As the world moves from the 5G towards the 6G era, the mobile communications fabric needs to be architected differently to accommodate the emerging stringent requirements of innovative extreme future-looking applications that cannot be served by existing 5G mobile networks. Heading towards the next decade, when 6G is expected to be widely deployed, 5G application types will be redefined by morphing the classical service classes of URLLC, eMBB, and mMTC and introducing new services. ADROIT6G is an SNS JU project supporting the EC’s 6G policy by implementing the first phase of the 6G SNS roadmap towards the evolution of a 6G architecture. ADROIT6G proposes disruptive innovations in the architecture of emerging 6G mobile networks that will make fundamental changes to the way networks are designed, implemented, operated, and maintained. Such innovations include: (i) AI/ML-powered optimizations across the entire network, for high performance and automation; (ii) Transforming to a fully cloud-native network software, which can be implemented across a variety of edge-cloud platforms, including Non-Terrestrial Networks, with security built integrally into the network user plane; (iii) Software driven, zero-touch operations and ultimately automation of every aspect of the network and the services it delivers. ADROIT6G innovations, functionalities and performance will be validated through 3 representative extreme 6G use cases (i.e., holographic telepresence, Industrial IoT, collaborative robots/drones) in corresponding PoCs over five well-established 5G testbeds, which will be upgraded to support ADROIT6G innovations and architectural elements. Our 13-partner consortium is driven by industry heavyweights from EU telecom and ICT industries and renowned research organisations, with a vast expertise and experience in 5G and beyond technologies. Most of ADROIT6G’s consortium partners have participated in 44 previously funded 5G-PPP projects and in several 5G-PPP Working Groups.

OnMoveID will leverage increasing sensory, computational and communicational technological capabilities of standard non-trusted smartphones for advanced privacy-preserving, legal and ethical compliant management of travel documents for fast on-the-move identification of travellers for all types of border crossings: land, sea, and air. High efficiency and security are achieved in three phases: (1) Registration of border crossing (duration ca. 10 min only once, then e.g. annually), within trusted extended 3rd generation EUID wallet. Also, self-scanned identity documents will be stored, verified and used to assess biometric standstill face images and fingerprints using smartphone cameras. (2) Back-up registration (duration ca. 5 min) at registration desk at border with advanced document scanning and digital identity generation using AI. (3.1) Walk-through along lanes (duration ca. 20 sec) of travellers is used to identify and track in consent smartphone positions using ultrasound, to conduct body count from heart beat detection and localization, to generate external best face images from multiple fixed (multi)spectral cameras, while using smartphone sensors to take walk-through face and fingerprint images. (3.2) Drive-through passenger vehicles (ca. 10 sec) uses multispectral cameras. (3.3) Bus inspection (duration ca. 2 min) uses in addition smartphone camera of border officers for taking in-consent images of passengers within the bus. OnMoveID will use rule- and risk-based decision making to accept (back-up) registration as well as final border crossing acceptance or rejection. It extends S-o-t-A of all existing legacy and emerging border management systems and data bases (e.g. EES, VIS, ETIAS) at EU level while improving travellers’ throughput, based on communication and cloud computing within extended EUID/digital wallet framework. OnMoveID is functionally and performance tested and iteratively improved at borders in (i) Finland, (ii) Slovakia, and (iii) UK.

New trends such as teleworking and e-commerce, as well as the need for a further increase of digital tools in all sectors (i.e., health, education, transportation, farming, etc.) demanded by the Covid-19 pandemic, are pointing out once again digital territorial inequalities, supply-chain disruptions and deficiencies in economic opportunities that hamper resilience and prosperity of rural communities. Accessibility and connectivity are key issues to mitigate this erosion of socio-territorial cohesion. However, identifying a common solution for equipping rural communities with increased access to services, opportunities and adequate innovation ecosystems ensuring that no one left behind is a challenging task, mainly due to the diversity of challenges and needs of different locations. In this respect, XGain fosters a sustainable, balanced and inclusive development of rural, coastal and urban areas by facilitating access to relevant stakeholders, such as municipalities, policymakers, farmers, foresters and their associations, to a comprehensive inventory of smart XG, last-mile connectivity and edge computing solutions, and of related assessment methods. The XGain overall project objective is, to deliver a Knowledge Facilitation Tool, facilitating business model development, supporting decision-making in the selection of an ecosystem of technologies, consisting of connectivity options and edge processing solutions, by following a multi-actor and practitioner-oriented approach, and by coherently assessing their socio-economic and techno-environmental effects, aiming at: increasing systemic resilience and energy efficiency; contributing to climate mitigation; and reducing the digital divides between different types of citizens, farms, sectors and regions.

cPAID envisions researching, designing, and developing a cloud-based platform-agnostic defense framework for the holistic protection of AI applications and the overall AI operations of organizations against malicious actions and adversarial attacks. cPAID aims at tackling both poisoning and evasion adversarial attacks by combining AI-based defense methods (e.g., life-long semi-supervised reinforcement learning, transfer learning, feature reduction, adversarial training), security- and privacy-by-design, privacy-preserving, explainable AI (XAI), Generative AI, context-awareness as well as risk and vulnerability assessment and threat intelligence of AI systems. cPAID will identify guidelines to a) guarantee security- and privacy-by-design in the design and development of AI applications, b) thoroughly assess the robustness and resiliency of ML and DL algorithms against adversarial attacks, c) ensure that EU principles for AI ethics have been considered, and d) validate the performance of AI systems in real-life use case scenarios. The identified guidelines aspire to promote research toward developing certification schemes that will certify the robustness, security, privacy, and ethical excellence of AI applications and systems.

The GOF2.0 Integrated Urban Airspace VLD (GOF2.0) very large demonstration project will safely, securely, and sustainably demonstrate operational validity of serving combined UAS, eVTOL and manned operations in a unified, dense urban airspace using current ATM and U-space services and systems. Both ATM and U-space communities depend extensively on the provision of timely, relevant, accurate and quality-assured digital information to collaborate and make informed decisions. The demonstrations focus on validation of the GOF 2.0 architecture for highly automated real-time separation assurance in dense air space including precision weather and telecom networks for air-ground communication and will significantly contribute to understanding how the safe integration of UAM and other commercial drone operations into ATM Airspace without degrading safety, security or disrupting current airspace operations can be implemented.