CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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id caadria2019_286
authors Dobbs, Tiara
year 2019
title Face-to-Face with People in Spaces - A method to identify face-to-face interactions using an indoor positioning system.
source M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 643-652
summary Recent developments in indoor positioning technology means gathering personal interaction data is possible however, the process of analysing this data to determine where and when interactions occur indoors is not yet standardised.This paper proposes a method to gather and examine indoor positioning data to infer face-to-face interactions indoors. The case study looks specifically at indoor office environment however the principles shown can be applied to other indoor spaces. This paper explores a high-level technological methodology that gathers indoor positioning data from users. A formula is used to calculate if, when and where interactions occur over a floor-plan, as well as visualising these interactions to highlight high and low interaction areas. The system considers the proximity between the individuals, the angle between their forward physical orientation, and any obstructions that might divide individuals from each other. The information presented in this paper can be used as a theoretical baseline to inform future post-occupancy evaluation methods. Additionally, this paper demonstrates the merit of using indoor positioning systems to test the effectiveness of design principles in encouraging face-to-face interactions of the users.
keywords Post-occupancy evaluations; Face-to-face interac-tions; Indoor positioning system; Data driven design
series CAADRIA
full text file.pdf (1,593,428 bytes)
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