Designing an adaptive room for captivating the collective consciousness from internal states
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866912090845872128 |
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| author | Flores-Ramírez, Adán Alarcón-López, Ángel Mario Vaca-Narvaja, Sofía Leo-Orozco, Daniela |
| author_facet | Flores-Ramírez, Adán Alarcón-López, Ángel Mario Vaca-Narvaja, Sofía Leo-Orozco, Daniela |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_21571 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Designing an adaptive room for captivating the collective consciousness from internal states Flores-Ramírez, Adán Alarcón-López, Ángel Mario Vaca-Narvaja, Sofía Leo-Orozco, Daniela Neural and Evolutionary Computing Neurons and Cognition 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. |
| title | Designing an adaptive room for captivating the collective consciousness from internal states |
| topic | Neural and Evolutionary Computing Neurons and Cognition |
| url | https://arxiv.org/abs/2410.21571 |