A preliminary cognitive model for the prediction of energy-relevant human interaction with buildings

The building and construction sector is responsible for approximately 40% of global energy consumption, which makes buildings a major factor in achieving the 2 °C global warming target. While the technical aspects of buildings, such as the insulation or window quality, have a strong influence on their energy consumption, it is ultimately the building occupant who consumes energy through his or her behavior. Understanding this type of behavior is therefore critical to limiting the energy consumption of buildings. This article introduces a preliminary cognitive model built on instance-based learning for energy-relevant human-building interaction. Though this model is not yet prepared to be subjected to statistical comparisons to empirical human behavior data, the results illustrate the high potential value of cognitive modeling for predicting energy-relevant human behavior in buildings, and thus for conserving energy in buildings.