SPARK WORKS LIMITED

One of the key enablers of 6G is undoubtedly the Native support of AI/ML at all the system levels, components, and mechanisms, from the orchestration and management levels to the low-level optimization of the infrastructure resources, including Cloud, Edge, RAN, Core Network, as well as a transport network. Despite the opportunities, there are several gaps that hinder the adoption of AI/ML in 6G, such as the lack of extensive and high-quality datasets that are required to train the models. On the other hand, AI model testing and performance evaluation in a representative staging environment (by emulation or real deployment) is also challenging without access to an end-to-end 6G testbed or representative Digital Twin environment. To this end, 6G-DALI aims to deliver an end-to-end AI framework for 6G, structured in two interdependent pillars, (1) AI experimentation as a service via MLOps and (2) Data and analytics collection and storage via DataOps. The 6G-DALI DataOps pillar provides the mechanisms for preparing clean and processed data that are stored within a 6G Dataspace and are made available for training and validating machine learning models as a service, a part of the MLOps Pillar. The end-to-end framework also delivers continuous monitoring, drift detection and retraining of models. Finally, 6G-DALI will deliver open datasets, a 6G Dataspace for dataset storage and secure sharing, and a Digital Twin testbed for data generation on demand.

EC contribution:

EUR 349k

Start:

2025-01-01

End:

2027-12-31

Status:

SIGNED

Scheme:

HORIZON-JU-RIA

Call:

HORIZON-JU-SNS-2024

View on CORDIS (DOI 10.3030/101192750)

WATERDEAL is an ambitious collaborative research and innovation project addressing the urgent global challenge of water scarcity, infrastructure failures, and inefficient water management through digital transformation. With water demand rising and losses reaching up to 50% in some regions due to leaks, aging infrastructure, and inefficient distribution, the project leverages cutting-edge technologies such as IoT, AI-driven analytics, and cloud-edge computing to create smart, adaptive, and energy-efficient Water Supply Systems (WSSs). Despite advances in digitalization, current water management solutions remain fragmented, and the full potential of data-driven optimization is largely untapped. WATERDEAL introduces novel, cost-effective strategies for sensor deployment, real-time leak detection, predictive maintenance, and demand-responsive water distribution, reducing energy consumption while enhancing resilience. The project’s interdisciplinary approach integrates expertise from water engineering, energy-efficient communication, AI-driven analytics, and secure digital infrastructure to develop scalable Smart Water Grid (SWG) technologies. Through an international and intersectoral consortium of universities, research institutions, and industry leaders, WATERDEAL fosters knowledge exchange via structured secondments and staff exchanges, ensuring cross-disciplinary collaboration and hands-on innovation. By advancing next-generation AI-driven water management solutions, the project directly supports Europe’s digital transformation and sustainability goals, paving the way for a more efficient, resilient, and equitable water future.

EC contribution:

EUR 160k

Start:

2026-06-01

End:

2030-05-31

Status:

SIGNED

Scheme:

HORIZON-TMA-MSCA-SE

Call:

HORIZON-MSCA-2025-SE-01

View on CORDIS (DOI 10.3030/101299840)