Cyber threats are the most significant and growing risk for public administrations (PA). However, technological, organisational and structural issues hamper the ability, especially for local PAs (LPAs) to improve their cyber security level. Budget constraints and evolving legal, ethical, societal and privacy regulations render the situation even more complex. COMPACT’s goal is to empower local LPAs to become the main actors of their cyber-resilience improvement process. COMPACT’s objectives are to 1) increase awareness, skills and protection; 2) foster information exchange between European LPAs; 3) link LPAs to major EU initiatives, including the newly created cyber-security private-public partnership. COMPACT innovates at technological level and at process level – an important dimension in engaging LPA employees in the improvement of cyber-resilience. At technological level, COMPACT innovates in real time security monitoring, security awareness training, information sharing, cyber-security gamification, risk assessment, and threat intelligence. At process level, COMPACT adapts the Plan-Do-Check-Act cycle for LPAs to do iterative removal of security bottlenecks and achieve compliance to EN ISO/IEC 27001 and BS ISO/IEC 27005. COMPACT delivers an integrated platform with 4 types of tools/services – 1) risk assessment, 2) education, 3) monitoring, and 4) knowledge sharing – characterized by a high degree of usability by non IT experts and automation. It protects LPAs’ investments by interoperating with market solutions from major vendors. It eases deployment and adoption by being both cloud-enabled (i.e. it addresses cloud specific issues) and cloud-ready (i.e. it can be deployed – if users wish– on the cloud). COMPACT validates its results through 5 challenging use cases provided by 5 users in 4 European countries. 90% of COMPACT solutions will achieve TRL7 and the residual part TRL6.

The adoption of robots in lower volume, diverse environment is heavily constrained by the high integration and deployment complexity that overshadows the performance benefits of this technology. If robots are to become well accepted across the whole spectra of production industries, real evidence that they can operate in an open, modular and scalable way is needed. ODIN aspires to fill this gap by bringing technology from the latest ground breaking research in the fields of a) collaborating robots and human robot collaborative workplaces b) autonomous robotics and AI based task planning c) mobile robots and reconfigurable tooling, d) Digital Twins and Virtual Commissioning and e) Service Oriented Robotics Integration and Communication Architectures. To strengthen the EU production companies’ trust in utilizing advanced robotics, the vision of ODIN is: “to demonstrate that novel robot-based production systems are not only technically feasible, but also efficient and sustainable for immediate introduction at the shopfloor”. ODIN will achieve this vision through the implementation of Large Scale Pilots consisting of the following components: - Open Component (OC): A small footprint, small scale pilot instance allowing the development, integration and testing of cutting-edge technologies. - Digital Component (DC): A virtual instance of the pilot implementing an accurate Digital Twin representation that allows the commissioning, validation and control of the actual pilot - Industrial Component (IC): A full-scale instance of the pilot, integrating hardware (HW) and software (SW) modules from the Open and Digital components and operating under an actual production environment. - Networked Component (IC): An integration architecture with open interfaces allowing the communication of all robotics HW and control systems through safe and secure means. ODIN will demonstrate its result in 3 Large Scale Pilots in the automotive, white goods and aeronautic sectors.

The project aerOS aims at transparently utilising the resources on the edge-to-cloud computing continuum for enabling applications in an effective manner, incorporating multiple services deployed on such a path. Therefore, aerOS will establish the missing piece: a common meta operating system that follows a collaborative IoT-edge–cloud architecture supporting flexible deployments (e.g., federated or hierarchical), bringing tremendous benefits as it enables the distribution of intelligence and computation – including Artificial Intelligence (AI), Machine Learning (ML), and big data analytics – to achieve an optimal solution while satisfying the given constraints. The overarching goal of aerOS is to design and build a virtualized, platform-agnostic meta operating system for the IoT edge-cloud continuum. As a solution, to be executed on any Infrastructure Element within the IoT edge-cloud continuum – hence, independent from underlying hardware and operating system(s) – aerOS will: (i) deliver common virtualized services to enable orchestration, virtual communication (network-related programmable functions), and efficient support for frugal, explainable AI and creation of distributed data-driven applications; (ii) expose an API to be available anywhere and anytime (location-time independent), flexible, resilient and platform-agnostic; and (iii) include a set of infrastructural services and features addressing cybersecurity, trustworthiness and manageability. aerOS will: (a) use context-awareness to distribute software task (application) execution requests; (b) support intelligence as close to the events as possible; (c) support execution of services using “abstract resources” (e.g., virtual machines, containers) connected through a smart network infrastructure; (d) allocate and orchestrate abstract resources, responsible for executing service chain(s) and (e) support for scalable data autonomy.

ASSIST-IoT will provide an innovative reference architecture, envisioned as a decentralized ecosystem, where intelligence is distributed among nodes by implementing AI/ML close to data generation and actuation, and hyperconnecting nodes, in the edge-cloud continuum, over softwarized smart network. Smart network will be realised by means of virtualized functions, with clear separation of control and data planes, facilitating efficient infrastructure programmability. Moreover, the action will follow a DevSecOps methodology to ensure the integration of security, privacy, and trust, by design, in all aspects of the envisioned ecosystems. ASSIST-IoT will be supported by several pillars: (i) innovative IoT architecture, to adapt to the NGI paradigm, with three-dimensional approach, including intelligence, security and privacy by design, supporting decentralized collaborative decision-making; (ii) moving from semantic interoperability to semantically-enabled cross-platform, cross-domain data transactions, within decentralized governance, DLT-anchoring transaction security, privacy and trust; (iii) development and integration of innovative devices, supporting context-aware computing, to enable effective decision making close to events; (iv) introduction of self-* mechanisms, supporting self-awareness and (semi-)autonomous behaviours across IoT deployments, and (v) Tactile Internet support for latency applications, like AR/VR/MR, and human-centric interaction with IoT components. Results of the action will provide foundation for a comprehensive practice-based methodology, for future designers and implementers of smart IoT ecosystems. Finally, to validate research results, and developed solutions, and to ensure their wide applicability, extended pilot deployments with strong end-user participation will take place in: (i) port automation; (ii) smart safety of workers, and (iii) cohesive vehicle monitoring and diagnostics, bringing about domain-agnostic aspect of the approach.

As part of the green, circular and digital transformation of the European manufacturing community, it is extremely important that data-driven digital manufacturing processes urgently incorporate innovative and active resiliency strategies at production and supply chain levels to maintain their sovereignty and competitiveness levels, respecting European digital values (excellence, privacy, trust) to improve individual and value chain flexibility. In order to achieve long-term resilience to reorganise supply chains or speed up decision making to dealt with any disruption, it is imperative to ensure the implementation of distributed data-intensive intelligent and dynamic industrial decision support, augmentation and automation processes, integrating Artificial Intelligence (smart anticipation) and Intelligent Automation (rapid response) capabilities in Human-Automation symbiosis. Hence, only businesses that can articulate their data, based on AI, digital thread and digital twin solutions, will be able to react rapidly to external shocks. RE4DY mission is to demonstrate that the European industry can jointly build unique data-driven digital value networks 4.0 to sustain competitive advantages through digital continuity and sovereign data spaces across all phases of product and process lifecycle, proposing ?Data as a Product? core concept to facilitate the implementation of digital continuity across digital threads, data spaces, digital twin workflows and AI/ML/Data pipelines. This concept leverages resiliency on top of advanced manufacturing digital processes and value ecosystems supporting the development and implementation of digital continuity, so distributed data management solutions implemented to deal with factory resiliency can be immediately and seamlessly reused to enhance connected factory and value network level processes.