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If you've ever bought anything online, you’re familiar with recommendation engines: buy a shower curtain from Amazon and chances are the site will ask you if you also need a shower curtain rod and rings to go with it.
“No one has done that yet for things in our real, physical world like with locations and Points of Interest”, Brian said. He believes that over the course of the year this sort of predictive computing power will move into the cloud, giving people predictions based on their real-time context. So people could get personalized place recommendations on their phones and even in their cars based on their activity, location and preferences. How about recommendations of jogging paths in a new city based on previous activity and popular routes of other joggers?
Over time, he says, these analytic engines will get more powerful and move from predictive to prescriptive. “So the system tells you what you should do, rather than what you might or will do.” That could be anything like getting an alert to leave 10 minutes earlier to beat traffic or be guided by your map to walk a specific route to work to avoid uncovered sidewalks while in the rain or avoid intersections under construction. “Our teams are working on a next generation platform to make this a reality sooner than you might think,” he said.
One of the biggest hits of 2014 was Uber. “Those taxi ordering apps have been around for a while, but they actually broke the ice,” said Preuss. “They promoted it in a way that people actually noticed.”
The taxi substitute transformed how people get around their cities- especially places like Atlanta and Los Angeles, without public transportation networks to match their vast sprawl. Preuss says that Uber did more than disrupt the taxi industry – it set a high bar for ease of getting around. Passengers never had to fiddle around for cash. Instead they got used to just pushing a button on their phone and hopping in and out of a car without once opening their wallets.
It’s the first step towards what Preuss calls mobility accounts, which will link services with payment and location services like routing and navigation, and will grow in popularity over the coming year. “We’re integrating urban services like taxis, car sharing and public transit with things like booking restaurants and merging them with online payment.”
That kind of integration will make cities even smarter by giving people tools to understand what is around them in a given moment and the capability to do something about it. And with services like Apple Pay, payment will be much easier, too.
How do you think location tech will impact on life in 2015?