BlueEye

Interesting applications of crowdsensing include measurement of crowdedness at public places and evaluating the extent of social interactions between people, at large gatherings. These require enabling the accurate estimation of proximity between two or more people. Since mobile phones have emerged as the most ubiquitous sensing and computing platform, carried by almost all people close to their body, it is logical to use the same for proximity detection. Further, in order to motivate people to use such application, it is necessary to estimate distances accurately, using only short blocks of sampled signal strengths. In this paper the authors present a mobile based proximity detection system, codenamed BlueEye which is based on Bluetooth. To achieve better distance estimates, BlueEye proposes a new form of path loss model which takes into account the relative orientation of mobile phones. The results show enhanced distance estimates when the separation between devices is less than 8 feet.