Seismic Event Detection in the Copahue Volcano Based on Machine Learning: Towards an On-the-Edge Implementation

Abstract

This study focuses on volcano seismic event detection using machine learning, leveraging the advantages of software/hardware co-design for system on chip (SoC) based on field programmable gate array (FPGA) devices. The case study was the Copahue Volcano, an active stratovolcano located on the border between Argentina and Chile. Volcano seismic event processing and detection were integrated into a PYNQ-based implementation by using a low-end SoC-FPGA device. We also provide insights into integrating an SoC-FPGA in the acquisition node, which can be valuable in scenarios where stations are deployed solely for data collection and holds the potential for developing an early alert system.