Research on image processing of electric power system terminals based on reinforcement learning and mobile edge computing optimization

This research is dedicated to the optimization of power system terminal image processing based on RL and MEC. With the continuous development of power system, the demand for image processing of terminal equipment is increasing day by day. However, traditional image processing methods have the problems of high computing complexity and real‐time and energy consumption. To solve this problem, this study introduces the idea of RL and MEC to improve the efficiency and performance of image processing of power system terminals. By modeling and optimizing the image processing task of the power system terminal equipment, the intelligent adjustment of the processing parameters is realized to adapt to the needs of different scenarios. MEC technology is introduced to move image processing tasks from the central server to the edge device, reducing data transmission delay and network burden, thus improving real‐time performance and reducing energy consumption. The experimental results show that the proposed optimization method based on RL and MEC has a significant performance improvement compared with the traditional method in the power system terminal image processing. The framework our proposed has achieved significant improvement in task completion latency, achieving higher system energy efficiency compared to traditional methods. This research focuses on optimizing power system terminal image processing using RL and MEC. By leveraging RL and MEC technologies, this study aims to enhance processing efficiency and performance while addressing issues such as high complexity and energy consumption. Intelligent parameter adjustments enable adaptability to varying scenarios. MEC transfers tasks to edge devices, reducing delays and network load, thereby boosting real‐time performance and reducing energy usage. Experimental results demonstrate significant performance enhancements over traditional methods in power system terminal image processing.