Enhancing cyber-physical systems by machine learning: Drilling holes into walls between disciplines

Описание: In the video from ESTC 2022 at the IEEE/ACIS 21st International Fall Virtual Conference on Computer and Information Science (ICIS 2021-Fall)
October 13-15 2021, in Xi'an, China, we introduce the notion of cyber-physical systems (CPS). For CPS, there is a complex interaction between the physical environment, hardware platforms, and the software running on them. We introduce CPS characteristics as well as challenges for their design. Mechanical, energy, thermal and dependability issues have to be considered, leading to the requirement of multidisciplinary design. Sensors may be providing huge amounts of data requiring sophisticated data analysis in order to generate reliable information.
The collaborative research center CRC 876* at TU Dortmund (see http://sfb876.tu-dortmund.de) addresses the need for data analysis and multidisciplinarity. Its focus is on resource constrained machine learning and its applications. With this focus, it merges fundamentals of embedded systems and machine learning with applications in many scientific areas such as physics, medicine, logistics, and factory automation. In the second part of the video, we present exemplary results from cooperative work at the collaborative research center. These results demonstrate the potential of interdisciplinary research using concrete examples.
Final remarks concern approaches for CPS education.
Supported by Deutsche Forschungsgemeinschaft (DFG)