Food security is a global challenge and is impacted by, rapidly compounding effects including climate change, supply chains, human labour shortages, driving the need for traceability, and technological innovation and automation to name a few. The latest important price increases of agricultural row products show the limitations of the available resources. Through this Joint Undertaking, the AGRARSENSE consortium of 57 partners (including 4 affiliates) plan to take agricultural technology and productivity to the next level, beyond the State-of-the-Art, by combining some of the most advanced organisational capabilities from across European industrial 16 Large Enterprises, 25 SMEs and 16 Research & Technology Organisations (RTOs), from 15 countries. The development of the most advanced sensory and autonomous agricultural capabilities requires a sophisticated governance structure, ensuring that all partners are aligned across Use Cases and Work Package deliveries. The AGRARSENSE consortium has one of the world’s leaders in Forestry automation, Komatsu, as Project Coordinator. The AGRARSENSE project goal of creating a holistic ecosystem of sensory and automated capabilities will further extend Europe’s lead in optimizing and securing agricultural value chains. To drive such an ambitious impact agenda, we have selected seven Use Cases which will, collectively, contribute to solving the challenges outlined. These Use Cases are Greenhouses (UC1), Vertical Farming (UC2), Precision Viticulture (UC3), Agri robotics (UC4), Autoforest (UC5), Organic Soils & Fertilizers (UC6) and Water (UC7). These Use Cases are fused together by the most advanced hardware, software and system integration technologies, which will drive new solutions for partners and the collective AGRARSENSE impacts at scale.

MOSAIC addresses a grand challenge for European competitiveness: technological independence and filled fabs in the landscape of automated systems. By fostering innovation in Electronic Components and Systems (ECS), MOSAIC aims to propel Europe to excellence and digital autonomy, directly linked to the EU Chips Act. The project achieves this through a comprehensive strategy. It will develop next-generation ECS offering superior, cognitive system intelligence, enabling energy efficiency and robustness. These results will be tailored to the demands of automated systems, enabling rapid data processing and intuitive, AI-enabled decision- making. MOSAIC tackles the challenge of integrating diverse perception hardware configurations, ensuring that automated systems can perceive their surroundings in a non-invasive manner, avoiding a single point of failure, with unparalleled accuracy and decreased complexity. Additionally, the project emphasizes standardized communication protocols and interoperability, fostering a collaborative ecosystem across several industries, namely automotive, aerospace, maritime, industrial automation and infrastructures. By spearheading such advancements, MOSAIC empowers European ECS manufacturers to gain a competitive advantage. The project's achievements will be demonstrated in 31 cutting-edge technical showcases, indicatively global perception through 360° distributed radar, AI-enabled reasoning through magnetic field signature and resilient communications by means of non-terrestrial networks. 2 accompanying impact studies, will solidify Europe's position as a global leader in automated systems. MOSAIC leverages a pan-European consortium encompassing the entire ECS value chain, ensuring a comprehensive effort towards filling the European fabs and ensuring digital sovereignty. In essence, MOSAIC is an investment in Europe's future – a secure digital future of technological leadership, economic prosperity, and strategic independence.

THEIA-XR (Making the invisible visible for off-highway machinery by conveying extended reality technologies) aims at improving human-machine interaction in mobile machinery by enhancing user technology fit and extending reality technologies and functionalities. The results will make the invisible visible respectively the non-perceivable perceivable to the human operator, extending the perceivable range of the operator without negatively influencing the performance of the human while controlling the machinery. The project will ensure positive impact of eXtended Reality technologies on the safety, security trustworthiness and societal aspects of the interaction between the machine, the human operator and public/non-users, and furthermore create an XR workplace that enables positive user experiences of self-efficacy and meaningfulness of work. THEIA-XR will leverage a human-centred transdisciplinary and scenario-based co-design methodology with users, stakeholders and multidisciplinary researchers as a fully integrated project team. This methodology serves to collect human requirements and to design, develop and deploy the extended reality technologies for information presentation and interaction in the off-highway domain. The targeted extended reality technologies will enhance conventional human-machine interfaces through multi-modal information and interaction technologies, deploying innovative data visualization methods, force feedback technology and acoustic information. The THEIA-XR approach for improving the human operator tasks by deploying extended reality technologies will be initially validated and tested in three uses cases in the off-highway domain, targeting snow grooming, logistics and construction scenarios, integrating real end-users, public/non-users and real-life data from dedicated industrial environments.

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.

The traditional cloud centric IoT has clear limitations, e.g. unreliable connectivity, privacy concerns, or high round-trip times. IntellIoT overcomes these challenges in order to enable NG IoT applications. IntellIoT’s objectives aim at developing a framework for intelligent IoT environments that execute semi-autonomous IoT applications, which evolve by keeping the human-in-the-loop as an integral part of the system. Such intelligent IoT environments enable a suite of novel use cases. IntellIoT focuses on: Agriculture, where a tractor is semi-autonomously operated in conjunction with drones. Healthcare, where patients are monitored by sensors to receive advice and interventions from virtual advisors. Manufacturing, where highly automated plants are shared by multiple tenants who utilize machinery from third-party vendors. In all cases a human expert plays a key role in controlling and teaching the AI-enabled systems. The following 3 key features of IntellIoT’s approach are highly relevant for the work programme as they address the call’s challenges: (1) Human-defined autonomy is established through distributed AI running on intelligent IoT devices under resource-constraints, while users teach and refine the AI via tactile interaction (with AR/VR). (2) De-centralised, semi-autonomous IoT applications are enabled by self-aware agents of a hypermedia-based multi-agent system, defining a novel architecture for the NG IoT. It copes with interoperability by relying on W3C WoT standards and enabling automatic resolution of incompatibility constraints. (3) An efficient, reliable computation & communication infrastructure is powered by 5G and dynamically manages and optimizes the usage of network and compute resources in a closed loop. Integrated security assurance mechanisms provide trust and DLTs are made accessible under resource constraints to enable smart contracts and show transparency of performed actions.