Demonstrating the potential of indoor positioning for monitoring building occupancy through ecologically valid trials

Mashuk, MS ORCID: https://orcid.org/0000-0001-7641-4865, Pinchin, J ORCID: https://orcid.org/0000-0001-6645-7212, Siebers, PO ORCID: https://orcid.org/0000-0002-0603-5904 and Moore, T ORCID: https://orcid.org/0000-0002-6169-059X 2021, 'Demonstrating the potential of indoor positioning for monitoring building occupancy through ecologically valid trials' , Journal of Location Based Services, 15 (4) , pp. 305-327.

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Abstract

Assessing building performance related to energy consumption in post-design-occupancy stage requires knowledge of building occupancy pattern. These occupancy data can potentially be collected from trials and used to improve the prediction capability of building performance models. Due to the limitations of passive sensors in detecting an individual’s occupancy throughout the building, indoor positioning can provide a viable alternative. Previous work on using indoor positioning techniques for detecting building occupancy mainly focused on passive monitoring through Wi-Fi or BLE proximity sensing by estimating the number of occupants at any given time. This paper extends our previous research and demonstrates the merit of occupancy monitoring through active tracking at an individual level using a smartphone-based multi-floor indoor positioning system. The paper discusses the design of a novel occupancy detection trial setup, mimicking real-world office occupancy and discusses the outcome of the ecologically valid trials using the developed positioning system. In total 50 occupancy trials were carried out by around 22 participants comprising of a variety of routes within the building. The trial results are presented to demonstrate the level of accuracy achievable against a specific set of the performance metric necessary for building occupancy detection and modelling.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Journal of Location Based Services
Publisher: Taylor & Francis
ISSN: 1748-9725
Depositing User: MS Mashuk
Date Deposited: 14 Nov 2022 12:00
Last Modified: 14 Nov 2022 12:00
URI: https://usir.salford.ac.uk/id/eprint/65579

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