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Fakultät für Elektrotechnik und Informationstechnik

CNI participates to first responder exercise in Ahr valley

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CNI Researchers at work in Ahrtal © CNI
Members of the CNI observe the communication aspects of the exercise in CNI's mobile wireless lab.
CNI in Ahrtal © CNI
Briefing of delegation of experts and stakeholders by the organizers
Measurement Campaign in Ahrtal © CNI
Close collaboration between research (TU Dortmund) and users (Red Cross, THW).
Snapshot of Ahrtal Measurement Campaign © CNI
The LARUS-PRO UAV to be used for sea rescue missions (by DGzRS) as well as floodings and other serach & Rescue missions (Red Cross, THW)

Networked Rescue robots can support first responders by providing high resolution situational insights in case of floodings and other large scale incidents. Therefore the LARUS-PRO UAV was tested jointly with rescue organizations in the Ahr valley (Germany), which was struck by a devastating flooding in 2021. CNI supported the excercise (on October 29, 2022) with its mobile wireless communication lab, which hosted a digital twin representation of the exploration mission. In addition, CNI gathered data of the public mobile radio networks in order to improve its data-driven radio channel prediction method DRaGoN, which is planned to be used for network planning of 5G and future 6G networks.

A press report about the excercise can be found here

Further information on the research in LARUS and LARUS-PRO can be found in the following publications:

The newly proposed DRaGoN method developed on the reserach projects DFG SFB 876, Plan& Play as well as 6GEM is described in detail in the following work:

  • M. Geis, B. Sliwa, C. Bektas, C. Wietfeld, "TinyDRaGon: Lightweight Radio Channel Estimation for 6G Pervasive Intelligence", In 2022 IEEE Future Networks World Forum (FNWF), Montreal, Canada, October 2022. (Best Paper Award). [pdf] [Details]
  • B. Sliwa, M. Geis, C. Bektas, M. Lopéz, P. Mogensen, C. Wietfeld, "DRaGon: Mining latent radio channel information from geographical data leveraging deep learning", In 2022 IEEE Wireless Communications and Networking Conference (WCNC), Austin, Texas, USA, May 2022. [pdf] [Details]