AI Takes the Wheel: How One System Mapped 40,000 Networks in Three Days

This project demonstrates how machine learning inference on resource-constrained devices like the Raspberry Pi can dramatically outperform traditional brute-force network scanning methods. By achieving 94%+ accuracy in real-time AP classification through a custom TinyML pipeline, it reveals both the transformative potential and concerning accessibility of intelligent network reconnaissance.