A Magnetotelluric Signal Acquisition and Monitoring System Based on a Cloud Platform - Qi Luo; Weibin Sun; Rujun Chen; Xiaoli Mi; Hongchun Yao (Applied Sciences)
This study designed and implemented an magnetotelluric signal acquisition and monitoring system (CMT) based on an Internet of Things (IoT) cloud platform. By integrating magnetotelluric monitoring stations, control terminals, and cloud servers, a real-time and efficient monitoring network was constructed. The hardware part of the system adopts a multi-module collaborative design, including signal conditioning circuits, FPGA control modules, DSP processing units, and embedded subsystems, achieving high-precision acquisition and processing of magnetotelluric signals. The software part employs a layered architecture, developing acquisition software, terminal control software, and a cloud platform monitoring system, which support multi-protocol communication, data parsing, and remote interaction. Through server stress testing, consistency testing, and cloud platform functional verification, the results showed that the system performs well under pressure even with limited server hardware bandwidth, with controllable consistency errors compared to the commercial device MTU-5A, and has stable field acquisition performance. The study validated the system’s advantages in real-time performance, reliability, and scalability, providing a feasible technical solution for the field of magnetotelluric monitoring. In the future, the system will be applied to geothermal monitoring.