See also the press release
DAIS – Distributed Artificial Intelligent System, a pan-European effort with 48 partners from 11 countries, aims to create intelligence-centered heterogeneous distributed edge computing systems and solutions.
DAIS’s approach is to develop intelligent, secure, and trustworthy systems for industrial applications to provide comprehensive cost and energy-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together.
In recent years, technological developments in consumer electronics and industrial applications have been advancing rapidly. More and more, small, networked devices can collect and process data anywhere. This Internet of Things (IoT) is a revolutionary change for many sectors like building, automotive, digital industry, energy, etc. As a result, the amount of data being generated at the Edge level will increase dramatically, resulting in higher network bandwidth requirements. In the meantime, with the emergence of novel applications, lower latency of the network is required. The new paradigm of edge computing (EC) provides new solutions by bringing resources closer to the user, keeps sensitive & private data on devices, and provides low latency, energy efficiency, and scalability compared to cloud services while reducing the network bandwidth.
At the same time, there is an increasing need to use Artificial Intelligence (AI) at the edge. Today, AI applications based on machine learning (especially deep learning algorithms) are fuelled by advances in models, processing power, and big data. The developments of AI applications mostly require the processing of data in centralized cloud locations. Hence, they cannot be used for applications where milliseconds matter in safety-critical applications, such as in autonomous vehicles. Similarly, there are high temporal requirements for processing either online or offline for face recognition and speech translation applications. In addition to speed, edge computing offers security benefits due to wider data distribution at the edge level. Reducing the distance data has to travel for processing means decreasing the opportunities for trackers and hackers to intercept it during transmission and preserves its privacy. With more data remaining at the network edges, central servers are also less likely to become targets for cyberattacks.
Overall Objectives of DAIS – Competitiveness for strong European Industry
DAIS has the ambitious objective to develop Intelligent and Secure Edge solutions for industrial applications for European industry throughout the whole Supply Chain. More precisely, we do so by:
- Providing intelligent processing of data and communication locally at the edge to enable real-time and safety-critical industrial applications.
- Developing industrial-grade secure, safe, and reliable solutions that can cope with cyberattacks and difficult network conditions.
- Providing AI techniques on the edge that match with diverse computing powers contrary to relatively consistent computing power on the cloud. As different AI algorithms have different computing power requirements, it is a big challenge to match an existing algorithm with a certain edge platform.
- Distribute and divide the complex AI operations between the cloud and edge, with edge undertaking early intelligent data processing reducing the bandwidth of data being transmitted to the cloud; and building the hardware and software infrastructure to provide for this in Europe.
- Providing data sharing and collaborating solutions on edge to handle the temporal-spatial diversity of edge data.
- Developing solutions for IoT, i.e., mostly wireless devices with energy- and processing- constraints, in heterogeneous and also hostile/harsh environments.
- Providing re-usable solutions across industrial domains.
- Methodological approach with the Integral Supply Chain, from academic, to system designers and integrators, to component providers, applications and services developers & providers and end-users
Participants:
External funding: DAIS has received funding from the ECSEL Joint Undertaking (JU). The JU receives support from the European Union’s Horizon 2020 research and innovation program and Sweden, Netherlands, Germany, Spain, Denmark, Norway, Portugal, Belgium, Slovenia, Czech Republic, Turkey
Duration: July 2021 – July 2024