A Study on Intelligent Remote Maintenance System for Computers and Electronic Boards Using IoT and AI Technology

Abstract

This study proposes an intelligent system construction plan for efficient maintenance of computers and electronic whiteboards used in educational settings. Analysis of 250 maintenance cases in the Busan, Ulsan, and Gyeongnam regions over six months from June to November 2024 revealed that the current maintenance system consists of 75% emergency response and 25% preventive maintenance. To overcome the limitations of this reactive maintenance approach, we propose a new maintenance system that combines real-time monitoring through IoT sensors and AI-based prediction models. The proposed system includes real-time equipment status detection, failure prediction, and remote control capabilities, and is expected to reduce maintenance costs by 45%, processing time by 50%, and increase preventive maintenance rates by 60%. In particular, noting that 79AN series and HDMI/video- related issues account for 48% and 35% of total failures respectively, we propose focused monitoring solutions for these areas. This study is significant in that it suggests improvements to electronic equipment maintenance systems in educational environments through empirical analysis based on actual field data. It is expected to contribute to the establishment of smart educational environments by examining the possibility of expanded application to various educational devices in the future.