The MMinE-SwEEPER project will advance knowledge, capability and capacity in Europe for dealing with marine munition in the non-military aspect of UXO-clearance. 21 partners from 7 EU and 2 associated countries bring experience and capabilities from the civil science community (9), military research (3), coast/border guards or EOD-services (4) as well as industry (3) and intergovernmental organizations (2). Jointly they will work in 8 technical work packages to a) advance automated munition detection, identification and data analyzing technologies and software, b) environmental monitoring of chemical contaminants, c) predictions of UXO-burial, contaminants spread and the state-of-corrosion, and will d) enable secure exchange of sensitive data (64% of person months). Three additional WPs will compile existing knowledge, learn about the legal responsibilities and technical approaches, assess remediation and mitigation measures and create training material for building European capacity (14% PM). Two WPs will engage in an intense stakeholder dialog and dissemination/outreach activities by utilizing capacities already existing at HELCOM and JPIO (14% PM). Outcomes with respect to specific technical advancements will include a) AI-supported detection of munition in hydroacoustic spatial mapping data (MBES, SSS; SAS), b) detection of buried munition objects (magnetic, SBP, LF-SAS), c) AI-supported object identification in optical and acoustic cameras and d) implementing trained AI-models into Smart-AUVs and -USVs for adaptive and cooperative mission execution. All this will utilize secure data exchange possibilities through a demonstrator data platform that will be refined during the project. Industry partners see a great benefit in developing technologies that later can be advanced further to become commercial products. At the end of the project most TRLs will be at 5 to 6, meaning they have been applied under real conditions and proved their applicability.

Travelling Ionospheric Disturbances (TIDs) constitute a specific type of space weather disturbance affecting the performance of critical space and ground infrastructure by disrupting operations and communications in multiple sectors. T-FORS aims at providing new models able to interpret a broad range of observations of the solar corona, the interplanetary medium, the magnetosphere, the ionosphere and the atmosphere, and to issue forecasts and warnings for TIDs several hours ahead. Machine Learning techniques are used to train the models based on existing databases developed in the frames of past Horizon 2020 projects, to estimate the occurrence probability of medium scale TIDs and to forecast the occurrence and propagation of large scale TIDs. Prototype services are developed based on specifications from the users' community and following harmonized standards and quality control similar to the best practices of meteorological services. On ground demonstration tests are organised, by aerospace and civil protection agencies, to validate the performance of the T-FORS prototype services. A comprehensive architectural concept is proposed, including the densification of ground instrument networks, and new space missions, and possible future adjustments in order to develop a real-time operational service fully compliant and complementary to the ESA Space Weather services.

The increasing complexity of security challenges combined with the accumulation of significant amounts of digital data calls for better and more widespread use of Artificial Intelligence (AI) capabilities for law enforcement agencies (LEAs). AI can provide benefits to LEAs at all levels given the right understanding, tools, data and protection while increased awareness of criminal misuse is providing an immediate and concerning threat that must be tackled rapidly. Furthermore, a community that brings together LEAs, researchers, industry, security practitioners and other actors in the security ecosystem under a coordinated and strategic effort is essential for the realisation of these efforts into operational practices. STARLIGHT presents an inclusive and sustainable vision for increasing the awareness, capability, adoption and long-term impact of AI in Europe for LEAs. Five strategic goals underpin STARLIGHT’s approach: (1) Improve the widespread UNDERSTANDing of AI across LEAs to reinforce their investigative and cybersecurity operations and the need to uphold legal, ethical and societal values; (2) Provide opportunities to LEAs to EXPLOIT AI tools and solutions in their operational work that are trustworthy, transparent and human-centric; (3) Ensure that LEAs can PROTECT their own AI systems through privacy- and security-by-design approaches, better cybersecurity tools and knowledge; (4) Raise LEAs’ expertise and capacity to COMBAT the misuse of AI-supported crime and terrorism; and (5) BOOST AI for LEAs in Europe through high-quality datasets, an interoperable and standardised framework for long term sustainability of solutions, and the creation of an AI hub for LEAs that supports a strong AI security industry and enhances the EU’s strategic autonomy in AI. STARLIGHT will ensure European LEAs lead the way in AI innovation, autonomy and resilience, addressing the challenges of now and the future, prioritising the safety and security of Europe for all.

Travelling Ionospheric Disturbances (TIDs) constitute a threat for operational systems for which the ionosphere is an essential part (i.e., radio systems) or for which the ionosphere is fundamentally a nuisance (i.e. GNSS based systems and applications). The overarching objective of TechTIDE is to design and test new viable TID impact mitigation strategies for the technologies affected by the TIDs and in close collaboration with operators of these technologies, to demonstrate the added value of the proposed mitigation techniques which are based on TechTIDE products. To achieve this main goal, it is necessary to address the following specific objectives: i. Improve understanding regarding the physical processes resulting in the formation of TIDs, and consequently to identify the drivers in the interplanetary medium, the magnetosphere and the atmosphere; ii. Define the impact of the TIDs on the space based navigation systems (mainly EGNOS services and N-RTK) and on ground-based HF communication and geolocation systems; iii. Develop improved methodologies, based on consortium partners’ algorithms, suitable to support for the first time the direct,real-time identification and tracking of TIDs over wide world regions; iv. Establish an operational system to issue warnings of the occurrence of TIDs over the region extending from Europe to South Africa, to estimate the parameters that specify the TID characteristics and the inferred perturbation, and provide all additional geophysical information to the users to help them assess the risks and to develop mitigation techniques, tailored to their applications; v. Work systematically with potential users to assess the functionality, reliability and efficiency of the TechTIDE services paving the way to its systematic exploitation from users and to its sustainable operation.