Biblio

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.