ROUTINE
Living lab for the transfer of digital health applications and AI into healthcare
Start: 12/2022
End: 11/2025
A vehicle’s power and data network must meet the highest standards of reliability and fault tolerance, energy efficiency and flexibility. With a host of new, intelligent functions and large data streams, future vehicle networks will be more than just a wiring harness. Together with sensors and distributed computing nodes, it will form the nerve and energy system of the vehicle.
KI4BoardNet explores new concepts for resource-optimized, continuously learning, distributed power management systems. This includes methods for developing application-specific system-on-a-chip (SoC) architectures for hardware-assisted, accelerated execution of machine learning algorithms. For this purpose, a generator-based design process for RISC-V systems will be adapted to allow for flexible SoC architecture configuration and optimization.
Regarding the generated SoC platform, different adopted model architectures for AI-supported energy consumption prediction and their integration into a distributed onboard network load management will be researched. The project will also examine novel algorithms based on auction theory for resource efficiency and economical use of available energy within the board network. An important aspect of the planned system is its ability to learn continuously and thus continuously adapt to various usage scenarios.
In addition to voltage stabilization in future board networks; the research results will enable the implementation of new AI applications.
In this research focus, the FZI prioritizes the topics of Artificial Intelligence (AI) as well as human and AI engineering. In addition, the FZI deals with questions on dedicated AI hardware and predictive AI.
Intelligent solutions for the transportation of people and goods represent a focus topic of FZI’s application research. Particular attention is paid to public transport, the application of artificial intelligence, the further development of driving functions and their safeguarding, and open source & open data.
Funding notice:
The KI4BoardNet project is funded by the Federal Ministry of Education and Research (BMBF).
Project partners:
Living lab for the transfer of digital health applications and AI into healthcare
Next-generation distributed, continuously learning onboard power management system
Safe use of automated shuttle vehicles in urban traffic through supporting infrastructure networking
Broker for dynamic production networks
Artificial Intelligence for Work and Learning in the Karlsruhe Region
Security at multiple system layers based on chains of trust and isolation
Software Engineering of Industrial, Hybrid Quantum Applications and Algorithms
Competence Cluster Anonymization for Interconnected Mobility Systems
Climate-friendly, neuromorphic and for a sustainable transport infrastructure of the future.
Actively addressing the challenges posed by climate change and using them as an opportunity for the German economy.