• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.305-308
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• 2014

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. The dynamic data of AIS is transmitted at intervals of 2 second to 3 minutes depending on ship's navigational status and speed. However, so often times it happens that some AIS data can not be received due to increasing AIS traffic and it's time slot confliction. In this paper, a revised reporting intervals of AIS dynamic data is proposed in order to decrease AIS data link load.

• 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.

• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.169-175
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• 2017

Accounting information systems (AIS) capture and process accounting data and provide valuable information for decision makers. However, in a rapidly changing environment, continual management of the AIS is necessary for organizations to optimize performance outcomes. I suggest that building a dynamic AIS capability enables accounting process and organizational performance. Using the dynamic capabilities framework (Teece 2007). I propose that a dynamic AIS capability can bedeveloped through the synergy of three competencies: having (1) a flexible AIS, (2) a complementary business intelligence system, and (3) accounting professionals with IT technical competency. Using survey data, I find evidence of a positive association between a dynamic AIS capability, accounting process performance, and overall firm performance. The results suggest that developing a dynamic AIS resource can add value to an organization. This study provides guidance for organizations looking to leverage the performance outcomes of their environment.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.44 no.3
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• pp.218-228
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• 2008

This paper describes on the real-time tracking of ship's dynamic behavior by AIS information in the coastal waters. The AIS data was received at a land station by using the antenna of AIS receiver mounted on the rooftop of the laboratory, Pukyong National University (PKNU), Busan, Korea, and stored as a NMEA format of serial output sentence of VDM(VHF Data-Link Message) and displayed on the ENC(Electronic Navigational Chart) of a PC-based ECDIS. In this study, the AIS receiver was mainly used to obtain the dynamic information that is necessary to evaluate and track the movement situation of training ship "KAYA" of PKNU in the coastal waters. The change of position with time for the ship turning under the rudder angle of port $30^{\circ}$ was correctly tracked with the turning circle of 940 m in diameter on the ENC of a PC-based ECDIS. Then, the dynamic information of the AIS system was updated every 6.29 seconds under the turning situation for the speed of 10.9 knots and every 21.65 seconds under the situation running at the speed of 11.05 knots on the straight line route of $155^{\circ}$, respectively. In case of AIS target tracking in the inshore zone behind large topographical obstructions, such as mountain and apartment buildings, the update rate of dynamic information was irregularly changed by the existence of land obstacles. However, the position tracking by AIS information under the situation existing no sea obstructions was achieved in real or near real-time and the instant presentation of course alternations for the ship was correctly monitored by using a PC-based ECDIS. From these results, we concluded that the PC-based ECDIS technology and methodology combined with the AIS information can be easily extended and applied to the surveillance and management for the fishing operation of fishing vessels in the coastal zone and in the EEZ fishing grounds.

• Journal of Navigation and Port Research
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• v.39 no.5
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• pp.377-384
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• 2015

The interpolation of missing AIS data can be used for recovering the lost data of a ship's state which is then able to produce useful information for VTS stations or other ships. Previous research has introduced some interpolating methods however there are some problems with regard to missing AIS data. This paper proposes one new method which includes linear interpolation, cubic Hermit interpolation and an identification mechanism to overcome some of those limitations, first AIS data regarding ship position, COG, SOG and HDG is divided into separate time series, then the characteristic of the missing data is investigated into through using an identification mechanism, an appropriate interpolation is selected to fit all the time series which matches the characteristics. Numerical experiments are carried out using real AIS data to validate the algorithm of this approach and the results are compared with the previous method, after which the actual missing area is suggested to be interpolated by the proposed method. The interpolation results show this approach can be applied well in practice.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.257-269
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• 2023

This paper presents a method for detecting faults in data obtained from the Automatic Identification System (AIS) of surface vessels. The data include latitude, longitude, Speed Over Ground (SOG), and Course Over Ground (COG). We derive two methods that utilize two models: a constant state model and a derivative augmented model. The constant state model incorporates noise variables to account for state changes, while the derivative augmented model employs explicit variables such as first or second derivatives, to model dynamic changes in state. Generally, the derivative augmented model detects faults more promptly than the constant state model, although it is vulnerable to potentially overlooking faults. The effectiveness of this method is validated using AIS data collected at a harbor. The results demonstrate that the proposed approach can automatically detect faults in AIS data, thus offering partial assistance for enhancing navigation safety.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.50 no.1
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• pp.21-29
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• 2014

The dynamic information of radar and automatic identification system (AIS) for targets obtained from the traffic vessels operating in the north outer harbor and surrounding waters of Busan port, Korea. The target information was analyzed to investigate the potential collision risk resulting from the invalid true heading (HDT) information of AIS and the integration ambiguity in the graphic presentation of both tracked data sets for two systems. An integrated display system (IDS) for supporting the navigator of offshore fishing vessels was also developed to find possible maneuvering solutions for collision avoidance by comparing radar data with AIS data in real-time at sea. Consequently, the multiple functions of IDS can provide additional information that is potentially valuable for taking action to avoid the collision in offshore fishing vessels. However, the integration criteria of radar and AIS targets in the IDS must be carefully established to eliminate the fusion ambiguity in the graphic presentation of both AIS and radar symbols such as the one or two physical targets which are very close to each other.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.285-289
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• 2012

In a coastal area, all of the vessels are always exposed to the potential risk, taking into the maritime accident statistics account over the last decades. To manage vessels underway safety, the characteristics of ship movements in a fairway should be recognized by VTS system or VTS operators. The IMO has already mandated the shipboard carriage of AIS since 2004, as stated in SOLAS Chapter V Regulation 19. As a result, the static and dynamic information of AIS data has been collected for vessel traffic management in the coastal areas and used for VTS. This research proposes a simple algorithm of recognizing potentially risky ships by observing their trajectories on the fairway. The static and dynamic information of AIS data are collected and the curvature for the ship trajectory is surveyed. The proposed algorithm finds out the irregularity of ship movement. The algorithm effectively monitors the change of navigation pattern from the curvature analysis of ship trajectory. Our method improves VTS functions in an intelligent way by analyzing the navigation pattern of vessels underway.