only the surface temperature of the ocean, so it is difficult to identify fishery resources according to depth and apply them to military operations such as submarine detection. Therefore, in this study, we predicted the temperature of the ocean mixed layer at a depth of 38m by using temperature data for each water depth in the upper mixed layer and meteorological data such as temperature, atmospheric pressure, and sunlight that are related to the surface temperature. The data used are meteorological data and sea temperature data by water depth observed from 2016 to 2020 at the IEODO Ocean Research Station. In order to increase the accuracy and efficiency of prediction, LSTM (Long Short-Term Memory), which is known to be suitable for time series data among deep learning techniques, was used. As a result of the experiment, in the daily prediction, the RMSE (Root Mean Square Error) of the model using temperature, atmospheric pressure, and sunlight data together was 0.473. On the other hand, the RMSE of the model using only the surface temperature was 0.631. These results confirm that the model using meteorological data together shows better performance in predicting the temperature of the upper ocean mixed layer.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.4
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• pp.251-261
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• 2007

The wind-wave interaction around the Kyung-gi Bay, Korea, was studied using the observed data from ocean buoy at DeuckJeuck-Do from Jan. to Dec., 2005, and from waverider data at KeuckYeulBee-Do on Mar. 19-26 and May 23-28, 2005. Wind-driven surface waves and wave-driven wind speed decrease were estimated from the ocean buoy data, and the characteristics of wave spectrum response were also investigated from the waverider data for the wave developing and calm stages of sea surface, including the time series of spectrum pattern change, frequency trend of the maximum energy level and spectrum slope for the equilibrium state range. The wind speed difference between before and after considering the wave effect was about $2ms^{-1}$ (wind stress ${\sim}0.1Nm^{-2}$) for the wind speed range $5-10ms^{-1}$ and about $3ms^{-1}$ (wind stress ${\sim}0.4Nm^{-2}$) for the wind speed range $10-15ms^{-1}$. Correlation coefficient between wind and wave height was increased from 0.71 to 0.75 after the wave effect considered on the observed wind speed. When surface waves were generated by wind, the initial waves were short waves about 4-5 sec in period and become in gradual longer period waves about 9-10 sec. For the developed wave, the frequency of maximum energy was showed a constant value taking 6-7 hours to reach at the state. The spectrum slope for the equilibrium state range varied with an amplitude in the initial stage of wave developing, however it finally became a constant value 4.11. Linear correlation between the frictional velocity and wave spectrum for each frequency showed a trend of higher correlation coefficient at the frequency of the maximum energy level. In average, the correlation coefficients were 0.80 and 0.82 for the frequencies 0.30 Hz and 0.35 Hz, respectively.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.2
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• pp.252-263
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• 1997

Temperature and salinity were observed in Kugum Suro Channel in February, April, August and October 1993. Temperature ranged from $7.0^{\circ}C\;to\;25.0^{\circ}C$ throughout the year and its variation was about $18^{\circ}C$. The maximum temperature difference between surface and bottom was less than $0.75^{\circ}C$ for a year, which meant that the temperature stratification in Kugum Suro Channel was considerably week. Salinity had also a small variation range of less than $0.5\%_{\circ}$. Salinity varied from $34.0\%_{\circ}$ in April to $30.0\%_{\circ}$ in August and its fluctuation patterns were quite similar to the seasonal variations of the precipitation and the duration of sunshine observed at Kohung Weather station. Seasonal variation of sea water density in T-S diagram showed that the water mass in Kugum Suro Channel could be largely affected by regional atmospheric conditions. Temperature increased in ebb tide and decreased in flood tide, but salinity decreased in ebb tide and increased in flood tide for a day. The period of fluctuations in temperature and salinity measured for 25 hours was nearly coincident with the semi-diurnal tide which was predominant in that region. Stratification parameters computed in Kugum Suro Channel areas were less than $4.0J/m^3$ the year round, which indicated that vortical mixing from the bottom boundary caused by tidal current played an important role in deciding the stratification regime in Kugum Suro Channel. In estimating the equation which defines stratification and mixing effects in the observed areas, the tidal mixing term ranged from $4.7J/M^3\;to\;14.1J/m^3$ was greater than any other terms like solar radiation, river discharge and wind mixing.