The 2021 EPBD recast highlights buildings' central role in the energy transition towards an integrated and renewable energy-based EU energy system. Smarter buildings will support the digitalisation and decarbonisation transition to the benefit of building occupants, owners and the energy system. Improving energy performance and reducing energy demands are even more relevant in the context of the REPowerEU Plan to rapidly reduce dependence on Russian fossil fuels and accelerate the green transition. BuildON seeks to develop a highly replicable, generic solution to deliver intelligent building services, facilitate the integration of heterogeneous systems and technologies, and help Build the next generatiON of Smart buildings. The main objective of BuildON is to develop and demonstrate a Smart Transformer Toolbox at TRL8 to plan and achieve improved energy performance applicable to the broadest range of building typologies and smart readiness levels via a comprehensive demonstration campaign involving five representative real-life use cases. This toolbox will offer affordable, adaptative, close-to-market and easy-to-install SRI-aligned services to continuously Monitor, Assess, Predict and Optimise (MAPO services) a building’s performance. A unified representation of the building, exposed through a Universal Building API, will abstract all field-level communication complexity, allowing the energy devices’ homogeneous real-time monitoring and control. Moreover, the generation of (Maturity Level 3 and 4) Digital Twins will allow simulation and control of a building and its systems. User-friendly decision support and user empowerment tools for facility managers and occupants will be part of the toolbox to explore, understand and expand their buildings' smart capabilities. By providing a unified approach to interacting with buildings, the floor is offered to develop a building app store that significantly accelerates the Smart Transformation of existing and new buildings

AI-empowered Personalized Medicine promises to find tailored, targeted, nearly “hand-made” cures for patients. Cancer treatment desperately needs boosters to find tailored, targeted cures for patients and Personalized Medicine can play a crucial role. Tailored targeted therapies in cancer treatment are already a reality but the current practice of targeted therapies in cancer treatment has been derived with traditional methods of data analysis. AI-empowered Personalized Medicine may help to bring targeted therapies to the next level. However, no matter how precise it is, no matter how many lives it can save in principle, and no matter if it can utilize the entire medical knowledge. If clinicians do not understand its suggestions and decisions, AI-empowered Personalized Medicine will not be a game changer, clinicians will not use it to make everyday decisions and, thus, it is doomed to fail. Hence, the real challenge is building AI-empowered Personalized Medicine systems that can be accepted by clinicians and clinical researchers. In KATY, we grasp the above challenge and we propose an AI-empowered Personalized Medicine system that can bring medical “AI-empowered knowledge” to the tips of the fingers of clinicians and clinical researchers. The AI-empowered knowledge is a human interpretable knowledge that clinicians and clinical researchers can: understand, trust and effectively use in their everyday working routine. KATY is then a AI-empowered Personalized Medicine system built around two main components: A Distributed Knowledge Graph and A pool of eXplainable Artificial Intelligence predictors. As a stress test and due to the lack of personalized clinical responses, KATY will be experimented in a low prevalence and complex cancer: Clear cell renal cell carcinoma (ccRCC).

The media sector is exposed to and undergoing continuous innovations that occur at a pace never seen before and have a non-negligible impact on citizens, democracy and a society as whole. A significant booster becomes a generative Artificial Intelligence, which already plays and will continue to play a critical role (in a positive as well as negative meaning) in creating and spreading information. Especially in next-generation social media, which refer to the anticipated evolution towards more AI-based decentralised and immersive virtual environments (like fediverses and metaverses), generative AI can become the most prominent enabler of disinformation growth accompanied by a lack of trusted information. Media professionals are not, however, currently well-equipped with supporting tools nor knowledge to operate in such already emerging environments. As a result, there is a tremendous need for innovative (AI-based) solutions ensuring media freedom and pluralism, delivering credible and truthful information as well as combating highly disinformative content. The main goal of the AI-CODE project is to evolve state-of-the-art research results (tools, technologies, and know-how) from the past and ongoing EU-funded research projects focused on disinformation to a novel ecosystem of services that will proactively support media professionals in trusted information production through AI. First, the project aims to identify, analyse, and understand future developments of next-generation social media in the context of rapid development of generative Artificial Intelligence and how such a combination can impact the (dis)information space. Second, the project aims to provide media professionals with novel AI-based services to coach them how to work in emerging digital environments and how to utilise generative AI effectively and credibly, to detect new forms of content manipulation, as well as to assess the reputation and credibility of sources and their content.

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.

ENPOWER will design, develop and demonstrate SSH-driven methodologies, interactive and closed-loop tools, and data-driven services for energy-activated citizens and energy-secure cross-sector communities towards a citizen-centric energy system. We combine leading-edge ICTs with social/behavioural dimensions and with sharing economy and value stacking business models to deploy: 1) a Social Science Framework for energy citizens activation and innovative multi-dimensional incentives for citizens participation in energy markets; 2) AI-based consumers clustering and segmentation algorithms; 3) interactive tools and facilitation services for energy community planning; 4) Energy Data Space adaptation to support community-level data-driven activation and interoperable automated privacy and sovereignty-preserving Demand Response (DR); 5) P2P DLT/Blockchain digital marketplace for tokenized energy and non-energy assets reciprocal compensation; 6) data-driven services and apps for energy efficiency and activation performance management; 7) ICT services and Digital Twins for community-level energy optimization and aggregated flexibility management to trade off local self-consumption against grid service provisioning, while boosting a beyond-energy community social welfare; 8) Edge monitoring hubs for automated DR; 9) Business Sandbox for novel sharing economy and social innovation-based business models; 10) methodologies for evaluating different energy community setups, upscaling and replication. ENPOWER framework will be validated along 4 Front Runners energy communities pilots and further replicated in 2 Early Adopters, covering different levels of maturity of communities, to demonstrate increased RES local self-consumption and consumers participation to the energy markets, while nurturing increased local security of supply. ENPOWER Leadership Programme and blueprints will support EU-wide replication and advice regulatory bodies on communities-friendly enabling frameworks.