客流量监测的WiFi嗅探网格化方法

A passenger flow monitoring method based on gridded WiFi sniffing

在众多监测客流量的方法中,WiFi嗅探客流监测方法具有硬件布置简单、监测范围适中的优点。但是,由于单个WiFi嗅探设备监测范围难以灵活改变,易发生整个客流监测系统监测范围无法准确覆盖目标区域的情况。为此,提出了一种通过约束单个WiFi嗅探设备监测范围,使目标区域网格化的客流监测方法。首先,通过采集大量基础数据,对不同传播距离的探寻请求帧RSSI最优估计值进行经典对数拟合、建模;其次,根据实际尺寸对目标区域进行网格划分,利用拟合模型计算网格划分的动态阈值,将WiFi嗅探设备的监测范围约束在网格内;最后,通过大数据分析合并网格内小客流数据,从而得知目标监测区域内整体客流情况。模型仿真和实际验证表明,本方法得到的整体客流量能够作为目标区域客流的实时基础数据,为大型区域的交通安全管理提供了一种实用的技术手段。

Among various methods of monitoring passenger flow,WiFi sniffer monitoring method has the advantages of simple hardware layout and intermediate monitoring range.But the entire passenger flow monitoring system can not accurately cover the target area due to the difficulty in flexibly changing the monitoring range of a single WiFi sniffer.To this end,this paper presents a monitoring method that constrains the monitoring range of a single WiFi sniffer to grid the target area.Firstly,Collecting a large amount of basic data and the RSSI optimal estimates of the probe request frame for different propagation distances are fitted and modeled by classical logarithmic model;Secondly,meshing the target area according to the actual size,and using fitting model to calculate the dynamic threshold of the grid to constraint the WiFi sniffer monitoring range into the grid;Finally,by large data analysis method to merge the small passenger flow data in the grid can show the overall passenger flow in the target area.Compared with the actual count results,the overall passenger flow obtained by this method can be used as the real-time basic data of the target area,which provides a practical technical means for large-scale traffic safety management.