Practical example and current challenges
- The intelligent and smart development of future urban and regional concepts poses great challenges for the public sector, especially since three-dimensional city models are available at low cost and area wide. A standard task to be solved is the automated integration of existing and planned buildings into 3D city models for the generation of so-called digital twins of reality. A challenge is to map different planning and design scenarios of one and the same area in a common 3D model.
- Once the 3D city model (described in point 1) has been generated, a further challenge is the calculation and visualization of future urban and regional developments. Planning processes are based on legal foundations such as land use and development plans. The calculation and comparison of future scenarios and their impact on capacity indicators (jobs, energy consumption, etc.) is a time-consuming task and requires considerable expertise. In addition, the Digital Twin is to be used as a basis for citizen participation. To this end, different stakeholders (citizens, interest groups, real estate companies) will be involved in the participation process as early as possible.
- The use case of the Smart Urban Planning project offers solutions for the challenges mentioned above. Projects can be visualized, observed and checked throughout their entire life cycle. Planned developments can be examined within a 3D model under the existing real conditions in the respective city. It is also possible to streamline the process of creating and sharing 3D zoning and land use plans. The Use Case makes it possible to configure 3D design rules, capture zoning and land use regulations and apply these rules directly in the web browser for future scenarios. This facilitates the creation and verification of plausible building designs. The data room required for this can be generated selectively for the planning and development area using the data platforms integrated in GAIA-X.
- Smart Urban Planning enables citizens, real estate developers and other community stakeholders to participate in the planning and development process. In this way, the community can be asked for feedback at an early stage. Stakeholders can use the Smart Urban Planning platform to access a web-based view of all plans and projects, as long as they are publicly approved..
- The planning, information and participation process is digitized and made more efficient thanks to a common 3D planning platform, the Digital Twin. Existing 3D context data from the surveying offices form the basis of the planning platform and can be used for this and many other applications, resulting in benefits for city and planning offices, regional planning authorities and the population.
What added value does the "GAIA-X project" offer?
- GAIA-X provides the necessary infrastructure for the integration of the Digital Twin and its data space, ensures secure data exchange and allows data to be made available without media disruption.
Based on the GAIA-X ecosystem, the Digital Twin can be used for any other applications and actors. Examples can be found in the domains:
- Public sector: The Digital Twin as the digital representation of a city plays an increasingly important role as a 3D register in the public sector, e.g. in the planning of events, citizen participation projects or road infrastructure projects. Single generation and multiple use in different GAIA-X Dataspaces is another added value.
- Smart Living: Detailed building models (Building Information Modelling, BIM) integrated in the Digital Twin ensure smart building management, including the exterior. The result is, for example, a contribution to increased energy efficiency.
- Energy: 3D models of buildings and cities are necessary when planning the future energy supply of the associated infrastructure. The Digital Twin can be used directly for the planning of photovoltaic systems or solar energy-efficient neighbourhood planning.
- Mobility: In traffic planning, the Digital Twin can be used for infrastructure planning, e.g. for intelligent traffic guidance, for modeling commuter and pedestrian flows or as a simulation environment for automated driving.
- Thomas Koblet – Esri Deutschland GmbH