Fusion of Static and Temporal Information for Threat Evaluation in Sensor Networks

WenJun Ma, Weiru Liu, Jun Hong

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)
249 Downloads (Pure)


In many CCTV and sensor network based intelligent surveillance systems, a number of attributes or criteria are used to individually evaluate the degree of potential threat of a suspect. The outcomes for these attributes are in general from analytical algorithms where data are often pervaded with uncertainty and incompleteness. As a result, such individual threat evaluations are often inconsistent, and individual evaluations can change as time elapses. Therefore, integrating heterogeneous threat evaluations with temporal influence to obtain a better overall evaluation is a challenging issue. So far, this issue has rarely be considered by existing event reasoning frameworks under uncertainty in sensor network based surveillance. In this paper, we first propose a weighted aggregation operator based on a set of principles that constraints the fusion of individual threat evaluations. Then, we propose a method to integrate the temporal influence on threat evaluation changes. Finally, we demonstrate the usefulness of our system with a decision support event modeling framework using an airport security surveillance scenario.
Original languageEnglish
Title of host publicationKnowledge Science, Engineering and Management
Subtitle of host publication8th International Conference, KSEM 2015, Chongqing, China, October 28-30, 2015, Proceedings
EditorsSongmao Zhang, Martin Wirsing, Zilil Zang
Number of pages12
ISBN (Electronic)9783319251592
ISBN (Print)9783319251585
Publication statusPublished - 3 Nov 2015

Publication series

NameLecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)
ISSN (Print)0302-9743


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