Crowd Counting is a very interesting problem aiming at counting people typically based on density averages
and/or aerial images. This is very useful to prevent crowd crushes, especially on urban environments with
high crowd density, or to count people in public demonstrations. In addition, in the last years, it has become
of paramount importance for pandemic management. For those reasons, giving users automatic mechanisms
to anticipate high risk situations is essential. In this work, we analyze ID-based Crowd Counting, and propose
a real-time Crowd Counting system based on the Ephemeral ID broadcast by contact tracing applications on
wearable devices. We also performed some simulations that show the accuracy of our system in different
situations.
