To support European manufacturing SMEs in their transition toward Industry 5.0 AI REDGIO 5.0 implemented a comprehensive set of activities.
The project developed a practical Conceptual Framework and Reference Architecture for AI-at-the-Edge Industry 5.0 applications and experimentations, enabling companies to design “self-aware” applications capable of monitoring industrial processes and detecting unusual behaviour.
It delivered a secure and trustworthy edge-to-cloud continuum Data and Computational Space for highly distributed AI applications, based on open-source tools that allow AI solutions to run seamlessly from edge devices to the cloud. The system is easy to adopt, well documented, and designed to make advanced AI technologies accessible and simple to deploy in real industrial environments.
AI REDGIO 5.0 ensured strong interoperability with the broader European AI ecosystem, including the AI-on-Demand Platform. By adopting appropriate standards and components, it enabled smooth exchange of data, models, and services across platforms and initiatives.
The project promoted the European approach to AI in manufacturing by building solutions grounded in open-source technologies and ethical principles. Tools were tested in controlled environments to ensure they are human-centric, trustworthy, reusable, and aligned with EU values for responsible AI.
AI REDGIO 5.0 managed and governed the transition from regional DIHs to a network of EDIHs in AI for manufacturing. This consolidated network now provides more than 500 services covering the DBEST dimensions (Data, Business, Ecosystem, Skills, Technology), aligned with the METHODIH methodology. The project leaves a European broader collaborative ecosystem comprising EDIHs, Didactic Factories, and Testing and Experimentation Facilities (TEFs). Long-term continuity and impact are reinforced by the EDIH4MANU network, the DIH4INDUSTRY initiative, and the AI REDGIO Ecosystem Portal, ensuring sustained visibility, value creation, and collaboration beyond the project’s end.
During the project, three types of experiments were carried out. Fourteen test-before-invest experiments in Didactic Factories tested and refined AI tools in real industrial environments, with particular attention to human-centric innovation. Seven SME-driven experiments focused on productivity and agility, with seven technology providers developing AI solutions tailored to SMEs’ needs; SMEs demonstrated the feasibility and benefits of adopting these technologies in real production contexts. Additionally, 20 SME-driven experiments were supported through cascade funding, focusing on sustainability and circularity, adopting advanced AI-at-the-edge solutions to reduce waste, optimise energy consumption, and support circular production models. The outcomes and lessons learned from all 41 experiments are compiled in a dedicated booklet available online.
To guide SMEs in digital transformation, the project developed a comprehensive framework of methods and tools to assess digital maturity and needs for AI-driven Industry 5.0 solutions. The model includes 10 pillars enabling companies to evaluate their situation and plan improvements, integrating sustainability, resilience, human-centricity, and scalability into their AI-driven transformation pathways.
Finally, AI REDGIO 5.0 established a sustainability, ecosystem development, and replication plan to ensure long-term impact beyond the project’s end. Through workshops, collaboration with European initiatives, and targeted exploitation actions, it laid the foundations for wider adoption of AI-at-the-edge solutions across manufacturing.
