Abstract
This paper attempts to utilize experimental results in order to correlate clothing insulation and metabolic rate with indoor temperature. Inferring clothing insulation and metabolic rate values from ASHRAE standards is an alternative that totally ignores environmental conditions that actually affect human clothing and activity. In this work, comfort feedback regarding occupants’ thermal sensation is utilized by an algorithm that predicts clothing insulation and metabolic rate values. The analysis of those values reveals certain patterns that lead to the formulation of two non-linear equations between clothing – indoor temperature and metabolic rate – indoor temperature. The formulation of the equations is based on the experimental results derived from the thermal comfort feedback provided by actual building occupants. On trial tests are presented and conclusions regarding the method’s effectiveness and limitations are drawn.
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Acknowledgements
This work is partially supported by the “enCOMPASS - Collaborative Recommendations and Adaptive Control for Personalised Energy Saving” project funded by the EU H2020 Programme, grant agreement no. 723059.
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Dimara, A., Timplalexis, C., Krinidis, S., Tzovaras, D. (2019). A Dynamic Convergence Algorithm for Thermal Comfort Modelling. In: Tzovaras, D., Giakoumis, D., Vincze, M., Argyros, A. (eds) Computer Vision Systems. ICVS 2019. Lecture Notes in Computer Science(), vol 11754. Springer, Cham. https://doi.org/10.1007/978-3-030-34995-0_62
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DOI: https://doi.org/10.1007/978-3-030-34995-0_62
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