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EXPEDITE

Financiado

EXPloring opportunitiEs for developing a risk and resilience climate service bas...

EXPloring opportunitiEs for developing a risk and resilience climate service baseD on bIg daTa and machinE learning Despite the urgent need for adopting multi-hazard risk approaches and for the implementation of resilience-enhancing measures in the EU and at the global scale, several challenges for effective implementation of risk assessment an... ver más

31/08/2025

UNIVE

189K€

Presupuesto del proyecto: 189K€

Líder del proyecto

UNIVERSITA CA FOSCARI VENEZIA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 4 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-07-19

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

HORIZON-MSCA-2021-PF-01-01: MSCA Postdoctoral Fellowships 2021

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Cerrada hace 3 años

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4 Participantes

UNIVE

188.59K€ | Lider

GECOSISTEMA SRL

N.D. | Participante

UNIGE

N.D. | Participante

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Duración del proyecto: 37 meses Fecha Inicio: 2022-07-19
Fecha Fin: 2025-08-31

Líder del proyecto

UNIVERSITA CA FOSCARI VENEZIA

TRL 4-5

Presupuesto del proyecto 189K€

Descripción del proyecto Despite the urgent need for adopting multi-hazard risk approaches and for the implementation of resilience-enhancing measures in the EU and at the global scale, several challenges for effective implementation of risk assessment and adaptation responses remain. In particular, the assessment of climate hazards, risk and resilience is often based on static models which lose the appreciation of the temporal and spatial dynamics and complex feedback responses within the system. As a consequence, the information provided often fails to inform decision-makers and other end-users with the correct data to be actioned through timely responses to emerging risks. Barriers to development and implementation of novel approaches and models include the availability, cost and reliability of input datasets; the computational times and costs; the lack of consideration of the combined effect of multiple hazards; the spatial and temporal changes in the exposure of assets and services; and the complex adaptive responses of government, society and the environment to emerging risks. EXPEDITE aims at exploring new pathways to reduce and remove these barriers by exploring, testing and deploying machine learning and data science techniques and by developing and testing a climate service prototype, tailored to end-users. These may include institutional clients (such as Regions) the private sector or individual consumers. The research project, which will last 24 months, will be mainly conducted at CMCC@Ca’Foscari in Venice (Italy) under the supervision of Prof. Andrea Critto, with targeted secondments for advanced training in machine learning and data science at MALGA, University of Genoa and for climate service design and prototyping at GECOsistema srl, a specialised R&D consulting lab. A targeted dissemination and communication plan will allow EXPEDITE to share the research activities, outcomes and outputs with researchers, policymakers, the private sector and the general public.

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