【摘要】 为解决无人艇运动过程中传感器数据采集和传输数据量过大问题，引入边缘计算技术，设计基于边缘计算的无人艇运动状态数据采集系统。通过将云端的数据采集与处理任务转移到边缘节点，减少上传至云端的数据量并提高无人艇运动状态数据传输与处理的实时性。该系统通过树莓派完成无人艇运动状态检测传感器的数据采集、处理和传输，实现无人艇运动状态数据的船端边缘计算功能。实验结果表明，该系统在传感器数据传输方面节省79%的数据传输量。最后在云端搭建可视化终端，实现无人艇航行状态的实时监测。更多还原

【Abstract】 In order to solve the problem of excessive data volume of sensor data acquisition and transmission during the movement of USV, edge computing technology is introduced to design a USV movement state data acquisition system based on edge computing. By transferring the data acquisition and processing tasks from the cloud to the edge nodes, the amount of data uploaded to the cloud is reduced and the real-time transmission and processing of the USV motion status data is improved. The system completes the data acquisition, processing and transmission of the motion state sensor of the USV through the Raspberry Pi, and realizes the ship-side edge computing function of the motion state data of the USV. The experimental results show that the system saves 79% of data transmission in sensor data transmission. Finally, a visualization interface is built in the cloud to realize the real-time monitoring of the sailing status of the USV.更多还原