The European Defense Fund (EDF) research project Prediction and Response of Effectors on Critical Infrastructure and Structural Environments (PRECISE) has started, bringing together a European consortium to develop advanced technologies for automated structural modelling of infrastructures and effect prediction in predominantly built-up environments.
“Coordinated by GMV, PRECISE is a four-year research action involving nine partners and two affiliated entities from five EU Member States: Belgium, France, Greece, Italy and Spain,” said GMV in a press release. “COTESA, FlySight, GMV, IKH, Indra, Indra Space, MEWS Partners, MEWS Labs and XenomatiX, together with the Royal Military Academy of Belgium and the Barcelona Supercomputing Centre, will work together to study the challenge, develop and integrate knowledge, and design the PRECISE toolset.
“GMV will act as the project’s integrator and coordinator and will lead the Systems Integration work package and the demonstration of the PRECISE solution. In addition, GMV will contribute to other work packages by leveraging the expertise gained in previous projects, such as the development of a Digital Twin for the FRONTEX agency and the development of effect analysis (weaponeering) applications for the Spanish Air and Space Force.”
The project addresses a growing operational need to better assess critical infrastructure and urban terrain in both defensive and offensive military use cases, as well as in civilian and dual-use contexts.
PRECISE will develop a European toolbox combining multi-source data collection, AI-based structural modelling, and hybrid AI and physics-based effect prediction models. By exploiting satellite imagery, aerial and ground collected data, from EO, SAR, LiDAR and other sensors, the project will enable the automated generation of detailed 3D structural models and the simulation of interactions between those structures and different physical effectors. This capability will support more informed decision-making, helping to improve optimized operational planning while reducing uncertainty and potential collateral effects, says the consortium.
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