Room-level proximity detection based on RSS of dual-band Wi-Fi signals

Proximity information of users can be used in various applications (e.g., user interactions in social networks). Applying conventional works to room-level proximity detection is difficult because there is a limitation of the proximity range within 5 m. In this paper, we propose a room-level proximity detection method based on the similarity of received information of Wi-Fi signals between users. We use Wi-Fi signals in both 2.4 GHz band and 5 GHz band, and use relevant features that indicate the similarity of received signal strength (RSS) of beacon frames and access points (APs) sets from which users receives them. Through extensive experiments, in which we recognize whether or not users exist in the same room with a size approximately from 10 to 15 m square, we demonstrate that our proposed method can realize room-level proximity detection with high robustness to relative location of users and APs.