UT San Antonio Researcher Builds Self-Powered TinyML Flood Warning Station Costing $150–$220

UT San Antonio's Chen Pan, assistant professor of electrical engineering, announced on September 28, 2026 a self-powered flood warning prototype that runs TinyML models directly on a microcontroller, reporting 98.82% validation accuracy without any cloud connection. Each solar-powered station combines temperature, humidity, light and precipitation sensors with four optical water-level sensors at different heights, and relays alerts over LoRa radio (about half a mile in urban areas, up to five miles in open terrain). Components cost roughly $150–$220 per station. The work, funded by a NOAA-backed Texas Coastal Management Program grant and done with Texas A&M University-Corpus Christi, targets low-cost hyperlocal flood alerts for communities lacking dense gauge networks. This is a university prototype, not yet a fielded deployment.