Article
Version 1
Preserved in Portico This version is not peer-reviewed
A Novel Device-Free Counting Method Based on Channel Status Information
Version 1
: Received: 1 August 2018 / Approved: 1 August 2018 / Online: 1 August 2018 (10:10:13 CEST)
A peer-reviewed article of this Preprint also exists.
Li, J.; Tu, P.; Wang, H.; Wang, K.; Yu, L. A Novel Device-Free Counting Method Based on Channel Status Information. Sensors 2018, 18, 3981. Li, J.; Tu, P.; Wang, H.; Wang, K.; Yu, L. A Novel Device-Free Counting Method Based on Channel Status Information. Sensors 2018, 18, 3981.
Abstract
Crowd counting is of significant importance for numerous applications, e.g., urban security, intelligent surveillance and crowd management. Existing crowd counting methods typically require specialized hardware deployment and strict operating conditions, thereby hindering their widespread deployment. To acquire a more effective crowd counting approach, a device-free counting method based on Channel Status Information (CSI) is proposed, which could mitigate environment noise through wavelet transform and extract the amplitude or phase covariance matrix as the feature vector. Moreover, both the spatial diversity and frequency diversity are leveraged to improve detection robustness. The accuracy of the proposed CSI-based method is compared with a renowned crowd counting one, i.e., Electronic Frog Eye: Counting Crowd Using WiFi (FCC). The experimental results reveal an accuracy improvement of 30% over FCC.
Keywords
wavelet transform; covariance matrix; spatial diversity;frequency diversity; robustness
Subject
Computer Science and Mathematics, Computer Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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