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VULCAN.ears SIGNED

Volcano-seismic Unsupervised Labelling and ClAssificatioN Embedded in A Real-time Scenario

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 VULCAN.ears project word cloud

Explore the words cloud of the VULCAN.ears project. It provides you a very rough idea of what is the project "VULCAN.ears" about.

architecture    types    big    classify    assign    proper    observatories    class    technologies    feedback    framework    psa    events    recognise    vsr    nevertheless    awaited    prototypes    seismicity    variability    description    society    solution    classification    gathering    time    difficult    seismic    data    searching    area    applicability    technicians    classes    learning    casualties    forecasting    volcano    unsupervised    channels    supervised    detect    innovative    volcanology    population    parallel    crisis    online    specialised    efficient    massive    demand    models    manual    scenarios    avoiding    markov    mainly    recognising    tools    few    event    structured    software    automatic    hidden    recognition    vm    eruption    centre    maximise    nowadays    designed    precursory    statistical    risk    economy    human    monitor    collaborative    volcanic    volcanoes    interaction    facilities    describe    correctly    expert    obtain    machine    standard    monitoring    appear   

Project "VULCAN.ears" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITA DEGLI STUDI DI UDINE 

Organization address
address: VIA PALLADIO 8
city: UDINE
postcode: 33100
website: www.uniud.it

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Total cost 180˙277 €
 EC max contribution 180˙277 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2017
 Duration (year-month-day) from 2017-11-01   to  2019-10-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITA DEGLI STUDI DI UDINE IT (UDINE) coordinator 180˙277.00

Map

 Project 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.

 Publications

year authors and title journal last update
List of publications.
2018 Guillermo Cortés; Roberto Carniel; Philippe Lesage; Mará A. Mendoza; Javier Almendros; Carmen Benítez; Raúl Arámbula-Mendoza
presentations & abstracts of the CoV.2018 related to Volcano-Seismic Recognition (VSR) performed by the VULCAN.ears-researching team
published pages: , ISSN: , DOI: 10.5281/zenodo.3596121
Cities on Volcanoes 10, IAVCEI International Congress 1 2020-01-29
2019 Guillermo Cortés; Roberto Carniel; Philippe Lesage; M. Ángeles Mendoza; Ivo Della Lucia
\" EGU.2019: \"\"Volcano-Independent Seismic Recognition: detecting and classifying events of a given volcano using data from others\"\" \"
published pages: 11386, ISSN: , DOI: 10.5281/zenodo.3595998
EGU General Assembly Conference Abstracts 1 2020-01-29
2019 Guillermo Cortés, Roberto Carniel, M. Ángeles Mendoza, Philippe Lesage
Standardization of Noisy Volcanoseismic Waveforms as a Key Step toward Station‐Independent, Robust Automatic Recognition
published pages: 581-590, ISSN: 0895-0695, DOI: 10.1785/0220180334
Seismological Research Letters 90/2A 2020-01-29
2019 Guillermo Cortés Moreno, Roberto Carniel, Philippe Lesage, and María Ángeles Mendoza Pérez
\"geoStudio & liveVSR - software supporting \"\"VULCAN.ears\"\" project (MSCA - IF - 20126, No.[749249])\"
published pages: , ISSN: , DOI: 10.5281/zenodo.3594080
geoStudio & liveVSR 2020-01-29
2019 Guillermo Cortés Moreno; Roberto Carniel; María Ángeles Mendoza Pérez; Philippe Lesage
\" preprint of the article \"\"Standardization of noisy volcano-seismic waveforms as a key step towards station-independent, robust automatic recognition\"\" published in Seismological Research Letters-2019 \"
published pages: , ISSN: , DOI: 10.5281/zenodo.3594863
1 2020-01-29
2019 Guillermo Cortés Moreno Roberto Carniel Philippe Lesage María Ángeles Mendoza Pérez
\"pyVERSO - software for building and evaluating Volcano-Seismic Recognition (VSR) system, part of \"\"VULCAN.ears\"\" project - framework\"
published pages: , ISSN: , DOI: 10.5281/zenodo.3594897
liveVSR 2020-01-29

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