Living lab for the transfer of digital health applications and AI into healthcare
Next-generation distributed, continuously learning onboard power management system
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.
Division: Intelligent Systems and Production Engineering
Applied Artificial Intelligence
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 Transportation Systems and Logistics
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.