Title: AIS Event-Based Knowledge Discovery for Maritime Situational Awareness
Authors: ALVAREZ ALVAREZ MarleneFERNANDEZ ARGUEDAS VIRGINIAGAMMIERI VINCENZOVESPE MICHELEAULICINO GiuseppeVOLLERO Antonio
Other Contributors: MAZZARELLA FABIO
Publisher: IEEE
Publication Year: 2016
JRC N°: JRC100883
ISBN: 978-0-9964-5274-8
URI: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7528111&refinements%3D4224302807%26filter%3DAND%28p_IS_Number%3A7527857%29
http://publications.jrc.ec.europa.eu/repository/handle/JRC100883
Type: Articles in periodicals and books
Abstract: The discovery of anomalies and, more in general, of events of interest at sea is one of the main challenges of Maritime Situational Awareness (MSA)-related activities. This paper proposes an event-based methodology for knowledge discovery without querying directly a huge amount of raw data. The proposed architecture analyses the maritime traffic data to detect maritime traffic patterns and events and aggregate them in an Event Map, namely a georeferenced grid. The Event Map offers visualisation capabilities and, more importantly, is used as access interface to the maritime traffic knowledge database. The proposed methodology offers real-time access to maritime data, without accessing the raw AIS data, and the possibility to perform more structured queries with respect to traditional basic queries (e. g. vessel proximity within a certain distance). The proposed approach is illustrated and assessed on real-world AIS data set revealing computational improvements and enriched monitoring capabilities.
JRC Directorate:Space, Security and Migration

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