Researchers from the Glasgow Intelligent Computing Laboratory (gicLAB) at the School of Computing Science are part of a new cross-Europe network of excellence which is setting out to apply artificial intelligence on edge computing platforms.
 
The network, named dAIEDGE for ‘A network of excellence for distributed, trustworthy, efficient and scalable AI at the Edge’, is led by Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI) – the German Research Center for Artificial Intelligence.
 
dAIEDGE, part of the European Union’s ‘European Network of AI Excellence Centres: Expanding the European AI lighthouse’ initiative, is supported by €14.4m (£12.3m) in new funding, €10.7m (£9.1m) of which is from the European Union. 
 
dAIEDGE will work closely with other major European AI initiatives such as HumanE-AI-Net, CLAIRE, ELLIS and AI4EU.
 
By combining edge computing and AI (Edge AI), devices can make decisions in a few milliseconds by processing data directly at the point of origin – without insecure connections, high latency, large energy overheads or costs due to transmission.
 
Edge AI is therefore a pathfinder and accelerator for many new applications in areas such as autonomous driving, personalized digital assistance and intelligent service robots.
 
To accelerate digital and green transformation through advanced AI technologies, applications and innovations, dAIEDGE builds on the existing assets and strengths of European industry and leverages gicLAB’s core competencies of across-stack acceleration of AI at the edge.
 
The main objective is to support and ensure rapid development and market adoption of distributed edge AI technologies, such as hardware, software, frameworks and tools.
 
The applications of dAIEDGE are expected to be used in a wide range of fields, such as the Internet of Things (IoT), intelligent transportation systems, robotics, and healthcare.
 
Under the leadership of DFKI, experts in artificial intelligence, embedded computing, microprocessors, distributed hardware and software, computer science, and engineering will work closely together to:

  • mobilize the AI and edge community
  • connect al-on-demand platforms, digital innovation centers, and AI and Edge projects with relevant stakeholders
  • initiate European partnerships and projects
  • provide ideas, tools, services, guidelines and trends to support the next generation of Edge AI technologies.

Dr José Cano Reyes, a senior lecturer at the University of Glasgow’s School of Computing Science and head of gicLAB, will lead the University’s contribution to dAIEDGE. Dr Cano Reyes said: “I’m pleased to be joining dAIEDGE, which brings together institutions from across Europe to help develop important new advances in AI at the edge. I’m looking forward to collaborating with colleagues both in dAIEDGE and with other European AI initiatives to deliver real impact in the years to come”.
 
Prof. Didier Stricker, head of research lab Augmented Vision at consortium leader DFKI in Kaiserslautern, said: “The development of smart edge devices increases drastically their ability to make complex decisions autonomously and respond to real-time data. This is the basis for a dynamic AI ecosystem with distributed, trustworthy, efficient and scalable AI methods.”
 
To support the mobility of scientists through research exchanges and to carry out industrial research projects, the Network of Excellence will support 30 projects through the publication of three open calls for a total funding of 1.8 million euros.