Work & Campus

Towards ‘Human Aware Architecture’: environment assisted learning and working

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In this study the Work & Campus workfield proposes a new use for augmented reality, or AR, in making work and learning spaces healthier for individuals by adjusting their environment based on their personal needs.

It is widely understood that mental and physical health affect each other, as well as the ability to efficiently, creatively and critically take on tasks in the world (and the workplace).

Environmental factors – the sensorial phenomena we encounter as we move through space – are also known to affect mental and physical health. Environmental factors such as the temperature of a room, the height of a table, the brightness of a screen, may produce different effects on the mental and physical health of different people.

Often the design of these environmental factors is standardised, not easily changed and yet expected to meet a divergent set of needs. Indeed, at times the design fails and leaves users of the environment in worse shape than when they entered.

The inadequacy of homogenously designed environments to meet these divergent needs is especially apparent in office spaces, where workers are subject to identical ambient conditions and given little latitude to adjust even their personal spaces. What’s more, the mental and physical stress people endure in environments which ill suit their needs only serves to compound the psychological stress induced by work itself.

Unhealthy places of work and learning

The 2015 European Risk Observatory Report from the European Agency for Safety and Health at Work counts work-related stress as the second most frequently reported work-related health problem in Europe. One way to address the ever-worsening issue of stress-related mental and physical health problems, which cause absenteeism and represent a significant burden on healthcare systems, is to alter environmental factors in such a way as to specifically adapt to the mental and physical needs of individual people.

The following proposal posits that there is a gap between the responsiveness of the environment to human mental and physical needs and the ability of individual humans to adjust the environment to meet their specific needs. It also posits that bioresponsive systems will soon be available for implementation in working and learning spaces, and can be used to close this gap.

A new use for AR

Similarly to MIT’s Fluid Interfaces Research Group, which seeks to develop 'human computer symbiotic systems’ that 'mediate [user's] interaction with the physical world around them', UNStudio’s Work & Campus workfield proposes expanding notions of 'augmented reality' from their current single-use (app-based retail and social media functions) into integrated systems with long-term, individualised purposes.

An environment which responds specifically to an individual’s mental and physical states could measure that user’s needs and record ‘biomarkers’ and behavioural patterns. Biomarkers include heart rate, blood sugar levels, body temperature, somatic activity and hormone levels, while behavioural patterns like toe-tapping and avoiding eye contact can correspond to emotional states such as agitation and worry, respectively.

This type of ‘human-computer symbiotic system’ could be piloted in workspaces and educational settings, becoming something called ‘environment assisted learning and working’, or EALW.

How it works

First, this EALW system would need to establish a baseline reading of a user’s biomarkers and behavioural patterns before launching a real-time feedback loop with the user via two types of inputs. Physical sensors, in a form resembling a FitBit, say, would record biomarkers from user’s bodies. Audiovisual interfaces like microphones and cameras would capture behavioural patterns, like changes in the speed or pitch of a voice, which can be ‘read’ as reflecting a particular emotional state of that user based on the baseline reading.

Once properly calibrated, the EALW system would be able to tailor a microclimate to precisely match the needs of a user, and thereby allow them the best possible conditions for work (or study) performance and personal health. The constant feedback of user information to the EALW system would sustain continual adaptation, the key to its functioning.

By adapting over time to produce personalised stimuli like changes to ambient light, graphics on augmented surfaces (such as desks and wall panels) and sound signals, the EALW system could (consciously or subconsciously) cue changes in the behaviour of the user. By monitoring glucose levels, for example, the EALW system could alert diabetic users (or anyone else) when their blood sugar fluctuates and encourage them to eat, hydrate, or rest. Instead of pinging the user's dedicated glucose monitor, as in Dexcom's 'continuous glucose monitoring' system, the EALW system could softly flash a light or make a subtle sound. In other words, the EALW system would merge previously disparate biomonitoring devices into one contiguous system.

Crucial to the EALW system is of course the privacy of its users' information, which would be stored securely and confidentially: private from employer, insurer, colleagues and doctor.

© Pim Top, courtesy of Prooff UNStudio's StandTable allows users to work at different heights.

System components

An EALW system would comprise a number of architectural elements from a broad collection, such as walls, windows, chairs, desks and glasses. These elements would each play a role in sensing biomarkers and behavioural patterns and, in turn, altering the microclimate and inspiring a change in behaviour. Further, each element would be linked in a network pattern to the other elements to synchronise data and seamlessly collaborate. Imagine a desk measures its user's pulse and changes colour to indicate that it is time for a break; a wall detects acoustic reverberation in a room and adjusts the pitch or echo by changing its texture or pattern; a chair sense its user is cold and alters its user's body temperature by conducting heat through the seat, backrest and armrests; a ceiling monitors the oxygen level above a workspace and sends a signal to a desk to release fresh air; a conference table curates the mood of the discussion by displaying inspiring images or emitting a glow; a mouse senses its user's emotions (that the user is distracted or frantic) and vibrates to prompt the user to refocus; or a glass monitors how often it is used and blinks to remind its user to drink more water.

© Oddproduzioni UNStudio's RESET pod installed at the 2017 Salone del Mobile in Milan.

Prototypes and precursors

One vision for the EALW involves creating a new environment into which a user enters, separate from traditional spaces of working and learning. In collaboration with SCAPE, UNStudio prototyped such a vision in its RESET pod, a fully immersive, modular structure that features six different scientifically-proven stress reduction methods in a playful and interactive manner.

Like the EALW, the RESET pod uses biomarkers to adjust the space according to the stress reduction needs of the user. However, in this situation the user must decide themselves when to use the RESET pod, and while the pod may improve their work / study by helping reduce their stress levels, it does not directly impact the conditions of their working / studying environment. This leads us to a second, more thorough application.

Another approach consists of adapting existing environments to better fit the needs of their users. The spaces in which we work and learn are becoming extensions of ourselves, and as a result, have the capacity to boost our performance and to improve our wellbeing and health. Assisted by computing, EALW environments will learn how to adapt to achieve certain conditions that the real-time empathetic feedback loop will evaluate. The ultimate goal of EALW system is to make work and study environments 'human aware', thereby sustaining the health of their users. Further, EALW environments function on the level of the individual, which means specific adjustments for one person do not affect the adjustments of another, and a third who opts out of an EALW system is not affected by it.

Author: Piotr Prokopowicz

Header image: William Iven via Unsplash