Developing an AI-enabled Industry 4.0 platform - Performance experiences on deploying AI onto an industrial edge device
| dc.contributor.author | Eichelberger, Holger | |
| dc.contributor.author | Palmer, Gregory | |
| dc.contributor.author | Niederée, Claudia | |
| dc.contributor.editor | Herrmann, Andrea | |
| dc.date.accessioned | 2024-02-22T10:37:52Z | |
| dc.date.available | 2024-02-22T10:37:52Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Maximizing the benefits of AI for Industry 4.0 is about more than just developing effective new AI methods. Of equal importance is the successful integration of AI into production environments. One open challenge is the dynamic deployment of AI on industrial edge devices within close proximity to manufacturing machines. Our IIP-Ecosphere1 platform was designed to overcome limitations of existing Industry 4.0 platforms. It supports flexible AI deployment through employing a highly configurable low-code based approach, where code for tailored platform components and applications is generated. In this paper, we measure the performance of our platform on an industrial demonstrator and discuss the impact of deploying AI from a central server to the edge. As result, AI inference automatically deployed on an industrial edge is possible, but in our case three times slower than on a desktop computer, requiring still more optimizations. | en |
| dc.identifier.issn | 0720-8928 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/43642 | |
| dc.language.iso | en | |
| dc.pubPlace | Bonn | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Softwaretechnik-Trends Band 43, Heft 1 | |
| dc.relation.ispartofseries | Softwaretechnik-Trends | |
| dc.subject | performance | |
| dc.subject | artificial intelligence | |
| dc.title | Developing an AI-enabled Industry 4.0 platform - Performance experiences on deploying AI onto an industrial edge device | en |
| dc.type | Text/Conference Paper | |
| mci.conference.date | 7.-9.11.2022 | |
| mci.conference.location | Stuttgart | |
| mci.conference.sessiontitle | 13th Symposium on Software Performance (SSP) | |
| mci.reference.pages | 35-37 |
Dateien
Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
- Name:
- SSP_22_paper_6955.pdf
- Größe:
- 357.93 KB
- Format:
- Adobe Portable Document Format