• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.61-73
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• 2020

Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.1068-1070
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• 2022

우리나라의 무역 활동을 처리하는 항만은 국가 주요시설로 보안에 만전을 기하고 있다. 그러나 항만의 면적이 넓고 복잡하기 때문에 사각지대가 존재하고 사각지대에서의 불법행위 단속 건수는 매년 증가하고 있다. 이에 항만의 보안 강화를 위한 대책이 필요하다. 본 논문은 항만의 상황을 이동형 CCTV에 부착된 IoT 센서들로 인식하여 YOLOv5 딥러닝 모델로 분석한 후 웹 대시보드에 시각화하는 항만 보안 시스템을 제안한다. 이동형 CCTV는 특정 위치로 직접 이동할 수 있어 거리에 따라 해상도가 낮아지는 기존 CCTV의 단점을 보완할 수 있다. 또한 해당 시스템은 주변에서 쉽게 구할 수 있는 장비들과 오픈소스 라이브러리를 활용하기 때문에 다른 보안장비들에 비해 효율적인 비용으로 높은 보안 효과를 얻을 수 있다는 강점을 지닌다. 본 시스템은 항만시설뿐 아니라 군사시설, 물류시설 등 보안을 중요시하는 다른 분야에 확대 적용될 수 있다는 점에서 의의가 있다.

• Journal of Navigation and Port Research
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• v.45 no.4
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• pp.181-185
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• 2021

This study deals with the development of a phrase buoy control system that can receive and analyze phrase information using an IoT-based communication network to determine whether a phrase is normal or missing, to manage the current state of the phrase, check the status of the phrase in case of abnormal conditions in the phrase, and conduct management of the phrase. The fishing gear management system and integrated control structure design using an IoT-based communication network were developed, and a system test and verification were carried out to verify the effectiveness of the system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.223-224
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• 2019

This paper deals in a realization of IoT-based ship control system Recently, ARM/ATmega-based MCU (Micro Control Unit) has been widely used. In this paper, we report hardware and software programming to realize ship control system using MCU.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.185-187
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• 2023

고장 진단은 IoT 장비의 안전성과 효율성을 유지하는데 필요한 기술 중 하나이다. 따라서, 본 연구는 IoT 센서 데이터를 기반한 고장 진단 알고리즘을 개발하는데 목적이 있다. 본 연구는 알고리즘의 효율성을 개선하기 위해 기술통계량을 기반하여 데이터 차원을 축소하였으며, 이를 바탕으로 고장 진단 알고리즘의 정확도 및 연산시간을 개선하였다. 본 연구는 다양한 후보 알고리즘을 활용하여 고장진단을 수행하였으며, 정확도를 기반으로 가장 우수한 알고리즘을 선정하였다. 연구 결과, Isolation Forest 알고리즘이 가장 뛰어난 분류 결과를 나타내었다. 본 연구결과를 통해 IoT 센서의 안전성과 신뢰성을 향상시키는 데 도움을 줄 수 있다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.275-277
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• 2019

최근 항만물류부문 4차 산업혁명과 IoT 기술 확산으로 스마트 물류와 자동화 항만에 대한 정부의 R&D 동향과 PA가 참여하는 기술개발 R&D 사업에 대한 추진전략을 제시함.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.408-409
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• 2022

슬릿을 통한 표면파 통신 가능성을 시험 검증하고 이를 통한 선박 밀폐구역에서의 선박 IoT 무선통신 시스템 구현 방안을 고찰하기 위해 선박 밀폐구역에서의 표면파 통신 환경을 구현하였고, 슬릿의 크기, 모양, 재질 변화 조건에 따라 표면파 통신 가능 여부와 전송속도 변화를 확인하였다.

• Journal of Korea Port Economic Association
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• v.36 no.2
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• pp.1-18
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• 2020

The Internet of things (IoT) has been applied to a variety of industrial uses such as public service sectors, medical industries, automotive industries, and so on. Led by smart cities, this is typical. However, from a logistics perspective, the level of application is insufficient. This study examines the applicability of IoT-related technology in a container terminal, an object of the present invention, to derive an applicable plan. Analytic network process (ANP) analysis reveals the following results for IoT applications in container terminals: operating systems (26.7%), safety/environmental/security systems (26.4%), equipment maintenance systems (25.3%), and facility maintenance systems (21.6 %). The second ANP analysis reveals the following results: Economy (40.2%), productivity (21.1%), service level (19.5%), and utilizing technology level (19.2%). The application or standard of evaluation is important when applying IoT technology to container terminals; however, it is not concentrated in a certain area. It is desirable to build each container system with linkage and efficiency from a macroscopic view.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.296-297
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• 2022

A smart port refers to a port built based on digital technologies such as IoT, big data, AI, and block chain, and refers to a port that minimizes waste of time, space and resources as the only means of survival of the port. Sustainability refers to 'environmental, economic, and social characteristics that enable people to continue to use the environment, ecosystem, or publicly used resources'. It contains the meaning of 'future sustainability' that can be maintained in the future. In the face of the 4th industrial revolution, interest and realization of smart port construction and sustainability are actively progressing around the world. In this study, core indicators of the ESG (Enviornment, Social, Governance) area, which are key elements of sustainable smart ports, were developed,

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.