Design of a Grid Management System for University Student Dormitories Based on Haar Features

With the continuous expansion of the university scale, the management of student dormitories is facing increasingly severe challenges. The purpose of this study is to design a grid management system for college students' dormitories based on Haar features by introducing advanced image processing technology and grid management concepts so as to improve the efficiency of dormitory management, ensure students' safety, and improve the quality of life. The system adopts client-server architecture, which realizes the separation of front-end display and back-end data processing and is convenient for system maintenance and expansion. Through face recognition and other technical means, the system can monitor the dormitory area in real time, identify the people entering and leaving, and store the monitoring video and image data. The database design fully considers the integrity, security, and expansibility of data and establishes data tables such as dormitory information, student information, grid information, and monitoring records. The system mainly includes functional modules such as dormitory information management, student information management, grid area division, real-time monitoring, anomaly detection and alarm, which can fully meet the needs of dormitory management. By introducing weighted Haar features and multi-scale Haar features, face recognition performance is enhanced, and the system's performance is tested under different lighting conditions. After a comprehensive functional test and performance test, the stability and efficiency of the system are verified, which provides an intelligent and efficient solution for managing college students' dormitories.