# Satellite IoT Edge Intelligent Computing: A Research on Architecture
## 1 Introduction  
The Internet of Things (IoT) is one of the new directions for the future development of the Internet, and intelligent networking devices will be connected [1; 2]. Although the number of IoT devices is increasing, some remote areas do not have network coverage. Terrestrial wireless networks are only covered by 20% due to extreme terrain or communication distance and cost constraints [3]. The wide-area coverage of satellite radio networks can solve the problem of ground coverage and solve the problem of communication interruption caused by natural disasters. Obviously, satellites have become an important part of the Internet of Things [4; 5]. At the same time, satellites are an achievable and powerful complement to terrestrial networks and future 5G/6G communications [6; 7; 8].  
The number of remote sensing satellites has increased dramatically in satellite launches in recent years [9; 10]. After acquiring the remote sensing image data of the satellite, the researchers used the artificial intelligence algorithm and the powerful computing power of the ground data center to extract the hidden information in the remote sensing image. However, researchers need to spend a lot of time and cost to complete this process. In the existing satellite communications, most of the observation, relay, and communication satellites are single-star and single-chain, and there is no network. Due to the limitation of energy consumption, the available processors on the satellites have poor performance and cannot meet the growing demand for space computing tasks [11]. At the same time, the satellite communication rate between satellites and other satellites, and between satellites and the ground, is generally not improved. The amount of data generated by the on-board sensor is large, causing a highdelay in the data transmission process, which is very disadvantageous for scenes with high real-time requirements (such as early warning).  
With the advancement of aerospace technology, commercial satellite companies such as OneWeb, O3b [12], and SpaceX Starlink [13] have proposed satellite constellation plans, increasing investment and research on satellite-related technologies, making satellites more powerful and smarter. The computing power of the high-performance computing unit mounted on the satellite has been greatly improved. Real-time intelligent computing of satellite remote sensing images will become possible.  
Compared with the method of transmitting satellite image data to the satellite ground station cloud computing data center and using deep learning for centralized processing, this paper proposes a method using edge intelligent computing processing and describes the satellite IoT edge intelligent computing architecture. Combined with edge computing technology [14], such as mobile edge computing [15; 16], fog computing [17; 18] fully utilizes the computing power from the cloud to the edge of the network to decompose the deep-learning tasks. Here, we use the more powerful on-board computing power in the future to place the deep-learning algorithm model at the source of satellite data generation to achieve edge intelligent computing. This architecture can reduce the amount of data transmitted from satellites, reduce data processing and communication delays, improve the bandwidth utilization of inter-satellite links, and reduce the pressure on data processing of satellite ground stations.  
This paper is organized as follows. Section 2 describes the related research work of satellite Internet of Things and edge intelligent computing and distributed deep learning. Then, Section 3 introduces the significance of edge computing and deep learning in satellite IoT and how to implement satellite IoT edge intelligent computing architecture. Section 4 mainly verifies the proposed solution, including the connectivity and coverage performance of the satellite IoT and the performance of the edge intelligent computing architecture. Finally, Section 5 concludes this work.