Future Initiative Test | Field Urban Robotics
Real-world laboratory for research and innovation in robotics in public spaces in Baden-Württemberg
Start: 03/2020
End: 02/2023
In the German healthcare system, patient-related data is collected and managed independently by various actors. Especially during transitions, for example from inpatient hospital treatment to rehabilitation or home environment, information gaps occur – data relevant to patient care is not available.
In response, the BloG³ research project is developing a blockchain-based, decentralised data and rights management system to make the scattered data stored in an individual health profile securely available, using the specific example of oncology patients. This networking of distributed health data can enable personalised medical care for the general population and thus more efficient treatment. At the same time, it allows medical institutions to integrate and automate cross-organisational processes: a digital platform enables transparent access to health data at any time, with full data sovereignty being retained by the individuals concerned, who determine the use of their data.
In addition to its role as consortium coordinator and project initiator, the FZI is responsible for mapping information coordination processes in blockchain-based health data management systems.
Funding notice:
The BloG3 project is funded by the Federal Ministry of Education and Research (BMBF) within the framework of the research program on human-machine interaction (Forschungsprogramm Mensch-Technik-Interaktion).
Project partners:
Real-world laboratory for research and innovation in robotics in public spaces in Baden-Württemberg
Sandbox for the transfer of digital health applications and AI to healthcare
Strengthening patient data sovereignty through blockchain-based health data management
Data trustee for sovereign management and effective use of medical data in sleep research
Digital platform for dementia prevention helps address the lack of exercise
Individual Training obsERvation and AdapTION
Hybrid Building Twins for Increased Energy Efficiency
More exercise in everyday life: Self-learning real-time system recognizes behavior patterns and recommends customized activities
AI-driven recognition and analysis of actions and processes based on merged multisensor data for optimizing surgical procedures
AI-based software detects and corrects motion artifacts in OCT images.