Welcome to the Embedded Systems Department
New and Interesting
Focusing on research Prof. Schiele taking a Sabbatical Term WS 2020/21
Prof. Schiele will take in the coming winter semester 2020/21 a "sabbatical term", focusing on research. For this reason the lecture "Embedded System" will not take place in that semester. If you are, however, interested in acquiring additional skills regarding how to develop embedded systems you can join our upcoming student project.
Theses will still be offered in that semester. All exams that we usually offer will be offered in this semester as well.
You can find additional information soon under our "Teaching" section.
Home Office, IoT Garage closed, teaching online The department in during the Coronavirus
Due to the current situation the department will continue working doing Home Office and are available via Email. Our IoT-Garage will remain closed. Meetings, discussions and presentations will be done electronically.
The University Duisburg-Essen has additionally moved the begin of the summer semester 2020 to the 20th of April. Due to this the start of all lectures, projects and the seminar are moved accordingly. Due to this, all courses will be offered digitally, via videos and live streams. To keep up to date please visit our teaching page (link), on Twitter (link) and on the website of the university (link)
1st IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2020) Won the Best Paper Award!
With their paper about Q-Learning to improve the decision making of offloading FPGA calculations on self-aware, networked sensor agents Alwyn Burger, David King and Gregor Schiele won this year's Best Paper Award at the ACSOS 2020 conference!
"[...] In this article, we present an array of self-aware sensors who use Q-learning to develop a policy that guides device reaction to various environmental stimuli. The novelty lies in the use of field programmable gate arrays embedded on the sensors that take into account internal system state, configuration, and learned state-action pairs, that guide device decisions in order to meet system demands. Experiments show that even relatively simple reward functions develop Q-learning policies that yield positive device behaviors in dynamic environments."
The goal of the Embedded Systems research group is to develop algorithms, concepts and procedures to develop networked embedded systems. Examples for this are the so called Internet of Things (IoT), Cyber-physical Systems (CPS) or Industrie 4.0. Currently our research consists of the following core aspects:
- Embedded Machine Learning
- Programming Adaptive Embedded Systems
- IoT Deployment and the Edge
- Embedded Security