Horizon Europe is the European Union (EU) funding programme for the period 2021 – 2027, which targets the sectors of research and innovation. The programme’s budget is around € 95.5 billion, of which € 5.4 billion is from NextGenerationEU to stimulate recovery and strengthen the EU’s resilience in the future, and € 4.5 billion is additional aid.
The use of artificial intelligence (AI) and machine-learning (ML) tools is increasingly at the core of first responder’s decision-making processes, including situational awareness, analysis and planning. Besides the needs to develop AI and ML tools, ground technologies such as miniaturised sensors that can operate autonomously for a long period in harsh environments and are fast and easy to deploy are needed for threat detection (such as chemical, biological or radiological substances) and/or identification of victims and possible locations for intervention. In addition, responders need to exchange information (language, data, video, etc.) in a reliable, secure, and universal way, while emergency communications throughout the European Union also need to be strengthened. In many instances, interoperability of tools, technologies and communication channels is still an open issue, requiring standard operating procedures, specific education, training and exercises of responders.
The European Commission is developing and implementing an EU Preparedness Union Strategy following whole-of-government and whole-of-society approaches. The proposals’ outcomes should especially work towards supporting the Strategy and follow the recommendations of the Directorate-General for European Civil Protection and Humanitarian Aid Operations (DG ECHO) to ensure a successful uptake to the end users. Under the open topic, proposals are welcome to testing / validate tools, technologies and data used in cross-border prevention, preparedness and responses to climate / geological / accidental fire disasters and chemical, biological or radiological emergency threats (including medical countermeasures) by different practitioner’s sectors in view of demonstrating their interoperability in real-case situations, with focus on the use of AI and ML tools, miniaturized sensors for threat detection and victim identification, and communication (including cross-border emergency communications).
Proposals are expected to address one of the following options focused on testing / validation of tools and technologies, and demonstration of their interoperability:
Option a: Use of artificial intelligence (AI) / machine learning (ML) tools to support first responder’s analysis, planning and decision-making;
Option b: Miniaturized sensors for threat detection and victim identification;
Option c: Information exchange / Communication among first responders in a reliable, secure and universal way, and cross-border emergency communications;
Option d: Alert system to detect CBRN threats, integrating different systems at national, regional and European levels.
Adapted to the nature, scope and type of proposed projects, proposals should also convincingly explain how they will plan and/or carry out demonstration, testing or validation of developed tools and solutions. Furthermore, proposals should outline the plans to develop possible future uptake and upscaling at national and EU level for possible next steps once the project is finalised. Proposals should also consider, build on if appropriate and not duplicate previous research, including but not limited to research by other Framework Programmes’ projects. Coordination among the successful proposals from this topic should be envisaged in order to avoid duplication and to exploit complementarities as well as opportunities for increased impact.
Proposals funded under this topic are expected to engage beyond the project consortium with disaster management authorities, Industry/SMEs and Standardisation Organisations during the lifetime of the project, including validating the outcomes, with the aim of facilitating future uptake of innovations for the Disaster Risk Reduction community.
To ensure the active involvement of and timely feedback from relevant practitioners, i.e., First Responders with expertise in the different types of natural or human-made threats, proposals should plan a mid-term deliverable consisting in the assessment, performed by the practitioners involved in the project, of the project’s mid-term outcomes.
70%
Expected EU contribution per project: €4.50 million.
Beneficiaries must provide financial support to third parties in the form of grants. The maximum amount to be granted to each third party is €100.000 to support the expected outcomes of the topic and effective collaboration and/or coordination with relevant First Responders covering different disciplines and sectors of intervention, including testing and validation activities within the projects, and/or SMEs from EU Member States or Associated Countries.
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects.
The following exceptions apply: subject to restrictions for the protection of European communication networks.
Due to the scope of this topic, legal entities established in LAC (Latin America/African/Caribbean) as well as Central Asian Countries are exceptionally eligible for Union funding.
The following additional eligibility conditions apply: this topic requires the active involvement, as beneficiaries, of at least 2 First responders or disaster management authorities and 2 SMEs from at least 3 different EU Member States or Associated Countries. For these participants, applicants must fill in the table “Information about security practitioners” in the application form with all the requested information, following the template provided in the submission IT tool.
If projects use satellite-based earth observation, positioning, navigation and/or related timing data and services, beneficiaries must make use of Copernicus and/or Galileo/EGNOS (other data and services may additionally be used).
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