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 the indoor office environments however the principles are 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.

A link to the CAADRIA published paper can be found here.

Pretty impressive right? We should talk about it!