A Bluetooth Dataset for Proximity Detection in Indoor Environments Collected with Smartphones

How to cite this work: Michele Girolami, Davide La Rosa, Paolo Barsocchi, "A CrowdSensing-based approach for proximity detection in indoor museums with Bluetooth tags", Ad Hoc Networks, Volume 154, 2024, 103367, ISSN 1570-8705, https://doi.org/10.1016/j.adhoc.2023.103367. The dataset contains 32 folders, named R, corresponds to the test number (R1 to R32). Each folder contains 2 files: - -beacons.csv: the file with the raw data - timestamp: Unix timestamps in millis - name: name of the artwork - address: MAC address of the artwork's tag - major: ID of the artwork -rssi: RSSI value expressed in dBm estimated by the receiving device --groundtruth.csv: the with the ground truth - timestamp: Unix timestamps in millis - event: the type of event associated with the entry. IN: visit check-in, OUT: visit check-out - artwork: ID of the artwork