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Mashuk, Md. Shadab, Pinchin, James, Siebers, Peer-Olaf and Moore, Terry (2018) A smart phone based multi-floor indoor positioning system for occupancy detection. In: IEEE/ION PLANS 2018, 23-26 Apr 2018, Monterey, USA.

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Abstract

At present there is a lot of research being done simulating building environment with artificial agents and predicting energy usage and other building performance related factors that helps to promote understanding of more sustainable buildings. To understand these energy demands it is important to understand how the building spaces are being used by individuals i.e. the occupancy pattern of individuals. There are lots of other sensors and methodology being used to understand building occupancy such as PIR sensors, logging information of Wi-Fi APs or ambient sensors such as light or CO2 composition. Indoor positioning can also play an important role in understanding building occupancy pattern. Due to the growing interest and progress being made in this field it is only a matter of time before we start to see extensive application of indoor positioning in our daily lives.

This research proposes an indoor positioning system that makes use of the smart phone and its built-in integrated sensors; Wi-Fi, Bluetooth, accelerometer and gyroscope. Since smart phones are easy to carry helps participants carry on with their usual daily work without any distraction but at the same time provide a reliable pedestrian positioning solution for detecting occupancy. The positioning system uses the traditional Wi-Fi and Bluetooth fingerprinting together with pedestrian dead reckoning to develop a cheap but effective multi floor positioning solution.

The paper discusses the novel application of indoor positioning technology to solve a real world problem of understanding building occupancy. It discusses the positioning methodology adopted when trying to use existing positioning algorithm and fusing multiple sensor data. It also describes the novel approach taken to identify step like motion in absence of a foot mounted inertial system. Finally the paper discusses results from limited scale trials showing trajectory of motion throughout the Nottingham Geospatial Building covering multiple floors.

Item Type:	Conference or Workshop Item (Paper)
RIS ID:	https://nottingham-repository.worktribe.com/output/936660
Additional Information:	© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. To be published in Proceedings of the 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS)
Keywords:	Occupancy; Particle Filter; Indoor Positioning; Wifi; Bluetooth; Multi sensor fusion; Motion detection
Schools/Departments:	University of Nottingham, UK > Faculty of Science > School of Computer Science
Related URLs:	URL URL Type https://www.ion.org/plans/abstracts.cfm?paperID=5866 UNSPECIFIED
Depositing User:	Eprints, Support
Date Deposited:	16 May 2018 08:08
Last Modified:	04 May 2020 19:39
URI:	https://eprints.nottingham.ac.uk/id/eprint/51816

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