Coordinator: Assoc. prof. Dessislava Petrova-Antonova
“City Digital Twin” is a large interdisciplinary pilot project that is being developed on the territory of Lozenets District in Sofia with the support of Sofia Municipality. It includes collecting, integrating and modelling data from the urban environment, simulating and analyzing urban processes and phenomena, and visualizing the results obtained in a way understandable to a wide range of stakeholders. The main goal of the digital twin is to provide a tool for interaction, design, experimentation and optimization of the city, which will support data based intelligent decision-making from the Sofia Municipality.
The pilot project receives great support from Sofia Municipality, Sofia Investment Agency and Sofiaplan by providing domain expertise, data provision and public engagement.
Cooperation for collaborative research has been established with Chalmers University of Technology, Twente University and New South Wales University in Sydney.
The creation of the digital twin includes the construction of a 3D model that presents the semantics and geometry of buildings, green areas, road infrastructure and other objects of the urban environment. The visualization of the 3D model is an example of multidimensional presentation of the data available for the city in an interactive and easy to understand way by stakeholders. The 3D model is constantly enriched with new data, allowing the implementation of various scenarios related to urban processes and phenomena.
In cooperation with Sofiaplan, a pilot scenario for parametric urban planning is being developed. The focus is on the implementation of tools to support urban planning, based on data, rules and indicators related to the demographic profile of the population, green areas, transport connectivity, pedestrian network and other factors that are important for the comfort and quality of life of citizens. Taking into account the specifics of the individual urban units makes the task even more complex. An analytical model is currently being developed to identify deficits and offer solutions related to the lack of social infrastructure – finding the optimal location for new kindergartens, schools, hospitals and green areas within walking distance, which can be covered in no more than 5 min., so as to optimally meet the needs of citizens.
A second pilot scenario developed within the project includes analysis and simulation of air quality, focusing on the distribution of pollutants depending on the direction and speed of the wind and the geometry of the buildings. The main goal is to study the situations in which pollutants remain in certain areas of the environment and to make recommendations for future planning of urban infrastructure. In collaboration with researchers from Chalmers University, simulations of air currents based on thermofluid dynamics are being developed to study the wind turbulence around tall buildings and its impact on citizens’ comfort. Thus, conclusions can be drawn about urban planning, which can hardly be taken into account in a real environment. Simulations in themselves are a powerful tool for testing the development of processes and phenomena in an environment close to the real one, allowing to take adequate actions in the real urban environment, afterwords.
The team working on the project is multidisciplinary. It includes researchers with experience in machine learning and artificial intelligence in general, as well as researchers with degrees in civil engineering, computer engineering and design in the field of aeronautics and astronautics.