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Occupancy detection for building emergency management using BLE beacons

Occupancy detection for building emergency management using BLE beacons

Filippoupolitis, Avgoustinos, Oliff, William and Loukas, George (2016) Occupancy detection for building emergency management using BLE beacons. In: Computer and Information Sciences: 31st International Symposium, ISCIS 2016, Kraków, Poland, October 27–28, 2016, Proceedings. Communications in Computer and Information Science, 659 . Springer International Publishing, Cham, Switzerland, pp. 233-240. ISBN 978-3-319-47216-4 ISSN 1865-0929 (Print), 1865-0937 (Online) (doi:10.1007/978-3-319-47217-1_25)

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Abstract

Being able to reliable estimate the occupancy of areas inside a building can prove beneficial for managing an emergency situation, as it allows for more efficient allocation of resources such as emergency personnel. In indoor environments, however, occupancy detection can be a very challenging task. A solution to this can be provided by the use of Bluetooth Low Energy (BLE) beacons installed in the building. In this work we evaluate the performance of a BLE based occupancy detection system geared towards emergency situations that take place inside buildings. The system is composed of BLE beacons installed inside the building, a mobile application installed on occupants' mobile phones and a remote control server. Our approach does not require any processing to take place on the occupants' mobile phones, since the occupancy detection is based on a classifier installed on the remote server. Our real-world experiments indicated that the system can provide high classification accuracy for different numbers of installed beacons and occupant movement patterns.

Item Type: Conference Proceedings
Title of Proceedings: Computer and Information Sciences: 31st International Symposium, ISCIS 2016, Kraków, Poland, October 27–28, 2016, Proceedings
Additional Information: © The Editor(s) (if applicable) and The Author(s) 2016. This book is published open access. This book is distributed under the terms of the Creative Commons Attribution 4.0 International License
Uncontrolled Keywords: Occupancy detection; BLE; Machine learning
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Computing & Information Systems
Last Modified: 31 Aug 2017 13:22
Selected for GREAT 2016: None
Selected for GREAT 2017: GREAT c
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/16037

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