• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.245-251
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• 2005

Ship's auto pilot is must necessary the azimuth data, which is supported by a gyro, geomagnetism and GPS compass. The gyro compass is operation of stability & correct , therefore it is used by big size shipping because of high cost. The other side, medium and small size shipping are used the geomagnetism and GPS compass of low cost. This paper have studied that the two jobs are going on at the same time both of there's advantage. Which is asked the algorithm for stability azimuth data on reject methode the defect of respect with geomagnetism & GPS compass.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.54-55
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• 2020

In 4th Industrial Revolution, technologies such as artificial intelligence, Internet of Things, and Big data are closely related to the maritime industry, which led to the birth of autonomous vessels. Due to the technical characteristics of the current vessel, the speed cannot be suddenly lowered, so complex communication such as the help of a tug boat, boarding of a pilot, and control of the vessel at the onshore control center is required to berth at the port. In this study, clustering analysis was used to resolve how to establish control criteria for vessels to enter port when autonomous vessels are operating. K-Means clustering was used to quantitatively stage the arrival pattern based on the accumulated AIS(Automatic Identification System) data of the incoming vessel, and the arrival phase using SOG(Speed over Ground), COG(Course over Ground), and ROT(Rate of Turn) Was divided into six phase.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.726-734
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• 2019

The current maritime industry is expected to have a significant impact on the role of maritime-related technologies and systems, especially seafarers, in the rapidly changing Fourth Industrial Revolution. The Maritime Autonomous Surface Ship (MASS) aims to reduce the number of safety accidents and improve seafarers' working environment. With regard to MASS, the International Maritime Organization has been trying to minimize unexpected impact in the maritime education and training sector by establishing international conventions such as the Standards of Training, Certification and Watchkeeping for Seafarers. However, domestic designated educational institutions have not yet established an education and training scheme to develop seafarers who will be on board for MASS. Therefore, this paper reviews the technology of MASS, analyzes the changes in education and training in order to upgrade the qualifications, and suggests the competencies of smart seafarers equipped with the integrated management ability required for Artificial Intelligence, Big Data, Cybersecurity, and the Digital System Revolution through education and training. In addition, this study provides basic information for the education and training of seafarers who are optimized for the rapidly changing technological environment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.199-209
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• 2022

As the uncertainty of technology development and market needs increases due to changes in the global business environment, the interest and demand for R&D activities of individual companies are increasing. To respond to these environmental changes, technology commercialization players are paying great attention to enhancing the qualitative competitiveness of R&D. In particular, R&D companies in the marine and fishery sector face many difficulties compared to other industries. For example, the R&D environment is barren, it is challenging to secure R&D human resources, and it is facing a somewhat more difficult environment compared to other sectors, such as the difficulty in maintaining R&D continuity due to the turnover rate of researchers. In this study, based on the empirical data and patent status of private companies closely related to the R&D technology status, big data analysis, and simulation analysis methods were used to identify the relative position of individual companies' R&D capabilities and industrial perspectives. In this study, based on industrial evidence and patent applications closely related to the R&D technology status, the R&D capabilities of individual companies were evaluated using extensive data analysis and simulation analysis methods, and a statistical test was performed to analyze if there were differences in capabilities from an industrial point of view. At this time, the industries to be analyzed were based on all sectors, the maritime industry, the fisheries industry, and the maritime industry integration sector. In conclusion, it was analyzed that there was a certain level of difference in the R&D capabilities of individual companies in each industry sector, Therefore when developing a future R&D capability system, it was confirmed that it was necessary to separate the population for each industry and establish a strategy.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.3
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• pp.281-287
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• 2023

Establishing a ship's passage plan is an essential step before it starts to sail. The research related to the automatic generation of ship passage plans is attracting attention because of the development of maritime autonomous surface ships. In coastal water navigation, the land, islands, and navigation rules need to be considered. From the path planning algorithm's perspective, a ship's passage planning is a global path-planning problem. Because conventional global path-planning methods such as Dijkstra and A^* are time-consuming owing to the processes such as environmental modeling, it is difficult to modify a ship's passage plan during a voyage. Therefore, the D^* algorithm was used to address these problems. The starting point was near Busan New Port, and the destination was Ulsan Port. The navigable area was designated based on a combination of the ship trajectory data and grid in the target area. The initial path plan generated using the D^* algorithm was analyzed with 33 waypoints and a total distance of 113.946 km. The final path plan was simplified using the Douglas-Peucker algorithm. It was analyzed with a total distance of 110.156 km and 10 waypoints. This is approximately 3.05% less than the total distance of the initial passage plan of the ship. This study demonstrated the feasibility of automatically generating a path plan in coastal navigation for maritime autonomous surface ships using the D^* algorithm. Using the shortest distance-based path planning algorithm, the ship's fuel consumption and sailing time can be minimized.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.158-159
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• 2023

