Dynamic Digital Twins: Challenges, Perspectives and Practical Implementation from a City’s Perspective

Digital twins that serve as virtual representations of real-world objects and structures, are used in various applications for urban environments. Challenges for creating and maintaining digital twins involve data acquisition, fusion of heterogeneous data types, AI-based data analysis, and the integration into existing applications and workflows. In this paper, we present the concept and implementation of a dynamic digital twin from a city’s perspective. The concept avoids explicit modeling to simplify the creation of a comprehensive data basis that can be easily updated frequently. 3D point clouds with semantics are used as representations for static objects and structures, such as buildings, infrastructure and subsurface structures. Dynamic aspects are represented through a time series of sensor data to enable real-time monitoring and change detection applications. A centralized data repository for applications, such as infrastructure monitoring, condition assessment, and inventory management represent a basis to support decisions. We present typical use cases and challenges from the perspective of a city and how the dynamic digital twins can create significant added value.