Research on Integrated Management System of Equipment State Sensing and Control in Intelligent Power Distribution Room Based on Internet of Things

This article presents the research and development of an advanced integrated management system for intelligent sensing and controlling equipment states in distribution rooms, leveraging the Internet of Things (IoT) technology. This system enables comprehensive monitoring of distribution rooms, catering to measurement requirements spanning metrology, production, electrical parameters, and environmental conditions. The study addresses three critical facets of enhancing distribution network monitoring: integration of diverse data sources, data fusion optimization, and model validation through splicing. Incorporating an attention mechanism, the system employs a novel hybrid Convolutional Neural Network (CNN) based on ResNet architecture, facilitating early intelligent monitoring and alert generation for power distribution equipment. Empirical testing of the system underscores its efficacy, with minimal transmission loss and robust communication quality, especially for distances under 100 meters. Notably surpassing conventional techniques, the hybrid network demonstrates an impressive 93% accuracy in predicting fault types, rendering it well-suited for fault detection across various scenarios.