With the development and state-of-the-art of ocean satellites, wide-area management of the waters around Korea has become possible. In particular, in the field of ship operation, as autonomous navigation technology based on artificial intelligence and big data is being developed, there is a need for additional analysis and observation through ocean satellite data.. Researches that can combine ship operation with ocean satellite data include ship detection based on ocean satellites and ship navigation assistance using marine weather forecasting.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.515-524
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• 2022

To effectively collect, manage, and share the maritime traffic information, it is necessary to identify the technology trends concerning this particular information and analyze its current status and problems. Therefore, this study observes the domestic and foreign technology trends involving maritime traffic information while analyzing and summarizing the current status and problems in collecting, managing, and sharing it. According to the data analysis, the problems in the collecting stage are difficulties in collecting visual information from long-distance radars, CCTVs, and cameras in areas outside the LTE network coverage. Notably, this explains the challenges in detecting smuggling ships entering the territorial waters through the exclusive economic zone (EEZ) in the early stage. The problems in the management stage include difficult reductions and expansions of maritime traffic information caused by the lack of flexibility in storage spaces mostly constructed by the maritime transportation system. Additionally, it is challenging to deal with system failure with system redundancy and backup as a countermeasure. Furthermore, the problems in the sharing stage show that it is difficult to share information with external operating organizations since the internal network is mainly used to share maritime transportation information. If at all through the government cloud via platforms such as LRIT and SASS, it often fails to effectively provide various S/W applications that help use maritime big data. Therefore, it is suggested that collecting equipment such as unmanned aerial vehicles and satellites should be constructed to expand collecting areas in the collecting stage. In the management and sharing stages, the introduction and construction of private clouds are suggested, considering the operational administration and information disclosure of each maritime transportation system. Through these efforts, an enhancement of the expertise and security of clouds is expected.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.116-117
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• 2019

자율운항선박 (MASS [Maritime Autonomous Surface Ship]) 선박은 육상 관제 센터에서 선박 기자재를 상태를 실시간 모니터링하고, 컨트롤 할 수 있는 기능을 탑재하는 걱이 필수적이다. 해상과 육상을 연결하는 통신 기술 발달 뿐 아니라, 4차 산업혁명시대에 따라 빅데이터 처리 기술과 이런 빅데이터를 딥러닝 기법을 통해 분석/예측할 수 있는 기반이 마련되고 있다. 따라서 선박 기자재를 빅데이터 기반 딥러닝 등의 기법을 활용하여 원격 진단 및 유지보수 할 수 있는

• Journal of Navigation and Port Research
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• v.42 no.5
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• pp.341-346
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• 2018

Supramax bulk carriers cover a wide range of ocean transportation requirements, from major to minor bulk cargoes. Market forecasting for this segment has posed a challenge to researchers, due to complexity involved, on the demand side of the forecasting model. This paper addresses this issue by using technical indicators as input features, instead of complicated supply-demand variables. Artificial neural networks (ANN), one of the most popular machine-learning tools, were used to replace classical time-series models. Results revealed that ANN outperformed the benchmark binomial logistic regression model, and predicted direction of the spot market with more than 70% accuracy. Results obtained in this paper, can enable chartering desks to make better short-term chartering decisions.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.3
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• pp.677-689
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• 2013

Recently, the supplying of basic materials for construction of building as sand is big issues due to lack of shoreside supply. For solving this problem, many suppliers attempt to gather aggregate from the sea bottom of the EEZ & west coastal area of Korea. In this regard, the 'Jangantoe' which exists in the westside of the Daesan port is worth noticing as good seasand supplying areas. The Chungnam Aggregate Association have plan to gather of seasand from 'Gaduckdo 5 regions & Igok 3 regions' which lies westside about 6 miles off from the Jangantoe areas. This designated area also locates upper parts of the Gadaeam TSS(Traffic Separation Scheme) which is very useful passing routes for the sailing vessels of Inchon & Daesan ports. In this study, the evaluation of the safety for passing vessels in the vicinity of the seasand gathering area was performed by various methods of radar observations & GICOMS AIS data for marine traffics and vessel traffic-flow simulation of the 'Marine Traffic Safety Diagnostic Scheme'. By the results of this evaluation, I suggested comprehensive countermeasures for the safety of passing vessels in the near the seasand gathering area.