Vertical Indexing for Moving Objects in Multifloor Environments

Sultan Alamri, David Taniar, Kinh Nguyen

    Research output: Contribution to journalArticleResearchpeer-review

    3 Citations (Scopus)

    Abstract

    The indexing and tracking of objects moving in indoor spaces has increasingly become an important area of research, which presents a fundamentally different challenge. There are two main reasons for why indoor should be treated as cellular space. Firstly, an indoor space has entities, such as rooms and walls, that constrain the movement of the moving objects. Secondly, the relevant notion of locations of an object is cell based rather than an exact Euclidean coordinate. As a solution, in our earlier works, we proposed a cell-based indexing structure, called the C-tree, for indexing objects moving in indoor space. In this paper, we extend the C-tree to solve another interesting problem. It can be observed that many indoor spaces (such as shopping centers) contain wings/sections. For such a space, there are queries for which the wing/section location of an object, rather than the cellular location, is the relevant answer (e.g., "the object is in the east wing"). In this paper, we propose a new index structure, called the GMI-tree ("GMI" stands for "Graph-based Multidimensional Index"). The GMI-tree is based on two notions of distance, or equivalently, two notions of adjacency: one represents horizontal adjacency and the other represents vertical adjacency.

    Original languageEnglish
    Article number4175298
    Pages (from-to)1-16
    Number of pages16
    JournalMobile Information Systems
    Volume2018
    DOIs
    Publication statusPublished - 2018

    Cite this

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    title = "Vertical Indexing for Moving Objects in Multifloor Environments",
    abstract = "The indexing and tracking of objects moving in indoor spaces has increasingly become an important area of research, which presents a fundamentally different challenge. There are two main reasons for why indoor should be treated as cellular space. Firstly, an indoor space has entities, such as rooms and walls, that constrain the movement of the moving objects. Secondly, the relevant notion of locations of an object is cell based rather than an exact Euclidean coordinate. As a solution, in our earlier works, we proposed a cell-based indexing structure, called the C-tree, for indexing objects moving in indoor space. In this paper, we extend the C-tree to solve another interesting problem. It can be observed that many indoor spaces (such as shopping centers) contain wings/sections. For such a space, there are queries for which the wing/section location of an object, rather than the cellular location, is the relevant answer (e.g., {"}the object is in the east wing{"}). In this paper, we propose a new index structure, called the GMI-tree ({"}GMI{"} stands for {"}Graph-based Multidimensional Index{"}). The GMI-tree is based on two notions of distance, or equivalently, two notions of adjacency: one represents horizontal adjacency and the other represents vertical adjacency.",
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    Vertical Indexing for Moving Objects in Multifloor Environments. / Alamri, Sultan; Taniar, David; Nguyen, Kinh.

    In: Mobile Information Systems, Vol. 2018, 4175298, 2018, p. 1-16.

    Research output: Contribution to journalArticleResearchpeer-review

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    AU - Alamri, Sultan

    AU - Taniar, David

    AU - Nguyen, Kinh

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