• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.319-322
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• 2014

VTS(Vessel Traffic Center)는 관할해역의 해상교통데이터를 수집하여 해상교통관제를 수행하고 있다. 이러한 해상교통데이터는 가공되지 않는 정보이므로, 관제사 및 선박 등 사용자가 유용하게 활용할 수 있는 형태로의 분석이 필요하다. 이는 객관적인 데이터로 관제사 및 선박에서 해상교통 안전정책을 수립하는데 중요하다. 이를 위해 본 연구에서는 수년간 VTS에 축적되고 있는 BIG DATA를 활용하여 해상교통패턴을 분석하고자 한다. 분석하는 해상교통패턴은 통항분포, 선종별 항적 비교, 예부선의 강 조류 주의구역 판별, 항로상 어선 조업 현황분석 등을 통해 빅데이터를 활용한 관제구역설정, 집중관제구역 검토가 가능하다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.267-268
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• 2022

Jeju coastal waters are limited to high-risk areas due to the passage of international cruise ships, passenger ships, with a large number of people and fishing boats, or to the jeju port and the jeju civilian-military combined port and near by seas, so a VTS system will be established along jeju and seogwipo coast. There is no accurate standard for determining the number of people required by the maritime traffic control center. Therefore, this study calculated the required operating personnel for control seats on the coast of jeju and seogwipo by using VTS big data to efficiently calculate the workload of maritime traffic control. It is judged that this study can be used basic data for research that sets the standard for calculating the control workload.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.379-384
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• 2013

For effective ship management in VTS(Vessel Traffic Service), it needs to assess the external force acting on ship. Big data in maritime traffic can be roughly categorized into two groups. One is the traffic information including ship's particulars. The other is the external force information e.g., wind, sea wave, tidal current. This paper proposes the method to assess the external force acting on ship using big data in maritime traffic. To approach Big data in maritime traffic, we propose the Waterway External Force Code(WEF code) which consist of wind, wave, tidal and current information, Speed Over the Water(SOW) of each ship, weather information. As a results, the external force acting a navigating ship is estimated.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.4
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• pp.311-318
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• 2016

The VTS concept was located as a principal methods of maritime safety administration in world's major harbors and expected to become the pivotal role for the future of the maritime and harbor society with e-Navigation epoch. If recent limelight concept of big-data has been included in aspect of information gathering and analysis with various studies, it's required advanced studies to improve the information analysis capability and application range of the data that can be mining by the VTS. In this study, contrast to other studies that aimed quantitative analysis as communication number, it can be mining the time information and each of the communication VTS for the target vessel, including qualitative analysis, such as the purpose or the type of communication. This comparison across multiple items of the collected information, and presenting the VTS data mining model (VCDF) that can be analyzed for the purpose of analyzing way, type and number of communication by ship's type, also number of violations through VTS communication. First, In Busan port case, it shows frequently information service and shows frequently communicating with particular types of vessels. Second, Passive VTS carried out notwithstanding many kinds of traffic violations due to communication congestion. This arranged information can be used as data for the analysis, as possible the level of traffic for VTSO situational awareness, which pointed to the 'workloads' in 'IALA Guideline' and could be used as a database for future research of e-Navigation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.15-16
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• 2023

해상교통관제 구역은 항만 시설을 사용하기 위한 입·출항 선박, 연안 해역을 이동하는 선박 등이 서로 복잡하게 운항하는 교통 패턴을 가지고 있다. 이를 안전하고 효과적으로 관리하기 위해 해상교통관제센터(VTS)에서는 선박을 실시간 모니터링하며 관제 업무를 수행하고 있지만, 교통 혼잡 상황에서는 업무 로드의 증가로 인해 관제 공백이 발생하기도 한다. 이에 교통 혼잡도 및 혼잡 구역을 예측한다면보다 효율적인 관제가 가능하지만 현재는 관제사의 경험에 전적으로 의존하고 있는 실정이다. 본 논문에서는 VTS 관점에서의 교통 혼잡을 정의하고, 과거 항적 데이터를 이용하여 항내 선박 교통 혼잡도 및 혼잡 구역을 예측하는 방법을 제안하였다. 또한, 실해역 데이터(대산항 VTS)를 적용하여 제안된 기술이 관제지원 도구로서 활용될 수 있는지 검토하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.24-25
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• 2019

최근 빅데이터 기술 개발로 방대한 데이터의 유의미한 분석 및 예측이 용이해졌다. 선박교통관제센터에서는 각종 센서와 다양한 정보를 기반으로 VHF 교신을 통해 선박교통관제를 수행한다. 관제사가 활용하는 레이더, AIS, Port-MIS. 센서 등의 데이터들이 디지털로 저장되고 있으며, 관제사의 VHF 교신내용은 디지털파일로 저장되어 선박교통관제센터의 서버 2개월간 보관된다. 본 논문에서는 관제 결과로 저장되고 있는 관제 로그 데이터를 활용하여 빅데이터를 구성하고 이를 기반으로 유의미한 정보를 생성할 수 있는 방안을 연구하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.265-266
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• 2022

전통적으로 선박교통관제서비스는 정보제공(INS), 항행지원(NAS), 교통관리(TOS)로 구분되어 왔으나, 최근 IMO 결의서 A.1158의 개정을 통해 선박교통관제서비스의 목적을 선박 항해에 안전하지 않은 상황을 선제적으로 모니터링하고 통제하는 것으로 규정하고 있다. 이를 위해 기존의 VTS 서비스 용어들을 모두 삭제하였으며, IALA에서도 관제사의 의사결정도구에 대한 개정을 논의하고 있는 상황이다. 이에 본 논문에서는 빅데이터 기반의 관제사 의사결정도구를 제안하였으며, 적용 가능성을 검토하였다. 제안하는 방법은 관제사의 주관적인 판단과 단순한 규칙에 의존하던 기존의 관제 방법과는 달리 데이터를 기반으로 하는 객관적인 관제 기준을 제시할 수 있으며, 이러한 방법이 실제 관제 현장에 적용되어 해양사고를 방지하고, 항만의 운영 효율을 향상시킬 수 있기를 기대한다.

• 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.