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View all- Ivanov R(2021)Accuracy analysis of BLE beacon-based localization in smart buildingsJournal of Ambient Intelligence and Smart Environments10.3233/AIS-21060713:4(325-344)Online publication date: 1-Jan-2021
Remote detection of social interactions in indoor environments through bluetooth low energy beacons
Pages 203 - 217
Abstract
The way people interact in daily life is a challenging phenomenon to be captured and studied without altering the natural rhythm of the interactions. We investigate the development of automated tools that may provide information to the researchers that analyse interactions among humans. One important requirement of these tools is that should not interfere with the subjects under observation, in order to avoid any alteration in the subject’s normal behaviour. Our approach is based on the detection of proximity among groups of people that is obtained using commercial wearable wireless tags based on Bluetooth Low Energy (BLE) and a novel algorithm called Remote Detection of Human Proximity (ReD-HuP) that analyses the wireless signal of tags and produce the proximity information. The algorithm, which has been validated against the ground truth of an experimental dataset, achieves an accuracy of 95.91% and an F-Score of 95.79%.
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Published: 01 January 2020
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View all- Ivanov R(2021)Accuracy analysis of BLE beacon-based localization in smart buildingsJournal of Ambient Intelligence and Smart Environments10.3233/AIS-21060713:4(325-344)Online publication date: 1-Jan-2021