Fahad Yaseen@fahadyaseen001

In underserved regions, network infrastructure faces numerous challenges, including adverse weather conditions, lack of technical expertise, and cloud dependency, leading to frequent disruptions. This project proposes an AI-driven, open-source solution to enhance network resilience and optimize public sector network management. The system includes: Weather Monitoring Dashboard: Predicts critical conditions affecting network stability and alerts users in advance, enabling them to download crucial files for operational continuity. AI-Powered Troubleshooting Assistant: Guides non-technical users through problem-solving with simple, step-by-step instructions. Edge AI for Local Analysis: Performs real-time network diagnostics and optimization without relying on cloud connectivity. Automatic Network Performance Monitoring: Detects congestion or failures early, helping prevent downtime. AI-based Image Recognition: Allows users to upload photos of network errors, LED indicators, or configuration screens, enabling the system to identify issues and suggest solutions automatically. This project is designed for schools, universities, SMEs, network providers, public institutions, hospitals, and remote communities that struggle with unreliable network infrastructure. By reducing downtime and providing easy troubleshooting tools, it ensures scalable, efficient, and sustainable network management in critical areas.