The shakedown: developing an indoor-localization system for quantifying toilet usage in offices

The design of sanitary facilities in Australia is subject to regulations prescribing minimum provision. In commercial office buildings, this is tied to male and female employee numbers. These requirements are derived from mathematical models, using queuing theory. Evidence of inadequate sanitary pro...

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Bibliographic Details
Published in:Architectural science review 2020-07, Vol.63 (3-4), p.325-338
Main Authors: Doherty, B., Gardner, N., Ray, A., Higgs, B., Varshney, I.
Format: Article
Language:English
Subjects:
Data science
evidence-based design (EBD)
indoor-localization
machine learning
post-occupancy evaluation (POE)
sensors
toilet usage
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Summary:The design of sanitary facilities in Australia is subject to regulations prescribing minimum provision. In commercial office buildings, this is tied to male and female employee numbers. These requirements are derived from mathematical models, using queuing theory. Evidence of inadequate sanitary provision in numerous contexts points to the necessity to refresh the data, and thinking, that underpins these regulations. Collecting empirical data on human occupancy in sanitary facilities using data science methods is a new way to achieve this and support a shift towards the evidence-based design of sanitary spaces. Accordingly, this article outlines the development and implementation of a novel, privacy-preserving, indoor localization system (ILS) that combines sensors and machine learning to collect and analyse toilet usage data in an office. By evaluating the system's capacity to identify occupancy patterns this research contributes to scholarship on ILS methods as well as a valuable data-set on Australian toilet usage..
ISSN:0003-8628
1758-9622
DOI:10.1080/00038628.2020.1748869