Exploration of optimal Wi-Fi probes layout and estimation model of real-time pedestrian volume detection

Real-time pedestrian volume data are becoming increasingly important to business strategy adjustment and guiding measures of shopping malls, tourist attractions, and transportation hubs. Wi-Fi probes are widely used to capture and study the media access control layer information of mobile devices but often with low detection and precision. This article mainly proposes an enhanced method to increase detection rate and precision under Wi-Fi-based system. Device test was first introduced to guarantee the performance of probes. Based on the theoretical analysis on the influences of probes’ relative locations, four layout schemes of multi-probes were compared, and the optimal one with the highest detection rate was identified experimentally. Based on the optimal layout, an estimation model between actual and detected volume was established after data cleaning. In total, two correction parameters were introduced to modify the model and shows a high estimation accuracy (root mean square error is 15.32 persons) in the experiment at Tongji University. The results of experiment proved that the proposed optimal layout scheme of multiple probes and estimation model can effectively improve the detection performance and precision of pedestrian volume and help increase the reliability and application value of Wi-Fi-based detection.