Indexing the Trajectories of Moving Objects in Symbolic Indoor Space

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53 Citationer (Scopus)

Resumé

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.
OriginalsprogEngelsk
BogserieLecture Notes in Computer Science
Vol/bind5644
Sider (fra-til)208-227
ISSN0302-9743
DOI
StatusUdgivet - 2009
BegivenhedThe 11th International Symposium on Spatial and Temporal Databases - Aalborg, Danmark
Varighed: 8 jul. 200910 jul. 2009
Konferencens nummer: 11

Konference

KonferenceThe 11th International Symposium on Spatial and Temporal Databases
Nummer11
LandDanmark
ByAalborg
Periode08/07/200910/07/2009

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

Bibliografisk note

Titel:
Advances in Spatial and Temporal Databases

Oversat titel:


Oversat undertitel:


Forlag:
Springer

ISBN (Trykt):


ISBN (Elektronisk):
978-3-642-02981-3

Publikationsserier:
Lecture Notes in Computer Science, Springer Verlag, 0302-9743, 1611-3349, 5644

Citer dette

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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",
note = "Titel: Advances in Spatial and Temporal Databases Oversat titel: Oversat undertitel: Forlag: Springer ISBN (Trykt): ISBN (Elektronisk): 978-3-642-02981-3 Publikationsserier: Lecture Notes in Computer Science, Springer Verlag, 0302-9743, 1611-3349, 5644",
year = "2009",
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language = "English",
volume = "5644",
pages = "208--227",
journal = "Lecture Notes in Computer Science",
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publisher = "Physica-Verlag",

}

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

I: Lecture Notes in Computer Science, Bind 5644, 2009, s. 208-227.

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

TY - GEN

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AU - Jensen, Christian Søndergaard

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PY - 2009

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AB - 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.

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