The main task of the IMS team is to provide a fully automated process for the needs-based collection of measurement data and its provision in the BIM model, the digital twin. Examples of automated measurement missions are carried out to create and optimize processes: outdoors with measuring drones and indoors with autonomous measuring robots. For this purpose, a framework software is created specifically (Python), into which the sub-applications and some commercial software are integrated. This automatic data collection and processing process is based on the use of the open standards IFC (Industry Foundation Classes) and BCF (BIM Collaboration Format). The use of IFC models enables precise and contextual robot/drone paths that ensure comprehensive coverage and efficient data collection. The routes are predetermined using mission planning software. This ensures that repeated measurements are also carried out precisely at the same points. As a result, high-resolution images and point cloud data are recorded and then integrated into the BIM model. Position markers are used to localize the autonomous measuring vehicles and in particular to transform the measurement data into the project's reference frame. Their use in the overall automated process is being developed in the technical center building of the ZHAW School of Engineering and demonstrated in practical use on the pilot construction sites. Automation creates a robust, user-friendly solution that delivers fast and precise measurements under the harsh conditions of the construction industry.

In another sub-project we support the development of solutions for the inspection of infrastructure structures. Again, the focus is to use and further develop existing technologies to improve inspector safety and capture the necessary data in a reliable, repeatable and precise manner. Drone-assisted inspections can be particularly beneficial in areas that are difficult to access, such as the undersides of bridges or busy lanes. High-resolution photos and recordings in other spectra are taken, which, in addition to visual evaluation, are also used in this project for AI-based evaluations such as crack detection.