In recent years, technological developments in consumer electronics and industrial applications have been advancing rapidly. More and more, small, networked devices are able to collect and process data anywhere. This Internet of Things (IoT) is a revolutionary change for many sectors like building, automotive, digital industry, energy, etc. The new paradigm of edge computing provides new solutions by bringing resources closer to the user, keeps sensitive & private data on device, 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. The developments of AI applications mostly require processing of data in centralized cloud locations and hence cannot be used for applications where milliseconds matter in safety-critical 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.
DAIS has 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 the 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 cloud; and building the hardware and software infrastructure to provide for this in Europe.
* Providing data sharing and collaborating solutions on the 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