# A Magnetotelluric Signal Acquisition and Monitoring System Based on a Cloud Platform
## 1 Introduction
The refinement of IoT technology and the widespread adoption of infrastructure such as signal base stations and smart devices have provided geophysical instrument development with wireless control and centralized data management capabilities [19]. The Internet of Things (IoT) is a concept of connecting and interacting devices and objects through the internet [20]. These devices can include sensors, actuators, embedded devices, and smart devices, which can communicate, share data, and perform specific tasks over a network [21]. In IoT, communication between devices can be achieved through various protocols and technologies, such as Wi-Fi, Bluetooth, Zigbee, and LoRa [22; 23; 24; 25]. In 2019, [PERSON] et al. designed a distributed hybrid geoelectric data acquisition system based on IoT [26]; in 2021, [PERSON] et al. integrated IoT technology into a four-dimensional high-density geophysical electrical instrument [27]; in 2022, researchers combined InSAR, GNSS, IoT, and 5G technologies to monitor and forecast earthquakes in Abuja, Nigeria [28]; and in 2024, [PERSON] et al. designed a landslide monitoring microseismic sensing system and platform based on IoT technology [29]. A cloud platform is a service and resource management platform based on cloud computing technology that provides various computing, storage, and network services over the internet [30]. The deep integration of cloud computing, big data, IoT, and geophysical technology has enabled remote control, fault detection, and real-time data transmission and analysis, making the connection of geophysical instruments to cloud platforms via IoT a hot research direction [31]. Previous research has mainly focused on IoT technology. By connecting devices and instruments to cloud platforms via sensors, they can communicate in real-time, collect data, and be remotely controlled [32]. IoT-connected cloud platforms allow geophysical instruments to monitor environmental parameters in real time and transmit data to the cloud or central servers, providing real-time data acquisition and monitoring. IoT-connected cloud platforms also allow users to adjust and manage geophysical instruments through remote control interfaces. Cloud platforms themselves are resource management platforms, offering more possibilities for interdisciplinary research, big data analysis, and model building [33]. The integration of IoT and cloud platforms has moved from theory to practice in the geophysical field. In 2014, [PERSON] et al. implemented a cloud-based electrical geophysical monitoring software package, enabling automatic data transmission, processing, visualization, and delivery to end-users [34]; in 2016, [PERSON] et al. designed a cloud-based 3D visualization software for geophysical data [35]; in 2022, [PERSON] et al. designed a new electromagnetic acquisition architecture combining artificial intelligence and cloud-based data transmission and quality assurance, achieving near-real-time operations [36]; in 2023, [PERSON] et al. designed a cloud-based machine learning seismic monitoring workflow [37]; and in 2024, [PERSON] et al. used cloud modeling technology to establish a UK ground electric field model for simulating geomagnetic storm-induced electric field changes [38]. IoT and cloud platform technologies have also been widely applied in geothermal research. In 2022, [PERSON] et al. designed an open-source IoT-based geothermal monitoring system and applied it to a nursing home in South Korea [39]; in 2023, [PERSON] et al. proposed a power generation system for IoT-based geothermal monitoring, forming a comprehensive geothermal monitoring system [40]; and in 2023, [PERSON] et al. developed an IoT-based monitoring system for measuring hydrogen sulfide concentrations in geothermal environments [41]. In summary, cloud platform technology has already been applied in the geophysical field, but it has the disadvantages of a late start and slow development, as well as shortcomings in integration and systematicity.