A study of anomaly detection in data from urban sensor networks

Authors:
Christoffer Brax;Anders Dahlbom
Affiliations:
Training Systems & Information Fusion, Business Area Electronic Defence Systems, Saab AB, Skövde, Sweden;Informatics Research Centre, University of Skövde, Skövde, Sweden
Venue:
MDAI'12 Proceedings of the 9th international conference on Modeling Decisions for Artificial Intelligence
Year:
2012

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Abstract

In many sensor systems used in urban environments, the amount of data produced can be vast. To aid operators of such systems, high-level information fusion can be used for automatically analyzing the surveillance information. In this paper an anomaly detection approach for finding areas with traffic patterns that deviate from what is considered normal is evaluated. The use of such approaches could help operators in identifying areas with an increased risk for ambushes or improvised explosive devices (IEDs).