An adaptive sensor network for home intrusion detection by human activity profiling

An adaptive sensor network for home intrusion detection by human activity profiling

An adaptive sensor network for home intrusion detection is proposed. The sensor network combines profile-based anomaly detection and adaptive information processing based on hidden Markov models (HMM) that allow the system to train and tune the profiles automatically. The trade-off between miss-alar...

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Bibliographic Details
Published in:Artificial life and robotics Vol. 16; no. 1; pp. 36 - 39
Main Authors: Tokumitsu, Masahiro, Murakami, Masashi, Ishida, Yoshiteru
Format: Journal Article
Language:English
Published: Japan Springer Japan 01-06-2011
Subjects:
Anomalies
Artificial Intelligence
Computation by Abstract Devices
Computer Science
Control
Human
Intrusion
Mathematical models
Mechatronics
Networks
Original Article
Robotics
Sensors
Tradeoffs
Trains
Adaptive information processing
Sensor network
Human activity profile
Home intrusion detection
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Summary:An adaptive sensor network for home intrusion detection is proposed. The sensor network combines profile-based anomaly detection and adaptive information processing based on hidden Markov models (HMM) that allow the system to train and tune the profiles automatically. The trade-off between miss-alarms and false alarms has been studied experimentally. Several types of hypothetical intrusion have been tested and successfully detected. However, hypothetical anomalies such as supposing that a resident has fallen down due to sudden illness have been difficult to detect.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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content type line 23
ISSN:1433-5298
1614-7456
DOI:10.1007/s10015-011-0872-5