UPDATED 17:40 EDT / SEPTEMBER 16 2016

NEWS

Alphabet buys Urban Engines to supercharge Google Maps

Alphabet Inc., the parent company of Google, has acquired Urban Engines Inc., a Big Data startup that specializes in using location analytics to power smart urban planning.

Urban Engines will be joining the Google Maps team, and while the startup did not say exactly how Google will be using its tools, the Urban Engines team did say that it’s “excited to combine forces to help organizations better understand how the world moves.”

Like many professions in recent years, urban planning has been reshaped by the Big Data explosion. Thanks to tools like Bluetooth beacons, computer vision and so on, city planners have more data than ever on foot and and vehicle traffic, and companies like Urban Engines are offering tools to sift through that data and offer valuable insights on how to better design roads, public spaces and more.

“With the rapid growth in sensors (GPS, beacons, etc.) on smartphones and cars and transit, we are now truly in the age of Internet of Moving Things,” the Urban Engines team said in a blog post. “The potential to improve the lives of millions of commuters, by learning from commuting behavior patterns, reshaping congestion and creating new consumer services in each minute-mile is incredible. In fact, we have an opportunity to create an urban OS — an intelligent software overlay for our real world.”

Real life SimCity

Urban Engines explained that accurately gathering city-wide location and time data in a single-moment snapshot is incredibly difficult and requires a significant amount of computing power. That’s why the startup had to build specialized algorithms for dealing with the information while also relying on cloud computing.

“For us CS geeks, space/time data is a new ‘data type’ with exciting new scaling and algorithmic challenges,” Urban Engines explained. “Over the past few years, we created Warp — a powerful, new space/time engine that stitches together millions of commuters and vehicles with special algorithms and cloud power.

“For example, how to reconstruct the flow of millions of commuters each day, how to analyze and learn from hotspots from this data at a large scale, and optimize trade-offs in ‘what if scenarios’ using large-scale emulations of real-world systems (like in SimCity).”

Neither Urban Engines nor Alphabet have revealed how this location data system will be used by Google Maps. But the service potentially could be used to help predict traffic patterns and feed valuable road analysis to Google’s self-driving vehicle projects.

Image courtesy of Urban Engines

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