Research Article
Design and Realization of Cloud Service Training Platform for Intelligent Unmanned Aerial Vehicle Interaction with Edge Computing
@INPROCEEDINGS{10.4108/eai.17-11-2023.2342819, author={Yuhua Wei and Yunxing Chen}, title={Design and Realization of Cloud Service Training Platform for Intelligent Unmanned Aerial Vehicle Interaction with Edge Computing}, proceedings={Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India}, publisher={EAI}, proceedings_a={ICSETPSD}, year={2024}, month={1}, keywords={uav interaction cloud service practical training platform edge computing cloud computing}, doi={10.4108/eai.17-11-2023.2342819} }- Yuhua Wei
Yunxing Chen
Year: 2024
Design and Realization of Cloud Service Training Platform for Intelligent Unmanned Aerial Vehicle Interaction with Edge Computing
ICSETPSD
EAI
DOI: 10.4108/eai.17-11-2023.2342819
Abstract
In view of the common problems of low resource utilization efficiency and high user demand in the operation of the current Unmanned Aerial Vehicle (UAV) interactive cloud service training platform, this paper used edge computing technology to build a network oriented UAV cloud work platform, and provided it as a service mode to users on the network. Firstly, the input devices on the user end were virtualized to have a unified standard. Secondly, the control strategy of the UAV was studied, and the user's input was matched with the actual actions of the UAV. Finally, using technologies such as speech recognition and finger manipulation, combined with multi-channel fusion algorithms, a natural and efficient multi-channel human-machine interaction was achieved. This article categorized and summarizes the existing boundary intelligent computing technologies based on UAV from the perspective of time delay, and analyzes and predicts the future development trends. This paper tested the delay performance of edge computing and cloud computing. Under the condition of large resource load, the average response speed of the edge computing cloud platform system was 2.26 seconds. This showed that the design and implementation of intelligent UAV interactive cloud service training platform based on edge computing is more practical.
