Abstract
This paper proposes a relational model able to predict thermal comfort/discomfort from users’ attributes and environmental conditions. The model uses a new subject attribute: the “thermotype”, which synthesizes its climatic preferences, body shape and thermal response using Artificial Intelligence (AI). A thermal avatar was created by mapping thermal layers to a 3D body representation, derived from the same infrared images. The result is a Digital Human Model that permits associate the perception to the thermal comfort preferences, integrating both the thermotype and the thermal avatar.
We have evaluated the model with real subjects in a thermal chamber simulating different environmental conditions that can be found in vehicles equipped with Heating and Ventilation Air Conditioning (HVAC) systems. Our model can provide product design and evaluation strategies to companies, to personalize intelligent self-adjustable thermal systems to achieve thermal comfort predictions.
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Acknowledgements
The authors would like to thank their colleagues Sonia Gimeno Peña, Isabel Roger López, Yoel García Marín and Luis Sánchez Palop for their participation in conduction of the user testing and data processing.
This study is supported under the frame of the project IMDEEA/2018/77, financed by the IVACE within the framework of the program of grants directed to technological centers of the Valencian Community for the development of non-economic R & D projects carried out in cooperation with companies for the financial year 2018, co-financed by the European Development Fund Regional (ERDF) in a percentage of 50% through the ERDF Operational Program of the Comunitat Valenciana 2014–2020.
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Latorre-Sánchez, C., Soler, A., Parrilla, E., Ballester, A., Laparra-Hernández, J., Solaz, J. (2020). Digital Human Updated: Merging the Thermal Layers with the 3D Anthropometric Model. In: Di Nicolantonio, M., Rossi, E., Alexander, T. (eds) Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping. AHFE 2019. Advances in Intelligent Systems and Computing, vol 975. Springer, Cham. https://doi.org/10.1007/978-3-030-20216-3_48
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