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Discovering Knowledge from AIS Database for Application in VTS

Published online by Cambridge University Press:  28 May 2010

Ming-Cheng Tsou
Ming-Cheng Tsou*
Affiliation:
(National Kaohsiung Marine University, Taiwan)
*
(Email:[email protected])
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Abstract

The widespread use of the Automatic Identification System (AIS) has had a significant impact on maritime technology. AIS enables the Vessel Traffic Service (VTS) not only to offer commonly known functions such as identification, tracking and monitoring of vessels, but also to provide rich real-time information that is useful for marine traffic investigation, statistical analysis and theoretical research. However, due to the rapid accumulation of AIS observation data, the VTS platform is often unable quickly and effectively to absorb and analyze it. Traditional observation and analysis methods are becoming less suitable for the modern AIS generation of VTS. In view of this, we applied the same data mining technique used for business intelligence discovery (in Customer Relation Management (CRM) business marketing) to the analysis of AIS observation data. This recasts the marine traffic problem as a business-marketing problem and integrates technologies such as Geographic Information Systems (GIS), database management systems, data warehousing and data mining to facilitate the discovery of hidden and valuable information in a huge amount of observation data. Consequently, this provides the marine traffic managers with a useful strategic planning resource.

Keywords

Marine Traffic EngineeringAISVTSGISData Mining
Type
Research Article
Information
The Journal of Navigation , Volume 63 , Issue 3 , July 2010 , pp. 449 - 469
Copyright
Copyright © The Royal Institute of Navigation 2010

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