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An approach for increased supply chain security by using automatic detection of anomalous vehicle behavior
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
2009 (English)In: CD-ROM Proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence (MDAI 2009), 2009, 165-176 p.Conference paper, (Refereed)
Abstract [en]

In recent years, the development of low-cost GPS transceivers has made it possible to equip all trucks in a fleet with equipment for automatically reporting the status of the trucks to a fleet management system. The downside is that the huge amount of information that is gathered must be evaluated in real-time by an operator. We propose the use of a data-driven anomaly detection algorithm that learns "normal" vehicle behaviour and detects anomalous behaviour such as smuggling, accidents and hijacking, The algorithm is evaluated on real-world data from trucks and commuters equipped with GPS transceivers. The results give initial support to the claim that anomaly detection based on statistical learning can be used to support human descision making. This ability can increase supply chain security by alerting an operator on anomalous vehicle behaviour.

Place, publisher, year, edition, pages
2009. 165-176 p.
Keyword [en]
Anomaly detection, Decision support system, Situation awareness, Statistical learning
National Category
Computer and Information Science
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-3535ISBN: 978-84-00-08851-4 (print)OAI: oai:DiVA.org:his-3535DiVA: diva2:284167
Conference
6th International Conference, MDAI 2009, Awaji Island, Japan, November 30–December 2, 2009
Available from: 2010-01-04 Created: 2010-01-04 Last updated: 2017-06-05Bibliographically approved

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Citation style
  • apa
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Language
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  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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  • asciidoc
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