To address the issues of large errors and low automation in real-time video transmission delay measurement methods for remote control video surveillance systems in smart port cranes, this paper first analyzes the key factors causing real-time video transmission delay in the video surveillance system and proposes a real-time video transmission delay measurement method based on video hashing technology. In the algorithm design, to uniquely identify video frames and establish correspondence between them, this paper utilizes perceptual hashing technology to extract motion features of video frames and perform hash matching. By incorporating Beidou timing technology, end-to-end clock synchronization is achieved, after which timestamp information is obtained to measure the real-time video transmission delay. In simulation experiments with known hardware configurations, even in relatively static monitoring scenarios where the content of consecutive video frames exhibits high similarity, the algorithm still demonstrated outstanding video frame matching performance and achieved precise real-time video transmission delay measurement. Compared with traditional measurement methods, this method preserves the original video content to the greatest extent while achieving continuous automated delay measurement, offering excellent delay measurement accuracy and a high degree of automation. It meets the requirements for real-time video transmission delay measurement in remote operation scenarios for port cranes.