The Low-power Embedded Networked Systems group is a team of researchers focusing on future connected wireless embedded systems. The team's activities can be broadly characterized as "systems and application-driven experimental research" at the intersection of wireless networking, embedded systems, and IoT applications.
The Embedded Learning and Sensing Systems group is a young team of researchers working on low-power sensing systems, information processing in IoT devices, embedded and mobile machine learning. The state-of-the-art computational models that, for example, recognize a face, or detect events of interest are increasingly based on deep learning principles and algorithms.
Cognitive products are products that recognize their environment, make optimal decisions and adapt to the situation to fulfill a higher goal. This requires basic building blocks of dependable but low-cost sensing, networking, SW- and HW-platforms, as well as infrastructures that provide industrial-grade robustness and performance. The working group studies and investigates technological building blocks required for future products and production systems. We demonstrate them by exploring and realizing several case studies and building prototypes together with industry.
Team subpage at Pro2Future