Project Summary

AIMS deals with landslide monitoring & prevention with the main objective of developing a tailored methodology for prediction & early forecasting usable in different ADRION areas. The proposal moves from the challenges posed by the high hydrological vulnerability of the Adriatic-Ionian to derive new predictive, AI-based models investigating connections of climate change-related events with augmented landslide hazard, with the idea of providing useful instruments for risk mitigation. To do so, AIMS develops the following outputs -1 Joint Strategy (O1.1) for a shared ADRION approach on landslides monitoring and early prediction -1 transnational pilot testing aimed to collect and aggregate data from 6 designated sites of geological interest -1 AI-based landslides monitoring and early prediction System O3.1  applicable to different morphological contexts of the macro-region. AIMS activities are developed across a 3-phase approach of (1) Investigation of common challenges & suitable technologies for effective predictive models; (2) Development, testing and fine-tuning of a joint landslide early prediction mechanism for the whole Adriatic-Ionian; (3) Capacity building & knowledge transfer for the uptake of the developed monitoring and early prediction system. To do so, the project approach is rooted in deep transnationality both in terms of ensuring a proper combination of competencies among implementing actors, and for the sake of producing a versatile predictive model on landslide risks applicable to numerous territories in the macro-region. Key target beneficiaries of the developed outputs are in fact public authorities at local/regional/national level, infrastructures developers and urban planners in their territorial management functions. AIMS introduces strong innovation as it devises an AI mechanism for the analysis of big data on landslide forecasting derived from a plurality of disciplines (climatology, geology, geotechnical engineering) for a wider cross-sectoral approach to the topic.