Positions, Regions, and Clusters: Strata of Granularity in Location Modelling

  • Hedda R. Schmidtke
  • Michael Beigl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6359)

Abstract

Location models are data structures or knowledge bases used in Ubiquitous Computing for representing and reasoning about spatial relationships between so-called smart objects, i.e. everyday objects, such as cups or buildings, containing computational devices with sensors and wireless communication. The location of an object is in a location model either represented by a region, by a coordinate position, or by a cluster of regions or positions. Qualitative reasoning in location models could advance intelligence of devices, but is impeded by incompatibilities between the representation formats: topological reasoning applies to regions; directional reasoning, to positions; and reasoning about set-membership, to clusters. We present a mathematical structure based on scale spaces giving an integrated semantics to all three types of relations and representations. The structure reflects concepts of granularity and uncertainty relevant for location modelling, and gives semantics to applications of RCC-reasoning and projection-based directional reasoning in location models.

Keywords

Spatial granularity uncertainty location model pervasive computing ubiquitous computing scale space qualitative spatial reasoning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hedda R. Schmidtke
    • 1
  • Michael Beigl
    • 1
  1. 1.Karlsruhe Institute of TechnologyTecOKarlsruheGermany

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