Document - Remote detection of indoor human proximity using bluetooth low energy beacons

2019

Conference article Closed Access

Remote detection of indoor human proximity using bluetooth low energy beacons

Mavilia F., Palumbo F., Barsocchi P., Chessa S., Girolami M.

Proximity Social Interactions Bluetooth Low Energy

The way people interact in daily life is a challenging phenomenon to capture and to study without altering the natural rhythm of interactions. Our work investigates the possibility of automatically detecting proximity among people, the first mandatory condition before a dyad starts interacting. We present Remote Detection of Human Proximity (ReD-HuP), an algorithm based on the analysis of Bluetooth Low Energy beacons emitted by commercial wearable tags. We validate ReD-HuP with real-world indoor settings and we compare its performance with respect to detailed ground truth data collected from a number of volunteers. Experimental results show an accuracy and F-Score metric up to 95%.

Source: IE 2019 - 15th International Conference on Intelligent Environments, pp. 16–21, Rabat, Morocco, June 24-27, 2109

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@inproceedings{oai:it.cnr:prodotti:415560,
	title = {Remote detection of indoor human proximity using bluetooth low energy beacons},
	author = {Mavilia F. and Palumbo F. and Barsocchi P. and Chessa S. and Girolami M.},
	doi = {10.1109/ie.2019.000-1},
	booktitle = {IE 2019 - 15th International Conference on Intelligent Environments, pp. 16–21, Rabat, Morocco, June 24-27, 2109},
	year = {2019}
}