BLESeis: Low-Cost IoT Sensor for Smart Earthquake Detection and Notification

Area of Science:

• Engineering
• Computer Science
• Earth Science

Background:

• Internet of Things (IoT) offers cost-effective event detection solutions.
• Seismic event detection remains challenging due to limitations in sensing fidelity and classification efficiency.

Purpose of the Study:

• To propose BLESeis, an IoT sensor system for smart earthquake detection.
• To enhance seismic event detection using high-fidelity sensing and efficient algorithms.

Main Methods:

• Developed BLESeis with MEMS accelerometer, digital filtering, an embedded earthquake detection algorithm, and Bluetooth low energy (BLE) beacon.
• Implemented a triggering algorithm and FIR low-pass filter for high-fidelity vibration sensing.
• Utilized time and frequency domain analysis for classifying earthquake signals.

Main Results:

• The proposed system achieved high-fidelity vibration sensing and efficient earthquake signal classification.
• BLE beacon effectively broadcasted notifications upon earthquake detection.
• Numerical simulations and shaking table tests validated the system's feasibility.

Conclusions:

• BLESeis demonstrates a feasible, low-cost solution for earthquake detection and notification.
• The system addresses limitations in current seismic event monitoring.
• IoT technology can be effectively applied to enhance earthquake early warning systems.