Social distancing estimation using an IoT-based system and Bluetooth signal detection

This paper shows the design of a low-cost IoT device which provides data that are processed in order to estimate the number of people in a room and how they interacted distancially over a period of time ranging from the minute to the week. Our device is based on the collection of Bluetooth IDs as well as their RSSI signal strength. The data collected is sent to a server through a LoRa communication. The data collected is then processed with MATLAB to estimate contacts in-between people and verify the compliance with the maximum human capacity in a room. The device had to collected a set of data over one week of experiments. This paper first presents the steps that were followed to create a prototype to retrieve the Bluetooth IDs. Then, it presents simulations carried out with the Matlab software to estimate the distribution of people in an environment. And finally, the experimental results are presented and analyzed. The analysis of the simulation results concluded about a possible efficiency of our device to estimate the distancing interaction between people in a community as well as if they respected quotas of people allowed in a room. In addition, the experimental results are very encouraging.