• 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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.6
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• pp.82-90
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• 2019

To reduce emissions of marine pollutants, regulations are being tightened around the world. In the shipbuilding and shipping industries, various countermeasures are being put forward. As there are limits to applying countermeasures to ships already in operation, however, it is necessary for these vessels to use energy efficiently. The sensors installed on ships typically gather a very large amount of data, and thus a big data platform is needed to manage and analyze the data. In this paper, we build a big data analysis platform based on Hadoop and Spark, and we present a method to detect abnormal ship operation using the platform. We also utilize real ship operation data to discuss the data analysis experiment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.137-139
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• 2023

MARPOL (Maritime Pollution Treaty) 부속서 (Annex VI) 경우 대기오염 규제 내용이며, 최근 선박 배기가스 배출규제 강화 목적 개정됨에 따라 관련 규정을 충족하기 위한 적극적인 조치가 요구된다. 예를 들어 Sulfur Dioxide (SOx, 황산화물) 경우 2020년 기준 전 세계 해역 내 운항하는 선박은 황 함유량 0.5% 기준의 배출 요구 기준을 충족해야 한다. 배출규제 해역 지정 시 해당 해역 선박 배기가스 배출량 계산 산정 기준 확립이 필요함에 따라 대기환경에 대한 종합적인 분석이 필수적으로 요구된다. 본 연구에서는 황산화물 배출량 산출 방법론으로써 그리드 셀 내 선박 점유시간을 계산한다. 점유시간이 길수록 선박 통항 및 배기가스 배출이 밀집되어 있음을 의미한다. 밀집도 분석에 더불어 선박의 특성이 반영된 시간당 배출량을 적용하여 배출 공간 인벤토리를 구축하였으며 분석 결과를 GIS (Geographical Information System) 환경에서 공간 지도로 시각화하였다. 기존 국내 황산화물 배출규제 해역의 효과 평가에 더불어 외항 범위까지 규제 확대 시나리오확립 후 비교 평가를 통하여 배출량 감소 효과를 정량적으로 확인하였다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.1
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• pp.15-21
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• 2020

This study analyzes the results of applying the ISO19030 (hull and propeller performance monitoring method) standard to an actual 178 k bulk vessel. Recently, there have been many attempts to apply various energy reduction solutions to vessels to continuously strengthen GHG reduction regulations and secure maritime competitiveness. However, it is not easy to quantitatively analyze the performance of a ship. To resolve these problems, shipping companies, marine paint companies, ship owners, and transportation associations have appointed specialists and standardized the ISO19030 (standard of hull and propeller performance monitoring method) guidelines in 2016 after three years of continuous review. The ISO19030 standard provides methods to monitor hull and propeller performance quantitatively through standardized procedures, thus allowing ship managers to arrive at informed decisions for hull and propeller maintenance, and to evaluate energy-saving solutions and ship-maintenance efficiency. The ISO19030 standard provides a method of analyzing the ship's own performance by collecting the ship's operation and agency data and correcting its environmental and operating factors. In this paper, we apply the ISO19030 standard to three actual ships and propose the ISO19030 application result and the improvement point of the current ISO19030 standard.

• The Journal of Bigdata
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• v.5 no.1
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• pp.181-188
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• 2020

As the size of the airport terminal grows in line with the rapid growth of aviation passengers, the advanced baggage handling system that combines various data technologies has become an essential element in order to handle the baggage carried by passengers swiftly and accurately. Therefore, this study introduces the method of analyzing the baggage handling capacity of domestic airports through the latest data analysis methodology from the process point of view to advance the operation of the airport BHS and the main points based on event log data. By presenting an accurate load prediction method, it can lead to advanced BHS operation strategies in the future, such as the preemptive arrangement of resources and optimization of flight-carrousel scheduling. The data used in the analysis utilized the APIs that can be obtained by searching for "Korea Airports Corporation" in the public data portal. As a result of applying the method to the domestic airport BHS simulation model, it was possible to confirm a high level of predictive performance.

• 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 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.

• The Journal of Bigdata
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• v.7 no.1
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• pp.125-137
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• 2022

The transportation industry is one of the important industries due to the geographical requirements surrounded by the sea on three sides of Korea and the problem of resource poverty, which relies on imports for most of its resource consumption. Among them, the proportion of the shipping industry is large enough to account for most of the transportation industry, and maintenance in the shipping industry is also important in improving the operational efficiency and reducing costs of ships. However, currently, inspections are conducted every certain period of time for maintenance of ships, resulting in time and cost, and the cause is not properly identified. Therefore, in this study, the proposed methodology, LSTM-AutoEncoder, is used to detect abnormalities that may cause ship failure by considering the time of actual ship operation data. In addition, clustering is performed through clustering, and the potential causes of ship main engine failure are identified by grouping outlier by factor. This enables faster monitoring of various information on the ship and identifies the degree of abnormality. In addition, the current ship's fault monitoring system will be equipped with a concrete alarm point setting and a fault diagnosis system, and it will be able to help find the maintenance time.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.78-80
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• 2021

This study is based on Degree of Recognition and AHP surveys for experts, this study investigates changes in the demand of seafarers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships(MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in seafarers' skills. It also analyzes and proposes a plan for cultivating seafarers accordingly. As a result of Degree of Recognition and AHP analysis, it is analyzed that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but jobs such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore based control.By evaluating the importance of change factors in the duties of seafarers in Maritime Autonomous Surface Ships, this study provides information on seafarers educational institutions response strategies for nurturing seafarers and prioritization of resource allocation, etc. The importance of factors was compared and evaluated to suggest changes in the duties of seafarers and methods of nurturing seafarers according to the introduction of Maritime Autonomous Surface Ships.It is expected that this study is meaningful as it systematically derived the duties and competency factors of seafarers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.45-46
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• 2023

현재 해운산업은 4차산업 인프라를 구축 중인 초입부 단계에 놓여져 있다. 미래 VTS운영시스템 개발을 위해 기존 시스템에서 보다 접근성이 용이하고 서비스 효율을 향상시킬 수 있는 방안을 모색할 필요가 있다. 현재 주어진 기술력, 인프라를 바탕으로 미래 VTS 운영시스템을 개발, 상용화에 성공한다면 자율운항선박, AI관제운영시스템 등 더 나은 미래 해운산업 기술개발에 중요한 자원이자 빅데이터가 될 수 있다.