Activity Learning as a Foundation for Security Monitoring in Smart Homes

被引:31
作者
Dahmen, Jessamyn [1 ]
Thomas, Brian L. [1 ]
Cook, Diane J. [1 ]
Wang, Xiaobo [2 ]
机构
[1] Washington State Univ, Sch Elect Engn & Comp Sci, Pullman, WA 99164 USA
[2] FutureWei Technol Inc, Santa Clara, CA 95050 USA
基金
美国国家科学基金会;
关键词
security monitoring; activity learning; anomaly detection; smart home automation; ACTIVITY RECOGNITION; FRAMEWORK; PATTERNS; BEHAVIOR;
D O I
10.3390/s17040737
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Smart environment technology has matured to the point where it is regularly used in everyday homes as well as research labs. With this maturation of the technology, we can consider using smart homes as a practical mechanism for improving home security. In this paper, we introduce an activity-aware approach to security monitoring and threat detection in smart homes. We describe our approach using the CASAS smart home framework and activity learning algorithms. By monitoring for activity-based anomalies we can detect possible threats and take appropriate action. We evaluate our proposed method using data collected in CASAS smart homes and demonstrate the partnership between activity-aware smart homes and biometric devices in the context of the CASAS on-campus smart apartment testbed.
引用
收藏
页数:17
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