Abstract
Spatial database indexes are basically designed to speed up retrievals where it is usually assumed that the objects of interest are constant unless conspicuously updated. Therefore, capturing continuously moving objects in traditional spatial indexes will require frequent updates of the locations of these objects. This paper outlines a PhD thesis that addresses the challenges of indexing the moving objects in indoor spaces. The main goal of this thesis is to develop new indoor index structures for moving objects focusing on the following four challenges: (1) introducing a queries taxonomy for moving objects to illustrate the query types for the databases of moving objects; (2) introducing an adjacency index structure for moving objects in indoor spaces; (3) capturing both spatial and temporal properties in an indoor data structure; (4) introducing an index structure for moving objects in indoor spaces that is based on a specific type of movement pattern.
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