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Ford supplements analytics with Google Predictive API: EV optimization on deck?

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Ford said it will supplement its own driver behavior analytics efforts with cloud-based data from Google, which unveiled a Prediction API that can crunch vast amounts of data.

Ford said it will supplement its own driver behavior analytics efforts with cloud-based data from Google, which unveiled a Prediction API that can crunch vast amounts of data.

The effort, unveiled at Google's I/O conference on Tuesday, was pitched as a way to bolster auto efficiency. Electric vehicle optimization is what Ford researchers used in a concept pitch. The aim is to create cars that can optimize fuel economy and efficiency based on driver habits. In other words, smarter cars will anticipate what you need and optimize accordingly.

Ford presented a case study on how Google's Prediction API could be used to enhance the performance of a plug-in hybrid electric vehicle. For instance, an electric vehicle driver could have access to a route that would take into account battery usage, optimize power and work out details to stay in all-electric mode in a city.

Johannes Kristinsson, system architect, Vehicle Controls Architecture and Algorithm Design, at Ford said:

“Ford already offers cloud-based services through Ford SYNC, but those services thus far have been used for infotainment, navigation and real-time traffic purposes to empower the driver. This technology has the potential to empower our vehicles to anticipate the driver's needs.”

Indeed, Ford's Google I/O announcement signals that in-car technology is moving beyond infotainment to more complicated tasks.

Today, the combination of Google and Ford data is largely conceptual---as are the outcomes. Ford envisions something like this happening:

  • Vehicle owner opts into the predictive service and driver data is collected and encrypted. The system learns over time and all data is encrypted for privacy and security.
  • When the car is started Google Prediction will use history to optimize routes and performance based on location and time of day.
  • The car via voice recognition would confirm its predictions based on input from the driver.

The next step for Ford is to use conduct feasibility studies for using Google's Prediction API.

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Larry Dignan

Editor-in-Chief

Editor-in-Chief Larry Dignan is editor-in-chief of SmartPlanet and ZDNet. He is also editorial director of TechRepublic. Previously, he was an editor at eWeek, Baseline and CNET News. He has written for WallStreetWeek.com, Inter@ctive Week, New York Times and Financial Planning. He holds degrees from the Columbia University Graduate School of Journalism and the University of Delaware. He is based in New York but resides in Pennsylvania. Follow him on Twitter. Disclosure