TY - GEN

T1 - Adaptive thermal modelling for buildings.

AU - Ellis, Carl

AU - Hazas, Michael

PY - 2010

Y1 - 2010

N2 - Modelling a house’s thermal properties and interactions is a difficult task, normally involving surveys and long periods of measurements. I propose a system which can learn all of these properties, or some aggregate representation, dynamically with very little to no input from inhabitants or trained personnel. This means the system would have to use what ever basic monitoring data was available to it and from this data create a model for each room and their interactions. This system must infer where a heating source is, and the way each heating source can affect the house individually and in tandem with multiple other sources. This shall allow for rapid deployment into unknown houses which rather than learning the behaviour of its occupants, learns the behaviour of the building itself.

AB - Modelling a house’s thermal properties and interactions is a difficult task, normally involving surveys and long periods of measurements. I propose a system which can learn all of these properties, or some aggregate representation, dynamically with very little to no input from inhabitants or trained personnel. This means the system would have to use what ever basic monitoring data was available to it and from this data create a model for each room and their interactions. This system must infer where a heating source is, and the way each heating source can affect the house individually and in tandem with multiple other sources. This shall allow for rapid deployment into unknown houses which rather than learning the behaviour of its occupants, learns the behaviour of the building itself.

M3 - Conference contribution/Paper

BT - Proceedings of Ubicomp 2010 Workshop: Ubiquitous Computing for Sustainable Energy (UCSE2010)

PB - ACM

CY - New York

T2 - Ubiquitous Computing for Sustainable Energy (UCSE2010)

Y2 - 25 September 2010

ER -