Detecting social interactions through commercial mobile devices

Social interactions represent an important factor in the human society and it presents different issues depending on the user category involved. In this paper, we present technological issues of using exclusively commercial mobile devices of the users to detect social interactions. Then, we propose a solution based on Bluetooth wearable tags, minimally invasive and low-cost. This solution is based on the analysis of the RSSI emitted by BLE beacon messages and received by the user personal device through a dedicated mobile app. We collected such information during a calibration campaign. To this purpose, we recruited volunteer students from a high school who mimic a number of interactions with class-mates. We compared the results of our algorithm with a diary of the interactions provided by the students, obtaining an overall accuracy of 81% and F-Score measure of 84%.