Objective
Volcanic eruptions have a high social and economic impact on a global scale, and they can be responsible for severe consequences into climate changes and on population’s life, determining severe damages to buildings, crops, telecommunications and air traffics. The security and protection of populations in sites exposed to risk requires the improvement of our ability to forecast volcanic eruptions and the development of better alert protocols, in order to take preventive measures and minimize their effects in both human and economic terms.
Volcano monitoring is mainly based on the analysis of seismic signals, in order to found precursory events which appear before an eruption. Due to the big amount of seismic data nowadays acquired by the volcanic observatory, in a volcano crisis it became difficult the manual supervised detection and classification carried out by expert technicians. So an automatic volcano-seismic signal processing is crucial to quickly detect and analyse the precursory seismicity and to correctly assess the population risk.
This project is conceived to advance beyond-the-state-of-the-art providing tools for a better and more accurate automatic volcano-seismic signals detection and classification to obtain Early Warning Decision Making algorithms. This is a highly interdisciplinary project, where the Signal Processing, Machine Learning, Big Data, and Knowledge Management are combined with the Volcanic Seismology science. In order to carry out this project, seismic records from some volcanoes (in particular, Etna, Colima, Montserrat volcanoes) are available.
The proposed strategy includes a new philosophy in database creation and new and innovative signal processing techniques, and will improve our ability to forecast volcanic eruptions. The proposed methodologies are new in the field of volcano-seismology, but researchers involved in the project have already applied them successfully in different contexts.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences data science big data
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering signal processing
- natural sciences earth and related environmental sciences geology volcanology
- natural sciences earth and related environmental sciences geology seismology
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF-EF-ST - Standard EF
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2017
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
18071 GRANADA
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.