• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.341-346
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• 2008

This paper is to develop a monitoring system with diagnosis for smart cargo sensors that is for management and maintenance of the liquid cargo ships. The main goal of the system is to achieve the total automation system of the cargo sensor. By this study, the active smart sensor for the liquid cargo ships is designed and developed that guarantees high-confidence, stability, and durability. The proposed system consists of a monitoring part of the steam pressure, high-level monitoring, over flowing monitoring, gas monitoring, and tank temperature monitoring. The signals transferred from each unit system are used for sensor diagnosis based on confidence and accuracy. Finally, in this study, the total supervisory monitoring system is developed to maintain and manage the cargo effectively based on fault diagnosis and prognosis of the each sensor system.

• Journal of information and communication convergence engineering
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• v.12 no.3
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• pp.168-172
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• 2014

In this paper, we propose an algorithm that can efficiently detect and monitor multiple ships in real-time. The proposed algorithm uses morphological operations and edge information for detecting and tracking ships. We used smoothing filter with a $3{\times}3$ Gaussian window and luminance component instead of RGB components in the captured image. Additionally, we applied Sobel operator for edge detection and a threshold for binary images. Finally, object labeling with connectivity and morphological operation with open and erosion were used for ship detection. Compared with conventional methods, the proposed method is meant to be used mainly in coastal surveillance systems and monitoring systems of harbors. A system based on this method was tested for both stationary and non-stationary backgrounds, and the results of the detection and tracking rates were more than 97% on average. Thousands of image frames and 20 different video sequences in both online and offline modes were tested, and an overall detection rate of 97.6% was achieved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1387-1392
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• 2003

For the structure of VMS by converting on digital the position reporting of departure fishery ship in the fishery communication that be required the management & operation of information in organizational. In particular, Must be made the regional & concentrational of the position reporting information. The division of region is considered to the circumstance of radio wave, fishing area, quantity of fishery ship and communication traffic etc.. It is capable to the DB of VMS by concentrate in head quarters, which is acquisition the position reporting information of respective region. In this study have designed for building of fishery information network and automatic transmission of the position reporting information from a fishery ship.

• Journal of Navigation and Port Research
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• v.37 no.6
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• pp.567-574
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• 2013

Although Korea coastal area has the increasing potential marine accident due to frequent ship's encounter, increased vessel traffic and large vessel, there is no specific model to evaluate the navigating vessel's risk considering the domestic traffic situation. The maritime transport environmental assessment is necessary due to the amended maritime traffic law. However, marine safety diagnosis is now carried out by foreign model. In this paper, therefore, we suggest a domestic traffic model reflecting the characteristics of korea coastal area and navigator's risk as we named PARK(Potential Assessment of Risk) model. We can evaluate the subjective risk by establishing the model and model output into maritime risk exposure system. To evaluate this model's effectiveness, we used ship handling simulation and applied, analyzed collision accident which occurred in korea coastal area. And also, we applied integrated to an ECDIS program for monitoring traffic risk of vessels with real time based AIS data and apply to evaluate traffic risk in busan harbor waterway. As a result, we could evaluate busan harbor waterway risk effectively.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.2
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• pp.163-168
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• 2008

Ship detection from satellite remote sensing is a crucial application for global monitoring for the purpose of protecting the marine environment and ensuring marine security. It permits to monitor sea traffic including fisheries, and to associate ships with oil discharge. An automatic ship detection approach for RADARSAT Fine Synthetic Aperture Radar (SAR) image is described and assessed using in situ ship validation information collected during field experiments conducted on August 6, 2004. Ship detection algorithms developed here consist of five stages: calibration, land masking, prescreening, point positioning, and discrimination. The fine image was acquired of Ulsan Port, located in southeast Korea, and during the acquisition, wind speeds between 0 m/s and 0.4 m/s were reported. The detection approach is applied to anchoring ships in the anchorage area of the port and its results are compared with validation data based on Vessel Traffic Service (VTS) radar. Our analysis for anchoring ships, above 68 m in length (LOA), indicates a 100% ship detection rate for the RADARSAT single beam mode. It is shown that the ship detection performance of SAR for smaller ships like barge could be higher than the land-based radar. The proposed method is also applied to estimate the ship's dimensions of length and breadth from SAR radar cross section(RCS), but those values were comparatively higher than the actual sizes because of layover and shadow effects of SAR.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.5
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• pp.78-87
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• 1994

In this paper design and implementation of ship's distributed remote control system using dual-microprocessor is presented for real time process. The proposed system is implemented with the single chip microprocessors in tightly coupled mode and results in speed up of $s_p$=1.74. Under the assumption that the nodes are interconnected in multidrop, the overall system performance such as average throughout-delay characteristics and effective throughput are analyzed using M/G/1 queneing model, and results show that the proposed node can be used in medium sized distributed monitoring and control system.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.105-106
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• 2006

In this paper we describe a driving, control and monitor of ship's emergency lighting system using power line modem.(PLM). Through this paper, experiment confirms that ON-OFF control of multiple SELP, real time transmission and monitor of parameters as to voltage, current, and power values are performed appropriately by PLM communication.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.1108-1112
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• 2005

Recently, the fuel charge is accounted for very high in the navigation cost. Therefore Shipowner is tried to find method for reducing oil consumption. ERCS(Energy Reduced Cooling System) is one of the method. The ERCS algorithm operates to decrease a power consumption of main sea water cooling pump through inverter control. We have developed ERCS controller with algorithm. The ERCS controller consists of CPU board, Digital I/O board, A/D board, D/A board and LCD/SW board. We tested with dummy signal to confirm the algorithm working correctly and achieved the good results. Before soon we will test under real condition in the ship and expect to get the result as forecasted.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.230-232
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• 2019

There is an accelerating need for ocean sensing where autonomous vehicles can play a key role in assisting engineers, researcher and scientists with environmental monitoring and collecting oceanographic data. This paper is performed to develops an autonomous sailing drone to be used as a sensor carrying platform for autonomous data acquisition at Sea. From a sailing drone design viewpoint, it is important to establish reliable prediction methods for sailing drone's resistance. The required power for the propulsion unit depends on the ship resistance and speed. There are three solutions for the prediction of ship resistance as follow analytical methods, model tests in tanks and Computational Fluid Dynamics (CFD). The present paper aims at simulating sailing drone friction resistance using numerical method. The dynamic mesh motion is used to describe the sailing drone movement.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.35-44
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• 2018

Monitoring through Synthesis Aperture Radar (SAR) is responsible for marine safety from floating icebergs. However, there are limits to distinguishing between icebergs and ships in SAR images. Convolutional Neural Network (CNN) is used to distinguish the iceberg from the ship. The goal of this paper is to increase the accuracy of identifying icebergs from SAR images. The metrics for performance evaluation uses the log loss. The two-layer CNN model proposed in research of C.Bentes et al.[1] is used as a benchmark model and compared with the four-layer CNN model using data augmentation. Finally, the performance of the final CNN model using the VGG-16 pre-trained model is compared with the previous model. This paper shows how to improve the benchmark model and propose the final CNN model.