Edge devices are network instruments responsible for connecting the local area network with wider area networks, i.e. operate on the network edge. In automation and cloud computing, they take up important roles like the translation of protocols between both ends. However, due to the increasing data processing demands in fields like Industrial Internet of Things (IIoT), there have been great efforts in the last years to shift some of the computational load onto these devices. This raises new challenges into the hardware, software, and general logic used on the edge.

In this project, we are exploring some of these challenges and opportunities using Siemens hardware conceived exactly for this purpose. Our focus lies on implementing and testing signal processing and Machine Learning (ML) algorithms and evaluating their usability and suitability for the device. Furthermore, we want to gain insights into appropriate procedures to deploy and update developed applications onto the devices.


Development Team: Johannes Enk, Moaaz Idlbi, Silvana Miranda, Ebru Navruz, Mahmoud Sanad, Brindha Selvaraj
Scrum Master: Misha Sadeghi, Simon Dietz

Partner: Siemens