AI Lifecycle Zero-Touch Orchestration within the Edge-to-Cloud Continuum for Industry 5.0
Author:
Alberti Enrico1ORCID, Alvarez-Napagao Sergio2ORCID, Anaya Victor3ORCID, Barroso Marta2, Barrué Cristian4, Beecks Christian5, Bergamasco Letizia6ORCID, Chala Sisay Adugna7ORCID, Gimenez-Abalos Victor2, Graß Alexander7, Hinjos Daniel2, Holtkemper Maike5, Jakubiak Natalia4, Nizamis Alexandros8, Pristeri Edoardo6, Sànchez-Marrè Miquel4ORCID, Schlake Georg5, Scholz Jona5, Scivoletto Gabriele1ORCID, Walter Stefan9ORCID
Affiliation:
1. Nextworks Srl, Via Livornese 1027, 56122 Pisa, Italy 2. Barcelona Supercomputing Center, Plaça Eusebi Güell 1-3, 08034 Barcelona, Spain 3. Information Catalyst SL, Cl Reina 27, 4-7, 46800 Xativa, Spain 4. Department of Computer Science, IDEAI Research Centre, Universitat Politècnica de Catalunya (UPC), Carrer Jordi Girona 1-3, 08034 Barcelona, Spain 5. Department of Data Science, University of Hagen, 58097 Hagen, Germany 6. LINKS Foundation, Via Pier Carlo Boggio 61, 10138 Torino, Italy 7. Fraunhofer Institute for Applied Information Technology (FIT), Schloss Birlinghoven, 53757 Sankt Augustin, Germany 8. Centre for Research and Technology Hellas-Information Technologies Institute (CERTH/ITI), Charilaou-Thermis, 57001 Thessaloniki, Greece 9. VTT Technical Research Centre of Finland Ltd., Tekniikantie 21, 02150 Espoo, Finland
Abstract
The advancements in human-centered artificial intelligence (HCAI) systems for Industry 5.0 is a new phase of industrialization that places the worker at the center of the production process and uses new technologies to increase prosperity beyond jobs and growth. HCAI presents new objectives that were unreachable by either humans or machines alone, but this also comes with a new set of challenges. Our proposed method accomplishes this through the knowlEdge architecture, which enables human operators to implement AI solutions using a zero-touch framework. It relies on containerized AI model training and execution, supported by a robust data pipeline and rounded off with human feedback and evaluation interfaces. The result is a platform built from a number of components, spanning all major areas of the AI lifecycle. We outline both the architectural concepts and implementation guidelines and explain how they advance HCAI systems and Industry 5.0. In this article, we address the problems we encountered while implementing the ideas within the edge-to-cloud continuum. Further improvements to our approach may enhance the use of AI in Industry 5.0 and strengthen trust in AI systems.
Subject
Information Systems and Management,Computer Networks and Communications,Modeling and Simulation,Control and Systems Engineering,Software
Reference72 articles.
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