By implementing PREVENT, we aimed to modernise higher-education engineering and ICT curricula so that students and educators can apply deep technologies to disaster prevention and climate-risk mitigation. We sought to: (1) equip HE educators with a practical pedagogical framework and updated content linking IoT, remote sensing, robotics and AI/ML to early warning, monitoring and decision support; (2) develop and pilot hands-on training materials, including a Virtual Learning Lab with programming micro-challenges; (3) build sustained collaboration with local communities and experts through Open Living Labs, round tables and hackathons, enabling students to co-create feasible solutions; and (4) improve employability and inclusion, including increased female participation in deep-tech activities. Overall, the objective was to bridge classroom coding with measurable societal impact in resilience and disaster-risk reduction.
Across Europe, climate change is amplifying floods, wildfires, and other extreme events, while local authorities often lack timely data and engineering capacity to anticipate risks and coordinate interventions. At the same time, higher-education programmes in engineering and computer science were not consistently equipping students with the deep-technology toolkit (IoT, remote sensing, robotics, and AI/ML) needed for early-warning, monitoring, and decision support. Skills gaps in programming and problem-solving, together with labour-market shortages in deep-tech profiles, created an apparent demand for modernised curricula and more engaging, hands-on pedagogies. PREVENT was proposed to meet these needs by empowering educators with structured guidance and practical, community-connected learning formats, and by motivating diverse learners (including more women) through real-world disaster challenges. This reduced the gap between abstract coding courses and visible societal impact.