• Title/Summary/Keyword: Vessel information Systems

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Analysis of User Requirements for Development of Vessel Traffic Services Cloud System (선박교통관제 클라우드 시스템 개발에 따른 사용자 요구사항 분석)

  • Lee, Li-Na;Kim, Joo-Sung;Lee, Hong-Hoon;Lee, Jin-Suk;Namgung, Ho
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.2
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    • pp.314-323
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    • 2022
  • Vessel Traffic Services (VTS) operators perform traffic management tasks using VTS systems and sensor equipment designated as VTS facilities to promote the safety and efficiency of vessel traffic. The necessary VTS information for effective operations could be obtained through the additional access of various information channels other than the designated VTS facility. To unify these various information access windows, the development of the VTS cloud system is in progress. In this study, the operational information analysis for VTS was performed through VTS tasks-facility linkage analysis to identify the user required information according to the introduction of the VTS cloud system. The VTS task analysis was performed through research of the international and domestic literature, and expert interviews. The necessary information were identified and linked according to the VTS facilities. As a result of the analysis, 37 categories of necessary information were identified for internal and external information windows, and 8 information windows were selected other than the present VTS equipment. The identified user requirements would be applied to the structure design of the VTS cloud system. In the future, it is necessary to update user requirements through scenario-based user operation analysis and to conduct additional research on the system interface design.

Detection of Abnormal Vessel Trajectories with Convolutional Autoencoder (합성곱 오토인코더를 이용한 이상거동 선박 식별)

  • Son, June-Hyoung;Jang, Jun-Gun;Choi, Bongwan;Kim, Kyeongtaek
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.4
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    • pp.190-197
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    • 2020
  • Recently there was an incident that military radars, coastal CCTVs and other surveillance equipment captured a small rubber boat smuggling a group of illegal immigrants into South Korea, but guards on duty failed to notice it until after they reached the shore and fled. After that, the detection of such vessels before it reach to the Korean shore has emerged as an important issue to be solved. In the fields of marine navigation, Automatic Identification System (AIS) is widely equipped in vessels, and the vessels incessantly transmits its position information. In this paper, we propose a method of automatically identifying abnormally behaving vessels with AIS using convolutional autoencoder (CAE). Vessel anomaly detection can be referred to as the process of detecting its trajectory that significantly deviated from the majority of the trajectories. In this method, the normal vessel trajectory is gridded as an image, and CAE are trained with images from historical normal vessel trajectories to reconstruct the input image. Features of normal trajectories are captured into weights in CAE. As a result, images of the trajectories of abnormal behaving vessels are poorly reconstructed and end up with large reconstruction errors. We show how correctly the model detects simulated abnormal trajectories shifted a few pixel from normal trajectories. Since the proposed model identifies abnormally behaving ships using actual AIS data, it is expected to contribute to the strengthening of security level when it is applied to various maritime surveillance systems.

A Study on the Information Management System Support for the Intelligent Autonomous Navigation Systems (지능형 자율운항시스템 지원을 위한 정보 관리 시스템에 관한 연구)

  • Kim, Eun-Kyoung;Kim, Yong-Gi
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.3
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    • pp.279-286
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    • 2015
  • The rapid increase of the current marine accidents is mainly due to the human execution errors. In an effort to address this, various kinds of researches such as construction of the digital vessels and vessel information monitoring systems have been conducted. But for safe navigation of vessels, it lack on systems study which can efficiently store, utilize and manage the mass data accepted by the vessel. In this paper, we propose a VWS(Virtual World System) that is based on the architecture of intelligent systems RVC(Reactive Layer-Virtual World-Considerative Layer) model of intelligent autonomous navigation system. VWS is responsible to store all the necessary information for safe navigation of the vessel and the information services to the sub-system of intelligent autonomous navigation system. VWS uses topology database to express the specific problem area, and utilizes a scheduling to reflect the characteristics of the real-time processing environment. Also, Virtual World defines API for the system to reflect the characteristics of the distributed processing environment. As a case study, the VWS is applied to a intelligent ship autonomous navigation system, and simulation is done to prove the effectiveness of the proposed system.

