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Green.Dat.AI

financed

Closed

Energy-efficient AI-ready Data Spaces

GREEN.DAT.AI aims to channel the potential of AI towards the goals of the European Green Deal, by developing novel Energy-Efficient Large-Scale Data Analytics Services, ready-to-use in industrial AI-based systems, while reducing t... see more

31/12/2025

INLECOM INNOVATION

7M€

Project Budget: 7M€

Project leader

INLECOM INNOVATION ASTIKI MI KERDOSKOPIKI ETA... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

Ver 21 Participantes

Financing granted El organismo HORIZON EUROPE notifico la concesión del proyecto The day 2022-11-14

HORIZON-CL4-2021-DATA-01-05: Future European platforms for the E... ExpectedOutcome:Proposal results are expected to contribute to the following expected outcomes:

I+D

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characteristics of the participant

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Private Information

No hay información privada compartida para este proyecto. Habla con el coordinador.

21 Participantes

INLECOM INNOVATION

599.00K€ | Leader

FISC-Ireland Limited

273.35K€ | participant

LA CAIXA

253.75K€ | participant

SUNESIS DOO

133.00K€ | participant

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Project duration: 37 months Date Start: 2022-11-14
End date: 2025-12-31

Project leader

INLECOM INNOVATION ASTIKI MI KERDOSKOPIKI ETA... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 7M€

participation deadline Sin fecha límite de participación.

Project description GREEN.DAT.AI aims to channel the potential of AI towards the goals of the European Green Deal, by developing novel Energy-Efficient Large-Scale Data Analytics Services, ready-to-use in industrial AI-based systems, while reducing the environmental impact of data management processes. GREEN.DAT.AI will demonstrate the efficiencies of the new analytics services in four industries (Smart Energy, Smart Agriculture/Agri-food, Smart Mobility, Smart Banking) and six different application scenarios, leveraging the use of European Data Spaces. The ambition is to exploit mature (TRL5 or higher) solutions already developed in recent H2020 projects and deliver an efficient, massively distributed, open-source, green, AI/FL - ready platform, and a validated go-to-market TRL7/8 Toolbox for AI-ready Data Spaces. The services 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. The GREEN.DAT.AI Consortium consists of a multidisciplinary group of 17 partners from 10 different countries (and one associated party), well balanced in terms of expertise. The vast majority of partners already have key roles in a number of projects funded under the Big Data PPP (ICT-16-2017) topic, namely BigDataStack, CLASS, Track & Know, and I-BiDaaS and are serving as active members of the BDVA/DAIRO Association, FIWARE, AIOTI, and ETSI. In addition, partners come from a variety of sectors, such as banking, mobility, energy, and agriculture, constituting a representative workforce of their respective domains, which will contribute to industry adoption and stimulate uptake in other sectors as well.

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