Objective Volcanic activity has a big impact on the economy and society. Nowadays, volcano monitoring (VM) is mainly based on the analysis of the seismicity, specifically on some type of precursory events (or classes) which appear before an eruption. The variability of the volcano-seismic classes and the increase of the seismicity in a volcano crisis difficult the manual supervised classification carried out by expert technicians to detect an event and assign it to its proper class. Most of the VM observatories demand an automatic Volcano Seismic Recognition (VSR) to quickly detect and analyse the precursory seismicity and to correctly assess the population risk, avoiding human casualties. Nevertheless, only a few VM facilities have their own VSR prototypes designed to monitor their volcanoes.The aim of this proposal is to build an automatic VSR system focused on recognising events in unsupervised scenarios, robust enough to be integrated into the VM centre of any volcano, allowing online risk assessment by real-time seismicity analysis. It will be based on state-of-the-art VSR technologies: a) class description by statistical means (structured Hidden Markov Models) and b) Parallel System Architecture (PSA-VSR) composed of specialised recognition channels, each designed to detect and classify events of a given type. To accomplish this goal, two objectives have to be achieved:1. To build models robust enough, which requires gathering massive data from different types of volcanoes and searching the most efficient way to describe each class.2. To maximise the system applicability: the system will be integrated into several VM scenarios and eruption forecasting tools to obtain useful feedback information.The interaction between machine learning and volcanology will be the key to build this innovative, long-awaited, standard solution in the VM area: a collaborative framework software able to recognise events from any volcano in real-time. Fields of science natural sciencescomputer and information sciencessoftwarenatural sciencescomputer and information sciencesdatabasesnatural sciencesearth and related environmental sciencesgeologyvolcanologysocial sciencessociologygovernancecrisis managementnatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2016 - Individual Fellowships Call for proposal H2020-MSCA-IF-2016 See other projects for this call Funding Scheme MSCA-IF-EF-ST - Standard EF Coordinator UNIVERSITA DEGLI STUDI DI UDINE Net EU contribution € 180 277,20 Address VIA PALLADIO 8 33100 Udine Italy See on map Region Nord-Est Friuli-Venezia Giulia Udine Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 180 277,20