“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.

Partnership

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.

Research

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.

More information at http://city.gate-ai.eu/

The main goal of the project is to develop methods, algorithms and tools that support risk prediction, diagnosis and treatment of cognitive diseases and in particular Alzheimer’s disease.

Partnership

The project is implemented through successful cooperation with leading universities at the international level such as Yale, Oxford, Stanford and Chalmers, as well as with the support of medical professionals in Bulgaria.

Research

The expected results from a research point of view are related to finding new classifications of patients with Alzheimer’s disease, developing models for predicting a cognitive decline, identifying structural variants of DNA in patients with Alzheimer’s disease, defining the necessary sample sizes in the planning of RNA research, development of optimal methods for finding genes that could be associated with Alzheimer’s disease, as well as methods for filling in missing data. Practitioners are expected to develop tools to facilitate the diagnosis, monitoring and treatment of patients with Alzheimer’s disease or people predisposed to it.
The developed methods, algorithms and tools can subsequently be integrated into an omix analytical model.

This project focuses on the compilation of datasets that allow to study disinformation in Bulgarian social media and on testing and developing analysis tools.

Within the project, we also deliver continuous professional development training sessions to journalists, librarians, teachers and early-stage researchers.

Partnership

AI4Media, A Centre of Excellence delivering next-generation AI Research and Training at the service of Media, Society and Democracy

Association for the Development of Information Society

Center for the Study of Democracy

National Library Ivan Vazov, Plovdiv

Ontotext

Relevant publications:

Disinformation research in Bulgarian datasets and tools

Expanding the boundaries of disinformation research on Bulgarian social media content: the experience from an inspirational summer school

Past events:

GATE organises a summer school on disinformation discovery