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A Compact Representation of Indoor Trajectories

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Farina_Antonio_2022_Compact_representation_indoor_trajectorie.pdf - Accepted version (562.1Kb)
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http://hdl.handle.net/2183/40123
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  • Investigación (FIC) [1728]
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Título
A Compact Representation of Indoor Trajectories
Autor(es)
Fariña, Antonio
Gutiérrez-Asorey, Pablo
Ladra, Susana
Penabad, Miguel R.
Varela Rodeiro, Tirso
Data
2022-01
Cita bibliográfica
A. Fariña, P. Gutiérrez-Asorey, S. Ladra, M. R. Penabad and T. V. Rodeiro, "A Compact Representation of Indoor Trajectories," in IEEE Pervasive Computing, vol. 21, no. 1, pp. 57-64, 1 Jan.-March 2022, doi: 10.1109/MPRV.2021.3120801.
Resumo
[Abstract]: We present a system that combines indoor positioning with a compression algorithm for trajectories in the context of a nursing home. Our aim is to gather and effectively represent the location of the residents and caregivers along time, while allowing for efficient access to those data. We briefly show the system architecture that enables the automatic tracking of user’s movements and consequently the gathering of their locations. Then, we present indRep, our compact representation to handle positioning data using grammar-based compression, and provide two basic operations that enable pseudo-random access to the data. Finally, we include experiments that show that indRep is competitive with well-know general-purpose compressors in terms of compression effectiveness and also provides fast access to the compressed data. We expect both features would enable exploitation functionalities even in computers with rather low computational resources.
Palabras chave
Trajectory
Maintenance engineering
Medical services
Receivers
Proposals
Tracking
 
Versión do editor
https://doi.org/10.1109/MPRV.2021.3120801
Dereitos
Copyright © 2022, IEEE
ISSN
1558-2590
1536-1268
 

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