Large structures

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 – also taking into account the resilience of cities against ever more frequent extreme weather events – requires a very extensive data base.

Digital twins of cities

We develop multimodal sensor systems that capture urban infrastructur in great detail and provide georeferenced data. We use cameras and laser scanners that are mounted on mobile platforms such as drones, special surveying vehicles or regularly circulating means of transport. Depending on the requirements, we include additional sensors such as thermal imaging cameras, sound level meters and lighting 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. For this reason, we work on concepts for robust and compact measurement technologies that can be installed on conventional vehicles. In the future, buses or garbage trucks could double as survey vehicles, ensuring the data basis is up-to-date.

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.