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AI Case Study

Iowa Department of Transportation uses machine learning to monitor traffic flows during winter

The Iowa Department of Transportation is working with researchers from the Iowa State University to use Google's Tensorflow to automate analysis of road conditions and traffic flow, particularly during the winter season when conditions are challenging.




Project Overview

"Iowa State’s technology helps analyze the visual data gathered from stationary cameras and cameras mounted on snow plows. They also capture traffic information using radar detectors. Machine learning transforms that data into conclusions about road conditions, like identifying congestion and getting first responders to the scenes of accidents faster... Officials in Iowa say machine learning could also be used to predict crash risks and travel speeds, and better understand drivers’ reactions or failures behind the wheel."

Reported Results

Planned; results not yet available


Uses Tensorflow, image classification, potentially some predictive capabilities.



General Operations


The state of Iowa averages about "33 inches of snow every year, keeping roads open and safe is an important challenge. Car accidents tend to spike during the winter months each year in Iowa, as do costly delays."



Incoming data from a variety of sources, including traffic cameras.

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