TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
A Robust and Device-Free Daily Activities Recognition System using Wi-Fi Signals |
| 영문제목(English Title) |
A Robust and Device-Free Daily Activities Recognition System using Wi-Fi Signals |
| 저자(Author) |
Enjie Ding
Yue Zhang
Yun Xin
Lei Zhang
Yu Huo
Yafeng Liu
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| 원문수록처(Citation) |
VOL 14 NO. 06 PP. 2377 ~ 2397 (2020. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Human activity recognition is widely used in smart homes, health care and indoor monitor. Traditional approaches all need hardware installation or wearable sensors, which incurs additional costs and imposes many restrictions on usage. Therefore, this paper presents a novel device-free activities recognition system based on the advanced wireless technologies. The fine-grained information channel state information (CSI) in the wireless channel is employed as the indicator of human activities. To improve accuracy, both amplitude and phase information of CSI are extracted and shaped into feature vectors for activities recognition. In addition, we discuss the classification accuracy of different features and select the most stable features for feature matrix. Our experimental evaluation in two laboratories of different size demonstrates that the proposed scheme can achieve an average accuracy over 95% and 90% in different scenarios.
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| 키워드(Keyword) |
CSI
human activities recognition
phase transform
device-free system
classification algorithms
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| 파일첨부 |
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