Enhancing decision support system for disaster crises: leveraging emerging technologies for improved civil preparedness and crisis management
eu HORIZON-CL3-2027-01-DRS-03 · Horizon Europe (HORIZON)
| Status | forthcoming |
|---|---|
| Opens | 05 May 2027 |
| Deadline | 04 Nov 2027 — 418 days |
| Action | HORIZON Innovation Actions |
| Official page | https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunit… |
| Fetched | 2026-09-12 04:00:03+00:00 |
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Expected Outcome: Project results are expected to contribute to some or all of the following expected outcomes: Development of decision support systems for disaster crises, utilizing near real-time data from the ground to enhance situational awareness and response; Creation of systems designed to bolster civil preparedness, that enhance operational efficiency and response times, ensuring timely and effective management of various disaster scenarios including from early warning to early action Integration of advanced data analysis and decision-making tools to support authorities and first responders in disaster situations. Scope: This topic focuses on enhancing existing decision support systems for disaster crises by integrating emerging technologies to improve civil preparedness and crisis management. The objective is to advance the capabilities of existing systems, making them more reliable, adaptable, and efficient through the incorporation of trustworthy AI technologies that ensure transparency, accountability, and ethical decision-making processes. Projects should aim to enable quicker and more informed responses during disaster scenarios. Proposals should focus on creating advanced systems designed to strengthen civil preparedness, helping authorities and responders manage various disaster situations in a timely and effective manner. These systems should leverage cutting-edge AI-driven tools to process large volumes of data, providing actionable insights that improve decision-making during critical moments, such as from early warning to early action. Emphasis should be placed on integrating advanced data analysis and predictive modelling to anticipate disaster developments and guide interventions, while ensuring that the systems are transparent, explainable, and built on principles of trustworthiness, inclusive and gender sensitive and ethical AI use and on secure AI deployments. Projects should conduct a stakeholder or market analysis and a roadmap or plan for uptake of the developed methodologies, findings, and technologies to the industry, the research and innovation community, and/or the relevant authorities. Additionally, test centres should play a key role in this research by increasing their capacity to trial and validate emerging technologies, supporting more effective civil preparedness and crisis response capabilities. The expected outcome is to create systems that not only enhance operational efficiency and response times but also foster better collaboration among stakeholders, including local authorities, emergency services, and other re…
What consortia for this call have looked like
2 projects
have been funded under this line
(HORIZON-CL3-DRS-03) in Horizon Europe and H2020. This is what they
were made of — not a recommendation, just what the Commission signed.
range 14–17
12 seen across all of them
across those projects
The mix of organisations
Who coordinated them
Coordinating an EU project is a demanding, specific job. These organisations have done it on this topic line before.
This is the shape, not the consortium. It says how many partners these projects had and what kinds of organisation were in them. It does not know whether your idea needs the same mix, who is available, who is already committed elsewhere, or how the work and the budget should be divided. Those are judgement calls on a specific proposal, and no amount of public data answers them.
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