Thinking and Research on the Intelligent Monitoring System for Network in the Smart Campus Environment

Abstract

The rapid evolution of Internet technologies has accelerated the development of smart campuses, where decentralized servers, storage resources, and application systems are increasingly consolidated into centralized data centers. Ensuring the security, stability, high performance, and seamless operation of software and hardware infrastructure is paramount for educational institutions. This paper examines the conceptual framework, key characteristics, and evolutionary trends of distributed monitoring systems in alignment with smart campus objectives. We propose a customized intelligent monitoring solution using open-source platforms Zabbix and Grafana, integrated with the iFlytek Spark large language model for intelligent question-answering capabilities. This system addresses comprehensive monitoring needs for university network infrastructure. Through detailed implementation, evaluation, and case studies, we demonstrate its effectiveness in enhancing network management efficiency, fault detection, and predictive maintenance. Empirical results show improved alert response times by 30% and reduced downtime by 25% in a simulated campus environment. This work provides valuable insights for deploying scalable, AI-enhanced monitoring systems in smart campuses, contributing to more resilient educational IT ecosystems.