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CORDIS - Forschungsergebnisse der EU
CORDIS

Energy-efficient AI-ready Data Spaces

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Stakeholder Engagement and Dissemination Plan (öffnet in neuem Fenster)

Document registering the key activities per target group, pertaining to maximizing the dissemination of GREEN.DAT.AI outcomes during and after the project’s lifecycle.

Pilots' Scoping Document (öffnet in neuem Fenster)

Report outlining the demonstrators’ implementation plans, milestones. The report will identify key stakeholders for the testing/validation phase and include the User Acceptance test templates.

Use Case Requirements, KPIs & Reference Architecture (öffnet in neuem Fenster)

Report consolidating results of work carries out in WP1 tasks T1.1 - T1.4. More specifically, it sets out the business & technical requirements, specifies the overall solution architecture based on the outputs of the activities in T1.2 and T1.3, and lays out the testing framework for all the pilots.

First Version of Energy-Efficient Large-Scale Data Analytics Services (öffnet in neuem Fenster)

D3.1 presents the first iteration of the work employed towards the design and development of nine different services that aspire to provide energy-efficient large-scale data analytics. The software library and report will cover AI-enabled data enrichment, Incentive mechanisms for Data Sharing, Synthetic Data Generation, Large-scale learning at the Edge/Fog, Federated & Auto ML at the edge/fog, Explainable AI, Feature Learning with Privacy Preservation, Federated & Automatic Transfer Learning, Adaptive FL for Digital Twin Applications, Automated IoT event-based change detection/ forecasting.

Data Management infrastructure and tools to support Dynamic Ecosystems (öffnet in neuem Fenster)

D2.1 showcases the design and development of the BDA infrastructure including the Federated Data Sovereignty services and the plan for data pipelines management and continuous integration. It also delivers the visualisation tools needed for the pilots, the workflow management engine required to schedule distributed analytics pipelines, and, finally, wrappers that secure computations & sensitive data at the edge/fog/cloud. A report will detail or the platform components, their interfaces, and data pipelines management mechanisms. The deliverable will include the first prototype of the visualisation workbench, interfaces, distributed analytics services, workflow management engine, and the wrappers for Securing Computations and Sensitive Data at the Edge/Fog/Cloud.

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