DilLT is a spin-off from the Faculty of Computer Science at TUG Graz. Our goal is to integrate cutting-edge AI technologies into building operations to pave the way for more efficiency and simplified processes for building operators. DiLT's hybrid approach combines data-driven methods utilizing machine learning and logic-based diagnosis, which is currently one of the grand challenges of AI. DiLT's solution includes detection and comprehensive diagnostics accompanied by actionable recommendations based on explainable AI. Furthermore, DiLT's solutions enable the predictive optimization of the heating and cooling of buildings, taking user behavior and weather forecasts into account. Our prototype builds on an open IoT platform connecting more than 30 buildings.
Team
Theresa Kohl, Christoph Siegl, Gerald Schweiger, Gerard Coleiro, Gerda Langer, Franz Wotawa, Reinhard Pertschy, Thomas Hirsch, Thomas Schwengler
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