Digital urban twins

Valid, comprehensive and – most importantly – up-to-date measurement data is essential for planning and developing cities and urban infrastructure. What is the condition of a city’s bridges, buildings, tunnels and roads? How can roads, development works and entire development areas be planned as efficiently and transparently as possible, and how can the construction process be monitored?

Answering these complex questions and working out urban development strategies requires an extensive and up-to-date data base. This also means taking into account the resilience of cities against increasingly frequent extreme weather events. 

Multimodal sensors provide the data for geographical information systems

Our multimodal sensor systems capture urban infrastructur in great detail and provide georeferenced data. These systems use cameras and laser scanners that are mounted on special surveying vehicles and other mobile platforms, such as drones and robot dogs. Depending on the requirements, we include additional sensors such as thermal imaging cameras, sound level meters, and multispectral sensors. The digital measurement data – camera images and 3D point clouds – are processed for use in geographic information systems (GIS). The long-term goal is to create a digital twin of cities as the ideal basis for planning and managing their physical infrastructure.

Cities are spaces that develop dynamically, which is why comprehensive, and – above all – current, measurement data is needed. We work on concepts for robust and compact measurement technologies that can be installed on conventional vehicles. In the future, regularly circulating buses, or garbage trucks could double as survey vehicles, ensuring that the data basis is always up-to-date.

Focus on smart cities (excerpt from our annual report 2024/25)

Fast data processing and AI-based data evaluation

The sheer size and complexity of cities results in an enormous amount of data being generated. To keep the data volume to the necessary minimum, our measurement systems always contain solutions for real-time processing and data reduction. We use specially trained artificial neural networks to automatically detect and classify desired objects within the data. What’s more, the data our camera images and measurement data provide go far beyond purely geometric object information. RGB color information and values on shadows or reflection surfaces, which, for example, are relevant for noise distribution or 5G networks, can be derived from the data.