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http://dx.doi.org/10.9708/jksci.2022.27.04.111

Abnormal Situation Detection Algorithm via Sensors Fusion from One Person Households  

Kim, Da-Hyeon (Dept. of Software, Korea National University of Transportation)
Ahn, Jun-Ho (Dept. of Software, Korea National University of Transportation)
Publication Information
Journal of the Korea Society of Computer and Information / v.27, no.4, 2022 , pp. 111-118 More about this Journal
Abstract
In recent years, the number of single-person elderly households has increased, but when an emergency situation occurs inside the house in the case of single-person households, it is difficult to inform the outside world. Various smart home solutions have been proposed to detect emergency situations in single-person households, but it is difficult to use video media such as home CCTV, which has problems in the privacy area. Furthermore, if only a single sensor is used to analyze the abnormal situation of the elderly in the house, accurate situational analysis is limited due to the constraint of data amount. In this paper, therefore, we propose an algorithm of abnormal situation detection fusion inside the house by fusing 2DLiDAR, dust, and voice sensors, which are closely related to everyday life while protecting privacy, based on their correlations. Moreover, this paper proves the algorithm's reliability through data collected in a real-world environment. Adnormal situations that are detectable and undetectable by the proposed algorithm are presented. This study focuses on the detection of adnormal situations in the house and will be helpful in the lives of single-household users.
Keywords
Abnormality detection; Single; 2DLiDAR; Dust sensor; Voice sensor; Sensors fusion;
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Times Cited By KSCI : 1  (Citation Analysis)
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