Predictive Learning System Overview

The Predictive Learning System is a contextual awareness engine that makes cars smarter and drivers happier, safer and more loyal.

Some key use cases that the Predictive Learning System enables include:

  • Streamlined interfaces that predict the driver’s next destination, maneuver or route
  • Interfaces that learn the driver’s preferences and habits
  • Personalized, contextually relevant search results
  • Safer driving with integration into ADAS
  • Adaptive displays that manage information flow to drivers ensuring they stay focussed on the road

Driver Loyalty

Cars with CloudMade’s Predictive Learning System feel particularly personal to their driver. They know the driver’s next destination recommend their preferred route or their driving style. They react to adverse road conditions caused by traffic, weather or other factors. They recommend the right restaurant, cafe or gas station at just the right time.

Using the Predictive Learning System to reward driver loyalty with a car that gets better and better the more its driven, manufacturers create powerful incentives that keep drivers attached to their brand.

Distributed Learning

By distributing computing between the car and the cloud, the Predictive Learning System leverages the best of both environments.

Inside the car the local components make decisions and recommendations as well as collecting data. A secure connection between the cloud and the car syncs data from the car to the cloud and syncs inferences from the cloud to the car. In the cloud, big data analytics techniques churn through the vast amounts of data the car generates.  The Predictive Learning System leverages CloudMade’s Smart Data technologies to provide advanced distributed learning capabilities.

Private and Secure

CloudMade’s Predictive Learning System uses industry standard encryption technologies to ensure that driver and manufacturer security is maintained. The Predictive Learning System can be configured in a number of different ways, ensuring that particular privacy requirements are met.