"Training a GNN on Real Mesh Network Data (Not Synthetic Garbage)"
Dev.to AI
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Machine Learning
AI Research
Most mesh network AI papers train on synthetic topology data. They generate random graphs, simulate traffic, and report accuracy numbers that look great in a paper. Then you point them at a real network with flaky links, power-cycling nodes, and actual human traffic patterns - and everything collapses. We didn't do that. We trained on 31 days of real data from GuifiSants - one of the world's largest community mesh networks in Barcelona. Here's how we built a Graph Neural Network that actually works in the wild.