• Title/Summary/Keyword: Maritime observation buoy

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A Study on Red Tide Monitoring system using Wireless Sensor Network (무선센서네트워크를 이용한 적조모니터링 시스템 구축을 위한 연구)

  • Min Heo;Mo Soo-Jong;Yim Jae-Hong;Kim Ki-Moon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2006.05a
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    • pp.489-492
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    • 2006
  • Red tide occurred sporadically in early 90s. But It is happening extensively by global warming. So, Airline observation, Red tide buoy development, and Red tide alarm system research is progressing for monitor ring. However, study to early forecast red tide and red tide alarm system did not exist hard. This paper proposed development that design and implementation red tide database of using wireless sensor network. There are GPS, Water Temperature sensor, Oxygen sensor, and Turbidity sensor in each node. And data is stored to red tide database through Ad-hoc network. This data is integrated and analyzed. So, forecast red tide. And red tide database has red tide data that happen at past. This is utilized to comparative analysis data for red tide estimate. Main screen displays position of node and measured value in electron map. Much studies must be backed for this a study. But I think that contribute to analyze red tide data by red tide database construction.

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Object Detection Algorithm Using Edge Information on the Sea Environment (해양 환경에서 에지 정보를 이용한 물표 추출 알고리즘)

  • Jeong, Jong-Myeon;Park, Gyei-Kark
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.9
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    • pp.69-76
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    • 2011
  • According to the related reports, about 60 percents of ship collisions have resulted from operating mistake caused by human factor. Specially, the report said that negligence of observation caused 66.8 percents of the accidents due to a human factor. Hence automatic detection and tracking of an object from an IR images are crucial for safety navigation because it can relieve officer's burden and remedies imperfections of human visual system. In this paper, we present a method to detect an object such as ship, rock and buoy from a sea IR image. Most edge directions of the sea image are horizontal and most vertical edges come out from the object areas. The presented method uses them as a characteristic for the object detection. Vertical edges are extracted from the input image and isolated edges are eliminated. Then morphological closing operation is performed on the vertical edges. This caused vertical edges that actually compose an object be connected and become an object candidate region. Next, reference object regions are extracted using horizontal edges, which appear on the boundaries between surface of the sea and the objects. Finally, object regions are acquired by sequentially integrating reference region and object candidate regions.

Study of Stability for Armor Weight of Stand-alone Caisson at Yongsu Wave Power Plant (용수 파력발전소 사례에서 독립 케이슨의 피복석 안정성 연구)

  • Kim, Gunwoo
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.31 no.6
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    • pp.478-484
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    • 2019
  • The submarine cable for Yongsu wave power plant was cut in 2014 winter. This study investigated the probability of high-wave occurrence exceeding the 50-year return period and the underestimation of armor unit weight used to protect the cable. The observation data from KMA buoy and the hindcast wave data were reviewed to determine the return period of wave height during the winter. In order to investigate the armor unit weight of cable-protection, we calculated the required weight of armor unit using not only Design Standard for Harbor and Fishery Port, but also the previous researches for the wave with large incident angle. As a result, it appeared that the high wave exceeding the 50-year return period did not occur during the winter of 2014 and the armor unit weight of the cable protection was not sufficient to sustain the obliquely incident wave, which induced the cable protection failure.

Quality Enhancement of Wave Data Observed by Radar at the Socheongcho Ocean Research Station (소청초 종합해양과학기지 Radar 파랑 관측 데이터의 신뢰도 향상)

  • Min, Yongchim;Jeong, JinYong;Shim, Jae-Seol;Do, Kideok
    • Journal of Coastal Disaster Prevention
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    • v.4 no.4
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    • pp.189-196
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    • 2017
  • Ocean Research Stations (ORSs) is the ocean platform type observation towers and measured oceanic, atmospheric and environmental data. These station located on the offshore area far from the coast, so they can produce the data without land effect. This study focused to improve the wave data quality of ORS station. The wave observations at ORSs are used by the C-band (5.8 GHz, 5.17 cm) MIROS Wave and Current Radar (MWR). MWR is convenient to maintenance and produce reliability wave data under bad weather conditions. MWR measured significant wave height, peak wave period, peak wave direction and 2D wave spectrum, so it's can provide wave information for researchers and engineers. In order to improve the reliability of MWR wave data, Datawell Waverider Buoy was installed near the one ORS (Socheoncho station) during 7 months and validate the wave data of MWR. This study found that the wave radar tend to be overestimate the low wave height under wind condition. Firstly, this study carried out the wave Quality Control (QC) using wind data, however the quality of wave data was limited. So, this study applied the four filters (Correlation Check, Direction Filter, Reduce White Noise and Phillips Check) of MWR operating software and find that the filters effectively improve the wave data quality. After applying 3 effective filters in combination, the RMSE of significant wave height decreased from 0.81m to 0.23m, by 0.58m and Correlation increased from 0.66 to 0.96, by 0.32, so the reliability of MWR significant wave height was significantly improved.

Sea Fog Level Estimation based on Maritime Digital Image for Protection of Aids to Navigation (항로표지 보호를 위한 디지털 영상기반 해무 강도 측정 알고리즘)

  • Ryu, Eun-Ji;Lee, Hyo-Chan;Cho, Sung-Yoon;Kwon, Ki-Won;Im, Tae-Ho
    • 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.