• DOI:10.1609/AAAI.V34I01.5376
Corpus ID: 208877225

A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning

@inproceedings{Fauvel2020ADM,
  title={A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning},
  author={Kevin Fauvel and Daniel Balouek-Thomert and D. Melgar and P. Silva and Anthony Simonet and G. Antoniu and Alexandru Costan and V{\'e}ronique Masson and M. Parashar and I. Rodero and A. Termier},
  booktitle={AAAI},
  year={2020}
}

• Kevin Fauvel, Daniel Balouek-Thomert, +8 authors A. Termier
• Published in AAAI 2020
• Computer Science

Our research aims to improve the accuracy of Earthquake Early Warning (EEW) systems by means of machine learning. EEW systems are designed to detect and characterize medium and large earthquakes before their damaging effects reach a certain location. Traditional EEW methods based on seismometers fail to accurately identify large earthquakes due to their sensitivity to the ground motion velocity. The recently introduced high-precision GPS stations, on the other hand, are ineffective to identify… Expand

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