29,000 Home Weather Stations and AI Agents Tested as Volcanic Early Warning System

Researchers used over 29,000 consumer-grade Netatmo barometric sensors across Japan, combined with Google Apps Script cloud archiving and Gemini AI agents in the Antigravity CLI environment, to detect atmospheric shockwaves from volcanic eruptions. The system was validated against two historical Japanese eruptions — the 2018 blasts at Mt. Kusatsu-Shirane and Mt. Shinmoedake. It reconstructed shockwave velocities within 98.5% of theoretical sound speeds, pinpointed unmonitored crater directions to within 1.78 degrees, and estimated explosive yields ranging from roughly 179 to 1,041 tons of TNT equivalent. The crowdsourced sensor network delivered between 2.5 and 15 minutes of advance warning with no recorded false positives, even during violent storm conditions. The findings, published on ESS Open Archive, suggest that dense consumer IoT networks grounded in physics-based AI analysis could help fill the large blind zones left by sparse government monitoring infrastructure.