Ford announced last week that it will use Google's new Prediction API, which uses cloud computing, storage and external data for analytics, and combine it with its own research and development on driver predictive behavior.
The idea is that cars would have enough information to change their performance to offer drivers both solid performance and optimum fuel efficiency, based on both historical driving data, drivers' preferred routes, and real-time information including traffic, weather, and time of day.
“The Google Prediction API allows us to utilize information that an individual driver creates over time and make that information actionable,” said Ford Research and Innovations' Ryan McGee, in a statement. “Between Google Prediction and our own research, we are discovering ways to make information work for the driver and help deliver optimal vehicle performance.”
The Prediction API accesses Google's machine learning algorithms to analyze historic data and predict likely future outcomes. It can be used for Recommendation systems, Spam detection, Customer sentiment analysis, Upsell opportunity analysis, Message routing decisions, Diagnostics, Document and email classification, Suspicious activity identification, Churn analysis or Language identification.
The API would also evaluate the overall trip to manage onboard energy and to ensure sufficient battery power was there when needed. It would also store the different habits of, say, a lead-footed driver and a more economical one, adding those wild cards into its analysis.
A service that automatically switched to electric power could soon become quite practical for Europe, where some cities have established low-emission zones. A plan proposed for eight large French cities, for instance, would impose fines on older passenger cars entering designated zones.
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