NIGHTINGALE will develop, integrate, test, deploy, demonstrate and validate a Novel Integrated Toolkit for Emergency Medical Response (NIT-MR), at the service of emergency medical services and non-medical civil protection agencies (fire brigades, police and search and rescue personnel, but also volunteers and citizens) which ensures an upgrade to Pre-hospital life support and Triage. This is achieved by delivering enhanced Operational Capacity to respond to mass casualty incidents complemented by the inclusion of commonly agreed methods and guidelines.
This will comprise a multitude of tools, services, and applications required for (i) upgrading evaluation of injured and affected population and handle casualties (Triage); (ii) optimizing pre-hospital life support and damage control through AI-based tracking, tracing, routing, and utilization enhancements of assets, resources, and capacities as well as enabling continuous monitoring and correlation of vital signs and actions, and (iii) allowing shared response across emergency medical services, non-medical civil protection personnel, volunteers, and citizens.
The NIT-MR will be composed by:
TREE will participate in the component definition/application sheet, and the deployment specifics, development & prototyping of the novel Triage System for the enhancement of Triage enablers by applying its expertise in Artificial Intelligence and Machine Learning. Furthermore, TREE will contribute to the Multi-agency Incident Management and Command and Control system. In the context of technological solution provider TREE will participate in the definition of Technical Requirements, Specifications and on the Toolkit Architecture and in the Toolkit Integration Testing and Validation and User familiarisation with the developed tools. Finally, TREE activities will also contribute to the Dissemination, Communication, Exploitation, and Standardisation & IPR and Data management of project tools and outputs.
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101021957
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