SOURCE-LINKED INTELLIGENCE

Multi-messenger AI-enhanced earthquake early warning

CORDIS · observation · Publication date unknown

mage. Therefore, making EWS faster and more accurate is crucial to mitigate the hazard associated with these catastrophic events. In the framework of the ERC StG project EARLI, we developed prototype Artificial Intelligence (AI) algorithms providing faster and more accurate theoretical estimates of the location and magnitude of large earthquakes than state-of-the-art EWS. We propose to implement these AI algorithms in the operational EWS of Peru, with the objective of transforming the theoretical developments of the ERC StG EARLI (Licciardi et al., Nature, 2022; Lara et al., JGR, 2023) into concrete operational improvements in EWS performance. The algorithms we developed use short records of traditional seismic waves and light-speed gravity signals. We will complement these two algorithms by a third AI-based one using GNSS, allowing the implemented EWS to leverage complementary real-time data, and making it the first operational multi-messenger AI-based EWS. The system will rapidly benefit millions of people at high risk from earthquakes in Peru, and serve as a Proof-of-Concept for e

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recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR