Earthquake hazard prediction method and system in mountainous areas based on drones and deep learning

CN119291757BActive Publication Date: 2025-03-28SICHUAN PROVINCIAL ARCHITECTURAL DESIGN & RES INST
-1 Cites -1 Cited by

Patent Information

Application Number
CN202411844087.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-12-15
Publication Date
2025-03-28
Estimated Expiration
2044-12-15

AI Technical Summary

Technical Problem

In mountainous regions, seismic waves can lead to amplification effects causing increased seismic activity, resulting in rock fractures and landslides, making it difficult to predict and prevent secondary disasters like landslides and slope collapses.

Method used

A method combining unmanned aerial vehicles (UAVs) and deep learning to collect and analyze data, constructing 3D terrain models, predicting seismic wave amplification effects, and classifying seismic hazard levels by extracting geologic and terrain information to create detailed hazard maps.

Benefits of technology

This approach enables real-time, accurate prediction of seismic hazards, providing effective support for disaster prevention and emergency response by reducing the impact of seismic events in mountainous areas.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN119291757B_ABST
    Figure CN119291757B_ABST
Patent Text Reader

Abstract

The present application relates to the technical field of disaster prevention and reduction, and discloses a method and system for predicting earthquake hazards in mountainous areas based on drones and deep learning, wherein drones are used to collect images and record data in the mountainous areas to be predicted, image data of the mountainous areas to be predicted is obtained, and a three-dimensional terrain model to be measured is constructed based on the image data; terrain information of the mountainous areas to be predicted is extracted from the three-dimensional terrain model to be measured, geological information of the mountainous areas to be predicted is collected, and fundamental frequency prediction is performed on the mountainous areas to be predicted to obtain fundamental frequency information of the mountainous areas; the seismic amplification effect of the mountainous areas to be predicted is predicted based on the fundamental frequency information, geological information and terrain information of the mountainous areas, and the envelope value of the seismic amplification coefficient of each characteristic point in the mountainous areas to be predicted under the action of seismic waves is obtained, and the seismic hazard level classification is performed, and a distribution map of earthquake disaster hazards in the mountainous areas to be predicted is drawn. The present invention improves the problem of difficulty in discovering earthquake disaster hazards in mountainous areas before an earthquake, and provides a more effective reference for the prevention and control of earthquake disasters in mountainous areas.
Need to check novelty before this filing date? Find Prior Art