Evaluation Management System

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AI REDGIO 5.0 - 1st Open Call

Call identifier: AI REDGIO 5.0 - 1st Open Call

Publication date: 2023-12-01

Status: Closed

Opening date: 2023-12-01 00:00:00 (Brussels time)

Closing date: 2024-03-01 12:00:00 (Brussels time)

Call general details Thematic areas Supporting documentation

Call Summary

AI REDGIO 5.0. aims at reinforcing the alliance between Vanguard European regions and EDIH for the adoption of AI-at-the-Edge by European manufacturing SMEs. This project gravitates towards the fulfilment of three main goals:
• Enabling the evolution of Manufacturing SMEs towards Industry 5.0.
• Evolution of cloud AI Technologies to AI-at-the-Edge procedures.
• Evolution and adaptation of H2020 programme into Horizon and Digital Europe programmes.

The objective for the first open call of AI REDGIO 5.0 project is to select up to 10 SME-driven experiments focused on the implementation of AI at the Edge and Industry 5.0 systems with the aim of improving existing solutions, products or processes in the manufacturing area. Additionally, the open call will contribute to extend the domains of AI REDGIO 5.0 and benefit directly manufacturing SMEs and small mid-caps.

Call Keywords

HBR Collaborative Intelligence
TERESA: Technological Regulatory Sandbox
Human robot interaction
Industry 5.0
AI-driven Autonomous System
Collaborative Intelligence
Manufacturing Data Spaces
Data4AI pipelines
Data Sets
Industrial Data Platforms
Business and Governance
AI at the Edge

AI REDGIO 5.0 - 1st Open Call

Topics:

TOPIC 1: AI at the Edge applications and edge-to-cloud continuum

AI's pivotal role extends to manufacturing, and AI REGDIO 5.0 aims to underscore the benefits of employing AI at the edge, leveraging the edge-to-cloud continuum and innovative cloud-to-edge frameworks. This involves capitalizing on the capabilities provided by AI models and libraries for local execution, offering advantages like low latency and enhanced data privacy.

Selected experiments should demonstrate this approach, presenting real-life use cases for AI execution at the edge or in hybrid cloud-edge infrastructures. Participants must build the necessary services and AI models, designing AI pipelines for local execution on edge computing environments.

Applications of interest span predictive maintenance, automation, operations planning, waste reduction, energy efficiency, resource optimization, etc. Throughout experiments, applicants should highlight how Human-AI teaming is achieved, showcasing the blending of AI and human interaction for mutual benefit.

Keywords:HBR Collaborative IntelligenceTERESA: Technological Regulatory SandboxHuman robot interactionIndustry 5.0AI-driven Autonomous SystemCollaborative IntelligenceManufacturing Data SpacesData4AI pipelinesData SetsIndustrial Data PlatformsBusiness and GovernanceAI at the Edge

TOPIC 2: Industry 5.0 and human-centric, resilient and sustainable manufacturing

Industry 5.0 prioritises not only technical and economic objectives but also human well-being, sustainability, and resilience. It marks the next phase of industrialization, emphasizing human involvement, distributed production, intelligent supply chains and hyper-customization for a personalized customer experience.

Selected experiments should explore how Industry 5.0 and human-centred digitalization enhance the flexibility and adaptability of SMEs production processes, fostering resilience and sustainability. Real use cases should illustrate the progress towards more human-centric stages in a digitalized manufacturing system, with a focus on measurable benefits.

Applicants are urged to adopt the AI REDGIO 5.0 reference architecture for comprehensive solutions. Proposals should present clear business scenarios reflecting real industry challenges, defining and measuring realistic technical and business KPIs.

TOPIC 3: TERESA (Technology Regulatory Sandboxes) experiments

Topic 3 proposals aim to develop a Technology and Regulatory Sandbox (TERESA) experiment within the DFs, focusing on Human-AI interactions, regulatory, and ethical issues. The experiments follow the "humans in the loop" train-explain-sustain paradigm, covering aspects such as well-being, comfort, and acceptance; inclusion and special categories of workers; safety of the worker; and ergonomics and improving working conditions. The TERESA experiment's objectives include technical validation of Human-AI interaction through DFs, adhering to the test-before-invest paradigm, and regulatory and ethical validation involving volunteers and competent authorities.
WISE aspects (Well-being, Inclussion, Safety and Ergonomics) need to be addressed to ensure a comprehensive evaluation of the experiment's impact on workers and the overall workplace environment.