Project Description
In the course of the digitization strategies of recent years, an IIoT infrastructure has been created on construction sites on the one hand. On the other, approaches and methods to generate optimal scheduling, sequencing, and resource deployment planning are based on computer-aided simulations and algorithms. The combination of IIoT and AI is missing for near-real-time, digital mirroring, and decision support of construction site processes. The research project will develop approaches for automated collection and model-based processing of reliable construction process data and simultaneous optimization of construction quality as well as resource consumption in a digital twin. In particular, a continuous integration of machine and construction process data into an intelligent digital twin for online optimization for construction and information feedback into the construction process will be implemented. The digital twin should have a high degree of interoperability and thus satisfy the diversity of construction processes and machines used.
Partners
- Technical University of Munich, Chair of Automation and Information Systems
Technical University of Munich, Chair of Materials Handling, Material Flow, Logistics - abaut GmbH
- Bauer Maschinen GmbH
- Bauer Spezialtiefbau GmbH
- Fielddata.io GmbH
- Sensor-Technik Wiedemann GmbH
- Straightlabs GmbH & Co. KG
- Wacker Neuson Produktion GmbH & Co. KG