Exploring spatio-temporal data from distributed Bluetooth scanning

Abstract

Roskilde Festival is a music event attended every year by 130.000 people, providing a big opportunity for collecting spatio-temporal data of the participants, given its high population density (0,78 [pop./m2]). In the current researches, the data collection has been achieved by installing smartphones in the areas of interest, which can detect the Bluetooth device of the participants’ mobile phones. However, the installation of these smartphones requires a permanent access to a power supply, which can be difficult to guarantee due to infrastructure limitations. Considering that during the 10 days of the event 50% of the participants may carry a smartphone, we propose the use these devices to collect other participants’ data. This solution should reduce the energy required to detect other devices, due to the limited access to recharge the battery of their smartphones. In this work, we present the design, implementation and deployment of software for scanning Bluetooth devices. This software can be attached as a library to other applications intended for the festival, running as the background process. We designed an algorithm to reduce the energy used in the Bluetooth devices detection. Using this technique, we could collect the data of 2.4% of the participants of the festival, with a 60% of the concerts area scanned at least once. This technique demonstrates to be highly scalable, depending on the amount of participants using the applications of the event and not on infrastructural limitations. The data collected comprises the location of the smartphone used in the scans, the detected devices and the network conditions, which can be used to analyze the behavior of the participants.