Passive Crowd Speed Estimation in Adjacent Regions With Minimal WiFi Sensing
Passive Crowd Speed Estimation in Adjacent Regions With Minimal WiFi Sensing
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DOI：
10.1109/tmc.2019.2924629
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发表时间：
2020-10-01
影响因子：
7.9
通讯作者：
Mostofi, Yasamin
中科院分区：
文献类型：
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作者：
Depatla, Saandeep;Mostofi, Yasamin
在本文中，我们提出了一种使用 WiFi 设备估算人群速度的方法，而不依赖于人们携带任何设备。我们的方法不仅可以估计有 WiFi 链接的区域的速度，还可以估计邻近可能无 WiFi 的区域的速度。更具体地说，我们在一个区域使用一对 WiFi 链路，然后使用其 RSSI 测量来估计人群速度，不仅在该区域，而且在邻近的无 WiFi 区域。我们首先证明互相关性和穿过两个链接的概率如何隐式地携带有关行人速度的关键信息，并开发一个数学模型将它们与行人速度联系起来。然后，我们在室内和室外进行了 108 次实验来验证我们的方法，其中最多 10 个人在两个相邻区域中行走，每个区域具有不同的速度，这表明我们的框架可以在一个区域中仅使用一对 WiFi 链路来准确估计这些速度。例如，所有实验的 NMSE 均为 0.18。我们还在博物馆类型的环境中评估我们的框架，并估计不同展品的受欢迎程度。最后，我们在 Costco 的过道中进行了实验，估计了买家行为的关键属性。
In this paper, we propose a methodology for estimating the crowd speed using WiFi devices without relying on people to carry any device. Our approach not only enables speed estimation in the region where WiFi links are, but also in the adjacent possibly WiFi-free regions. More specifically, we use a pair of WiFi links in one region, whose RSSI measurements are then used to estimate the crowd speed, not only in this region, but also in adjacent WiFi-free regions. We first prove how the cross-correlation and the probability of crossing the two links implicitly carry key information about the pedestrian speeds and develop a mathematical model to relate them to pedestrian speeds. We then validate our approach with 108 experiments, in both indoor and outdoor, where up to 10 people walk in two adjacent areas, with a variety of speeds per region, showing that our framework can accurately estimate these speeds with only a pair of WiFi links in one region. For instance, the NMSE over all experiments is 0.18. We also evaluate our framework in a museum-type setting and estimate the popularity of different exhibits. We finally run experiments in an aisle in Costco, estimating key attributes of buyers' behaviors.