The Overlay Media context engine has been built to enable personal, context-aware user experiences. For example, the mobile device can, upon detecting that the user is travelling in a car, automatically provide information to the user via synthesized voice e.g. read out incoming SMS messages. Or when the user nears their home, the mobile device can pre-fetch content that the user regularly views at that location e.g. Facebook content. Alternatively, the mobile device can deactivate services that are not used when performing specific activities e.g. turn off Bluetooth when the user is sat in their office.

In order to enable this behaviour each application needs to understand the users' context. This requires the use of context sensing technologies e.g. activity recognition techniques to understand when the user is walking, driving etc. location techniques to understand where the user is and machine learning techniques to understand what the user is doing. Implementing these behaviours on an application by application basis results in a duplication of development effort and a duplication of on device resource usage. That is, there will be multiple applications performing the same task e.g. sensing that the user is walking. This results in an ineffective use of resources.

Overlay Media's context engine addresses this issue by providing a single interface for multiple high-level applications to connect to in order to obtain contextual information. The engine intelligently internally manages multiple context sensing services in order to provide the contextual information that is needed by the higher level applications.