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A Dempster‐Shafer theory and uninorm‐based framework of reasoning and multiattribute decision‐making for surveillance system
Author(s) -
Ma Wenjun,
Liu Weiru,
Luo Xudong,
McAreavey Kevin,
Jiang Yuncheng,
Ma Jianbing
Publication year - 2019
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22175
Subject(s) - computer science , event (particle physics) , rank (graph theory) , object (grammar) , field (mathematics) , alarm , dempster–shafer theory , fuse (electrical) , function (biology) , data mining , artificial intelligence , computer security , mathematics , physics , materials science , combinatorics , quantum mechanics , evolutionary biology , biology , pure mathematics , electrical engineering , composite material , engineering
Abstract Closed‐circuit television and sensor‐based intelligent surveillance systems have attracted considerable attentions in the field of public security affairs. To provide real‐time reaction in the case of a huge volume of the surveillance data, researchers have proposed event‐reasoning frameworks for modeling and inferring events of interest. However, they do not support decision‐making, which is very important for surveillance operators. To this end, this paper incorporate a function of decision‐making in an event‐reasoning framework, so that our model not only can perform event‐reasoning but also can predict, rank, and alarm threats according to uncertain information from multiple heterogeneous sources. In particular, we propose a multiattribute decision‐making model, in which an object being watched is modeled as a multiattribute event, where each attribute corresponds to a specific source, and the information from each source can be used to elicit a local threat degree of different malicious situations with respect to the corresponding attribute. Moreover, to assess an overall threat degree of an object being observed, we also propose a method to fuse the conflict threat degrees regarding all the relevant attributes. Finally, we demonstrate the effectiveness of our framework by an airport security surveillance scenario.