Distributed Artificial Intelligent Systems
Acronym
DAIS
Type
research
Duration
2021 - 2024
Content
The use of artificial intelligence (AI) in Edge computing is entering a new era based on the use of ubiquitous small and connected devices. Until now, Europe has not been doing well, as America sets the standards and most components are produced in Asia or America. This project believes doing better is realized by (1) Putting European values of self-organization, privacy by design and low use of energy in the core of the Edge Computing components that shape this new era, and delivering the technology needed to promote these values; (2) Focusing on pan European cooperation to ramp up the capabilities needed to deliver these new components at a scale that can make a real impact. Europe does not have huge IT leaders so cooperation from a very early phase is key. All partners in the project participate in delivering key parts of these new Edge Computing components; and (3) Demonstrating the use of these components in key European industrial areas. Clear and early examples are needed to un-lock corporate and external funding to deliver on the promise of this very exciting project.<br/> The DAIS project will research and deliver distributed artificial intelligent systems. It will not research new algorithms, as such, but solves the problems of running existing algorithms on these vastly distributed edge devices that are designed based on the above three European core values. The research and innovation activities are organized around eight complementary and mutually supportive supply chains. Five of these focus on delivering the hardware and software that is needed to run industrial-grade AI on different types of networking topologies. Three of the supply chains demonstrate how known AI challenges, from different functional areas, are met by this pan European effort.
Our role
We act in this project as a national coordinator where we coordinate work of the three Slovenian partners in a joint use case and also as as a partner where we develop an edge based computational solution to guide the industrial Automated Guided Vehicles using visual and other sensor information.
Funding
ECSEL / H2020