System Integration consists of architecture definition, modeling, integration and validation of different hardware and software components to form a superior overall system with increased functionality and performance. These systems are also becoming increasingly autonomous and cognitive through embedded artificial intelligence. When integrating systems, it is a matter of optimizing security, coexistence, interoperability, power consumption, electromagnetic compatibility, compactness and costs.
MAIN AREAS OF RESEARCH
Physical integration has been dominated by planar PCB technology for a long time and still is. Nevertheless, the integration of electronic subsystems or smart sensors and actuators into vehicles, robots, products or machines, for example, requires completely new, more-miniaturized approaches in 3D and heterogeneous constructions. This also presents new challenges in material and microsystem process technology, which have to be taken into account.
- The combination of very sensitive electronic subsystems and assemblies that cause a high level of interference and the resultant electromagnetic interference requires a deep understanding of electromagnetic compatibility and coexistence. This understanding brings about new types of modeling approaches and methods to speed up design, guarantee the highest performance and comply with legal requirements.
- New algorithm classes, as have been established in the field of deep learning/machine learning, but also in the cognitive compute field, demand new, more-appropriate hardware concepts – FPGA derivatives and massive parallel processors (GPUs) are just the first steps.
- In addition to the hardware challenges, the integration of the software in such systems is also a challenging issue in order to investigate all tasks in relation to signal processing, algorithms, communication protocols, real-time requirements, security and robust functionality.
Virtual prototyping and model-based design
Electromagnetic compatibility and coexistence
- Heterogeneous integration
- Machine learning and autonomous systems
- Embedded software and security