부산대학교 도서관

In recent years, owing to the rapid advancements in science, technology and digital innovations, the digitalization of technical supervision for electric energy metering devices has been making steady progress. We aim to explore in depth the application of image recognition function under the Flask architecture in the Web front-end. The Web front-end has the potential to leverage on-site image recognition, background model reasoning, and image upload scoring functional modules for enabling technical personnel to digitally oversee and control on-site operations, thereby comprehensively enhancing the efficiency and precision of technical supervision for electric energy metering devices, and aiding in the supervision of power safety. In this paper, we provide a useful reference for the application of image recognition in the digital technical monitoring of electric energy metering devices on the Web front-end and points the direction for further development in the future.