Adaptive Real-Time Ship Detection and Tracking Using Morphological Operations

  • Arshad, Nasim;Moon, Kwang-Seok;Kim, Jong-Nam
    • Journal of information and communication convergence engineering
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    • v.12 no.3
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    • pp.168-172
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    • 2014
  • In this paper, we propose an algorithm that can efficiently detect and monitor multiple ships in real-time. The proposed algorithm uses morphological operations and edge information for detecting and tracking ships. We used smoothing filter with a $3{\times}3$ Gaussian window and luminance component instead of RGB components in the captured image. Additionally, we applied Sobel operator for edge detection and a threshold for binary images. Finally, object labeling with connectivity and morphological operation with open and erosion were used for ship detection. Compared with conventional methods, the proposed method is meant to be used mainly in coastal surveillance systems and monitoring systems of harbors. A system based on this method was tested for both stationary and non-stationary backgrounds, and the results of the detection and tracking rates were more than 97% on average. Thousands of image frames and 20 different video sequences in both online and offline modes were tested, and an overall detection rate of 97.6% was achieved.

Similarity Measurement Using Ontology in Vessel Clearance Process (온톨로지를 이용한 선박 통관 프로세스의 유사성 측정)

  • Yahya, Bernardo N.;Park, Jae-Hun;Bae, Hye-Rim;Mo, Jung-Kwan
    • Journal of Korean Institute of Industrial Engineers
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    • v.37 no.2
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    • pp.153-162
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    • 2011
  • The demands of complicated data communications have issued a new challenge to port logistics systems. Customers expect ports to handle their generated administrative data while a vessel is docked in a port. One port logistics system, known as the Vessel Clearance Process (VCP), manages large numbers of documents related to port of entry. In the VCP, information flows through many organizations such as the port authority, shipping agents, marine offices, immigration offices, and others. Therefore, for effective management of the Business Process (BP) of the VCP, a standardized method of BP modeling is essential, especially in heterogeneous system environments. In a port, according to port policy, terms and data are sued that are similar to but different from those of other logistics partners, which hinders standardized modeling of the BP. In order to avoid tedious and time-consuming document customization work, more convenient modeling of BP for VCP is essential. This paper proposes an ontology-based process similarity measurement to assist designer for process modeling in port domain, especially VCP. We expect that this methodology will use convenient and quick modeling of port business processes.

Automated Vessels Detection on Infant Retinal Images

  • Sukkaew, Lassada;Uyyanonvara, Bunyarit;Barman, Sarah A;Jareanjit, Jaruwat
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.321-325
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    • 2004
  • Retinopathy of Prematurity (ROP) is a common retinal neovascular disorder of premature infants. It can be characterized by inappropriate and disorganized vessel. This paper present a method for blood vessel detection on infant retinal images. The algorithm is designed to detect the retinal vessels. The proposed method applies a Lapalacian of Gaussian as a step-edge detector based on the second-order directional derivative to identify locations of the edge of vessels with zero crossings. The procedure allows parameters computation in a fixed number of operations independent of kernel size. This method is composed of four steps : grayscale conversion, edge detection based on LOG, noise removal by adaptive Wiener filter & median filter, and Otsu's global thresholding. The algorithm has been tested on twenty infant retinal images. In cooperation with the Digital Imaging Research Centre, Kingston University, London and Department of Opthalmology, Imperial College London who supplied all the images used in this project. The algorithm has done well to detect small thin vessels, which are of interest in clinical practice.

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A Study on the Feedforward Control Algorithm for Dynamic Positioning System Using Ship Motion Prediction (선체운동 예측을 이용한 Dynamic Positioning System의 피드포워드 제어 알고리즘에 관한 연구)

  • Song, Soon-Seok;Kim, Sang-Hyun;Kim, Hee-Su;Jeon, Ma-Ro
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.22 no.1
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    • pp.129-137
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    • 2016
  • In the present study we verified performance of feed-forward control algorithm using short term prediction of ship motion information by taking advantage of developed numerical simulation model of FPSO motion. Up until now, various studies have been conducted about thrust control and allocation for dynamic positioning systems maintaining positions of ships or marine structures in diverse sea environmental conditions. In the existing studies, however, the dynamic positioning systems consist of only feedback control gains using a motion of vessel derived from environmental loads such as current, wind and wave. This study addresses dynamic positioning systems which have feedforward control gain derived from forecasted value of a motion of vessel occurred by current, wind and wave force. In this study, the future motion of vessel is forecasted via Brown's Exponential Smoothing after calculating the vessel motion via a selected mathematical model, and the control force for maintaining the position and heading angle of a vessel is decided by the feedback controller and the feedforward controller using PID theory and forecasted vessel motion respectively. For the allocation of thrusts, the Lagrange Multiplier Method is exploited. By constructing a simulation code for a dynamic positioning system of FPSO, the performance of feedforward control system which has feedback controller and feedforward controller was assessed. According to the result of this study, in case of using feedforward control system, it shows smaller maximum thrust power than using conventional feedback control system.

