  Counting the number of people inside a building, from outside and without
entering the building, is crucial for many applications. In this paper, we are
interested in counting the total number of people walking inside a building (or
in general behind walls), using readily-deployable WiFi transceivers that are
installed outside the building, and only based on WiFi RSSI measurements. The
key observation of the paper is that the inter-event times, corresponding to
the dip events of the received signal, are fairly robust to the attenuation
through walls (for instance as compared to the exact dip values). We then
propose a methodology that can extract the total number of people from the
inter-event times. More specifically, we first show how to characterize the
wireless received power measurements as a superposition of renewal-type
processes. By borrowing theories from the renewal-process literature, we then
show how the probability mass function of the inter-event times carries vital
information on the number of people. We validate our framework with 44
experiments in five different areas on our campus (3 classrooms, a conference
room, and a hallway), using only one WiFi transmitter and receiver installed
outside of the building, and for up to and including 20 people. Our experiments
further include areas with different wall materials, such as concrete, plaster,
and wood, to validate the robustness of the proposed approach. Overall, our
results show that our approach can estimate the total number of people behind
the walls with a high accuracy while minimizing the need for prior
calibrations.
