This workflow automates the high-volume, low-signal bottleneck of manually monitoring social platforms for infrastructure damage reports during storms or earthquakes. By deploying specialized AI agents to continuously scan for keywords like 'power line down' or 'gas smell,' the system filters noise, geolocates posts, and validates them against sensor grids and asset registries. The operational upside is measured in hours saved on initial damage assessment, enabling utilities and emergency operations centers to prioritize field crews based on fused intelligence rather than delayed 911 calls, directly reducing outage duration and public safety risk.




