Use Cases


Motor condition monitoring

  • Battery driven, low power device with DL-based data processing
  • Integrated sensing, data processing and communication capabilities
  • State estimators for operational, thermal and mechanical conditions
  • Robustness against external disturbing events e.g. neighboring drives
  • Main challenge: usage of up to three DL models with a ultra-low energy budget

Arc detection

  • DL-based protection device for energy distribution systems
  • Focusing on DC supplies and distribution setups
  • Very low latency from first spark till inference, including sensing and preprocessing
  • Arc localization for faster fault detection and repair
  • Main challenge: Ultra-low false negative error rate for a smooth operation


The automotive use-case focuses on increasing the processing efficiency DL tasks over the resources that are present in the traffic environment. This will be achieved through distribution of the processing tasks over resources such as the ego vehicle, cellular base station(s) in the close proximity,  as well as the cloud.

The key research areas are:

  • Distributed processing including vehicle, base station and cloud
  • Ensuring safety of the function, security and robustness of the distributed system
  • AEB Vehicle to Pedestrian Use-Case [Ref to NCAP]
  • Increased performance using cellular base station processing resources



Smart Mirror as demonstrator for smart home applications

  • Serves as interface between residents and the smart environment
  • Combination of a mirror and a display
  • Visualize personalized Information (e.g., News or the status of the smart home environment)
  • Featuring face, object, gesture, and speech recognition

Goals within VEDLIoT

  • Virtual mirror image using 3D point clouds
  • Optimizing commonly used DNN models like Yolo
  • Utilizing embedded edge computing for resource efficiency (t.RECS)
  • Combining GPU, CPU and FPGA computation
  • Porting of individual parts (e.g. speech recognition as voice assistant) on minimal specialized embedded hardware (µ.RECS)