DiggiTwin : End-to-end use of digital twins to  realize a climate-neutral building stock

The 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.

Subjects

Anomaly Detection

Digital Twin

IoT

Monitoring & Optimisation

Simulation

DDC Class

720: Architecture

621: Applied Physics

006: Special computer methods

711: Area Planning (Civic Art)

Publication version

publishedVersion

Lizenz

https://creativecommons.org/licenses/by/4.0/

Name

DiggiTwin End-to-end use of digital twins to realize a climate-neutral building stock.pdf

Type

Main Article

Size

357.44 KB

Format

Adobe PDF

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DiggiTwin : End-to-end use of digital twins to realize a climate-neutral building stock