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Signature-based activity detection based on Bayesian networks acquired from expert knowledge
University of Skövde, School of Humanities and Informatics.
2008 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The maritime industry is experiencing one of its longest and fastest periods of growth. Hence, the global maritime surveillance capacity is in a great need of growth as well. The detection of vessel activity is an important objective of the civil security domain. Detecting vessel activity may become problematic if audit data is uncertain. This thesis aims to investigate if Bayesian networks acquired from expert knowledge can detect activities with a signature-based detection approach. For this, a maritime pilot-boat scenario has been identified with a domain expert. Each of the scenario’s activities has been divided up into signatures where each signature relates to a specific Bayesian network information node. The signatures were implemented to find evidences for the Bayesian network information nodes. AIS-data with real world observations have been used for testing, which have shown that it is possible to detect the maritime pilot-boat scenario based on the taken approach.

Place, publisher, year, edition, pages
Skövde: Institutionen för kommunikation och information , 2008. , 46 p.
Keyword [en]
Signature-based detection, Bayesian networks, knowledge elicitation, information fusion, maritime situation awareness
National Category
Computer Science
Identifiers
URN: urn:nbn:se:his:diva-1123OAI: oai:DiVA.org:his-1123DiVA: diva2:2245
Presentation
(English)
Uppsok
teknik
Supervisors
Examiners
Available from: 2008-06-12 Created: 2008-06-12 Last updated: 2009-06-17

Open Access in DiVA

fulltext(1011 kB)466 downloads
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf