Start Date
4-9-2026 12:00 AM
Description
Utah's Uinta Basin is home to over 58,000 residents, yet every route in and out crosses one of three mountain passes, and the nearest Doppler radar is approximately 200 km away. These factors make winter travel hazardous and weather information scarce. BasinWX (basinwx.com) is a public platform developed at the Bingham Research Center that provides real-time weather and air quality data tailored to the Uinta Basin. Its newest feature, BasinWX Roads (basinwx.com/roads), applies a computer vision pipeline to 46 existing Utah Department of Transportation (UDOT) traffic cameras and integrates data from 9 Roadway Weather Information System (RWIS) stations to deliver automated road condition assessments, all without deploying any new hardware. During its first full winter of operation (2025-26), the platform served an estimated 3,325 unique visitors across December through March. Future development includes a machine learning classification pipeline, construction of a labeled UDOT camera dataset, and improved nighttime and low-visibility detection capabilities.
BasinWX: Real-Time Weather and Road Conditions for Utah's Uinta Basin
Utah's Uinta Basin is home to over 58,000 residents, yet every route in and out crosses one of three mountain passes, and the nearest Doppler radar is approximately 200 km away. These factors make winter travel hazardous and weather information scarce. BasinWX (basinwx.com) is a public platform developed at the Bingham Research Center that provides real-time weather and air quality data tailored to the Uinta Basin. Its newest feature, BasinWX Roads (basinwx.com/roads), applies a computer vision pipeline to 46 existing Utah Department of Transportation (UDOT) traffic cameras and integrates data from 9 Roadway Weather Information System (RWIS) stations to deliver automated road condition assessments, all without deploying any new hardware. During its first full winter of operation (2025-26), the platform served an estimated 3,325 unique visitors across December through March. Future development includes a machine learning classification pipeline, construction of a labeled UDOT camera dataset, and improved nighttime and low-visibility detection capabilities.