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Next Generation Open Innovations in Trustworthy Embedded AI Architectures for Smart Cities, Mobility and Logistics

Project
Data and AI-driven smart technologies, with an emphasis on (i) the connection between the urban space and the industrial space, (ii) sustainable living and (ii) sustainable industrial production, hold the transformative potential to enhance the sustainability and climate resilience across EU, in private and work spaces. Assuming this, NexTArc is devoted to augmenting the adoption of Trustworthy edge AI and IoT across 3 complementary and interrelated application domains, organised as Use Cases (UC): SLN - Smart, sustainable and Liveable Neighbourhood in Urban Spaces; STI - Smart, sustainable and transparent industrial Spaces; and TEM - Trustworthy and Eco-friendly Multimodal Connectivity of Urban and Industrial Spaces through people and freight mobility, incl. the inter and intra-mobility. Building on this vision, NexTArc aims to promote the cross-fertilization of ideas among a broad spectrum of stakeholders, 38 partners in 10 countries, integrated over a four-fold Innovation Module (IM) approach: i) cyber-resilience on chip; ii) low-power embedded AI; iii) improved computation and dependability covering the high-performance needs; iv) holistic solution stack to enable trustworthy services, which resonate with the EU Chips Act, etc. NexTArc has identified 6 Specific Objectives: 1) Driving adoption of AI while enhancing connectivity preparedness; 2) Targeting a 40% increase in data transmission rates and a 30% reduction in energy use during data processes, while ensuring robust architectural resilience; 3) Fortifying cyber-physical security with an aim for full-compliance with EU’s Chip and Cybersecurity act; 4) Realising open HW/SW to ensure designs that are secure, safe, private, and accountable; 5) Proactively adapting to the dynamic landscape of open-source innovations and key industry standards; 6) Orchestrating 4 IM, unveiling 15 Key Innovations to develop the solutions that are needed for Europe to take the technological lead towards a sustainable society.
  • Overview
  • Skills
  • Research Outputs

Overview

Contributor

CALDERARA Simone   Scientific Manager  

Leading department

"Enzo Ferrari" Department of Engineering   Principale  

Term type

ECSEL

Financier (2)

Ministero dell'Università e della Ricerca
Funding Organization
UNIONE EUROPEA
Funding Organization

Partner

Università degli Studi di MODENA e REGGIO EMILIA

Total Contribution (assigned) University (EUR)

313,250€

Date/time interval

September 1, 2025 - August 31, 2028

Project duration

36 months

Skills

Concepts (3)


PE6_1 - Computer architecture, embedded systems, operating systems - (2024)

PE6_7 - Artificial intelligence, intelligent systems, natural language processing - (2024)

Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni

Research Outputs

Research outputs

Dataless Weight Disentanglement in Task Arithmetic via Kronecker-Factored Approximate Curvature 
2026
Conference Paper
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