• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1739-1749
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• 2018

We propose a marine observation system using existing light buoys to observe various marine information of marine locations. Our proposed ocean observation system is composed of the existing standard light buoy type and can be easily connected to the light buoy. The proposed marine observation system measures the mean wave height, maximum wave height, mean wave height and water temperature measured in the ocean. Besides, it can measure the air pressure, temperature, wind speed and wind speed in real time. In order to measure important peaks in marine observations, 2200 peak data are collected for 10 minutes, and the collected data are subjected to spectral analysis to extract significant wave and wave period data. The developed system removes the noise by using the filter because the marine observation system attaches to the light buoy. We compare and analyze the measurement data of the existing proven floating marine observation system and the standard equivalent system developed. Also, it is proved that the data of the standard type backbone ocean observation system developed through the comparative experiment is similar to that of the existing ocean observation system.

• Journal of Navigation and Port Research
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• v.47 no.4
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• pp.231-238
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• 2023

The position of a light buoy is always flexible due to the influence of external forces such as tides and wind. The position can be checked through AIS (Automatic Identification System) or RTU (Remote Terminal Unit) for AtoN. As a result of analyzing the position data for the last five years (2017-2021) of a light buoy, the average position error was 15.4%. It is necessary to detect position error data and obtain refined position data to prevent navigation safety accidents and management. This study aimed to detect position error data and obtain refined position data by DBSCAN Clustering position data obtained through AIS or RTU for AtoN. For this purpose, 21 position data of Gunsan Port No. 1 light buoy where RTU was installed among western waters with the most position errors were DBSCAN clustered using Python library. The minPts required for DBSCAN Clustering applied the value commonly used for two-dimensional data. Epsilon was calculated and its value was applied using the k-NN (nearest neighbor) algorithm. As a result of DBSCAN Clustering, position error data that did not satisfy minPts and epsilon were detected and refined position data were acquired. This study can be used as asic data for obtaining reliable position data of a light buoy installed with AIS or RTU for AtoN. It is expected to be of great help in preventing navigation safety accidents.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.164-170
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• 2024

The light buoy, a floating structure at sea, is prone to drifting due to external factors such as oceanic weather. This makes it imperative to monitor for any loss or displacement of buoys. In order to address this issue, the Ministry of Oceans and Fisheries aims to issue alerts for buoy displacement by analyzing historical buoy position data to detect patterns. However, periodic lifting inspections, which are conducted every two years, disrupt the buoy's location pattern. As a result, new patterns need to be analyzed after each inspection for location monitoring. In this study, buoy position data from various periods were analyzed using convex hull and distance-based clustering algorithms. In addition, the optimal data collection period was identified in order to accurately recognize buoy location patterns. The findings suggest that a nine-week data collection period established stable location patterns, explaining approximately 89.8% of the variance in location data. These results can improve the management of light buoys based on location patterns and aid in the effective monitoring and early detection of buoy displacement.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.104-110
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• 2001

Ocean heat fluxes over a wide region are generally estimated by an aerodynamic bulk fromula. Though a remote sensing technique can be expected to estimated global heat flux, it is difficult to obtain air temperature and specific humidity at sea surface by a remote sensor. In this study present a new method with which to determine near-sea surface air temperature from in situ data. Also, These methods compared with other methods. A new method used a linear regression equation between sea surface temperature and air temperature of the buoys data. In this study new method is validated using observed monthly mean data at the Japan Meteorological Agency(JMA), National Data Buoy Center(NDBC) and Tropical Ocean-Global Atmosphere(TOGA)-Tropical Atmosphere Ocean(TAO) buoys. The result that bias and rmse are 0.28, 1.5$0^{\circ}C$ respectively. The correlation coefficient is 0.98. Also, to retrieve near-sea surface specific humidity(Q) from good nonlinear regression relationship between vapor pressure(Ea) of buoy data and air temperature, after obtained the third-order polynomial function, compared with that of estimated from SSM/I empirical equation by Schussel et al(1995). The result that bias and rmse are -1.42 and 1.75(g/kg).

