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

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

28 Oct 2024arXiv:2410.21571archive 2025-07-28

Adán Flores-Ramírez, Ángel Mario Alarcón-López, Sofía Vaca-Narvaja, Daniela Leo-Orozco

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.

PaperPDFCode

Code

afr2903/neuroadaptive-meeting-room officialmentioned on GitHub report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Methods

Focus

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections