DigiT4TAF-BW
AI in the Mobility Sector
Start: 10/2017
End: 12/2021
Software systems in industrial manufacturing constantly face new challenges, such as those arising from Industry 4.0 and the Internet of Things (IoT) paradigm. At the same time, industrial standards for functional safety require holistic protection concepts that safeguard the entire automation solution as well as individual components and subsystems.
The SAFE4I project provides a partially automated, model-based development process to accelerate the design of functionally safe software while reducing development efforts. The solution provides a strict separation between the application-specific software functionality and the software safety measures. The provided process automatically combines these two views and generates safe software. In addition, the framework offers the potential for the realization of customer-specific automation solutions. SAFE4I is therefore a quality and cost lever for end users as well as for component and tool suppliers.
The FZI adopted the SAFE4I methodology for a UML/SysML-based design flow. This includes a tooling framework for template-based modeling of safety mechanisms, model-to-model transformations for automated integration of safety mechanisms, and generation of the final safe software.
At the heart of the methodology is the Universal Safety Format (USF), which facilitates the introduction of safety mechanisms regardless of the system specification format like source code or UML models. This enables the generalization of the specification and the integration of safety mechanisms along the design process, thereby increasing reusability as well as significantly reducing development efforts.
The FZI focuses in this research area on the topics of resilience for critical infrastructures, managing security, legal tech and (post-)quantum cryptography, and also deals with the mutual influence of artificial intelligence on safety and security.
Funding notice:
The SAFE4I project is funded by the Federal Ministry of Education and Research (BMBF).
Project partners:
AI in the Mobility Sector
Supercomputing Platform for Highly Automated Vehicles
Cybersecurity for SMEs
Data management repository for care-supporting AI applications
Innovation with Cybersecurity for SMEs in Baden-Württemberg
Hardening of embedded RISC-V software by means of code transformations
Automatic Integration of Avionik Racks via Artificial Intelligence
Buildings as efficient and interoperable components of the future energy system
Hybrid building twins for increased energy efficiency
Flexible refrigeration systems against the background of increased decarbonization