TY - GEN
T1 - CrowdFi
T2 - 25th International Conference on Mobile Human-Computer Interaction, MobileHCI 2023 Companion
AU - Lei, Shoujie
AU - Sun, Zhuo
AU - Yu, Zhiwen
AU - Wang, Zhu
AU - Guo, Bin
N1 - Publisher Copyright:
© 2023 Owner/Author.
PY - 2023/9/26
Y1 - 2023/9/26
N2 - 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 , while achieving the comparable or even improved recognition accuracy.
AB - 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 , while achieving the comparable or even improved recognition accuracy.
KW - channel state information
KW - deep learning
KW - multi-device wireless sensing
UR - http://www.scopus.com/inward/record.url?scp=85174306271&partnerID=8YFLogxK
U2 - 10.1145/3565066.3608697
DO - 10.1145/3565066.3608697
M3 - 会议稿件
AN - SCOPUS:85174306271
T3 - Proceedings of the 25th International Conference on Mobile Human-Computer Interaction, MobileHCI 2023 Companion
BT - Proceedings of the 25th International Conference on Mobile Human-Computer Interaction, MobileHCI 2023 Companion
A2 - Komninos, Andreas
A2 - Santoro, Carmen
A2 - Gavalas, Damianos
A2 - Schoening, Johannes
A2 - Matera, Maristella
A2 - Leiva, Luis A.
PB - Association for Computing Machinery, Inc
Y2 - 26 September 2023 through 29 September 2023
ER -