Recent disaster events, like the 2021 flood in Germany showed clearly, that even the best alert systems and top first responder organisations can not prevent fatalities and serious damage on property without having prepared the citizens how to act and react during disaster situations and crises, understand alerts and follow instructions. B-Prepared offers a cost-effective solution for building a culture of disaster preparedness with a multi-actor approach in realistic historical scenarios. B-prepared builds on a freely accessible massive collaborative knowledge base and data hub, demonstrating its usefulness via three demonstrator applications: a cooperative multiplayer VR serious game, simulating real disaster scenarios for the safest near-real experience; an interactive gamified mobile app with age-appropriate content and enhanced accessibility to people with specific functional needs for the widest possible reach; and an LMS system to effectively and comparably measure preparedness levels achieved by VR and/or mobile users on a unified scale. Players can take different roles to solve puzzle tasks in an immersive experience. Teamplay, collaboration and communication are keys to survival, strengthening the culture of mutual assistance and cooperation in danger. Player behaviour and gameplay logged in a privacy-preserving way helps collect data on in-game behaviour which serves assessment of preparedness but will also be shared with other synergic research in the same field. A large-scale virtual reality hackathon series will demonstrate its features. The open beta will be publicly available as a giveaway, inviting stakeholders via direct outreach. After closing beta, the game will be available in a non-profit freemium model where in-game purchases are replaced by in-game donations for relief organizations, with a small percentage kept for maintenance and further development.

The emergency medical care in the EU is a fragmented chain including population, emergency medical services, volunteers, hospitals and cooperation with fire services, police and authorities. It needs to prepare to respond to new threats and assist casualties after security incidents. In response to this challenge, NO-FEAR proposes to bring together a pan-European network of practitioners, decision and policy makers in the medical and security fields. They will collaborate to achieve a common understanding of needs, as well as - in collaboration with academia and industries – increase the EU innovation potential that could better fill the operational gaps and recommend areas for future innovations. NO-FEAR main objectives are to: - create a long-lasting community of practitioners, interacting with a network of suppliers and academia, - elaborate an innovation roadmap, with practical recommendations for uptake, - advise relevant Research and Innovation projects, - support market uptake of EU research results, - issue policy and regulatory recommendations enabling collective procurement, - indicate priorities for standardisation; - support quick wins and practical short term results, - implement a transactional dynamic portal providing fora, a catalogue, market place and flexibility to address new threats. The project will be conducted by a consortium of 18 partners, of which 11 and the coordinator are practitioners, under the advice of the EC Community of Users. It aggregates the various dimensions of the project (acute care, operations and training), supported by the already large networks. To disseminate and exploit the NO-FEAR recommendations, an ambitious strategy will be implemented, including workshops, demonstrations and communication events every 6 months. This will enable knowledge sharing, build a common understanding and promote innovation uptake by organising technology showcases and demonstrations in a real practitioner environment.

The Energy Efficiency Directive, in its art.8, requires Member States to develop programmes encouraging SMEs to undergo energy audits and implement the recommended energy-saving measures. However uptake of energy audits and implementation of energy conservation measures (ECM) among SMEs has been low to date. The barriers to uptake cited in the literature include lack of in-house expertise; lack of resource (time & money); perception that energy auditing is expensive; inability to act due to lack of control of services in the building they use; lack of willingness from landlords to act; inability to access finance due to the small nature of most projects. The SPEEDIER project will address these barriers by providing a self-financing outsourced energy management service to SMEs. By outsourcing the role of energy manager to SPEEDIER Experts, SMEs can access the expertise needed at the required time, leading to greater uptake of energy audits and implementation of energy efficiency measures. SPEEDIER will target groups of SMEs in 4 EU pilot regions: in Spain we will test a location based approach, engage with SMEs based at a single business park to demonstrate that advantages of clustering SMEs give them better access to the economies of large scale projects; in Ireland and Romania SMEs in the manufacturing and hospitality sectors respectively will be approached to test a sector based approach to service delivery; in Italy, a more general approach of accessing SMEs from any sector via ESCOs will be tested. The project is to be self-financing to remove any financial barriers to energy audit uptake and implementation of ECMs. The mechanism for making this work in practice follows an Energy Performance Contract model where the consultant delivering the support retains a share of the savings as payment for the duration of the contract. This ensures that the Service is also suitable for large enterprises. The project consists of 6 RTDs, 3 SMEs, 1 NGO from 5 Member States

The main aim of FAITH is to apply the latest Artificial Intelligence (AI) and Big Data analytics techniques to better model and predict disease/treatment trajectories of cancer patients, with the goal of improving their quality of life and aftercare. To protect privacy of the individual, but still gain insights that are beneficial to the broader population, FAITH will be applying the concept of federated machine learning, which makes it possible to build machine learning systems without direct access to personal treatment data that will be used for training in machine learning. Devices private to the patient will run their own personalised AI models, via the project’s ‘AI Angel’ application, while a global AI model aggregates the individual model learnings (rather than the traditional approach of a central repository of holding all private patient data). FAITH’s ‘AI Angel’ will remotely analyse depression markers, predicting negative trends in their disease trajectory, giving their healthcare providers advanced warnings to allow for timely intervention. These markers are treated under several distinct categories: Activity, Outlook, Sleep, and Appetite, in accordance with the 3M strategy for population health: Monitor–Measure–Manage. Central to the vision of the FAITH project is to measure population health deeply, it is necessary to monitor individuals on a continuous basis to cast a wide enough net over a user’s health data. A key strength of FAITH is the involvement of eminent cancer hospitals and specialists in the consortium to provide relevant applicable cancer care related use cases that can effectively leverage a big data framework using computational intelligence approaches and methodologies that can be used for long term cancer care health risk and symptom minimisation for patients. FAITH has trial sites in Madrid, Waterford, and Lisbon, with real end users to assess and validate the adoption and usage of the FAITH technologies and platform.

FITTER-EU (FITTER) aims to contribute to existing research on the origins, dynamics and determinants of inequalities and enable anticipatory governance to support a fair and inclusive twin transition in Europe. The project innovates by the formulation and development of an ecosystem (FITTER ecosystem) that pivotally includes a highly interactive and gamified Digital Platform powered by an Intelligent Predictive Decision Support System. Through a co-creation methodological approach, this ecosystem will enable policymakers to predict which social groups may be at risk of being adversely affected by twin transition policies under different scenarios, with the option to simulate the implementation of these policies to assess inequalities and social exclusion risks. The Digital Platform within the ecosystem will provide proposed mitigation measures and better practice guides that can be used to curve potential negative effects of policies on identified at-risk groups. The FITTER ecosystem also incorporates wider platform connectivity capability and better practice guides which, through a foresight engagement process, will help to meet the needs of the engaging FITTER Cluster Community Group of Stakeholders (CCGS). The CCGS includes key pan-European members such as policymakers, civil society organisations including trade unions, as well as business angels among other targets.