FUSION METHODOLOGIES FOR HETEROGENEOUS DATA SOURCES WITHIN A REDUNDANT POSITIONING ARCHITECTURE

Kieran Sullivan, Tom Pfeifer

    Research output: Other contribution

    Abstract

    Ubiquitous computing is growing and emerging as an increasingly significant part of our everyday lives. It offers us the chance to work and interact with others in a safer and more efficient manner. Context awareness – knowledgeable of a user’s surrounding environment, used to characterise the situation of the user - will play a substantial role in achieving this. Location is a major part of context but many factors have contrived to prevent the widespread deployment of location-aware technologies outside of a few niche areas. Included here would be coverage, obtrusiveness, cost, low granularity and a lack of reliability. A Redundant Positioning Architecture will go a long way to combating these drawbacks and this research endeavour aims to implement a prototype positioning system based on the principles of this architecture. This articular document introduces data representation & data fusion in regard to a redundant positioning architecture. The many methodologies available to accomplish this representation and fusion are discussed and a canonical example of how one particular approach evaluates information is presented.
    Original languageEnglish
    Publication statusUnpublished - 2005

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