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Indexing uncertain spatio-temporal data

Published: 29 October 2012 Publication History

Abstract

The advances in sensing and telecommunication technologies allow the collection and management of vast amounts of spatio-temporal data combining location and time information.Due to physical and resource limitations of data collection devices (e.g., RFID readers, GPS receivers and other sensors) data are typically collected only at discrete points of time. In-between these discrete time instances, the positions of tracked moving objects are uncertain. In this work, we propose novel approximation techniques in order to probabilistically bound the uncertain movement of objects; these techniques allow for efficient and effective filtering during query evaluation using an hierarchical index structure.To the best of our knowledge, this is the first approach that supports query evaluation on very large uncertain spatio-temporal databases, adhering to possible worlds semantics. We experimentally show that it accelerates the existing, scan-based approach by orders of magnitude.

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    cover image ACM Conferences
    CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management
    October 2012
    2840 pages
    ISBN:9781450311564
    DOI:10.1145/2396761
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    Published: 29 October 2012

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    1. indexing
    2. uncertain spatio-temporal data
    3. uncertain trajectory

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