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Home - AT&T uses big data for smart traffic management
Big Data AnalyticsCarriersInternet of Things (IoT)

AT&T uses big data for smart traffic management

by Jeff Hawn October 1, 2015
written by Jeff Hawn October 1, 2015 Share
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Average commuter spends 42 hours each year stuck in traffic

WASHINGTON – Every day AT&T collects millions of pings from its customers’ smartphones. These pings only provide a general idea – within 100 feet – of where an AT&T customer is and do not provide any user identification unless special measures are taken. Now AT&T is looking to capitalize on this location information through a combination of big data analytics and “Internet of Things” technology.

AT&T has partnered with the University of California at Berkeley and the California Department of Transportation to use aggregated data to help manage traffic patterns by using the pings to track commuter patterns and identify trouble spots.

Lessening congestion has a real economic impact. According to AT&T data: “The average American commuter spends 42 hours a year stuck in traffic. That’s almost two days wasted every year. It’s worse for drivers in Los Angeles, who spend 80 hours a year sitting in traffic. And congestion has a cost. In 2014, it cost Americans $160 billion, averaging $960 per auto commuter.” 

Chris Volinsky, AVP of AT&T Labs, told RCR Wireless News, “By leveraging data from our networks, we can make cities more sustainable.”

AT&T can only use the data from its own network, meaning people not on an AT&T network are not included in the data. Volinsky points out this can be easily rectified because AT&T has a good notion of its market share in terms of population and can calculate accordingly.

Moreover, he points out the massive advantages of this real-time data. Urban planners and city officials can now see where people are working, living and shopping without waiting for slow and imprecise census data or cross-referencing multiple sources of information.

This technology is already proven to work. COMSAT is a system of tracking criminal activity and directing police resources accordingly. The system has been in place since the late 1990s and has helped reduce the crime rate nationally. Using big data analytics to track commuter patterns could have a similar impact on traffic congestion and mass transit projects.

AT&T has currently limited its efforts in this field to California Bay Area, but Volinsky is optimistic about the future. “I’d like to see a gradual implementation and there are benefits to scaling up the geographic scale of these systems,” he said.

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Jeff Hawn

Contributing [email protected] Jeff Hawn was born in 1991 and represents the “millennial generation,” the people who have spent their entire lives wired and wireless. His adult life has revolved around cellphones, the Internet, video chat and Google. Hawn has a degree in international relations from American University, and has lived and traveled extensively throughout Europe and Russia. He represents the most valuable, but most discerning, market for wireless companies: the people who have never lived without their products, but are fickle and flighty in their loyalty to one company or product. He’ll be sharing his views – and to a certain extent the views of his generation – with RCR Wireless News readers, hoping to bridge the generational divide and let the decision makers know what’s on the mind of this demographic.

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