DAIS
About the *project.*
The DAIS approach develops intelligent, secure, and reliable systems. This targets industrial applications, providing comprehensive, cost- and energy-efficient solutions for intelligent, secure, and reliable end-to-end connectivity and interoperability. The process will bring together the Internet of Things and Artificial Intelligence.
The main objective of the DAIS project is to research, promote, and deliver distributed AI systems and their respective architectures. By doing so, the project aims to solve the problems associated with running existing algorithms on decentralized edge devices. In other words, the project seeks to address the challenges of implementing AI systems in highly decentralized environments. This is a significant step toward more robust and efficient AI solutions.
The DAIS project is organized around eight different supply chains. Specifically, five of these supply chains focus on delivering the hardware and software needed to run industrial-grade AI across different networking topologies. In contrast, the other three supply chains will demonstrate how this pan-European effort can address known AI challenges from various functional areas. These supply chains are designed to tackle the complex issues of implementing AI systems in highly decentralized environments.
Key *objectives.*
Edge-Enabled Safety in Industrial Applications
Providing intelligent data processing and communication at the edge to enable real-time, safety-critical industrial applications.
Cybersecurity Solutions
Developing industrial-grade secure, safe, and reliable solutions that can withstand cyberattacks and challenging network conditions.
Efficient Cloud-Edge AI Distribution in Europe
Distribute complex AI operations between the cloud and edge to reduce data transmission bandwidth to the cloud through early intelligent data processing. Develop the necessary European hardware and software infrastructure to support this approach.
Tailoring Edge AI to Diverse Computing Power
Offering AI techniques on edge devices with varying computing capacities is challenging because algorithms must align with specific edge platforms and their diverse computing-power requirements.
Integrated Supply Chain Methodology
A methodological approach to the Integrated Supply Chain, from academics to system designers and integrators, to component providers, application and service developers & providers, and end users.
IoT Solutions for Energy-Efficient, Hostile Environments
Developing IoT solutions, i.e., mostly wireless devices with energy and processing constraints, in heterogeneous and hostile/harsh environments.
Data Collaboration for Temporal-Spatial Diversity
Providing data-sharing and collaboration solutions at the edge to handle the temporal-spatial diversity of edge data.
Cross-Industry Reusable Solutions
Providing reusable solutions across industrial domains.
Beyond Vision's *role*.
Edge Intelligence (EI) has emerged as a promising solution to develop intelligent, secure, and energy-efficient systems for industrial applications. The DAIS project is a leading approach that integrates cutting-edge technologies to provide comprehensive solutions for decentralized environments.
By combining the Internet of Things and Artificial Intelligence, DAIS ensures secure, trustworthy connectivity and interoperability. This drives technological advancement and contributes to economic growth.