## 4 Key Enabling Technologies
### System Deploy
#### 4.3.2 Software System  
The system adopts a cloud-edge-terminal collaborative architecture, integrating cloud computing, edge computing, and IoT technologies to build an efficient, stable, and scalable intelligent agricultural scheduling and autonomous driving control system. It employs a four-layer architecture, including the data acquisition layer, edge computing layer, cloud platform layer, and application layer, to ensure efficient data processing and system scalability. The system adopts a dual-channel communication mode with NB-IoT and 5G, optimizing transmission based on different data types. NB-IoT is responsible for low-power, wide-coverage data transmission, including weather monitoring, soil sensor data, and the operational status of the weather station (as shown in Figure 14). These data have lower real-time requirements but need to be uploaded continuously and stably over the long term to support remote monitoring and long-term decision optimization. The edge computing layer is deployed on the embedded computing unit NVIDIA Jetson Xavier NX in agricultural machinery, utilizing Robot Operating System 2 (ROS 2) for data fusion and path computation. NVIDIA Container Runtime + Docker is employed for containerized deployment, enhancing the portability and stability of software modules. For \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Type** & **Devices Name** & **Function** & **Protocol** & **Devices Details** & **Photo** \\ \hline \multirow{8}{*}{Sensor Unit} & Camera & Display Environment & IEEE 802.3 Ethernet & DS-2 CD3955 FWD-IWS (Hikvision, Hangzhou, China) & \\  & Millimeter & & & 24 GHz SRR308 (Continental, Frankfurt, Germany) & \\  & Wave Radar & Collision Prevention & CAN Bus & (Continuental, Frankfurt, Germany) & \\ \cline{2-5}  & IMU & Posture Detection & RS232 & YIN680 (Yiesense, Shenzhen, China) \\ \cline{2-5}  & RTK & Position & RS232 & BT-B109 (Beifian, Shenzhen, China) \\ \cline{2-5}  & Weather & Monitoring temperature, humidity, wind speed, wind direction, illumination, rainfall, etc. & NB-IoT & FT-QX (Fengtu, Guangzhou, China) \\ \hline \hline \multirow{8}{*}{Data Processing Unit} & 4G DTU & Upload camera images & RS232/RS485 TO 4G & HS2060-CAT4 (Huawei, Shenzhen, China) \\  & & & & \\ \cline{1-1}  & 5G DTU & Networking For Central Controller & 5G NR & RM500Q-AE (Quacetel, Shanghai, China) \\ \cline{1-1}  & & & 4G LTE Cat.20 & Shanghai, China) \\ \cline{1-1}  & NB-IoT DTU & Networking for environmental sensors & RS485/RS232 & E840-DTU (Lierda, Suzhou, China) \\ \hline \hline \multirow{2}{*}{Actuator} & \multirow{2}{*}{Tractor} & \multirow{2}{*}{Farmland operation organization} & \multirow{2}{*}{Mixed} & WF1404-2 (Wode Machinery, Jiangsu, China) \\  & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Hardware infrastructure of the prototype. low-latency tasks like path tracking, Jetson's GPU acceleration is leveraged for real-time computation, combined with a Real-Time Operating System (RTOS) to optimize response time. Some computational tasks, especially those requiring immediate processing, are handled directly on the edge device, while remote monitoring and data storage tasks are transmitted to the cloud. To reduce data transmission overhead, the edge device preprocesses high-frequency sensor data (e.g., downsampling and data compression) before uploading, ensuring stable cloud communication and efficient bandwidth utilization. The cloud platform serves as the core computing and storage center, utilizing Alibaba Cloud Elastic Compute Service (ECS) as the primary server and Relational Database Service (RDS) for data management. The system is built on Kubernetes (K8s) for microservices management, enhancing scalability and fault tolerance. In terms of database architecture, PostgreSQL is used to store structured data such as user information, scheduling records, and device statuses, while TimescaleDB handles time-series data from sensors, improving high-concurrency query performance.