An Analysis of Distance Estimation to Detect Proximity in Social Interactions

In the area of human behaviour analysis, smartphones are opening new possibilities where a multitude of embedded sensors can be used to regularly monitor users’ daily activities and interactions in a non-obtrusive way. In this paper we focus on proximity detection, which refers to the ability of a system to recognize the co-location of two or more individuals and infer interpersonal distances. We present Comm2Sense, our mobile platform to detect proximity among users exploiting sensing capabilities available in modern smartphones, namely Wi-Fi hotspot and Wi-Fi receiver. The platform estimates the distance between subjects applying data mining techniques to the analysis of the Wi-Fi RSSI. We describe the design and implementation of the platform, together with the technical solutions implemented in each module. We demonstrate that the proposed platform is able to achieve a resolution of 0.5 m.