• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.4
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• pp.294-302
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• 2019

As a series of fundamental researches on the development of an automatic identification monitoring system for fishing gear. Firstly, the study on the installation method of automated identification buoy for the coastal improvement net fishing net with many loss problems on the west coast was carried out. Secondly, the study was conducted find out how to install an automatic identification buoy for coastal gill net which has the highest loss rate among the fisheries. GPS for fishing was used six times in the coastal waters around Seogwipo city in Jeju Island to determine the developmental status and underwater behavior to conduct a field survey. Next, a questionnaire was administered in parallel on the type of loss and the quantity and location of fishing gear to be developed and the water transmitter. In the field experiment, the data collection was possible from a minimum of 13 hours, ten minutes to a maximum of 20 hours and ten minutes using GPS, identifying the development status and underwater behavior of the coastal gillnet fishing gear. The result of the survey showed that the loss of coastal net fishing gear was in the following order: net (27.3%), full fishing gear (24.2%), buoys, and anchors (18.2%). The causes were active algae (50.0%), fish catches (33.3%) and natural disasters (12.5%). To solve this problem, the installation method is to attach one and two electronic buoys to top of each end of the fishing gear, and one underwater transmitter at both ends of the float line connected to the anchor. By identifying and managing abnormal conditions such as damage or loss of fishing gear due to external factors such as potent algae and cutting of fishing gear, loss of fishing gear can be reduced. If the lost fishing gear is found, it will be efficiently collected.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.397-402
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• 2021

The real-name electric fishing gear system is one of the important policy capable to build 'abundant fishing ground' and to protect marine environment. And, fishing gear automatic-identification system is one of IoT services that can implement above-mentioned policy by using communication such as low power wide area (LPWA) and multi-sensing techniques. Fishing gear automatic -identification system can gather the location data and lost/hold data from electric buoy floated in sea and can provide them to fishermen and monitoring center in land. We have developed the communication modules and electric buoy consisted of fishing gear automatic-identification system. In this paper, we report the test results of communication distance between electric buoy and wireless node installed in fish boat and location error of electric buoy. It is confirmed that line of sight (LOS) distance between electric buoy and wireless node is obtained to be 62 km, which is two times of the desired value, and location error is obtained to be CEP 1 m, which is smaller than the desired value of CEP 5 m. Therefore, it is expected that service area and accuracy of the developed fishing gear automatic-identification system is more extended.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.390-396
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• 2021

In this research, design and fabrication of marine repeater capable to extend communication coverage in monitoring system of fishing gear automatic identification, which is one of implementation method of the real-name electric fishing gear system declared by Ministry of Oceans and Fisheries in 2016, is reported. The proposed marine repeater is fabricated in a form of RF repeater with interference cancellation system (ICS), which can cancel the oscillation due to feedback signal between service antenna and link antenna. In design process, we secure the isolation of 30 dB between service antenna and link antenna. It is confirmed that when the level of feedback signal into repeater input be lower of 15 dB than repeater gain, error vector magnitude due to oscillation can be lower than the performance criterion of 6%, from the test verification. It is expected that the service coverage will be extended by applying the developed marine ICS RF repeater into marine IoT network including monitoring system of fishing gear automatic identification.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.81-87
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• 2021

Many merchant ships sail in the waters surrounding Jeju Island and many fishing vessels catch fish using gill nets, trolling lines, and so on. Meanwhile, marine waste has collected in the coastal waters of Jeju Island. However, there has been little research on the collection of marine waste in coastal waters. In this study, marine waste deposited in Jeju Island's northwest sea was collected using Jeju National University's training ship, and related vessels were analyzed for each gear type. According to the results, most coastal waters had abandoned fishing grounds, which were from fishing vessels, and a large proportion of them was gill net and trap fishing gear. To analyze how much marine waste is accumulating in a certain area and ship's stay time, we use automatic identification system (AIS) data to extract the time spent in the target sea, and the amount of marine waste per hour was analyzed in a unit distance of 1 ㎢. The average amount of marine waste generated per hour in the unit area was found to be 0.94 kg for gillnet fishing gear, 3.49 kg for trap fishing gear, 0.10 kg for trawl fishing gear, 0.11 kg for longline fishing gear, and 0.02 kg for other fishing gear.

• Journal of IKEEE
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• v.25 no.1
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• pp.193-200
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• 2021

In order to prevent illegal fishing and reduce lost fishing gear, it is necessary to develop a constant and continuous fishing gear monitoring system in the marine environment. In this paper, we design a long-term operational, reliable system model with communication coverage of more than 25Km considering the reality of gradually expanding fishing activity due to the depletion of fishery resources and marine environments. The design results are implemented to verify the operability of the system by separating the communication success rate of SKT and private LoRa networks and verifying the control function of each control system through the collected location information, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1228-1236
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• 2018

Recently, the maritime environment contaminated by the abandoned fishing gears. To solve this problem, there requires systematic management techniques for the fishing gears based on ICT technologies. The existed systems are optionally used by owners, but the systems need to adopt the monitoring and control architecture for integrated national surveillance. To do this, we designed an architecture for effective monitoring and management which collects position and state information using automatic identification buoy (AIB) device, to send the fishing ship, administrator ship, and shore side control center based on the IoT networks. Especially, in this paper, we developed the ENC-based integrated control system for efficient management which provides functions for position indication, state information display and loss alarm of fishing gears. Also, we conduct performance tests for data processing and visualization functions of the system to use a virtual buoy generation module.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.33-34
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• 2019

대부분의 나라에서는 어선의 위치발신장치를 이용하여 어선 조업상황을 모니터링 한다. 우리나라도 어선의 위치발신장치를 이용하여 어선 조업량, 불법조업 유무를 판별한다. 현재까지는 어선의 불법조업 유무 판별은 어선의 위치정보 기반으로 이루어 졌으나, 허가받지 않는 어구를 사용하는 불법조업에 대한 판별은 불가능 하였다. 이에 본 논문에서는 어선 항적과 조업면허 데이터를 이용하여 데이터 기반의 어선 조업 판별모델을 개발하고자 한다. 이를 위해 어선 항적데이터를 시계열 단위로 전처리하여 학습 이미지들을 생성하고, 해당 어선의 조업면허 정보를 레이블로 하여 학습 데이터를 제안하는 딥러닝 모델에 적용한다. 제안하는 방법의 검증을 위해 1년 동안 제주 주변해역에서 조업하는 어선의 선박자동식별장치의 항적데이터를 수집하여 실험을 하였다. 실험 결과 제안한 방법의 분류정확도는 71.5%를 얻었다.