End-user and societal acceptance is critical to the success of the IoT large scale pilots. U4IoT combines complementary RRI-SSH expertise encompassing social and economic sciences, communication, crowdsourcing, living labs, co-creative workshops, meetups, and personal data protection to actively engage end-users and citizens in the large scale pilots. It will: • Develop toolkit for LSPs end-user engagement and adoption, including online resources, privacy-compliant crowdsourcing tools, guidelines and an innovative privacy game for personal data protection risk assessment and awareness, online training modules. • Direct Support to mobilize end-user engagement with co-creative workshops and meetups, trainings, Living Labs support, and an online pool of experts to address LSPs specific questions. • Analyse societal, ethical and ecological issues and adoption barriers related to the pilots with end-users and make recommendations for tackling IoT adoption barriers, including educational needs and sustainability models for LSPs and future IoT pilots’ deployment in Europe. • Support communication, knowledge sharing and dissemination with an online portal and interactive knowledge base gathering the lessons learned, FAQ, tools, solutions and end-user feedbacks. The U4IoT platform will support IoT take-up in Europe by better aligning it with end-user and societal expectations, mutualizing information and learning experiences, and improving communication with the public,- enabling Europe to take the lead in IoT user (and market) adoption. U4IoT will work in close cooperation with the other CSA, AIOTI and the IoT Forum who will maintain the platform after the end of the project to continue serving the European IoT community.

The EU dry-cured ham (DCH) sector faces growing challenges related to fraud, supply chain transparency, and compliance with PDO/PGI certification standards, threatening consumer trust and market competitiveness. While blockchain-based traceability is emerging, current systems rely solely on QR codes and labeling, lacking integration with chemical fingerprinting authentication to verify product authenticity at a granular level. Additionally, smaller producers struggle with resource limitations to adopt cutting-edge traceability solutions, restricting their ability to compete in premium markets. HAMTRACE addresses these gaps by developing an interoperable, privacy-preserving, and regulation-compliant traceability framework, integrating advanced analytical chemistry, AI, blockchain, and federated learning. The project will 1) Map critical control points across the value chain to enhance risk assessment. 2) Implement high-precision elemental fingerprinting to distinguish authentic DCH from fraudulent imitations. 3) Leverage AI-driven hyperspectral imaging and elemental fingerprinting to authenticate curing time and regional specificity. 4) Develop a Hyperledger Fabric blockchain system, embedding tamper-proof smart tags and real-time fraud detection using AI-enhanced anomaly detection. HAMTRACE goes beyond conventional traceability by introducing a human-in-the-loop AI model, ensuring ethical compliance and transparent decision-making. This aligns with GDPR, the EU AI Act, the Green Deal, or the Farm-to-Fork Strategy, reinforcing EU’s leadership in food safety R&I. By offering scalable, industry-ready solutions, HAMTRACE enhances consumer confidence, protects PDO/PGI certifications, and strengthens the EU DCH sector’s competitive edge globally. This groundbreaking fusion of analytical chemistry and digital technologies will set new industry standards for authenticity, transparency, and food integrity, shaping the future of fraud-resistant premium food traceability in EU