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Visual Analytics for Maritime Anomaly Detection

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2011 issn 1650-8580 isbn 978-91-7668-782-6

Maria Riveiro holds a M.Sc. in Telecommunication Engineering. Since 2005, she has been a member of the Skövde Artificial Intelligence Lab and the Information Fusion Research Program at the University of Skövde, Sweden. Her research interests include visual analytics, information visualization, data mining and information fusion.

The surveillance of large sea areas typically involves the analysis of huge quantities of heterogeneous sensor data. In order to support the operator while monitoring maritime traffic, the identifi-cation of anomalous behavior may reduce operators’ cognitive load. However, anomaly detection is normally a complex problem that can hardly be solved by using purely visual or purely computational methods.

In this doctoral thesis, Riveiro investigates the use of combined visual and data mining methods to support the detection of anomalous vessel behavior.

Örebro Studies in Technology 46

örebro 2011 Doctoral Dissertation

Visual Analytics for Maritime Anomaly Detection

Maria Riveiro

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