AI-Driven Zabbix for School Networks

Our project integrates AI with Zabbix to develop an intelligent network monitoring and diagnostic system tailored for educational institutions. Schools rely heavily on stable internet connectivity for digital learning, online assessments, and cloud-based applications. However, network issues such as downtime, high latency, or bandwidth constraints can disrupt these activities. To address this, we enhance Zabbix with AI-powered analysis using Orca Mini and GPT-4. Our system detects, analyzes, and diagnoses network problems in real time, providing automated insights and recommendations to IT administrators. The AI assistant runs on Windows, communicating with a Zabbix server on Ubuntu via SSH, ensuring seamless interaction between AI and network monitoring tools. When an issue arises, Zabbix detects the alert, and the AI assistant processes logs, configurations, and network metrics to determine potential root causes. It then generates detailed recommendations for resolution, helping IT teams act faster and prevent prolonged downtime. The system also supports predictive analytics, identifying trends that may lead to future network failures and suggesting proactive solutions. This AI-enhanced network management drastically reduces IT workload, optimizes resource allocation, and ensures continuous, high-quality connectivity for students, teachers, and administrators. By making network troubleshooting faster and smarter, our project empowers schools with self-healing, AI-driven infrastructure that supports modern education and digital transformation. 🚀