TIIS (한국인터넷정보학회)
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| 한글제목(Korean Title) |
Anomaly Detection in Smart Homes Using Bayesian Networks |
| 영문제목(English Title) |
Anomaly Detection in Smart Homes Using Bayesian Networks |
| 저자(Author) |
Sasan Saqaeeyan
Hamid Haj Seyyed javadi
Hossein Amirkhani
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| 원문수록처(Citation) |
VOL 14 NO. 04 PP. 1769 ~ 1816 (2020. 04) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
The health and safety of elderly and disabled patients who cannot live alone is an important issue. Timely detection of sudden events is necessary to protect these people, and anomaly detection in smart homes is an efficient approach to extracting such information. In the real world, there is a causal relationship between an occupant’s behaviour and the order in which appliances are used in the home. Bayesian networks are appropriate tools for assessing the probability of an effect due to the occurrence of its causes, and vice versa. This paper defines different subsets of random variables on the basis of sensory data from a smart home, and it presents an anomaly detection system based on various models of Bayesian networks and drawing upon these variables. We examine different models to obtain the best network, one that has higher assessment scores and a smaller size. Experimental evaluations of real datasets show the effectiveness of the proposed method.
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| 키워드(Keyword) |
Smart homes
Sensory data
Anomaly detection
Bayesian networks
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| 파일첨부 |
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