Observational analysis highlights system reliability challenges in Inner Mongolia's earthquake early warning, suggesting AI integration for improved predictions.
The earthquake early warning system (EEWS) is instrumental in significantly reducing disaster losses, with such systems already established in numerous countries worldwide. This paper delves into the developmental history of EEWS, tracing its evolution from basic seismic detection to advanced, real - time alert mechanisms. It provides an overview of China's national seismic intensity rapid warning and early warning project, underscoring its importance in enhancing national disaster resilience. Focusing on the Inner Mongolia project, the paper details the construction of its data processing system. The author primarily introduces the deployment of the hardware platform and software system at the Inner Mongolia early warning data center, ensuring efficient data handling and alert generation. However, the construction of the early warning platform in Inner Mongolia has encountered challenges, like ensuring system reliability in extreme weather and optimizing data transmission speeds. Looking forward, there are promising prospects, including the integration of AI for more precise predictions. By summarizing various EEWS models, this study offers valuable references for optimizing the design of future early warning structures.
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Zhai et al. (2025) studied this question.
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