The purpose of this study was to achieve intelligent management of the full life cycle of RFID (Radio-Frequency Identification) building equipment through visualization technology, and to solve the problems existing in traditional research. By integrating BIM (Building Information Modeling) visualization technology and RFID data collection, this study achieved efficient information integration and real-time monitoring in building equipment management. To evaluate the performance of a visualized RFID building equipment life cycle intelligent management system in different aspects through experiments, this paper mainly included three key parts: information integration accuracy experiment, fault identification and prediction accuracy experiment, and automation operation efficiency improvement experiment. The experimental results showed that the accuracy of using visualization tools to integrate information was significantly higher than that of manual integration, with an accuracy of 92–97%, while the accuracy of manual integration was only 85–90%. In terms of fault identification and prediction, the algorithm based on Convolutional Neural Network (CNN) performed well, with an accuracy improvement from 95 to 97%, and the highest recall and accuracy also improved to 96% and 95%, respectively. In the automation operation efficiency experiment, the reduction rate of maintenance frequency and the maintenance cost savings rate were increased by the highest of 30% and 25%, respectively. These achievements demonstrate the significant advantages of intelligent management systems in improving the efficiency, accuracy, and cost-effectiveness of building equipment management.