• 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 Navigation and Port Research
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• v.46 no.5
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• pp.409-417
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• 2022

The International Association of Lighthouse Authorities (IALA) utilizes a questionnaire to investigate the status of Aids to Navigation (AtoN) around the world. However, results of the IALA questionnaire have limited use because respondent understanding is inconsistent. In addition, there is uncertainty regarding the appropriateness of the questionnaire content. Furthermore, the overall response rate is low. Therefore, the status of AtoN is not clearly understood. AtoN data from around the world are generated hourly. Thus, big data solutions are required to effectively exploit the information. Digitization of analog data is an important component of building big data. Hence, the IALA has developed a Maritime Resource Name (MRN) scheme and an information exchange standard. Here, we used the AtoN information exchange standard and designed an S-201-based big data construction process that could collect and manage global AtoN information. In this study, construction of an IALA AtoN portal was proposed as the core of the construction of the AtoN big data. The process was divided into three stages. IALA AtoN portal is developed by IALA with the goal to provide various meaningful statistical analysis results based on AtoN data while managing AtoN information around the world based on S-201. If an AtoN portal capable of constructing S-201-based big data is developed, then a data collection and storage system that can gather basic S-201 AtoN data from the IALA and global AtoN management agencies could be achieved. Furthermore, insightful statistical analysis of AtoN status worldwide and changes in manufacturing technology will be possible.

• Journal of the Korean Society for Marine Environment & Energy
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• v.20 no.2
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• pp.117-125
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• 2017

SNS Big-data Analysis means to find potential value from big data which has produced by the social media. In this paper, SNS Big-data has been analysed to find Korean concerns by using 24 key words from the marine and fisheries sector. Among 24 key words, seafood, shipping and Dokdo Island are the most mentioned ones. Some key words such as ocean policies and marine security that have less concerns have bess mentioned less. Also, key words that are led by government are mostly mentioned by news media, but key words that are led by private sector and have intimate relationship with people's lives are mostly mentioned by Blogs and Twitters. Therefore, reflecting close national concerns by SNS Big-data Analysis and especially resolving negative factors are the most significant part of the policy establishment. Also, differentiated promotion methods need to be prepared because the frequency of key words mentioned from each type of media are different.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.126-128
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• 2013

빅데이터(Big Data)는 현재 생산되고 있는 데이터 중 그 규모가 방대하고, 생성 주기가 짧으며, 수치 데이터 뿐 아니라 텍스트 이외의 멀티미디어 등 비정형화된 데이터를 포함하는 대규모 데이터를 말한다. 빅데이터를 처리하여 가치 있는 정보를 추출하는 방법에 관한 연구가 활발하게 진행되고 있으며, 이를 바탕으로 빅데이터가 다양한 분야에서 활용되고 있다. 현재 국내 주식시장에서도 빅데이터를 이용하여 기업의 투자에 활용하고 있다. 이 논문에서는 인터넷의 증권과 관련된 뉴스를 수집하여 수집된 뉴스와 주가 지수를 이용하여 기업 뉴스 평가 시스템을 개발하는 방법을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.6
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• pp.567-580
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• 2016

In recent years, our society, because of the arrival of a new paradigm according to the rapid changes in ICT has entered into future smart society and the ubiquitous era. So it can be a notable turning point in the marine disaster prevention system with big data, aspects of the era change. Therefore, this study was to derive a desirable vision for the big data marine disaster prevention informatization in terms of ICT maritime disaster prevention system development as preparedness for the maritime disaster by applying 'scenario planning' as a foresight method. Soon this study derived a successful marine disaster prevention informatization strategy as preparedness for the maritime disaster like Ferry Sewol Disaster. It proposed the big data marine disaster prevention informatization system with the use of the administrative aspects of information with spatial informatization as big data information. Also this study explored the future leadership strategy of the big data marine disaster prevention informatization in smart society. Eventually in 2030 to around, In order to still remain our marine disaster prevention informatization as a leading ICT nation, this study suggested the following strategy. It is important to ready the advanced Big Data administrative spatial informatization system In terms of prevention of incidents like Ferry Sewol Disaster.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.63-63
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• 2017

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1195-1202
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• 2016

Recently, a lot of studies that applying the big data technology to various fields, are progressing actively. In the maritime domain, the big data is the meaningful information which makes and gathers by the navigation and communication equipment from the many ships on the ocean. Also, importance of the maritime safety is emphasized, because maritime accidents are rising with increasing of maritime traffic. To support prevention of maritime accidents, in this paper, we developed a vessel traffic display and statistic system based on AIS messages from the many vessels of maritime. Also, to verify the developed system, we conducted tests for vessel track display function and vessel traffic statistic function based on two test scenarios. Therefore, we verified the effectiveness of the developed system for vessel tracks display, abnormal navigation patterns, checking failure of AIS equipments and maritime traffic statistic analyses.

• Journal of Korea Trade
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• v.26 no.1
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• pp.113-125
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• 2022

Purpose - The primary purpose of this study is to verify whether the target set out by the International Maritime Organization (IMO) for reducing carbon emissions from ships can be achieved by quantitatively analyzing the trends in technological advances of fuel oil consumption in the container shipping market. To achieve this purpose, several scenarios are designed considering various options such as eco-friendly fuels, low-speed operation, and the growth in ship size. Design/methodology - The vessel size and speed used in prior studies are utilized to estimate the fuel oil consumption of container ships and the pace of technological progress and Energy Efficiency Design Index (EEDI) regulations are added. A database of 5,260 container ships, as of 2019, is used for multiple linear regression and quantile regression analyses. Findings - The fuel oil consumption of vessels is predominantly affected by their speed, followed by their size, and the annual technological progress is estimated to be 0.57%. As the quantile increases, the influence of ship size and pace of technological progress increases, while the influence of speed and coefficient of EEDI variables decreases. Originality/value - The conservative estimation of carbon emission drawn by a quantitative analysis of the technological progress concerning the fuel efficiency of container vessels shows that it is not possible to achieve IMO targets. Therefore, innovative efforts beyond the current scope of technological progress are required.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1179-1187
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• 2019

In today's technology environment, most big data-based applications and solutions are based on real-time processing of streaming data. Real-time processing and analysis of big data streams plays an important role in the development of big data-based applications and solutions. In particular, in the maritime data processing environment, the necessity of developing a technology capable of rapidly processing and analyzing a large amount of real-time data due to the explosion of data is accelerating. Therefore, this paper analyzes the characteristics of NiFi, Kafka, and Druid as suitable open source among various open data technologies for processing big data, and provides the latest information on external linkage necessary for maritime service analysis in Korean e-Navigation service. To this end, we will lay the foundation for applying open data framework technology for real-time data processing.

• 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.