A Deep Learning Assisted Intelligent Monitoring System for Smart Grid
Bin Luo, Wen Chen, Xinxiu Xiao, Weibing Weng · 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence · 2021
The smart grid provides effective power supply by integrating the traditional grid system with the latest information technologies. Video surveillance is widely used in smart grid to monitor the system behavior as well as detect illegal intrusions. Currently, this video data is normally processed and analyzed manually in real-world applications, which is not only cost inefficient but also error-prone. To enhance the utilization of this video data, we investigate how to design a deep learning assisted intelligent monitoring system for smart grid. First, we classify the characteristics of various target detection algorithms and discuss their potential applications in smart grids. Second, we analyze the challenges of employing target detection algorithms in smart grids. Finally, we propose a framework for constructing intelligent processing systems for smart grids. Our work contributes novel research ideas for the construction of a strong smart grid.