{"id":13738,"date":"2023-02-08T10:07:00","date_gmt":"2023-02-08T16:07:00","guid":{"rendered":"https:\/\/www.arch.tamu.edu\/?p=13738"},"modified":"2023-04-13T09:44:10","modified_gmt":"2023-04-13T14:44:10","slug":"stop-gather-critical-information-proceed","status":"publish","type":"post","link":"https:\/\/www.arch.tamu.edu\/news\/2023\/02\/08\/stop-gather-critical-information-proceed\/","title":{"rendered":"Stop. Gather Critical Information. Proceed."},"content":{"rendered":"\n
Flooding tops the list of natural hazards in the United States and many parts of the world. <\/p>\n\n\n\n
However, in an age when reams of data about almost everything are readily available, real-time flooding data and analysis still remains mostly a concept to first responders and the public, said Amir Behzadan, professor of construction science<\/a> at Texas A&M University, who is developing a new system to collect, curate, and communicate this kind of data.<\/p>\n\n\n\n \u201cWhen it comes to disaster impact, there are \u2018data deserts\u2019 \u2014 large areas in our communities in which we have very little information about the likelihood and extent of damage,\u201d said Behzadan. \u201cIf this data is available, informed decisions can be made about immediate needs like search and rescue, as well as longer-term needs such as debris cleanup, economic recovery efforts, and where insurance companies can focus.\u201d <\/p>\n\n\n\n Flood data gathering measures in many neighborhoods are very basic \u2014 if they exist at all, he said.<\/p>\n\n\n\n \u201cThere are flood gauges that are operated by the U.S. Geological Survey or local governments, but these have limited coverage and do not provide the full picture of how floodwaters move, especially in residential neighborhoods,\u201d he said. \u201cIn Houston, some areas have buoys or gauges in rivers and creeks, but those only register conditions close by.\u201d<\/p>\n\n\n\n More imprecise methods are used for large areas that don\u2019t have these devices.<\/p>\n\n\n\n \u201cAs you move farther away from the small number of flood gathering devices we do have, you have to rely on modeling that uses hydrological equations and other mathematical techniques. Many times, these techniques are inaccurate because floodwaters\u2019 movement depends on many variables, such as characteristics of the terrain it\u2019s on, which affects how much water is being absorbed and how much of it runs off,\u201d he said.<\/p>\n\n\n\n Behzadan, whose research aims to enhance the interface of artificial intelligence and the built environment, wondered how real-time flood data could be much more accurately gathered, analyzed, and widely distributed. As he pored over flood photos online, an idea came to him: what about an artificial intelligence-based solution that involved a standard unit of measurement that\u2019s a common sight in neighborhoods everywhere \u2014 the stop sign?<\/p>\n\n\n\n \u201cIn a way, it\u2019s really a very simple concept,\u201d said Behzadan, who is heading the project with collaborators Michelle Meyer, director of the Hazard Reduction and Recovery Center<\/a>, Courtney Thompson and Zhe Zhang, Texas A&M assistant professors of geography. The project is funded with a grant from the Texas Sea Grant Program<\/a> from the U.S. Department of Commerce National Oceanic and Atmospheric Administration.<\/p>\n\n\n\n The system that Behzadan and his collaborators are developing works with data that can easily be captured in a flooded area.<\/p>\n\n\n\nA research idea happened in a \u2018flash\u2019<\/strong><\/h3>\n\n\n\n