Thermal Comfort Metabolic Rate and Clothing Inference

Abstract

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.