Excerpt of full story written by Adele Peters, Fast Company, originally published on Oct 17, 2019
For cities trying to understand how to get more people to walk and bike, one place to start is data about existing pedestrians and cyclists—but the traditional tools to figure out how many people are biking on a particular route, like sensors embedded in roads, are both expensive and time-consuming to use.
A new tool from the mobility analytics company StreetLight Data maps bike and pedestrian data in much more detail, using machine learning to analyze location data from mobile phones and understand how many people are walking, biking, or driving on any particular street throughout the day.
“The ability of cities to be able to understand the movement of people and bikes is really impaired,” says Martin Morzynski of StreetLight Data. “Not until you get into location-based services and GPS data like ours do you actually get to have a comprehensive perspective on literally every street across the city.”
