EASY: Energy-Efficient Analysis and Control Processes in the Dynamic Edge-Cloud Continuum for Industrial Manufacturing
Abstract 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.
Authors
- Simon Bergweiler (ORCID: https://orcid.org/0000-0003-0383-8338)
- Sebastian Weber (ORCID: https://orcid.org/0000-0001-8260-2248)
- Martin Ruskowski (ORCID: https://orcid.org/0000-0002-6534-9057)
- Benjamin Alt (ORCID: https://orcid.org/0009-0002-8790-1671)
- Sebastian Bast (ORCID: https://orcid.org/0009-0008-4666-7579)
- David Jilg (ORCID: https://orcid.org/0000-0002-4841-3512)
- Alexander Schultheis (ORCID: https://orcid.org/0000-0002-2458-9943)
- Tobias Schlagenhauf (ORCID: https://orcid.org/0000-0002-9415-8997)
- Ralph Bergmann (ORCID: https://orcid.org/0000-0002-5515-7158)
- Darko Katić
- Achim Guldner (ORCID: https://orcid.org/0000-0002-7532-4523)
- Lukas Malburg (ORCID: https://orcid.org/0000-0002-6866-0799)
- Lars Creutz
- Guido Dartmann (ORCID: https://orcid.org/0000-0002-6786-6664)
- Mahdi Rezapour
- Stefan Naumann (ORCID: https://orcid.org/0009-0000-6542-2229)
- Johannes Mundorf
Institutions
- Trier University of Applied Sciences (DE)
- University of Kaiserslautern (DE)
- Center for Art and Media Karlsruhe (DE)
- German Research Centre for Artificial Intelligence (DE)
- SmartFactory (Germany) (DE)
- Robert Bosch (Netherlands) (NL)
- University of Applied Sciences Kaiserslautern (DE)
- Universität Trier (DE)
Publication Details
- Journal
- KI - Künstliche Intelligenz
- Published
- 2024-09-03
- DOI
- https://doi.org/10.1007/s13218-024-00868-3
- Citations
- 8
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 2.79
Funders
- Universität Trier
- Österreichische Forschungsförderungsgesellschaft