## 1 Introduction  
The purpose of this research project is to combine the heat transfer modelling analysis and the neural network prediction model algorithm to provide environmental prediction and support strategies to support the work of automated observation equipment related to space physics in the region. So far, China has established five research camps in Antarctica, of which the Tai-Shan field in the Princess Elizabeth area is the only inland summer camp. Since Tai-Shan Camp is located inland in Antarctica, 520 kilometres from the coastline, the energy demand and fuel transportation costs are higher than other coastal checkpoints. In the research process of the Antarctic continent, including glaciology, geophysics, astronomy, and other disciplines, an essential reason for its progress is the improvement of data quality. The need for more and better measurements along with advances in technical capabilities is driving the ambition to deploy arrays of autonomous geophysical instrument platforms in remote regions. Researchers have an even more urgent need for observations in the Antarctic region. Due to remote areas, lack of infrastructure, and harsh environments, the current measurement is sparse [1]. The activity of the sun has always been very closely related to the change in the earth's natural environment. The magnetic interaction between the high-speed solar particle flow (solar wind) and the earth's magnetosphere is a vital manifestation of the sun's influence on the ground environment. These interactions can initiate geomagnetic disturbances resulting in geomagnetic storms at Earth that may have an impact on technology and endanger human activity and health [2]. This design serves the physical observation of Earth space. The data obtained during the observation process include aurora, ionosphere, and geomagnetism, which can reflect the activities of the sun and its impact on the earth. There are natural, high-quality observation conditions in the Antarctic inland area, and the development of related physical research in this area is less disturbed by human activities. Taking neutrino detection as an example, the Antarctic is an excellent place for neutrino detection on Earth. The Ice Cube project transforms 1 km\({}^{3}\) of ultra-transparent Antarctic ice into a particle detector. A total of 5160 optical sensors is embedded into a gigaton of Antarctic ice to detect the Cherenkov light emitted by secondary particles produced when neutrinos interact with nuclei in the ice [3]. However, the premise of this research is to carry out under the circumstances of someone on duty. For some actions that require interannual observations or observations in an unmanned area in the polar night, the unattended remote measurement and control system that replaces people is particularly important. Besides, in the perennial unmanned area, the Antarctic inland environment is more special than other regions, and the unique environment creates excellent observation conditions. Dome A, the summit of the Antarctic Plateau, proved to be an excellent location for optical, near-infrared, and terahertz astronomical observations. Gattini is a wide-field camera installed on the PLATO instrument module as part of the Chinese-led traverse to Dome A in 2009 January [4]. No matter what the system is, we will face the same problem in the interior of Antarctica: the observation in the interior of Antarctica is carried out by automated observation equipment and automated sensors. Moreover, space observations and astronomical observations involve more sophisticated equipment, and the environmental conditions required are different from those of conventional sensors. In the application process, several factors make the deployment of a network particularly complicated; these include difficulties of physical access, extreme climate conditions, potential vandalism, as well as data quality and remote data access in real-time [5]. The system is very stable in the Dome A area.