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VERGE

Financiado

AI-powered eVolution towards opEn and secuRe edGe architEctures

VERGE will tackle evolution of edge computing from three perspectives: Edge for AI, AI for Edge and security, privacy and trustworthiness of AI for Edge. Edge for AI defines a flexible, modular and converged Edge platform that is... ver más

30/06/2025

UPC

5M€

Presupuesto del proyecto: 5M€

Líder del proyecto

Universidad Politécnica de Cataluña No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 9

Ver 16 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-11-22

HORIZON-JU-SNS-2022-STREAM-A-01-05: Edge Computing Evolution ExpectedOutcome:A clear technological strategy for edge integration into a cloud continuum offering...

I+D

Cerrada hace 2 años

0% 93% 100%

16 Participantes

UPC

495.75K€ | Lider

ERICSSON ARASTIRMA GELISTIRM...

549.00K€ | Participante

UNISI

45.00K€ | Participante

HOLOINDUSTRIE 4.0 SOFTWARE G...

334.69K€ | Participante

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Duración del proyecto: 31 meses Fecha Inicio: 2022-11-22
Fecha Fin: 2025-06-30

Líder del proyecto

Universidad Politécnica de Cataluña No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 9

Presupuesto del proyecto 5M€

Descripción del proyecto VERGE will tackle evolution of edge computing from three perspectives: Edge for AI, AI for Edge and security, privacy and trustworthiness of AI for Edge. Edge for AI defines a flexible, modular and converged Edge platform that is ready to support distributed AI at the edge. This is achieved by unifying lifecycle management and closed-loop automation for cloud-native applications, MEC and network services, while fully exploiting multi-core and multi-accelerator capabilities for ultra-high computational performance. AI for Edge enables dynamic function placement by managing and orchestrating the underlying physical, network, and compute resources. Application-specific network and computational KPIs will be assured in an efficient and collision-free manner, taking Edge resource constraints in to account. Security, privacy and trustworthiness of AI for Edge are addressed to ensure security of the AI-based models against adversarial attacks, privacy of data and models, and transparency in training and execution by providing explanations for model decisions improving trust in models. VERGE will verify the three perspectives through delivery of 7 demonstrations across two use cases - XR-driven Edge-enabled industrial B5G applications across two separate Arçelik sites in Turkey, and Edge-assisted Autonomous Tram operation in Florence. VERGE will disseminate results to academia, industry and the wider stakeholder community through liaisons and contributions to relevant standardization bodies and open sources, a series of demonstrations showing progression through TRLs and by creating an open dataspace for enabling public access to the datasets generated by the project.

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