AI for Connectivity Hackathon II: Building Resilient Networks 

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Cool Cat

CatIsLife

Muhammad Ibrahim Basit

Adil Mubashir Chaudhry

gNIPP is an AI-powered network infrastructure analysis tool designed to provide insights into network tower distribution, coverage, and signal strength. The platform allows users to visualize network tower data on an interactive map while summarizing key statistics for better decision-making. It leverages AI capabilities to analyze current network infrastructure and create strategies to develop underserved regions. It utilizes RAG and Agentic AI capabilities to provide reliable data regarding definitions of different keywords and procurement policies.

gNIPP processes network tower data and uses geographical information about schools to analyze the wireless network infrastructure available to these regions.
- Curated Dataset for School geographical information and details regarding their network performance made available through Giga School Mapping Data
- Using OpenCellID API to fetch Network Tower Data around a specific bounding box of latitude and longitude
- Utilize Gemini API to analyze the network performance and availability
- Provide Heatmap of underserved regions based on key network performance metrics allowing users to quickly identify key regions of interest
- Use AI Agent to access wikipedia allowing users to get access to correct information regarding keywords and jargon
- Use RAG to access gppd data and extract procurement information of various countries.

gNIPP uses RAG and Agentic AI technologies for network infrastructure analysis tool designed to provide insights into network tower distribution, coverage, and signal strength. It also serves a guide for procurement policies and infrastructure planning.

"Cool Cat team on AI for Connectivity Hackathon II: Building Resilient Networks Hackathon"

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