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Off-the-shelf wearable sensing devices for personalized thermal comfort models: A systematic review on their use in scientific research

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Off-the-shelf wearable sensing devices for personalized thermal comfort models: A systematic review on their use in scientific research

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Costantino, A.; Ferrara, M.; Arnesano, M.; Fabrizio, E. (2023). Off-the-shelf wearable sensing devices for personalized thermal comfort models: A systematic review on their use in scientific research. Journal of Building Engineering. 70. https://doi.org/10.1016/j.jobe.2023.106379

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/211706

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Título: Off-the-shelf wearable sensing devices for personalized thermal comfort models: A systematic review on their use in scientific research
Autor: Costantino, Andrea Ferrara, Maria Arnesano, Marco Fabrizio, Enrico
Fecha difusión:
Resumen:
[EN] Human thermal comfort depends on objective variables -related to the environment- and to subjective variables, related to physiological conditions. While the former are relatively easy to be measured, the latter are ...[+]
Palabras clave: Artificial intelligence , Deep learning , Machine learning , Multi-domain comfort , Physiological signals
Derechos de uso: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Fuente:
Journal of Building Engineering. (eissn: 2352-7102 )
DOI: 10.1016/j.jobe.2023.106379
Editorial:
Elsevier
Versión del editor: https://doi.org/10.1016/j.jobe.2023.106379
Código del Proyecto:
info:eu-repo/grantAgreement/MIUR//20172FSCH4_002/
Agradecimientos:
The research has been funded by the Italian Ministry of Research through the NEXT. COM (Prot. 20172FSCH4) "Towards the NEXT generation of Multiphysics and multidomain environmental COMfort models: theory elaboration and ...[+]
Tipo: Artículo

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