A Foundation for Efficient Indoor Distance-Aware Query Processing

Lu, Hua; Cao, Xin; Jensen, Christian S.

doi:10.1109/icde.2012.44

Cited by 67 publications

(100 citation statements)

References 13 publications

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“…However, in most applications of indoor navigation, we need geometric data to calculate indoor distance. There are several studies [12,13] to compute the optimal path and its distance between two points in indoor space, and we will discuss indoor distance in Section 6.…”

Section: Topology Between Cellsmentioning

confidence: 99%

“…In addition to geometric models and symbolic space models, other data models were also proposed to facilitate the computation of indoor distance [12,13], which are based on graph models, but also include geometric properties. Additionally, some indoor spatial data models were introduced to support specific indoor spatial information services.…”

Section: Indoor Spatial Data Modelsmentioning

confidence: 99%

“…This means the information about indoor connectivity and architectural components is necessary to compute indoor distance. First, the indoor connectivity, called the indoor accessibility graph [13,23], has to be prepared, as we need a road network graph to compute distance on the road network. An indoor accessibility graph is represented as G = (V, E), where a node n ∈ V is a room or a space unit in indoor space and an edge e ∈ E represents the connectivity between two adjacent space units, for example via the door.…”

Section: Indoor Distancementioning

confidence: 99%

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A Standard Indoor Spatial Data Model—OGC IndoorGML and Implementation Approaches

Kang

2017

IJGI

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Abstract:With the recent progress in indoor spatial data modeling, indoor mapping and indoor positioning technologies, several spatial information services for indoor spaces have been provided like for outdoor spaces. In order to support interoperability between indoor spatial information services, IndoorGML was published by OGC (Open Geospatial Consortium) as a standard data model and XML-based exchange format. While the previous standards, such as IFC (Industrial Foundation Classes) and CityGML covering also indoor space, aim at feature modeling, the goal of IndoorGML is to establish a standard basis for the indoor space model. As IndoorGML defines a minimum data model for indoor space, more efforts are required to discover its potential aspects, which are not explicitly explained in the standard document. In this paper, we investigate the implications and potential aspects of IndoorGML and its basic concept of the cellular space model and discuss the implementation issues of IndoorGML for several purposes. In particular, we discuss the issues on cell determination, subspacing and the hierarchical structure of indoor space from the IndoorGML viewpoint. Additionally, we also focus on two important issues: computation of indoor distance and the implementation of indoor context-awareness services based on IndoorGML. We expect that this paper will serve as a technical document for better understanding of IndoorGML throughout these discussions.

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Section: Topology Between Cellsmentioning

confidence: 99%

Section: Indoor Spatial Data Modelsmentioning

confidence: 99%

Section: Indoor Distancementioning

confidence: 99%

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A Standard Indoor Spatial Data Model—OGC IndoorGML and Implementation Approaches

Kang

2017

IJGI

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“…In [25], Lu et al proposed a distance-aware indoor space structure which integrates indoor space distances.…”

Section: Related Workmentioning

confidence: 99%

Vertical Indexing for Moving Objects in Multifloor Environments

Alamri

Taniar

Nguyen

2018

Mobile Information Systems

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e indexing and tracking of objects moving in indoor spaces has increasingly become an important area of research, which presents a fundamentally different challenge. ere 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"). e 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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“…However, in most applications of indoor navigation, we need geometric data to calculate the routing distance. There are several studies to compute optimal path between to point in indoor space (Lu, H., Cao, X., and Jensen, C. S. 2012), (Yuan, W., and Schneider, M. 2010).…”

Section: Topology Between Cellsmentioning

confidence: 99%

INDOORGML – A STANDARD FOR INDOOR SPATIAL MODELING

Li¹

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:With recent progress of mobile devices and indoor positioning technologies, it becomes possible to provide location-based services in indoor space as well as outdoor space. It is in a seamless way between indoor and outdoor spaces or in an independent way only for indoor space. However, we cannot simply apply spatial models developed for outdoor space to indoor space due to their differences. For example, coordinate reference systems are employed to indicate a specific position in outdoor space, while the location in indoor space is rather specified by cell number such as room number. Unlike outdoor space, the distance between two points in indoor space is not determined by the length of the straight line but the constraints given by indoor components such as walls, stairs, and doors. For this reason, we need to establish a new framework for indoor space from fundamental theoretical basis, indoor spatial data models, and information systems to store, manage, and analyse indoor spatial data. In order to provide this framework, an international standard, called IndoorGML has been developed and published by OGC (Open Geospatial Consortium). This standard is based on a cellular notion of space, which considers an indoor space as a set of non-overlapping cells. It consists of two types of modules; core module and extension module. While core module consists of four basic conceptual and implementation modeling components (geometric model for cell, topology between cells, semantic model of cell, and multi-layered space model), extension modules may be defined on the top of the core module to support an application area. As the first version of the standard, we provide an extension for indoor navigation.

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A Foundation for Efficient Indoor Distance-Aware Query Processing

Cited by 67 publications

References 13 publications

A Standard Indoor Spatial Data Model—OGC IndoorGML and Implementation Approaches

A Standard Indoor Spatial Data Model—OGC IndoorGML and Implementation Approaches

Vertical Indexing for Moving Objects in Multifloor Environments

INDOORGML – A STANDARD FOR INDOOR SPATIAL MODELING

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A Foundation for Efficient Indoor Distance-Aware Query Processing

Cited by 67 publications

References 13 publications

A Standard Indoor Spatial Data Model—OGC IndoorGML and Implementation Approaches

A Standard Indoor Spatial Data Model—OGC IndoorGML and Implementation Approaches

Vertical Indexing for Moving Objects in Multifloor Environments

INDOORGML &ndash; A STANDARD FOR INDOOR SPATIAL MODELING

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INDOORGML – A STANDARD FOR INDOOR SPATIAL MODELING