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Flow Labs' Predictive Traffic Control AI software provides transportation agencies with a more resource efficient way to make roads safer and reduce traffic through end-to-end traffic signal management. The process to monitor and update traffic signal timing is typically highly manual and expensive, often requiring up to 70 hours of expert labor per intersection and installation of costly hardware sensors. For this reason, traffic signals are updated once every five years.
For Flow Labs' Predictive Traffic Control platform to measure and optimize signal timing, it required reliable and accurate data on what is happening on the roads at any given time. And traditional IoT hardware sensors were not providing it.
By integrating Wejo connected vehicle data into its data set, Flow Labs' virtual sensors could generate volume accuracy of 94.4%.
But how did we do it? Read the full case study to discover the full challenges, our solution and results.