DocumentCode
2915508
Title
Spatial ontologies for detecting abnormal maritime behaviour
Author
Vandecasteele, Arnaud ; Napoli, Aldo
Author_Institution
Centre for Res. on Risk & Crises (CRC), MINES ParisTech, Evry, France
fYear
2012
fDate
21-24 May 2012
Firstpage
1
Lastpage
7
Abstract
The upsurge in piracy and the impact of recent environmental disasters have highlighted the need to improve maritime surveillance. Governmental and private initiatives have developed monitoring systems with improved acquisition and analysis capabilities. These systems rely on one major component, namely the detection of abnormal ship behaviour. This implies a detailed formalisation of expert knowledge. However, the quantity of data, the complexity of situations, the failure to take into account their spatial characteristics and the potential for the same scenario to be interpreted in different ways have proved to be significant problems. We therefore propose a new prototype for the analysis of abnormal ship behaviour. The system is based on a spatial ontology associated with a geographical inference engine. It automatically identifies suspicious vessels and associates them with probable behaviours defined by operational staff.
Keywords
disasters; expert systems; inference mechanisms; marine engineering; ontologies (artificial intelligence); ships; surveillance; abnormal maritime behaviour detection; abnormal ship behaviour detection; acquisition capabilities; automatic suspicious vessel identification; detailed expert knowledge formalisation; environmental disasters; geographical inference engine; governmental initiatives; maritime surveillance; monitoring systems; operational staff; piracy; private initiatives; spatial ontology; Engines; Marine vehicles; OWL; Ontologies; Sensors; Surveillance; Anomaly detection; Automated reasoning; Maritime surveillance systems; Spatial ontology;
fLanguage
English
Publisher
ieee
Conference_Titel
OCEANS, 2012 - Yeosu
Conference_Location
Yeosu
Print_ISBN
978-1-4577-2089-5
Type
conf
DOI
10.1109/OCEANS-Yeosu.2012.6263532
Filename
6263532
Link To Document