Door-Monitor: Counting In-and-Out Visitors with COTS WiFi Devices

Visitor counting can be attractive to various applications, like business management and marketing investigation. Recently, many studies have employed wireless signals to achieve visitor counting without people's active participation and privacy intrusion. However, existing systems mainly count the overall visitors inside a certain area, which fails to provide the fine-grained information of the coming and leaving visitor flow. Unlike previous studies, this article proposes to count the in-and-out visitors to monitor visiting frequency and population, which can be applied for many indoor places, such as shops and restaurants. Therefore, we present the first WiFi-based in-and-out visitor counting system, Door-Monitor, which obtains the direction (enter or exit) and the number of visitors passing by the door. The WiFi signals enable us to count the visitors in a low-cost and nonintrusive way, and it can tell the exact number of visitors even when multiple persons pass by the door simultaneously. To detect the visitors' passing direction, we show that the patterns in the phase difference series can indicate the entering and exiting passing directions by analyzing the effects of the passing behavior on the signal's phase information. To count the passing visitors, we perform a short time Fourier transformation on the phase difference series to generate the spectrogram, on which the convolutional neural network is applied for building a counting model. The experimental results show that the average accuracies of passing direction detection and visitor counting are 95.2% and 94.5%, respectively.