Numerous approaches have been developed to quantify people's comfort levels in indoor spaces, often for productivity purposes: the first studies in the field involved comparing indoor temperatures in factories with production quality or absenteeism.
The application of comfort models in the building and planning sector generally takes place prior to project construction, in order to evaluate construction variants against an objective criterion.
In special cases, the indoor comfort temperature can be determined by an empirical method. For example, the adaptive approach of standard EN 15251 used for naturally ventilated buildings gives a linear relationship between comfort temperature and the sliding one-month average outdoor temperature, calibrated from thousands of measurements.
In indoor environments, the most widely used indicator is Fanger's Predicted Mean Vote, which links the flow (negative or positive) to which the individual is subjected to the sensation of comfort or discomfort. The link was made possible by combining an equational approach, enabling the heat balance to be established, with statistical regression on the comfort level of a sample of several thousand people.
However, recent work has shown the limitations of the Predicted Mean Vote (PMV) approach, which is based on a male morphology and leads to significant shifts in the comfort range according to gender.
The equational approach discussed here is the "two-node model" developed at the J. B. Pierce Foundation (also known as the "Pierce model") during the 20th century.