Thermal Comfort Metabolic Rate and Clothing Inference

  • Christos Timplalexis
  • Asimina Dimara
  • Stelios KrinidisEmail author
  • Dimitrios Tzovaras
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11754)


This paper examines the implementation of an algorithm for the prediction of metabolic rate (M) and clothing insulation (\(I_{cl}\)) values in indoor spaces. Thermal comfort is calculated according to Fanger’s steady state model. In Fanger’s approach, M and \(I_{cl}\) are two parameters that have a strong impact on the calculation of thermal comfort. The estimation of those parameters is usually done, utilizing tables that match certain activities with metabolic rate values and garments with insulation values that aggregate to a person’s total clothing. In this work, M and \(I_{cl}\) are predicted utilizing indoor temperature (T), indoor humidity (H) and thermal comfort feedback provided by the building occupants. The training of the predictive model, required generating a set of training data using values in pre-defined boundaries for each variable. The accuracy of the algorithm is showcased by experimental results. The promising capabilities that derive from the successful implementation of the proposed method are discussed in the conclusions.


Thermal comfort Metabolic rate Clothing insulation 



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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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Christos Timplalexis
    • 1
  • Asimina Dimara
    • 1
  • Stelios Krinidis
    • 1
    Email author
  • Dimitrios Tzovaras
    • 1
  1. 1.Centre for Research and Technology Hellas/Information Technologies InstituteThermi-ThessalonikiGreece

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