The landscape of smart cities and urban digital twins has grown significantly over the years. Digital twin platforms have evolved into operational, data-rich, and AI-optimized systems actively used by cities, municipalities, and infrastructure operators. INTERGEO 2025 demonstrated advances in unified data ecosystems, high-precision reality capture, and practical urban applications.
Technologies for capturing the built environment continue to evolve, enabling accurate representations of both indoor and outdoor environments. Indoor point cloud scans are integrated with street-level and aerial point clouds either through control point alignment or cloud-to-cloud registration. SLAM-based systems ensure reliable accuracy in complex indoor environments, while cloud platforms enable semantic enrichment during post-processing. However, the native and complete export of semantic formats such as IFC and OGC CityGML remains limited, highlighting that achieving semantic interoperability (and thus avoiding vendor lock-in) continues to be a major challenge for the industry. The management of high-resolution scans, including those of building interiors and sensitive infrastructure, raises significant concerns regarding privacy and security. Municipalities are calling for stronger data governance frameworks to ensure the protection of sensitive information. Currently, no unified industry standards exist for this topic.
Data integration and improved compatibility between different spatial datasets, which are essential for the development of urban digital twins, continue to gain importance. GIS platforms are increasingly capable of processing a wide range of heterogeneous datasets, including 3D surface meshes (“reality meshes”), point clouds, as well as BIM and semantic 3D city models. Information-rich formats such as OGC CityGML for semantic 3D city modeling and IFC for BIM are increasingly supported by GIS desktop applications. Such platforms can directly interpret complex object hierarchies and attributes, thereby helping to minimize semantic loss. Although most digital twin platforms currently offer capabilities for representing and visualizing IoT data, full integration with other spatial datasets such as 3D city models remains a challenge. In addition, the deployment and management of IoT sensors are largely handled by external providers, which limits integration and the ability of these platforms to deliver comprehensive end-to-end solutions.
As user expectations rise for urban digital twins to be both functional and visually immersive, visualization methods continue to evolve. The growing adoption of visualization and streaming standards, along with the introduction of new technologies, has significantly driven this development. Currently, web-based platforms are typically used for visualization, with quality and performance dynamically balanced. Lightweight meshes and standardized streaming formats such as OGC 3D Tiles or OGC I3S are used to efficiently render urban environments. Platforms that prioritize immersive visualization, as exemplified in Figure 4, often rely on established game engines such as Unreal Engine or Unity to achieve realistic representations of city models. Furthermore, the emergence of 3D Gaussian Splatting enables more realistic visualization of urban 3D scenes with greater levels of detail.
