The aim of this project is to develop a human-centric approach to evaluate the comfort performance of buildings using Bayesian Networks, Building Information Modeling and Digital Twin. The results of this project aim to accelerate people-centric innovation in the built environment by engaging end users for creating the demand for healthy and comfortable spaces.
The goals include the analysis of the variables that influence the integrated evaluation of a building’s comfort performance and evaluation of the tradeoffs when modifying the variables in a cause-effect chain. Facility managers will be able to use this decision-making system to support their decision regarding operation and maintenance tasks to improve performance of buildings and satisfaction of end users. The most probable causes of an inadequate performance will be assessed to improve building management.