A Compact Representation of Indoor Trajectories





Publicado en

Actas de las XXVI Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2022)

Licencia Creative Commons


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.


Acerca de Fariña, Antonio

Palabras clave

Compression, Data Structures, Indoor Trajectories
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