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

Mashuk, Md Shadab; Pinchin, James; Siebers, Peer Olaf; Moore, Terry

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.

Citation

Mashuk, M. S., Pinchin, J., Siebers, P. O., & Moore, T. (2021). Demonstrating the potential of indoor positioning for monitoring building occupancy through ecologically valid trials. Journal of Location Based Services, 15(4), 305-327. https://doi.org/10.1080/17489725.2021.1893394

• Journal Article Type: Article
• Acceptance Date: Feb 16, 2021
• Online Publication Date: Mar 2, 2021
• Publication Date: Oct 2, 2021
• Deposit Date: Oct 1, 2022
• Publicly Available Date: Oct 3, 2022
• Journal: Journal of Location Based Services
• Print ISSN: 1748-9725
• Electronic ISSN: 1748-9733
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 15
• Issue: 4
• Pages: 305-327
• DOI: https://doi.org/10.1080/17489725.2021.1893394
• Keywords: Electrical and Electronic Engineering; Computer Networks and Communications; Signal Processing
• Public URL: https://nottingham-repository.worktribe.com/output/7353676
• Publisher URL: https://www.tandfonline.com/doi/abs/10.1080/17489725.2021.1893394?journalCode=tlbs20
• Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Location Based Services on 02/03/2021, available at: https://www.tandfonline.com/doi/abs/10.1080/17489725.2021.1893394?journalCode=tlbs20