DocumentCode :
2650644
Title :
Anomaly event detection in temporal sensor network data of intelligent environments
Author :
Ye, Li ; Qin, Zhi-guang ; Wang, Juan ; Jin, Jing
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Volume :
7
fYear :
2010
fDate :
16-18 April 2010
Abstract :
Intelligent environments enhanced the interactions between human and computers. People can seamlessly communicate with the system via some event, such as gesture, voice, motion and context. Anomaly event detection in the temporal data, which collected in sensor network of intelligent environments, is a challenging problem, particularly there have no direct priori knowledge of the anomaly events and no prominent patterns are known. In this paper, we propose a technique which can extract patterns in the temporal sensor data and identify the anomaly events efficiently. This method is based on the covariance information of temporal data, and T2 test of Mahalanobis distance is used to detect the outliers. The experiment results show that the propose method can detect the anomaly and uncommon events in temporal data. It can be of great use in intelligent environments.
Keywords :
human computer interaction; pattern recognition; wireless sensor networks; Mahalanobis distance; covariance information; event detection; human computer interaction; intelligent environment; pattern extraction; temporal sensor network; Computer networks; Data mining; Event detection; Humans; Intelligent networks; Intelligent sensors; Intrusion detection; Minutes; Pattern recognition; Testing; Anomaly Event Detection; Intelligent Environments; Sensor Application; Temporal Data Mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6347-3
Type :
conf
DOI :
10.1109/ICCET.2010.5485505
Filename :
5485505
Link To Document :
بازگشت