Three-dimensional positioning system using Bluetooth low-energy beacons

Park, Hyunwook; Noh, Jaewon; Cho, Sunghyun

doi:10.1177/1550147716671720

Cited by 16 publications

(11 citation statements)

References 11 publications

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“…Park et al [115] performed 3-dimensional localisation based on triangulation scheme from BLE nodes. The author performed the experiment, whereby 4 BLE beacons would be placed in the periphery of the central node.…”

Section: Radio Frequency Sensorsmentioning

confidence: 99%

Sensor Modalities and Fusion for Robust Indoor Localisation

Kozłowski¹,

Santos-Rodríguez²,

Piechocki³

2019

ICST Transactions on Ambient Systems

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The importance of accurate and efficient positioning and tracking is widely understood. However, there is a pressing lack of progress in the standardisation of methods, as well as generalised framework of their evaluation. The aim of this survey is to discuss the currently prevalent and emerging types of sensors used for location estimation. The intent of this review is to take account of this taxonomy and to provide a wider understanding of the current state-of-the-art. To that end, we outline various sensor modalities, as well as popular fusion and integration techniques, discussing how their combinations can help in various application settings. Firstly, we present the fundamental mechanics behind sensors employed by the localisation community. Furthermore we outline the formal theory behind prominent fusion methods and provide exhaustive implementation examples of each. Finally, we provide points for future discussion regarding localisation sensing, fusion and integration methods.to user's preference and experience. This makes the relative selection space large, and frequently open to interpretation with regard to available resources and constraints.Whilst the survey literature pertaining to localisation systems and methods is large [54,171,181], there exists very little in the way of localisation-centric sensor utilisation. This encompasses the use of bespoke [39] or off-the-shelf [13,118] sensors, specifically for the use of location estimation, robustification and optimisation. This area is extensive [20,35,57,83,136,146], yet very often bundled along with localisation technology surveys, without subsequent scrutiny. We aim to close this gap, by reviewing sensors, their fusion and utilisation as applied to localisation, in contrast to localisation methods, technologies and implementations themselves.Most of the existing localisation surveys include technology-specific reviews [30,54,92,181]. They concentrate upon the methods and algorithms related to indoor localisation [30,92], techniques and technologies [181]. Some work also addresses localisation from the perspective of the device itself, such as smartphones [171]. Xiao et al. study [171] is the most closely related work to our proposed examination. The main difference is, that instead of reviewing the devices as

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Section: Radio Frequency Sensorsmentioning

confidence: 99%

Sensor Modalities and Fusion for Robust Indoor Localisation

Kozłowski¹,

Santos-Rodríguez²,

Piechocki³

2019

ICST Transactions on Ambient Systems

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“…Localization methods for UWB sensors include trilateration [ 12 ], the least-squares (LS) method [ 13 ], partial filtering [ 14 ], and the extended Kalman filter (EKF) [ 15 ]. EKF outperforms other methods regarding positioning accuracy and stability, particularly when the UWB-sensor data have outliers.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Improvement of Indoor Positioning Accuracy for UWB Sensors

Yao

2021

Sensors

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Ultra-wideband (UWB) sensors have been widely applied to indoor positioning. The indoor positioning of UWB sensors usually refers to the positioning of the mobile node that interacts with the anchors through radio for calculating the distance between the mobile node and each of the surrounding anchors. The positioning accuracy of the mobile node is affected by the installation positions of surrounding anchors. A mathematical model was proposed in this paper to respectively analyze the mobile node’s 2-dimensional (2D) and 3-dimensional (3D) positioning errors. The factors influencing the mobile node’s positioning errors were explored through the mathematical models. The best installation positions of surrounding anchors were obtained based on the mathematical models. The mobile node’s 2D and 3D positioning errors were reduced based on the anchor positions derived from the mathematical model. Both computer simulations and practical experiments were implemented to justify the results obtained in the mathematical models.

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“…As part of the project, key elements of the system will be designed and developed, the implementation of methods and algorithms (statistical computer intelligence of deep learning) will be carried out, the design of the communication module will be developed, as well as the analysis of individual technologies and their classification. Then, a demo version of the system will be developed research platform will have all the functionalities of the designed system and will allow for energy management in terms of controlling existing systems (in this case it is exactly about lighting, heating, ventilation and air conditioning), as well as for access control (Styła et al, 2019;Lehtimäki, 2019;Wei et al, 2014;Park, Noh, and Cho, 2016).…”

Section: Introductionmentioning

confidence: 99%

System of Prediction, Optimization and Detection of Users with the Use of Radio Tomography and Computational Intelligence Methods

Styła¹,

Adamkiewicz²,

Wojciechowski³

et al. 2021

ERSJ

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Purpose:The objective of the article is to present a comprehensive building management system using radio tomography methods and computational intelligence methods. Design/Methodology/Approach: The system under development integrates a number of proprietary solutions with solution existing on the market, the best and most recent communication standards for IoT (Internet of Things) devices have been used, the software used allows for high scalability of the platform in the future, easy adaptation to various types of supported facilities, while remaining open to new integration with more and more popular solutions for servicing the Smart Home / Building market. Great emphasis was placed on the visualization on both tomographic solutions and presentation of the current state of the building equipped with a number of software and hardware solutions. Findings: The results of the research work indicate that created building system will optimize energy consumption through direct management of energy receivers as well as indirectly through appropriately adapted control algorithms taking into account many internal and external factors. Detection of people by means of radio tomography, automation adjusting the operation of devices to the environmental conditions of the building and individual rooms, prediction of behavior, appropriate visualizations and the ability to check the energy condition of the building. Practical Implications: The system can be used to analyze and predict the behavior of consumers in any larger facility equipped with standard comfort systems like lighting, heating, ventilation and air conditioning. Originality/Value: The created innovative system, thanks to the ability to accurately determine the position (RTI) and identification of a person (individual tags), will allow to manage building systems in an individual way.

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Three-dimensional positioning system using Bluetooth low-energy beacons

Cited by 16 publications

References 11 publications

Sensor Modalities and Fusion for Robust Indoor Localisation

Sensor Modalities and Fusion for Robust Indoor Localisation

Analysis and Improvement of Indoor Positioning Accuracy for UWB Sensors

System of Prediction, Optimization and Detection of Users with the Use of Radio Tomography and Computational Intelligence Methods

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