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FRACTAL

Cognitive edge node for edge computing – design and build a reliable computing node that creates a cognitive edge compliant with industry standards. This node acts as a scalable building block for IoT systems from low‑power to high‑performance edge nodes. Its cognitive skills come from an internal and external architecture capable of forecasting its internal state and the surrounding world, enabling it to learn and improve performance under uncertainty. When these nodes are integrated into a fractal network, they confer autonomy, adaptability and emergent functions to the edge and facilitate seamless interaction between the physical world and the cloud

Description

FRACTAL addresses the challenge of industrial edge computing, which requires time‑predictability, dependability, energy‑efficiency and security. The project aims to create an open‑safe‑reliable and power‑efficient cognitive edge node to serve as a building block for scalable IoT from smart low‑energy systems to high‑performance edge nodes. Cognitivity is achieved via AI‑enabled architectures that allow the node to adapt to changes in real time and improve its performance despite environmental uncertainty. These nodes are integrated into a fractal edge network that delivers safety, adaptability and emergent functionality, bridging the physical world and the cloud.

Focus points/areas

  • Open, safe, low-power cognitive edge nodes with AI-driven adaptation in a fractal edge network.

 

 

Methodology

1

Datenbasierte Geometrie­vorhersage

Entwicklung einer datenbasierten Vorhersage für diskrete Rohrgeometrien und Evaluierung der Einflüsse unterschiedlicher Eingabeparameter auf die Rohrgeometrie.

Project team

Roman Obermaisser

Univ.-Prof. Dr.-Ing. Roman Obermaisser

Professor

Prof. Dr. Roman Obermaisser is full professor at the Division for Embedded Systems of University of Siegen. Roman Obermaisser has finished his doctoral studies in Computer Science with Prof. Hermann Kopetz at Vienna University of Technology as research advisor in 2004.

Personal profile photo

Dr.-Ing. Daniel Lucky Ndubuisi Onwuchekwa

Research assistant