- Location awareness is ubiquitous
- Internet connectivity is intermittent and expensive
- Content is heterogenous and fragmented
- Vehicle sensors create many gigabytes of data per minute
- Consumers expect highly personalized experiences
Ubiquitous Location. Intermittent Connectivity.
Cars, smartphones, watches, glasses share a few things in common. They all know their location and they all suffer from intermittent internet connectivity. Whether caused by a mobile network blackspot, a congested network or a dropped tethered connection, intermittent internet connectivity negatively impacts the end user experience. CloudMade’s technologies are built with the assumption that internet connectivity is intermittent and expensive.
Technologies like Hybrid Data make content such as POIs, weather, gas prices and more, available offline, using an internet connection to keep local data up to date. Smart Data uses a distributed approach to data processing to minimize costly data transfer whilst making its predictions available to users who maybe offline.
The comlexity of global launches are multiplied by the requirements of consumers to access content from many local sources. CloudMade’s Hybrid Data is a content management solution that addresses these problems in several ways:
- Provides a single solution to manage all types of geodata (road networks, POIs, traffic, gas prices, building polygons, etc)
- A cloud based content management system makes it fast to import location based content from multiple sources
- The content provider is abstracted, meaning that the OEM communicates with a single set of APIs, regardless of the data provider
Making Sense Of User Data
With cars generating such massive volumes of data, CloudMade’s Smart Data helps OEMs manage data collection, storage and analysis. OEMs use Smart Data to:
- Learn about their driver’s habits and intentions
- Deliver streamlined user experiences that anticipate user’s needs
- Provide a comprehensive analytics backend and frontend
Smart Data is a highly adaptable and customizable distributed learning machine. It is used with Mapsafe, a repository for user identity and personal information, to delivery highly customized, personalized services to end users.