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A Compact Representation of Indoor Trajectories

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In this article, 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… Click to show full abstract

In this article, 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 pseudorandom access to the data. Finally, we include experiments that show that indRep is competitive with well-known 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.

Keywords: compression; compact representation; representation indoor; access; indoor trajectories; representation

Journal Title: IEEE Pervasive Computing
Year Published: 2022

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