Research on 3D Intelligent Monitoring Model of Public Computer Rooms in Higher Vocational Colleges Based on Big Data
(Guangdong Food and Drug Vocational College, Guangzhou 510520, China)
Abstract
The demand for virtual training teaching in higher vocational colleges continues to grow, and the scale of public training computer rooms keeps expanding. However, the shortage of professional maintenance personnel is becoming increasingly prominent, and the contradiction between equipment quantity and operation and maintenance manpower has become a critical pain point in computer room management. Traditional maintenance models suffer from delayed response and low efficiency, making it difficult to meet current equipment support needs; thus, the upgrade of computer room operation and maintenance is imperative. Therefore, this paper relies on big data technology to design and develop an intelligent monitoring and early warning system for public computer rooms. The system integrates core modules such as intelligent monitoring and analysis-based early warning, and combines Unity WebGL visualization technology to achieve automated collection of equipment operating status, precise identification and rapid localization of suspected faulty equipment, effectively narrowing the scope of fault diagnosis and reducing manual inspection costs. It significantly enhances the intelligence and refinement of computer room operation and maintenance, providing practical technical support and solutions for the efficient and stable operation of training computer rooms in higher vocational colleges.
Keywords
Big Data; public computer room; intelligent monitoring; WebGL; 3D visualization
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Funding
Guangdong Provincial Education Planning Project (2024GXJk1000); Natural Science Research Project of Guangdong Food and Drug Vocational College (2024ZR182024ZR212024ZR28)
About the authors
Yang Yunchong (1982-), male, Han ethnicity, a famous figure from Maoming, Guangdong, is a network engineer and a master's student. His research interests include computer networks and data mining; Corresponding author: Qiao Liang (1983-), male, Han ethnicity, from Wuyi, Hebei Province, China. He is a computer experimenter with a bachelor's degree and research interests in computer applications and virtual simulation.