Edge-based Parametric Digital Twins for Intelligent Building Indoor Climate Modeling

arXiv:2403.04326v1 Announce Type: cross
Abstract: Digital transformation in the built environment generates vast data for developing data-driven models to optimize building operations. This study presents an integrated solution utilizing edge computing, digital twins, and deep learning to enhance the understanding of climate in buildings. Parametric digital twins, created using an ontology, ensure consistent data representation across diverse service systems equipped by different buildings. Based on created digital twins and collected data, deep learning methods are employed to develop predictive models …

abstract arxiv building buildings built environment climate climate modeling computing cs.ai cs.lg cs.sy data data-driven deep learning digital digital transformation digital twins edge edge computing eess.sy environment intelligent modeling operations parametric solution study transformation twins type understanding vast vast data