Designing Integrated Diagnosis Platform for Heterogeneous Combat System of Surface Vessels (다기종 수상함 전투체계의 통합 진단 플랫폼 설계)

  • Kim, Myeong-hun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.186-188
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    • 2021
  • The architecture named IDPS is a design concept of web-based integrated platform for heterogeneous naval combat system, which accomplishes efficiency(decreasing complexity) of diagnosis process and reduces time to diagnose system. Each type of surface vessel has its own diagnostic processes and applications, and that means it also requires its own diagnostic engineer(inefficiency in human resource management). In addition, man-based diagnostic causes quality issues such as difference approach of log analysis in accordance with engineer skills. Thus In this paper, we designed integrated diagnostic platform named IDPS with simplified common process regardless of type of surface vessel and we reinforced IDPS with status decision algorithm(SDA) that judges current software status of vessel based on gathered lots of logs. It will enable engineers to diagnose system more efficiently and to use more resources in utilizing SDA-analyzed diagnostic results.

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Robust Ultrasound Multigate Blood Volume Flow Estimation

  • Zhang, Yi;Li, Jinkai;Liu, Xin;Liu, Dong Chyuan
    • Journal of Information Processing Systems
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    • v.15 no.4
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    • pp.820-832
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    • 2019
  • Estimation of accurate blood volume flow in ultrasound Doppler blood flow spectrograms is extremely important for clinical diagnostic purposes. Blood volume flow measurements require the assessment of both the velocity distribution and the cross-sectional area of the vessel. Unfortunately, the existing volume flow estimation algorithms by ultrasound lack the velocity space distribution information in cross-sections of a vessel and have the problems of low accuracy and poor stability. In this paper, a new robust ultrasound volume flow estimation method based on multigate (RMG) is proposed and the multigate technology provides detail information on the local velocity distribution. In this method, an accurate double iterative flow velocity estimation algorithm (DIV) is used to estimate the mean velocity and it has been tested on in vivo data from carotid. The results from experiments indicate a mean standard deviation of less than 6% in flow velocities when estimated for a range of SNR levels. The RMG method is validated in a custom-designed experimental setup, Doppler phantom and imitation blood flow control system. In vitro experimental results show that the mean error of the RMG algorithm is 4.81%. Low errors in blood volume flow estimation make the prospect of using the RMG algorithm for real-time blood volume flow estimation possible.

Rolling Motion Simulation in the Time Domain and Ship Motion Experiment for Algorithm Verification for Fishing Vessel Capsizing Alarm Systems (어선전복경보시스템 알고리즘 검증을 위한 어선 횡동요 시험 및 시간영역 횡동요 시뮬레이션)

  • Yang, Young-Jun;Kwon, Soo-Yeon
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.23 no.7
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    • pp.956-964
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    • 2017
  • This study contributes to deepening understand of the characteristics of fishing vessel rolling motions to improve the development of capsizing alarm systems. A time domain rolling motion simulation was performed. In order to verify capsizing alarm systems, it is necessary to carry out experiments assuming a capsizing situation and perform actual fishing vessel measurements, but these tasks are impossible due to the danger of such a situation. However, in many capsizing accidents, a close connection with rolling motion was found. Accordingly, the rolling motion of a fishing boat, which is the core of a fishing vessel capsizing alarm system, has been accurately measured and a time domain based on a rolling motion simulation has been performed. This information was used to verify the algorithm for a capsizing alarm system. Firstly, the characteristics of rolling motion were measured through a motion experiment. For small vessels such as fishing vessels, it was difficult to interpret viscosity due to analytical methods including CFD and potential codes. Therefore, an experiment was carried out focusing on rolling motion and a rolling mode RAO was derived.