Objetivo
SafeClouds is a research project supported by EASA and powered by a full spectrum of aviation stakeholders (Airlines, Airports, ANSPs, Eurocontrol, Research Entities, Safety Agencies) that develops cutting-edge technologies for aviation safety assurance in a cost-effective manner. SafeClouds proposes a data-driven approach to achieve a deeper understanding of the dynamics of the system, where risks are pro-actively identified and mitigated in a continuous effort to enhance the already excellent European aviation safety records.
SafeClouds develops an innovative aviation safety data analysis approach. Currently each stakeholder owns different isolated datasets and data-sharing paradigms are rare. However, the combination of those datasets is critical in discovering unknown safety hazards and in understanding and defining a performance-based system safety concept. The new data-driven paradigm, capable of extracting safety intelligence in a fast, connected and inexpensive way requires the collaboration of aviation and IT entities sharing their raw datasets, tools, techniques and information.
SafeClouds high level objectives are:
- To define a user-requirement driven approach for data mining in aviation safety, covering several current safety challenges within airlines and runway operations.
- To develop novel data structures and safety intelligence representation. Given the complexity of the datasets, SafeClouds aims to solve their current challenges in data handling and knowledge discovery.
- To develop the proof of concept and validate in a laboratory the safety data analysis paradigms, at different levels: historical analysis, predictive analytics, automatic safety data monitoring and unknown hazards identification.
- To assemble a group of entities that encompasses the entire data-cycle for a unified, achievable vision for the future of safety analytics in Europe, including: users, data providers, data infrastructure researchers, operators and data scientists.
Ámbito científico
- natural sciencescomputer and information sciencescomputer securitydata protection
- natural sciencescomputer and information sciencesdata sciencedata mining
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- social sciencessocial geographytransporttransport planningair traffic management
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-MG-2016-SingleStage-INEA
Régimen de financiación
RIA - Research and Innovation actionCoordinador
28007 Madrid
España
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Participantes (14)
80686 Munchen
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01360 SAINT GENIS POUILLY
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Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.
28022 Madrid
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602 27 Norrkoping
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1366 LYSAKER
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34912 Istanbul
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28027 Madrid
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07620 LLUCMAJOR
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08820 Prat De Llobregat El Barcelona
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2628 CN Delft
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80333 Muenchen
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581 83 Linkoping
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1130 Bruxelles / Brussel
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28046 Madrid
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