The tool works in collaboration with Europe's Flood Awareness System (EFAS). When EFAS identifies areas with heightened flood risks, it triggers SMFR to begin collecting flood-related tweets from users in those areas. Gathering reliable information from Twitter is no easy task, especially considering that EFAS covers an area with more than 27 languages. That's where the team put AI to work. To start, the researchers trained SMFR to spot flood-related keywords in English, German, Spanish and French. In a test during floods in Calabria, Italy, last fall, the tool successfully gathered 14,347 tweets over three days, sorted them by relevance and provided geo-location data.

The Joint Research Center hopes EFAS might use the tweets alongside other flood data it collects, like satellite imagery. As the paper explains, we know social media can provide timely data during natural disasters, but less attention has been paid to how to integrate social media in a seamless, reliable way with other tools for disaster forecasting and monitoring. The Joint Research Center is not alone. Both Google and Facebook have committed to using AI to gather flood data. Together, all of these tools could give first responders a better picture of what they're heading into.