Indexing the Trajectories of Moving Objects in Symbolic Indoor Space

Research output: Contribution to journalConference article in JournalResearchpeer-review

53 Citations (Scopus)

Abstract

Indoor spaces accommodate large populations of individuals. With appropriate indoor positioning, e.g., Bluetooth and RFID, in place, large amounts of trajectory data result that may serve as a foundation for a wide variety of applications, e.g., space planning, way finding, and security. This scenario calls for the indexing of indoor trajectories. Based on an appropriate notion of indoor trajectory and definitions of pertinent types of queries, the paper proposes two R-tree based structures for indexing object trajectories in symbolic indoor space. The RTR-tree represents a trajectory as a set of line segments in a space spanned by positioning readers and time. The TP2R-tree applies a data transformation that yields a representation of trajectories as points with extension along the time dimension. The paper details the structure, node organization strategies, and query processing algorithms for each index. An empirical performance study suggests that the two indexes are effective, efficient, and robust. The study also elicits the circumstances under which our proposals perform the best.
Original languageEnglish
Book seriesLecture Notes in Computer Science
Volume5644
Pages (from-to)208-227
ISSN0302-9743
DOIs
Publication statusPublished - 2009
EventThe 11th International Symposium on Spatial and Temporal Databases - Aalborg, Denmark
Duration: 8 Jul 200910 Jul 2009
Conference number: 11

Conference

ConferenceThe 11th International Symposium on Spatial and Temporal Databases
Number11
CountryDenmark
CityAalborg
Period08/07/200910/07/2009

Fingerprint

Moving Objects
Indexing
Trajectories
Trajectory
Positioning
R-tree
Data Transformation
Bluetooth
Query processing
Space applications
Query Processing
Radio Frequency Identification
Line segment
Radio frequency identification (RFID)
Planning
Query
Scenarios
Vertex of a graph

Cite this

@inproceedings{c954a540eb1211deb63d000ea68e967b,
title = "Indexing the Trajectories of Moving Objects in Symbolic Indoor Space",
abstract = "Indoor spaces accommodate large populations of individuals. With appropriate indoor positioning, e.g., Bluetooth and RFID, in place, large amounts of trajectory data result that may serve as a foundation for a wide variety of applications, e.g., space planning, way finding, and security. This scenario calls for the indexing of indoor trajectories. Based on an appropriate notion of indoor trajectory and definitions of pertinent types of queries, the paper proposes two R-tree based structures for indexing object trajectories in symbolic indoor space. The RTR-tree represents a trajectory as a set of line segments in a space spanned by positioning readers and time. The TP2R-tree applies a data transformation that yields a representation of trajectories as points with extension along the time dimension. The paper details the structure, node organization strategies, and query processing algorithms for each index. An empirical performance study suggests that the two indexes are effective, efficient, and robust. The study also elicits the circumstances under which our proposals perform the best.",
author = "Jensen, {Christian S{\o}ndergaard} and Hua Lu and Bin Yang",
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year = "2009",
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language = "English",
volume = "5644",
pages = "208--227",
journal = "Lecture Notes in Computer Science",
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}

Indexing the Trajectories of Moving Objects in Symbolic Indoor Space. / Jensen, Christian Søndergaard; Lu, Hua; Yang, Bin.

In: Lecture Notes in Computer Science, Vol. 5644, 2009, p. 208-227.

Research output: Contribution to journalConference article in JournalResearchpeer-review

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