WiCrowd: Counting the Directional Crowd With a Single Wireless Link

Wi-Fi-based crowd counting is predominant because of its noninvasive and ubiquitous advantages. However, the existing Wi-Fi-based crowd counting systems have the constraint that there is always a maximum number of people counted. In order to address this issue, a Wi-Fi-based cross-environment crowd counting system, which has the capability of both estimating the walking direction and crowd counting by only one single link, called WiCrowd is proposed. WiCrowd relaxes the restriction of people number counted and demonstrates its extraordinary robustness when the environment changes. The signal change trends of the people flow are theoretically analyzed and people flow moving direction is inferred. The unique features using the eigenvalue of the convariance matrix of amplitude and phase are derived to effectively detect prominent signal changes led by the crowd movement near LoS. By adopting the augmented feature representations, the robustness of WiCrowd is improved when the environment changes. The experimental results in a typical indoor environment demonstrate the superior performance of WiCrowd. This system achieves 87.4%, 85.8%, and 79.4% recognition accuracy for the flow movement direction estimation, respectively, and 82.4% and 81.6% of the overall cross-environment accuracy for the number of subjects counted in the people flow.