Wireless Power Transfer System for the Intelligent Video Monitoring and Analysis Based on the Safety of Power Grid Construction Site

Abstract

This study describes a power grid construction site surveillance system that includes wireless power transmission and an improved Yolo V3 detection model. An artificial intelligence and wireless power transfer methodology is employed used for continuous monitoring. Improved Yolo V3 detection is optimized using Hierarchical Particle Swarm Optimization (HPSO) for enhanced efficacy in detecting power grid development threats. The methodology is compared to existing methods in terms of precision, accuracy, recall, and speed. The findings indicate that the proposed method is achieved a real-time and accurate power grid development site monitoring. Experiments on test sets in various situations improved the detection accuracy, and indicate that the proposed technique is quite robust. Also the detection accuracy and speed of the proposed method have improved over existing approaches, indicate that the strategy provides superior detection efficacy. This method considerably improves risk source detection, that's critical for assuring safety on power grid building sites.