On location models for ubiquitous computing

Becker, Christian; Dürr, Frank

doi:10.1007/s00779-004-0270-2

Cited by 191 publications

(117 citation statements)

References 16 publications

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“…Becker proposed the set-based model [12] to represent the inclusion between indoor elements, which is convenient for range query. The topology-based semantic model [13] represents indoor elements as a single set of objects for indoor analysis.…”

Section: Related Workmentioning

confidence: 99%

“…Besides, indoor positioning usually provides relative locations which need to consult the indoor geometry. Due to the specialty of indoor space, various kinds of indoor space data model have been presented in several domains, such as cognitive navigation services with object feature model [4,5], and the indoor space design and visualization using geometric models [6][7][8][9][10][11], and topological studies of indoor elements with symbolic models [12][13][14][15][16][17]. However, these model representations usually focus on their own domains, and cannot be directly applied to other applications fields.…”

Section: Introductionmentioning

confidence: 99%

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A Multi-Granularity Grid-Based Graph Model for Indoor Space

Wang¹,

Jin

Xiong³

et al. 2014

IJMUE

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Multi-Granularity Grid-Based Graph Model for Indoor Space

Wang¹,

Jin

Xiong³

et al. 2014

IJMUE

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“…Jensen et al [15] and Bercer and Dürr [35] extended this from outdoor to indoor localization by constructing indoor location models. The location model representing the indoor topology at different levels offers a uniform data management infrastructure for different positioning technologies.…”

Section: Introductionmentioning

confidence: 99%

Robust Indoor Mobile Localization with a Semantic Augmented Route Network Graph

Zhou¹,

Zheng²,

Xiong³

et al. 2017

IJGI

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Abstract:In recent years, using smartphones to determine pedestrian locations in indoor environments is an extensively promising technique for improving context-aware applications. However, the applicability and accuracy of the conventional approaches are still limited due to infrastructure-dependence, and there is seldom consideration of the semantic information inherently existing in maps. In this paper, a semantically-constrained low-complexity sensor fusion approach is proposed for the estimation of the user trajectory within the framework of the smartphone-based indoor pedestrian localization, which takes into account the semantic information of indoor space and its compatibility with user motions. The user trajectory is established by pedestrian dead reckoning (PDR) from the mobile inertial sensors, in which the proposed semantic augmented route network graph with adaptive edge length is utilized to provide semantic constraint for the trajectory calibration using a particle filter algorithm. The merit of the proposed method is that it not only exploits the knowledge of the indoor space topology, but also exhausts the rich semantic information and the user motion in a specific indoor space for PDR accumulation error elimination, and can extend the applicability for diverse pedestrian step length modes. Two experiments are conducted in the real indoor environment to verify of the proposed approach. The results confirmed that the proposed method can achieve highly acceptable pedestrian localization results using only the accelerometer and gyroscope embedded in the phones, while maintaining an enhanced accuracy of 1.23 m, with the indoor semantic information attached to each pedestrian's motion.

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“…Context-aware Systems allow to develop a new kind of location-aware mobile applications in different sectors such as healthcare, military, emergencies, and recently retail and agriculture [2,5]. These applications could be represented as a context based scenario where there are individuals who require a satisfaction of their needs and there are providers who can solve these lacks.…”

Section: Introductionmentioning

confidence: 99%

Multi-sensor and Multi Agents Architecture for Indoor Location

Gil

Berlanga

Lopéz

2010

Advances in Intelligent and Soft Computing

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This paper aims to present a new architecture to provide location services using multiple communication technologies such as Wifi, UWB, RFID and so on. Firstly, it will explain the advantages of multi sensor architecture against to use unique indoor location system and the reasons which led us to take this solution. Besides, this paper discusses the suitability of using ontologies for modeling message structure to locate in context-aware services platforms. This message will be described based on the concept of Asterix format used in aerospace multi-sensor communications.

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On location models for ubiquitous computing

Cited by 191 publications

References 16 publications

A Multi-Granularity Grid-Based Graph Model for Indoor Space

A Multi-Granularity Grid-Based Graph Model for Indoor Space

Robust Indoor Mobile Localization with a Semantic Augmented Route Network Graph

Multi-sensor and Multi Agents Architecture for Indoor Location

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