• Journal of Fisheries and Marine Sciences Education
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• v.28 no.6
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• pp.1812-1821
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• 2016

The purpose of this study is to survey input data error of ship automatic identification system (AIS) and suggest its improvement. The effects of AIS were observed. Input data error of AIS was investigated by dividing it into dynamic data, static data by targeting actual ships and its improvement method was suggested. The findings are as follows. Looking into accidents before and after AIS is enforced to install on the ship, total collision were decreased after AIS installed. Static data error of AIS took place mainly in the case that ship name, call sign, MMSI, IMO number, ship type, location of antenna (ship length and width) were wrongly input or those data were not input initially. Dynamic data error of AIS was represented by input error of ship's heading. As errors of voyage related data take place as well, confusion is made in sailing or ship condition. Counter measures against the above are as follows. First, reliability of AIS data information should be improved. Second, incessant concern and management should be made on the navigation officers.

• Journal of Ocean Engineering and Technology
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• v.37 no.5
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• pp.198-204
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• 2023

In response to the complexity and time demands of conventional methods for estimating the hydrodynamic coefficients, this study aims to revolutionize ship maneuvering analysis by utilizing automatic identification system (AIS) data and the Support Vector Regression (SVR) algorithm. The AIS data were collected and processed to remove outliers and impute missing values. The rate of turn (ROT), speed over ground (SOG), course over ground (COG) and heading (HDG) in AIS data were used to calculate the rudder angle and ship velocity components, which were then used as training data for a regression model. The accuracy and efficiency of the algorithm were validated by comparing SVR-based estimated hydrodynamic coefficients and the original hydrodynamic coefficients of the Mariner class vessel. The validated SVR algorithm was then applied to estimate the hydrodynamic coefficients for real ships using AIS data. The turning circle test wassimulated from calculated hydrodynamic coefficients and compared with the AIS data. The research results demonstrate the effectiveness of the SVR model in accurately estimating the hydrodynamic coefficients from the AIS data. In conclusion, this study proposes the viability of employing SVR model and AIS data for accurately estimating the hydrodynamic coefficients. It offers a practical approach to ship maneuvering prediction and control in the maritime industry.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.24-29
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• 2019

AIS is one of the most critical systems in any organization. Data quality plays a critical role in a knowledge-based economy. The objective of this study is to identify the most important factors for accounting information quality and their impact on AIS data quality outcomes. This study includes an extensive literature review to identify a set of CSF for data quality. The study uses empirical data to test the research hypothesis and resluts show that the top three most important factors that affect AIS's data quality are toop management commitmentm the nature of the AIS and input controls. The study further uses regression analysis to test the effect of those factors on AIS data quality, finding that there is a significant positive relationship between the perceived performance of the three factors and AIS data quality putcomes. To be develop to AIS data quality further study for CSF's control methodology is necessary.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.10a
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• pp.114-116
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• 2014

The interpolation of the missing AIS dynamic data can be used for predicting the lost data of the ship's state which is able to product the valuable information for analyzing and investigating the maritime accidents. The previous research proposed some interpolating methods however there exists some problem, firstly, the interpolated parameters such as COG, SOG, HDG weren't described sufficiently and accurately as in AIS message, secondly, each method is only suitable to some kinds of given AIS data, finally at heavy wind and current area, the parameters of AIS dynamic change quickly in short time, therefore, the modelling of the variation of ship's dynamic based on the physical characteristic is very difficult, in these cases the time-series and numerical method are usually better. This research proposes the other method through numerical analysis which can be suitable for many different kinds of the lost data, parameters are interpolated sufficiently, beside that this model is appropriate to all variation in short time interval. All the given AIS dynamic are regarded as the functions to time, then curves are established for fitting all data. Experiments are carried out to evaluate the performance of this approach, the interpolation results show this approach can be applied well in practice.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.430-432
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• 2013

AIS(Automatic Identification System) is a radionavigation equipment for exchanging safety related information between ships as well as ship and shore station, introduced by SOLAS convention and widely used especially in vessel traffic service. However, in an area of broad communication coverage of coast station, various problems may appear in receiving AIS data from ships. In this paper, AIS problems that may happen in broad communication coverage of coast station are analyzed using received data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.992-1001
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• 2022

The maritime traffic analysis has been conducted in various ways to solve problems arising from the complex marine environment. However, recent trends in the maritime industry, such as the development of the maritime autonomous surface ships (MASS), suggest that maritime traf ic analysis needs change. Accordingly, based on the studies conducted over the past decade for improvements, automatic identification system (AIS) data is mainly used for maritime traffic analysis. Moreover, the use of geographic information that directly af ects ship operation is relatively insufficient. Therefore, this study presented a method of using a combination of shape format data and AIS data to enhance maritime traffic analysis in preparation for the commercialization of autonomous ships. Consequently, extractable marine traffic characteristics were presented when shape format data were used for marine traffic analysis. This is expected to be used for marine traffic analysis for the introduction of autonomous ships in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1515-1521
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• 2013

AIS is a core service in the maritime safety domain. AIS Message type #6 and #8(for binary date) can be used for carrying any kind of MSI(Maritime Safety Information). The MSC(Maritime Safety Committee) approved SN/Circ. 289 on Guidance on the use of AIS Application-Specific Messages in 2010. The MSI that carried by AIS-ASM can support to reduce the maritime accidents. Since a new AIS-ASM service places an additional load on the VDL(VHF Data Link), there should be a deployment process for new AIS-ASM services. In this paper we analyze the AIS-ASM services and survey the extended functions and systems for each AIS-ASM service. We also present the survey of the statistical analysis of local AIS messages. and suggest preliminary research topics for the deployment of new AIS-ASM services. VDL monitoring system, system for detection and removal of malfunctioning AIS equipments, and value analysis process of the MSI services are required.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.327-338
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• 2018

The possibility of ship detection monitoring at operational level using KOMPSAT-5 Synthetic Aperture Radar (SAR) and Automatic Identification System (AIS) data is investigated. For the analysis, the KOMPSAT-5 SLC images, which are collected from the west coast of Shinjin port and the northern coast of Jeju port are used along with portable AIS data from near the coast. The ship detection algorithm based on HVAS (Human Visual Attention System) was applied, which has significant advantages in terms of detection speed and accuracy compared to the commonly used CFAR (Constant False Alarm Rate). As a result of the integrated analysis, the ship detection from KOMPSAT-5 and AIS were generally consistent except for small vessels. Some ships detected in KOMPSAT-5 but not in AIS are due to the data absence from AIS, while it is clearly visible in KOMPSAT-5. Meanwhile, SAR imagery also has some false alarms due to ship wakes, ghost effect, and DEM error (or satellite orbit error) during object masking in land. Improving the developed ship detection algorithm and collecting reliable AIS data will contribute for building wide integrated surveillance system of marine territory at operational level.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.256-261
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• 2013

The AIS(Automatic Identification System) has been widely used for ship safety at sea over the last 10 years. The AIS traffic load at VDL(VHF Data Link) has been continuously increased. As the traffic load at VDL increases, the quality of AIS service may be deteriorated. In the previous research, the AIS traffic has been analyzed in the major ports of Korea, and its problem due to traffic overload has been suggested. However, no solutions has been given so far. In this paper, the method of autimatically controlling the VDL traffic at AIS base station is represented.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.155-156
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• 2022

Efficient operation of ships can transport cargo to ports safer and faster, and reduce fuel costs. Therefore, in this study, the pattern was analyzed using AIS data of ships passing near Busan Port, a representative port in Korea. The analysis of vessel traffic patterns was approached with a grid-based node generation method, which can be used for research such as optimal route and route prediction.