• 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.

• 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.

• 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.

• Asian Journal of Business Environment
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• v.12 no.3
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• pp.1-12
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• 2022

Purpose: This study aims to investigate whether AIS data can be used as a supporting indicator or as an initial signal to describe Indonesia's export-import conditions in real-time. Research design, data, and methodology: This study performs several stages of data selection to obtain indicators from AIS that truly reflect export-import activities in Indonesia. Also, investigate the potential of AIS indicators in producing forecasts of the value and volume of Indonesian export-import using conventional statistical methods and machine learning techniques. Results: The six preprocessing stages defined in this study filtered AIS data from 661.8 million messages to 73.5 million messages. Seven predictors were formed from the selected AIS data. The AIS indicator can be used to provide an initial signal about Indonesia's import-export activities. Each export or import activity has its own predictor. Conventional statistical methods and machine learning techniques have the same ability both in forecasting Indonesia's exports and imports. Conclusions: Big data AIS can be used as a supporting indicator as a signal of the condition of export-import values in Indonesia. The right method of building indicators can make the data valuable for the performance of the forecasting model.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.219-228
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• 2024

Vessels can operate with their Automatic Identification System (AIS) turned off, prompting the development of strategies to identify them. Among these, utilizing satellites to collect radio frequency (RF) data in the absence of AIS has emerged as the most effective and practical approach. The purpose of this study is to develop a matching algorithm for RF with AIS data and find the RF's applicability to classify a suspected ship. Thus, a matching procedure utilizing three RF datasets and AIS data was employed to identify ships in the Yellow Sea and the Korea Strait. The matching procedure was conducted based on the proximity to AIS points, ensuring accuracy through various distance-based sections, including 2 km, 3 km, and 6 km from the AIS-based estimated points. Within the RF coverage, the matching results from the first RF dataset and AIS data identified a total of 798 ships, with an overall matching rate of 78%. In the cases of the second and third RF datasets, 803 and 825 ships were matched, resulting in an overall matching rate of 84.3% and 74.5%, respectively. The observed results were partially influenced by differences in RF and AIS coverage. Within the overlapped region of RF and AIS data, the matching rate ranged from 80.2% to 98.7%, with an average of 89.3%, with no duplicate matches to the same ship.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.92-99
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• 2016

AIS(Automatic Identification System) is an vessel traffic management system which exchanges vessel data with other nearby ships, AIS base stations using VHF band. A domestic AIS base station is located along coast lines or island. So it is difficult to collect vessel data from the ocean. To solve this problem, we adopted AIS payload on the low earth orbit satellite. The AIS payload on the satellite is interfaced with OBC(On-Board Computer) via UART and the FSW(Satellite Flight Software) manages it. The FSW have to receive AIS command from ground station and forward to AIS payload. Similarly FSW have to receive response, OBP, OGP data from AIS payload and it is downlink to the ground station. So in this paper we describe the FSW design & implementation for AIS payload.

• 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 Navigation and Port Research
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• v.46 no.6
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• pp.576-584
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• 2022

AIS is widely utilized in vessel traffic services for marine traffic safety. In 2021, Korea deployed the high-speed maritime wireless communication system (LTE-Maritime) on the sea following IMO's proposal for the introduction of e-Navigation. In this paper, vessel trajectory data from AIS and LTE-Maritime were used for vessel trajectory prediction to compare and analyze the two systems. The results show that the trajectory prediction error of LTE-Maritime was smaller than that of AIS due to the granular and uniform data provided by LTE-Maritime. Additionally, it was revealed that time interval is the most important factor influencing the errors in trajectory prediction, with the prediction error of LTE-Maritime growing at a slower rate of 17% than AIS. This research contributes to the literature by quantitatively comparing AIS and LTE-Maritime systems for the first time.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.4
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• pp.345-351
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• 2013

The IWRAP program (Inland Waterway Risk Assessment Program) is a useful program for risk assessment of a waterway. However, in the basic version, the function which is used to import AIS data is not included. So users have to prepare the data and input to the program manually. And not all waterways have enough statistical data about passing vessels especially in developing countries as Vietnam. This paper studies the development of a program to pre-process AIS data for using the IWRAP Mk2 program basic version. In addition, it provides users basic information about marine traffic in a waterway such as routes layout, number of passages at a gate classified by type, size and time. The developed program, named TOAIS (Total AIS), was successfully used to pre-process AIS data collected in the Vung Tau waterway-Vietnam. As a result, the IWRAP Mk2 program basic version using data pre-processed from TOAIS could effectively assess the risk of collision in this waterway.