Badri, SriramSriramBadriMohan, NijanthanNijanthanMohanOyen, MarcMarcOyenSchnittcher, LukasLukasSchnittcher2024-10-222024-10-222024-09-1835. Forum Bauinformatik, fbi 2024: 432-439https://hdl.handle.net/11420/49636The construction sector is one of the most resource-intensive sectors and responsible for a considerable share of energy consumption and greenhouse gas emissions. In order to achieve the sector targets of the German government's climate protection plan, the planning, construction, operation, maintenance and dismantling of buildings must be completely rethought and reassessed. This paper proposes an end-to-end digital method which captures the entire life cycle of a building. An interdisciplinary work that combines expertise from the fields of computer science, electrical, civil and energy engineering and tests the method on existing buildings at Aachen University of Applied Science with a main focus on optimising the building's energy consumption. The digital twin is created using methods from the field of Building Information Modelling and linked with sensor technology, data analysis and artificial intelligence in order to identify anomalies in energy consumption. With the availability of geometric, functional and real-time data from the sensors, one can identify key performance indicators relevant to the respective use cases and simulate "what if" scenarios by making predictions to achieve optimum results in terms of sustainability.enhttps://creativecommons.org/licenses/by/4.0/Anomaly DetectionDigital TwinIoTMonitoring & OptimisationSimulationArts::720: ArchitectureTechnology::621: Applied PhysicsComputer Science, Information and General Works::006: Special computer methodsArts::711: Area Planning (Civic Art)Conference Paper10.15480/882.1353610.15480/882.13536Conference Paper