DYNAMIC ABSTRACTION AND PROVISIONING OF CONTEXT INFORMATION

Venet Osmani, Sasitharan Balasubramaniam

    Research output: Other contribution

    Abstract

    Ubiquitous computing environments are perceived as having a wide array of embedded sensors and other computing artefacts that provide information regarding the current state of the physical environment. Utilisation of such information by contextaware applications has the potential to alter the surroundings of users in order to adapt the environment to suit the user’s needs and assist in their tasks. However, as the primary sources of context information, sensors1 provide raw data that typically stand at a low point in the abstraction scale. Data yielded from these artefacts might not be in the required format or type, or generally might not be useful unless it is processed and combined with data from other sources. As a consequence the end result is a generation of information that has little or no value when consumed in isolation. Here, an approach that will enable flexible transformation, composition and interpretation of the low-level data into high-level context information will aid context-aware applications. Raising the level of abstraction of context information, allows context-aware applications to adapt the environment at a level, closer to meeting human expectations of a truly intelligent system rather than simply altering the environment based on single sensor readings. The proposed research programme, described in this report, addresses these issues focusing on a context aggregation process that will process collected data from multiple and diverse sources enabling reasoning over this data to deduce conclusions that cannot directly be sensed from the environment.
    Original languageEnglish
    Publication statusUnpublished - 2005

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