dAIEDGE Collaborative Projects

Funding for research and development projects relating to distributed, trustworthy, efficient and scalable artificial intelligence (AI) and edge technologies.

dAIEDGE is a Network of Excellence (NoE) for distributed, trustworthy, efficient and scalable artificial intelligence (AI) at the Edge. It seeks to strengthen and support the development of a dynamic European cutting-edge AI ecosystem under the umbrella of the European Lighthouse for AI, and to sustain the development of advanced AI. dAIEDGE main objective is to advance Europe’s innovation and technology base by developing a comprehensive policy and governance approach to AI.

The dAIEDGE Collaborative Projects Open Call aims to expand the role of the dAIEDGE Network of Excellence in the edge AI continuum, encompassing micro-, deep-, and meta-edge, with a focus on standardisation, opensource contributions, and infrastructure development. Participants can submit a proposal for research and development activities to solve or push forward the research in the identified Challenges.

Funding is provided for research and development activities to solve or push forward the research in the following Industrial Challenges:

1. Balancing Energy Efficiency and Trustworthiness in Federated Learning Across the Edge-Cloud Continuum.
2. Enabling On-Device Training Support in TFLite Micro for Resource-Constrained Edge Devices.
3. Very low consumption of speech enhancement AI algorithm at the edge.
4. High-Performance Bayesian-based AI Agents for Embedded Intelligence in Smart Environments.
5. Towards a Unified Semantic and Hyperspatial World Model: Enabling Smart Edge Systems through Domain-Aware Graphs and Agent Governance.
6. Automated Edge deployment, tuning and Performance Evaluation of Binary Neural Networks targeting FPGA enabled platform.
7. Towards Automatic DMWay Configuration with Generative AI.
8. Health Monitoring AI for Edge Devices with Privacy-First.
9. Edge AI framework for web browsers empowering Federated Machine Learning applications addressing Classification problems over multiple format data (text and images).
10. Off-Chip Weights for Streaming Architectures.
11. 2D Vehicle Detection Network on PYNQ-Z1.
12. Real-Time Vision Transformer (ViT) on FPGA SoC for Image Classification.
13. Generative AI for object detection in Edge scenarios.

To receive funding, single applicant or consortium must select and reply in its proposal to one of the challenges.

Projects should start at a Technological Readiness Level (TRL) of 2-3 and to achieve a TRL 4-5.

For the 3rd Open Call, up to 10 projects will be selected for funding.