{"id":6513,"date":"2020-08-25T18:49:33","date_gmt":"2020-08-25T23:49:33","guid":{"rendered":"https:\/\/arch.tamu.edu.staging2.juiceboxint.com\/news\/2020\/08\/25\/crowdsourced-flood-level-app-developedby-cosci-researcher-colleagues\/"},"modified":"2023-08-17T15:52:22","modified_gmt":"2023-08-17T20:52:22","slug":"crowdsourced-flood-level-app-developedby-cosci-researcher-colleagues","status":"publish","type":"post","link":"https:\/\/www.arch.tamu.edu\/news\/2020\/08\/25\/crowdsourced-flood-level-app-developedby-cosci-researcher-colleagues\/","title":{"rendered":"First responders tout AI-based\nflood app created in part by COSC prof"},"content":{"rendered":"
As Hurricane Laura<\/a>\u2019s menacing march to the Texas and Louisiana coasts continues, first responders and Gulf Coast residents are touting the benefits of a new app<\/a> developed by Amir Behzadan, Texas A&M associate professor of construction science<\/a>, and collaborators that will help provide precise, timely information about flood levels.<\/p>\n The concept of the app, BluPix<\/a>, is simple: anyone can use the free app to upload a photo of floodwaters that includes a stop sign and pole. The uploaded image, and a photo of the same location taken before the flood, are then pinned to the app\u2019s built-in map using the photos\u2019 metadata.<\/p>\n Because stop signs in the U.S. are all the same height and width, a computer algorithm can \u201cturn them into low-tech flood sensors,\u201d Behzadan told KHOU-TV<\/a>. First responders and citizens can use the app to quickly determine the height of flood waters and use its built-in map to determine flood risk in their area. The app processes the crowdsourced photos with an artificial intelligence algorithm to calculate floodwater depth.<\/p>\n