Communication Technologies for Distributed Embedded Real-Time Systems

In this area, we are researching dependable communication in industrial contexts. In addition, we are exploring how artificial intelligence can be reliably integrated into existing systems. The first topic is about ensuring that high-level communication between components can be guaranteed. Real-time protocols and network technologies will be used and evaluated for this purpose.

The second topic is about how the advantages of artificial intelligence can also be used in industrial and safety-critical environments. For this, suitable monitoring and control mechanisms must be used to ensure that the AI behaves correctly. Interested students therefore have a lot of freedom as far as the specific topic is concerned.

Research Area:

  • Industrial Informatics
  • Smart Systems

Thesis Type

  • IT-Project / Project / Seminar
  • BSc Thesis
  • Master Thesis
  • PhD

Goals and Tasks

  • Create a reliable industrial IoT communication system by utilizing smart contracts, arbitration, and network management tools.
  • Explore the integration of AI in safety-critical (autonomous) applications (e.g., driving, robots, manufacturing, drones, …)
  • Build a demonstrator platform to evaluate distributed industrial control algorithms based on ARM/X86 processor architectures running real-time Linux.
  • Analyze and compare the features of modern industrial & automotive real-time network technologies (e.g., EtherCAT, Time-Sensitive Networking, TTEthernet, Profinet, Sercos III, …).

Required Prior Knowledge

  • Most important: Interest for the topic!
  • Required: The willingness to get involved in a difficult topic and to spend a lot of time on it (perseverance and tenacity!)
  • Required: Knowledge of programming languages and frameworks, e.g., C/C++, Python, maybe Tensorflow
  • Beneficial: Experience with AI, industrial communication, and real-time environments




6-12 months