Roadway-related incidents are a leading cause of flood fatalities nationwide, but limited flood-reporting tools make it difficult to evaluate road conditions in real time.
Roadway-related incidents are a leading cause of flood fatalities nationwide, but limited flood-reporting tools make it difficult to evaluate road conditions in real time.
Existing tools — traffic cameras, water-level sensors and even social media data — can provide observations of flooding, but they are often not primarily designed for sensing flood conditions on roads and do not work in conjunction. A network of sensors could improve situational flood level awareness; however, they are expensive to operate at scale.
Engineers at Rice University have developed a possible solution to this problem: an automated data fusion framework called OpenSafe Fusion. Short for Open Source Situational Awareness Framework for Mobility using Data Fusion, OpenSafe Fusion leverages existing individual reporting mechanisms and public data sources to sense quickly evolving road conditions during urban flooding events, which are becoming increasingly frequent.
Read more at: Rice University
Rice engineers Pranavesh Panakkal (left) and Jamie Padgett (right) analyze a map of road links in the Houston area. (Photo Credit: Jeff Fitlow)
