Presentation 2006-11-16
Detecting Unusual Events in Ubiquitous Sensor Environments using Bayesian Networks and Nonparametric Regression
Sun Yong KIM, Masakatsu OHTA, Mitsuo TERAMOTO,
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Abstract(in English) We propose a novel anomaly detection method for the heterogeneous sensor environment in the living space where we hardly analyze the entire mechanism of the environment and unlikely to predict the irregular events. By using Bayesian networks and nonparametric regression, our method learns the ordinary behaviors of sensor values and examines the degree of anomaly for each observation according to the estimated variance from the learning result. We applied our method to the data collected in an office room equipped by brightness and motion sensors, and obtained the putative sensor relation networks with no prior knowledge. We detected some symptoms of anomalous events, and furthermore, we found out the causal sensors by using the network structure.
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Keyword(in English) Ubiquitous / Sensor networks / Anomalous detection / Bayesian networks / Nonparametric regression / Machine learning
Paper # IN2006-94
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Committee IN
Conference Date 2006/11/9(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Detecting Unusual Events in Ubiquitous Sensor Environments using Bayesian Networks and Nonparametric Regression
Sub Title (in English)
Keyword(1) Ubiquitous
Keyword(2) Sensor networks
Keyword(3) Anomalous detection
Keyword(4) Bayesian networks
Keyword(5) Nonparametric regression
Keyword(6) Machine learning
1st Author's Name Sun Yong KIM
1st Author's Affiliation Nippon Telegraph and Telephone Corporation()
2nd Author's Name Masakatsu OHTA
2nd Author's Affiliation Nippon Telegraph and Telephone Corporation
3rd Author's Name Mitsuo TERAMOTO
3rd Author's Affiliation Nippon Telegraph and Telephone Corporation
Date 2006-11-16
Paper # IN2006-94
Volume (vol) vol.106
Number (no) 358
Page pp.pp.-
#Pages 6
Date of Issue