• Journal of Ocean Engineering and Technology
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• v.23 no.1
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• pp.89-95
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• 2009

The purpose of the present study was to evaluate the safety under extreme environmental conditions and the dynamic safety under service environment conditions, of oceanographic buoy mooring systems consisting of a variety of materials, including chain, wire rope, nylon rope, and polypropylene rope. For the static safety assessment of a mooring system, after the calculation of external forces and the division of a mooring system into finite elements, the numerical integral was conducted to yield the elemental static tension until satisfying the geometrical convergence condition. To evaluate the dynamic safety, various processes were considered, including data collection about the anticipated areas for mooring, a determination of the parameters for the interpretation, the interpretation of the dynamic characteristics based on an analytic equation that takes into account the heave motion effect of a buoy hull and a mooring system, and a fatigue analysis of the linear cumulative damage. Based on the analysis results, a supplementary proposal for a wire rope that has a fracture in an actual mooring area was established.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1200-1207
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• 2015

A gateway buoy system connects a underwater network to a terrestrial network, which enables to efficiently monitor the underwater network on a land station. In this paper, we introduce an implemented gateway buoy system which relays gathered data from multiple underwater nodes to a land station in a real time. The gateway buoy hardware system is composed of a underwater acoustic modem system, a radio frequency modem system, and a gateway operating system. in additional, we have implemented a land operating program and a land monitoring program for gateway system and states of underwater network, respectively. We also perform real-sea experiments to verify the performance of the gateway buoy system which real-time monitors underwater network states and gateway system states.

• Proceedings of the KSRS Conference
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• v.1
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• pp.394-397
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• 2006

Gridded products of surface wind/wind-stress over the world ocean have been constructed by using satellite scatterometer as the Japanese Ocean Flux data sets with Use of Remote-sensing Observation (J-OFURO) data. Our previous validation study in the tropical Pacific using TAO/Triton and NDBC buoys revealed high reliability of our products. In this study, the Kuroshio Extension Observatory (KEO) buoy data are used for validation of other gridded wind-stress products including the NCEP-1 and 2 in the western North Pacific region where there have been few in-situ data. Results reveal that our J-OFURO product has almost zero mean difference and smallest root-mean-square (RMS) difference, while the NCEP-1 and 2 ones significantly positive biases and relatively high RMS difference. Intercomparison between the J-OFURO and NCEP products in a wide region of the North Pacific covered by the westerly winds exhibits that the NCEPs have larger magnitudes in the wind stress than the J-OFURO's, suggesting overestimation of the NCEPs.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.33-36
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• 2007

We have persistently constructed gridded products of surface wind/wind stress over the world ocean using satellite scatterometer (ERS and Qscat). They are available for users as the Japanese Ocean Flux data sets with Use of Remote sensing Observation (J-OFURO) data together with heat flux components. Recently, a new version data of the Qscat/SeaWinds based on improved algorithm for rain flag and high wind-speed range have been delivered, and allowed us to reconstruct gridded product with higher spatial resolution. These products are validated by comparisons with in-situ measurement data by mooring buoys such as TAO/TRITON, NDBC and the Kuroshio Extension Observation (KEO) buoys, together with numerical weather prediction model products such as the NCEP-1 and 2. Results reveal that the new product has almost the same magnitude in mean difference as the previous version of Qscat product and much smaller than the NCEP-1 and 2. On the other hand, it is slightly larger root-mean-square (RMS) difference than the previous one and NCEPs for the comparison using the KEO buoy data. This may be due to the deficit of high wind speed data in the buoy measurement. The high resolution product, together with sea surface temperature (SST) one, is used to examine a new type of relationship between the lower atmosphere and upper ocean in the Kuroshio Extension region.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.186-197
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• 2023

In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy's status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of 'AIR_TEMPERATURE' data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real-world scenarios.

• 한국해양학회지
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• v.30 no.1
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• pp.27-38
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• 1995

For the study of oceanic surface current, this work presents a system design which is composed of three parts, a Global Positiong System(GPS) unit, a transmitter with radio frequency (RF) modem and an antenna which are housed in a plastic spherical buoy, and computerised of VHF receiving system. The key idea for this study is to employ a commercially available GPS on a drifting buoy and to utilize the receiver position information from the buoy in determining the Lagrangian motion of surface ocean waters. Great efforts has been paid to the system design which would demand several points in harsh conditions common in the sea surface, that is power supply problems housed inside of a plastic buoy, optimizing transmitting radio frequency which limits transmitting distance to a receiving station. for all these difficulties, the system appears to be promising in future oceanic applications and is considered to economical compared to ARGOS drift buoy which is being used by commercial base. We believe that the system needs to be improved in terms of several aspects such as a longer transmitting distance, a power supply and software. for the test experiments in situ, the system has employed off the coast of Ku Ryong Po int the southeast part of Korea and successfully collected the surface current data. The results are presented for two cases from 21 to 31, March 1994 and 21 to 25, June 1994 in terms of current statistics and trajectories of drifting buoys.