CrowdFi: A Communication Efficient Multi-device Wi-Fi Sensing System
Authors: 
Shoujie Lei, Zhuo Sun, Zhiwen Yu, Zhu Wang, Bin GuoAuthors Info & Claims
Shoujie Lei, Zhuo Sun, Zhiwen Yu, Zhu Wang, Bin GuoAuthors Info & ClaimsArticle No.: 2, Pages 1 - 7
Abstract
In this paper, we propose a novel multi-device wireless sensing system, called CrowdFi, to balance the sensing performance and the transmission cost. In the CrowdFi, from the perspectives of devices, data, and bits, we propose the adaptive priority based transmission scheme for the heterogeneous data importance and time-varying channel of each device. Moreover, we design a two-stage training procedure and the loss functions to achieve a good tradeoff between the sensing accuracy and the transmission delay. We develop a prototype of the CrowdFi, and validate its performance by employing gait recognition as the application case. Experimental results demonstrate that the proposed CrowdFi system can reduce the transmission delay by 86.9%, while achieving the comparable or even improved recognition accuracy.
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Index Terms
- CrowdFi: A Communication Efficient Multi-device Wi-Fi Sensing System
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Published In
September 2023
256 pages
ISBN:9781450399241
DOI:10.1145/3565066
Copyright © 2023 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Published: 26 September 2023
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MobileHCI '23
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MobileHCI '23: 25th International Conference on Mobile Human-Computer Interaction
September 26 - 29, 2023
Athens, Greece
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Overall Acceptance Rate 202 of 906 submissions, 22%
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