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Publikation

EASY: Energy-Efficient Analysis and Control Processes in the Dynamic Edge-Cloud Continuum for Industrial Manufacturing

Alexander Schultheis; Benjamin Alt; Sebastian Bast; Achim Guldner; David Jilg; Darko Katic; Johannes Mundorf; Tobias Schlagenhauf; Sebastian Weber; Ralph Bergmann; Simon Bergweiler; Lars Creutz; Guido Dartmann; Lukas Malburg; Stefan Naumann; Mahdi Rezapour; Martin Ruskowski
In: KI - Künstliche Intelligenz, German Journal on Artificial Intelligence - Organ des Fachbereiches "Künstliche Intelligenz" der Gesellschaft für Informatik e.V. (KI), Springer, 9/2024.

Zusammenfassung

According to the guiding principles of Industry 4.0, edge computing enables the data-sovereign and near-real-time processing of data directly at the point of origin. Using these edge devices in manufacturing organization will drive the use of industrial analysis, control, and Artificial Intelligence (AI) applications close to production. The goal of the EASY project is to make the added value of edge computing available by providing an easily usable edge-cloud continuum with a runtime environment and services for the execution of AI-based analysis and control processes. Within this continuum, a dynamic, distributed, and optimized execution of services is automated across the entire spectrum from centralized cloud to decentralized edge instances to increase productivity and resource efficiency.

Projekte