Self-Contained Earthquake Early Warning System Based on Characteristic Period Computed in the Frequency Domain
This study presents the design, implementation, and experimental validation of a self-contained earthquake early warning system (EEWS) based on real-time frequency-domain analysis of ground motion. The proposed system integrates a low-noise triaxial micro-electro-mechanical system (MEMS) accelerometer with a high-performance microcontroller, enabling autonomous seismic event detection without dependence on external communications or centralized infrastructure. The characteristic period of ground motion (τc) is estimated using a spectral moment method applied to the first three seconds of vertical acceleration following P-wave arrival. Event triggering is based on a short-term average/long-term average (STA/LTA) algorithm, with alarm logic incorporating both spectral and amplitude thresholds to reduce false positives from low-intensity or distant events. Experimental validation was conducted using a custom-built uniaxial shaking table, replaying 10 real earthquake records (Mw 4.1–7.7) in 20 repeated trials each. Results show high repeatability in τc estimation and strong correlation with event magnitude, demonstrating the system’s reliability. The findings confirm that modern embedded platforms can deliver rapid, robust, and cost-effective seismic warning capabilities. The proposed EEW solution is well-suited for deployment in critical infrastructure and resource-limited seismic regions, supporting scalable and decentralized early warning applications.
Authors
- Codrin Donciu
- Elena Serea (ORCID: https://orcid.org/0000-0001-5348-1635)
- Marinel Costel Temneanu (ORCID: https://orcid.org/0009-0001-0597-0087)
Institutions
- Gheorghe Asachi Technical University of Iași (RO)
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-08-15
- DOI
- https://doi.org/10.3390/app15169026
- Citations
- 1
- Primary Topic
- Seismology and Earthquake Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.48