  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 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.
