Periodic Reporting for period 1 - dAIEDGE (A network of excellence for distributed, trustworthy, efficient and scalable AI at the Edge)
Okres sprawozdawczy: 2023-09-01 do 2025-02-28
The vision of dAIEDGE Network of Excellence (NoE) is to strengthen and support the development of the dynamic European edge and distributed Artificial Intelligence (AI) ecosystem as an essential ingredient in the growth and competitiveness of European industrial sectors. The dAIEDGE Network aims to reinforce the research and innovation value chains to accelerate the digital and green transitions through advanced edge AI technologies, applications, and innovations, building on Europe's existing assets and industrial strengths. In parallel, it will fortify the edge AI research and industrial communities through technological developments beyond state of the art and become a dependable and strategic pillar for the European AI Lighthouse. This will be achieved by mobilising and connecting the European AI and edge AI constituency, the relevant stakeholders, European partnerships, and projects, to provide roadmaps, guidelines and trends supporting the next-generation edge AI technologies. The key aim is to support and ensure rapid development, market uptake and open strategic sovereignty for Europe in the critical technologies for distributed edge AI (hardware, software, frameworks, tools). The dAIEDGE NoE will play a catalyst role in building a solid edge AI virtual network of research facilities and laboratories to benefit the European research and industrial community. The NoE multidisciplinary concept provide an arena for matchmaking, exchanging ideas, tools, and services, by bringing together the leading research centres, AI-on-demand platforms, digital innovation hubs, AI projects and initiatives. The ultimate goal for the dAIEDGE NoE is to support Europe to become a global centre of excellence with unique human-centred edge AI competence addressing the social and economic challenges and the needs of the citizens and society.
With the goal of pushing the boundaries of scientific and technological research on Edge AI, the project dAIEDGE is developing technical solutions covering software, hardware and middleware aspects.
On the software side, the development of edge AI algorithms has been organized into thematic subgroups to address the diverse challenges presented by resource-constrained environments. These efforts are made by dividing the sub-tasks of developing edge AI algorithms and methods into four sub-groups of: federated systems, continual learning, neuromorphic computing, and on-the-edge inference.
Our work on middleware has led to the review, proposal and integration of functional and non-functional requirements, and the establishment of a middleware architecture.
The hardware platforms led to research on innovative, resource-efficient hardware and software platforms tailored to the unique demands of modern and emerging Edge AI deployments, focusing on three thematic areas: (1) Retraining at the edge, (2) Inference across diverse edge devices and (3) hardware for emerging neuro-inspired technologies.
Our technological developments are demonstrated in three use cases: warehouse monitoring, satellite imagery and smart city.
On the software side, the development of edge AI algorithms has been organized into thematic subgroups to address the diverse challenges presented by resource-constrained environments. These efforts are made by dividing the sub-tasks of developing edge AI algorithms and methods into four sub-groups of: federated systems, continual learning, neuromorphic computing, and on-the-edge inference.
Our work on middleware has led to the review, proposal and integration of functional and non-functional requirements, and the establishment of a middleware architecture.
The hardware platforms led to research on innovative, resource-efficient hardware and software platforms tailored to the unique demands of modern and emerging Edge AI deployments, focusing on three thematic areas: (1) Retraining at the edge, (2) Inference across diverse edge devices and (3) hardware for emerging neuro-inspired technologies.
Our technological developments are demonstrated in three use cases: warehouse monitoring, satellite imagery and smart city.
The project dAIEDGE has contributed to several advances beyond the state of the art in the technical and scientific topics listed above.
The results have been published in peer-reviewed conferences and journals.
The results have been published in peer-reviewed conferences and journals.