Project description
AI-based solutions for disaster prediction
Advancements in digital technology are testing the capabilities of Law Enforcement Agencies (LEAs) and First Responders across all operational phases, including disaster prediction and recovery. The EU-funded LEAD-PRo project aims to equip these agencies and responders with advanced AI-based tools and technologies to enhance their effectiveness. The project focuses on using mature technological solutions, fostering collaboration among small and medium-sized enterprises, involving end-users in the validation process, and promoting cooperation between technology companies and research organisations. It aims to develop a platform for real-time disaster prediction, optimise data processing for disaster prevention, and propose solutions for post-crisis and disaster recovery, including robotics for hazardous areas and UAV/UAS assessment of areas of interest.
Objective
LEAD-PRO focuses on mature technological solutions, achieving a Technology Readiness Level (TRL) 8, fostering collaboration among SMEs from different Member States, fostering collaboration among SMEs from different Member States, involving LEA/First Responder end-users in the validation process, and promoting collaboration between small technology companies and research organisations. With a consortium comprising three SMEs from Spain, Lithuania, Ireland, as well as three partner LEAs serving as end users from Spain, Lithuania, Latvia, complemented by dynamic NGO, the project spans 24 months.
The project's primary aim is to equip LEAs and first responders with advanced AI-based tools and technologies that enhance their capabilities across all operational phases and contribute to digital societal resilience.
The LEAD-PRO solution encompasses three advances:
*Real-Time Information Collection and Analysis for Disaster Prediction: The project develops an innovative platform for gathering, processing, and sharing real-time data and information. This includes CCTV, cameras, drones, and anomaly detection systems. The platform integrates state-of-the-art technologies such as artificial intelligence, cloud computing, and big data to create a robust warning system and enhance geolocation capabilities for both the public and rescue teams.
*Optimisation of Disaster Prevention: LEAD-PRO exploits monitoring data, satellite/remote sensing information, and artificial intelligence to conduct high-level assessments. This involves optimising the processing of data from satellite and aerial imagery, sensor networks, and weather information.
*Robust Response for Better Recovery: The project focuses on innovative solutions for post-crisis and disaster recovery, including robotics for tasks in hazardous areas. Utilizing UAV/UAS for assessing areas of interest, the project addresses energy and data network rehabilitation, autonomous systems, and decentralised operation.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- social sciencespolitical sciencespolitical policiescivil societynongovernmental organizations
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsautonomous robotsdrones
- social scienceslaw
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HORIZON-IA - HORIZON Innovation ActionsCoordinator
20009 San Sebastian
Spain
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.