Previous research (for example resulting from EBC Annex 53) has identified the strong influence of occupants on building performance. Recently, EBC Annex 66 has provided a sound framework for experimentally studying and modelling different behavioural actions, including the implementation of these models into simulation platforms. But, real operation of buildings shows that many such models do not represent the manifold human interactions with a building appropriately enough, and that there is no guidance for designers and building managers on how to apply occupant behaviour models in everyday practice. The purpose of this project is to provide new insights into comfort-related occupant behaviour in buildings and its impact on building energy performance. An open collaboration platform for data and software is being created to support the use of ‘big data’ methods and advanced occupant behaviour models. It is further promoting the application of this knowledge in building design and operation processes by assisting decision making and by supporting practitioners.
The project objectives are to:
– develop new scientific knowledge about adaptive occupant actions driven by multiple interdependent indoor environmental parameters
– understand interactions between occupants and building systems
– deploy ‘big data’ (e.g. data mining and machine learning) for the building sector based on various sources of building and occupant data as well as sensing technologies
– develop methods and guidelines and preparing standards for integrating occupant models in building design and operation
– create focused case studies to test the new methods and models in different design and operation phases
The planned outcomes from the project are as follows:
– Enhanced scientific knowledge about comfort-driven occupant interactions with building technologies. This includes methodological approaches to examine multistressor effects by environmental influences on human subjects.
– Informed insight into the potential of various data sources and sensing technologies, as well as applications of data-based methods for knowledge discovery and modelling of occupant behaviour.
– An open collaboration platform for data and software for supporting the use of data-mining methods and tools for applications within the area of occupant behaviour.
– A repository of advanced occupant behaviour models for digital planning environments.
– Proposals for standards and policy support for implementing occupant behaviour simulation in building design and operation practice. This also includes the integration of the models in modern digital planning (BIM) environments.
– Guidelines on how to apply occupant models and occupant behaviour issues within building technologies, including user interfaces, as part of everyday design and planning processes.
Australia, Austria, Canada, P.R. China, Denmark, Germany, Italy, Japan, the Netherlands, Norway, Switzerland, UK, USA.
Observers: Brazil, Hungary, UAE