Climate change poses significant threats to human health and well-being, impacting not only the EU Boreal region but also Europe as a whole. The increasing frequency and severity of extreme events, like floods, wildfires, rising sea levels, and heatwaves have far-reaching consequences for local communities. The need to adapt to climate change's impacts and embrace transformative solutions has garnered recent political attention. Nevertheless, recent extreme incidents, such as the 2021 wildfires in the Boreal region and similar events in Europe, have underscored the imperative of systemic actions and revealed the disproportionate vulnerability of already marginalized populations. The AURORA project aims to enhance resilience against health risks stemming from climate change and contribute to the overarching Mission objectives. It seeks to achieve this by developing a suite of tools capable of: 1) Monitoring climate stressors, 2) Creating climate and epidemiological models 3) Generating forecasts via simulated scenarios 4) Identifying climate change risks and vulnerabilities in the Boreal region. These risks will be complemented by a reliable AI-driven technology that will 5) Issue early warnings and recommend adaptive measures and nature-based solutions. These components will form a robust Decision Support system providing specific recommendations. The AURORA consortium, with its vast experience in research projects, envisions active engagement with stakeholders throughout all project stages via Living Mission Labs. This engagement aims to foster behavioral change and showcase the project's solutions in 5 Demo cities (Riga, Tallinn, Vilnius, Tampere, Pori ) and 3 replicant cities (Klaipeda, Joniskis, Jurmala). The knowledge and insights generated by AURORA will be disseminated through clustering activities, ultimately empowering local policymakers to make evidence-based decisions, reassess strategies, and develop management plans for climate-resilient cities.

GreenFit is a collaborative project uniting research institutions, technology developers, agricultural practitioners, and field actors to tackle the barriers limiting farmers from adopting climate-smart practices. Through a combination of advanced technologies such as AI-powered decision support systems, IoT sensors, and XR-based training tools, GreenFit focuses on optimizing resource use, enhancing decision-making, and building resilience to climate change. The project also promotes value-chain partnerships and strengthens digital infrastructure, ensuring scalability and sustainability. Through the use of real-time tools, including the LLM-based AgriChatbot and a drone-in-a-box system for soil analysis and crop health monitoring, GreenFit empowers farmers with the practical, innovative solutions needed to transition toward sustainable practices. GreenFit focuses on capacity building and community-driven dissemination, communication, and exploitation, as through hands-on training, workshops, and stakeholder engagement, it empowers local communities to adopt and sustain climate-smart practices. The project’s capacity-building program and knowledge-sharing platforms ensure that farmers and rural stakeholders are actively involved in the development process. GreenFit's community-led approach enhances local ownership of solutions, driving sustained environmental and economic benefits.

ARMADILLO aims to equip Law Enforcement Authorities (LEAs) and more particularly, Police Authorities and Forensic Institutes, with a holistic, ground-breaking, easy-to-use, portable toolset that rapidly detects GHB concentrations in urine, saliva and beverages. To realize this, the project will focus on the design and development of in-situ GHB detection systems, integrating advanced optical spectroscopy and electrochemical techniques for precise GHB identification in the different matrices. Both optical and electrochemical detection techniques will be integrated to portable readers capable of quantitative GHB on-site determination. The optical spectroscopy techniques will explore surface-enhanced signal-based approaches (Raman and fluorescence) alongside paper strip methods, while electrochemical detection will combine a specialized fluidics module and NAD/NADH electrodes. In parallel, GHB-specific antibodies will be developed aiming to further enhance its detection selectivity and accuracy. The project will prioritize the enhanced collection and sharing of forensic evidence, emphasizing on forensics' data management and ensuring interoperability and harmonization across systems. By integrating data fusion mechanisms, it will provide reliable, safe, and court-proof forensic evidence, while also leveraging the potential of AI for refined Raman analysis. Concurrently, it will undertake a comprehensive risk assessment to bolster prevention strategies against drug-facilitated violence and assault, all while standardizing user interfaces and employing advanced visualization and reporting techniques. In order to avoid clinical trials and comply with the ethical considerations including the privacy and safety of any involved human subject, ARMADILLO will assess the accuracy, sensitivity and specificity of its sensing technologies using synthetic samples that simulate a wide range of GHB concentrations in urine and saliva samples.