An Empirical Study of How Socio-Spatial Formations are Influenced by Interior Elements and Displays in an Office Context

Abstract

The design of a workplace can have a profound impact on the effectiveness of the workforce utilizing the space. When considering dynamic social activities in the flow of work, the constraints of the static elements of the interior reveals the adaptive behaviour of the occupants in trying to accommodate these constraints while performing their daily tasks. To better understand how workplace design shapes social interactions, we ran an empirical study in an office context over a two week period. We collected video from 24 cameras in a dozen space configurations totaling 1,920 hours of recorded activities. We utilized computer vision techniques, to produce skeletonized representations of the occupants, to assist in the annotation and data analysis process. We present our findings of socio-spatial formation patterns and the effects of furniture and interior elements on the observed behaviour of collaborators for both computer-supported work and for unmediated social interaction. Combining the observations with an interview of the occupants' reflections, we discuss dynamics of socio-spatial formations and how this knowledge can support social interactions in the domain of space design systems and interactive interiors.

Is an outgroup welcome with open arms? Approach and avoidance motor activations and outgroup prejudice.

“…In all of these cases designing workstations and adjusting furniture may have implications on social behaviors (Lee, Lee, Zhang, Tessier, & Khan, 2019). In an office context, people naturally use body adjustments to achieve face-to-face interaction and improve social communication while taking into consideration design limitations (Lee et al, 2019). But what if interaction were to be with an outgroup person?…”

“…In different societies contact with outgroup members having a salient group identity is inevitable, and occurs, for example, in community services (health care, governmental offices), educational systems or multicultural workspaces. In all of these cases designing workstations and adjusting furniture may have implications on social behaviors (Lee, Lee, Zhang, Tessier, & Khan, 2019). In an office context, people naturally use body adjustments to achieve face-to-face interaction and improve social communication while taking into consideration design limitations (Lee et al, 2019).…”

Towards Responsive Architecture that Mediates Place

“…For instance, the discrepancies between sensor-based readings and comfort satisfaction ratings [105] were contrasted by in-situ tangible objects allowing occupants to report experiential data opportunistically [8]. Human space-use behaviour has been tracked by pervasive sensing technologies such as movement-tracking bracelets [102], infrared markers [6] or advanced computer vision algorithms [43]. These developments revealed that the socio-spatial usage of a workplace is influenced by the professional profiles of the occupants [102], as well as architectural qualities such as visual exposure and visual openness [6] or spatial layout of office desks and partitions [43].…”

“…Spatial adaptation has existed since the early days of architecture, as adjustable elements like windows, doors or curtains allow occupants to adapt their exposure to light, ventilation, noise or privacy. Although it has been shown that certain spatial layouts can inform the ergonomic [43] or social comfort [44] of occupants, architects only sparingly integrated sliding [84] or rotating [90] walls in their designs probably because they require a considerable amount of manual labour to be altered. However, as recent technological advances in robotic furniture [86,88], shape-shifting public displays [93] and haptic feedback in virtual reality [37,91] have demonstrated how mobile robots can now move life-sized physical elements like sofas, chairs or room dividers, one could foresee a future in which such architecturally-scaled spatial layouts could become autonomously adapted.…”

Contact Area Detector using Cross View Projection Consistency for COVID-19 Projects

“…We use the office dataset from [12], The people from the video are not performers, they are office users being captured from two cameras as shown in Fig. 1.…”