Designing an adaptive room for captivating the collective consciousness from internal states

TL;DR

This research proposes a conjectural neuro-adaptive room that enhances group interactions by adjusting the physical environment to desired internal states, fostering a sense of collective consciousness and improving workplace well-being.

Abstract

Beyond conventional productivity metrics, human interaction and collaboration dynamics merit careful consideration in our increasingly digital workspace. This research proposes a conjectural neuro-adaptive room that enhances group interactions by adjusting the physical environment to desired internal states. Drawing inspiration from previous work on collective consciousness, the system leverages computer vision and machine learning models to analyze physiological and behavioral cues, such as facial expressions and speech analysis, to infer the overall internal state of occupants. Environmental conditions of the room, such as visual projections, lighting and sound, are actively adjusted to create an optimal setting for inducing the desired state, including focus or collaboration. Our goal is to create a dynamic and responsive environment to support group needs, fostering a sense of collective consciousness and improving workplace well-being.

Figures (2)

• Figure 1: Neural network for output prediction, based on input on physiological and behavioral aspects of the human being
• Figure 2: Feedback Loop system integrated with neural network for controlling output parameters