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Iowa may be heaven<\/a>, but it\u2019s a snowy one. With an average of around 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. And dangerous commutes can mean hazards for people and commerce alike: the state is one of the country\u2019s largest producers of agricultural output, and much of that is moved on roads.<\/p>\n To improve road safety and efficiency, the Iowa Department of Transportation has teamed up with researchers at Iowa State University to use machine learning, including our TensorFlow framework<\/a>, to provide insights into traffic behavior. Iowa State\u2019s 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..<\/p>\n This is just one recent example of TensorFlow being used to make drivers\u2019 lives easier across the United States. In California, snow may not be an issue, but traffic certainly is, and college students there used TensorFlow<\/a> to identify pot holes and dangerous road cracks in Los Angeles.<\/p>\n Officials in Iowa say machine learning could also be used to predict crash risks and travel speeds, and better understand drivers\u2019 reactions or failures behind the wheel. But that doesn\u2019t mean drivers will be off the hook. Iowa\u2019s transportation and public safety departments constantly spread the same message: when it\u2019s winter, slow down. Add some time onto your daily commute, and don\u2019t use cruise control during a storm. That way, both drivers and state officials can work together to make winter travel less dreary\u2014and a lot safer.<\/p>\n<\/div>\n<\/div>\n<\/div>\n Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"