The idea is to Build a Knowledge Base, that can be used to trace all activities related to the overall life-cycle of buildings. Since various directives of the EU are related to sustainability, resilience and energy efficiency of building stock, it is necessary to provide a marketplace where various actors can share their offers, including their quality certificates and credentials, and where it would be possible to log and trace every information, activity and change, and use the knowledge to improve sustainability. The project will extend a Digital Building LogBook (DBL), used by a municipality for the management and the administration of its huge set of buildings, with several available and novel data, tools and functionalities, by the help of a Decentralized Knowledge Graph (DKG), an open source blockchain-based solution. DKG software will include specific building-related ontologies, so that the whole knowledge base about the life-cycle of the building can be logged and by that continuously updated, providing mechanisms and interfaces for the relevant stakeholders, to publish, trace, share, tokenize, end even trade models in a market economy. Such information integration can support decisions on optimal adaptation and intervention planning strategies for large populations of buildings. The DBL will be integrated with several new functionalities demonstrated on a dozen of use cases via easily accessible and publicly available APIs. These functionalities will assure a high interoperability between legacy systems and existing tools (e.g. BIM, HBIM), compliance with standards, providing automated warning and alerting system with the help of machine learning tools, digital twinning, and decision-making support. The new DBL based applications will be tested on pilot projects focusing on historical and critical buildings, and on building stocks. The project targets a smarter and more sustainable built environment of the EU providing new market and new value creation.

The world population living in urban settlements is expected to increase to 70% of 9.7 billion by 2050. Historically, as cities grew, new water infrastructures followed as needed. However, these developments had less to do with real planning than with reacting to crisis situations and urgent needs, due to the inability of urban water planners to consider long-term, deeply uncertain and ambiguous factors affecting urban development and water demand. These, coupled with increasingly uncertain climate conditions, indicate the need for a more holistic and intelligent decision-making framework for managing water infrastructures in the cities of the future. This project aims to develop a new theoretical framework for the allocation and development decisions on drinking water infrastructure systems, so that they are socially equitable, economically efficient and environmentally resilient, as advocated by the UN Agenda 2030, Sustainable Development Goals. The framework will integrate real-time monitoring and control with long-term robustness and flexibility-based pathway methods, and incorporate economic, social, ethical and environmental considerations for sustainable transitioning of urban water systems under deep uncertainty with multiple possible futures. The Water-Futures team will build on synergies from the four research groups, transcending methodologies from water science, systems and control theory, economics and decision science, and machine learning, into an integrated decision and control framework, to be implemented as an open-source research toolbox. The new science outcomes will be applied to three case studies exemplifying different types of urban water systems: a mature, relatively stable system; a mature and rapidly expanding system; and a relatively recent supply system in a developing country with high growth and special challenges, including limited resources, intermittent supply and high water losses.

PRUDENT aspires to change the way agriculture and forestry systems currently operate and to accelerate the transition to sustainable agriculture and forestry practices and smart farming technologies. The project will identify and evaluate the most effective green nudges, in the context of appropriate behavioural and experimental settings, that can enable farmer/forester behavioural change to more sustainable agriculture and forestry. Nudges will be also tested in natural contexts to evaluate the interactive effect of nudges with actual policy changes in the transition to sustainability. Innovative nudging tools, in the form of web/mobile apps, will be employed to boost farmer/forester self-regulatory capacity and enhance the durability of nudging effects. Four different systems, representing major farming and forestry systems in Europe (arable crops [wheat], perennial crops [grapevines, apples, olives], livestock [bovines] and forests [boreal forests]) in various EU regions (Northern, Southern, and Central Europe) will be studied to account for the heterogeneity of farming/forestry systems and contexts in the EU. The behavioural insights are used to develop transformative pathways, via social innovations, business models and policy recommendations, to encourage transition to fair, healthy and environmentally-friendly agriculture and forestry systems. PRUDENT will provide a set of social innovations and business models establishing roadmaps for a shift towards sustainable agriculture and forestry and will develop a series of policy recommendations and tools to foster behaviourally informed policy design and implementation. Throughout the project's lifespan, multiple value chain actors, at various levels of society, will actively participate in co-creation activities to establish a mutual understanding of the benefits and bottlenecks of the value chain, as well as effective transformation pathways to change.

There is a need for a radical step-up in the attention we pay to current and future climate impacts and associated efforts. Despite inspiring examples of adaptation solutions, stand-alone risk reduction projects that tackle issues through direct or existing policy levers are common practice. Adopting a systemic, transformative approach is advocated by the Mission Adaptation and European Green Deal. P2R takes an innovative systemic approach to regional climate resilience; one indivisible from Europe’s future economic and social development, intersecting with net zero commitments, and demanding a markedly different approach from the one adopted so far. P2R will empower at least 100 regions and communities to co-design visions of a climate resilient future and corresponding transformative, locally led pathways and innovation agendas that ensure long-term impact through political commitment. We do this by: (a) mobilising regional interest and progressively elevating the ambition and capability of regions; (b) developing a Regional Resilience Journey framework (and supporting services) to equip regions and communities in developing climate resilience pathways and connected innovation agendas; (c) allocating €21M across 100 regions and communities via two open call cycles to support their Journeys (d) triggering a wide engagement of citizens and diverse stakeholders in the co-creation of the pathways; (e) increasing knowledge on adaptation innovations across Key Community Systems (KCS) and enabling conditions; (f) boosting literacy and access to (innovative) adaptation finance; and (g) developing a Resilience Maturity Curve to baseline and monitor regional resilience capacities. Led by Climate KIC, the P2R consortium brings the combined strength of: regional network organisations, technical designers and innovators of transformative adaptation, adaptation finance experts, learning and capability building specialists, and monitoring and innovation impact partner.

Radiotherapy is a widely used cancer treatment, however some patients suffer side effects. In breast cancer, side effects can include breast atrophy, arm lymphedema, and heart damage. Some factors that increase risk for side effects are known, but current approaches do not use all available complex imaging and genomics data. The time is now ripe to leverage the huge potential of AI towards prediction of side effects. This project will use rich datasets from three patient cohorts to design and implement an AI tool that predicts the risk of side effects, including arm lymphedema in breast cancer patients and provides an easily understood explanation to support shared decision-making between the patient and physician. The PRE-ACT consortium combines the expertise in computing (MDW, AUEB-RC), AI (HES-SO, CENTAI), radiation oncology (MAASTRO, UNICANCER), medical physics (THERA), genetics (ULEIC), psychology (CNR) and health economics (UM) that is necessary to tackle this problem. The project will integrate data from the three cohorts and build AI predictive models with built-in explainability for each of the key side effects of breast cancer radiotherapy. These AI models will be incorporated into an existing commercial radiotherapy software platform to create a world-leading product. The extended platform will be validated in a clinical trial to support treatment decisions regarding the irradiation of lymph nodes. The trial will adopt an innovative design in which the patients and medical team in the test arm will receive the risk prediction, but those in the control arm will not. A communication package built with a co-design methodology will ensure that AI outcomes are tailored to stakeholders effectively. The trial will evaluate whether using the AI platform changed the arm lymphedema rate and impacted treatment decisions and quality-of-life. Generalizability of the AI models for other types of cancer will be sought through transfer learning techniques.