Conformal Prediction for indoor localisation with fingerprinting method

Khuong An Nguyen; Zhiyuan Luo

doi:10.1007/978-3-642-33412-2_22

Conformal Prediction for indoor localisation with fingerprinting method

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Indoor localisation is the state-of-the-art to identify and observe a moving human or object inside a building. Location Fingerprinting is a cost-effective software-based solution utilising the built-in wireless signal of the building to estimate the most probable position of a real-time signal data. In this paper, we apply the Conformal Prediction (CP) algorithm to further enhance the Fingerprinting method. We design a new nonconformity measure with the Weighted K-nearest neighbours (W-KNN) as the underlying algorithm. Empirical results show good performance of the CP algorithm.

Original language	English
Title of host publication	IFIP Advances in Information and Communication Technology
Publisher	Springer
Pages	214-223
Number of pages	10
ISBN (Print)	9783642334115
DOIs	https://doi.org/10.1007/978-3-642-33412-2_22
Publication status	Published - 2012

Publication series

Name	IFIP Advances in Information and Communication Technology
Publisher	Springer

Access to Document

10.1007/978-3-642-33412-2_22

Cite this

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title = "Conformal Prediction for indoor localisation with fingerprinting method",

abstract = "Indoor localisation is the state-of-the-art to identify and observe a moving human or object inside a building. Location Fingerprinting is a cost-effective software-based solution utilising the built-in wireless signal of the building to estimate the most probable position of a real-time signal data. In this paper, we apply the Conformal Prediction (CP) algorithm to further enhance the Fingerprinting method. We design a new nonconformity measure with the Weighted K-nearest neighbours (W-KNN) as the underlying algorithm. Empirical results show good performance of the CP algorithm.",

author = "Nguyen, {Khuong An} and Zhiyuan Luo",

year = "2012",

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language = "English",

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series = "IFIP Advances in Information and Communication Technology",

publisher = "Springer",

pages = "214--223",

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T1 - Conformal Prediction for indoor localisation with fingerprinting method

AU - Nguyen, Khuong An

AU - Luo, Zhiyuan

PY - 2012

Y1 - 2012

N2 - Indoor localisation is the state-of-the-art to identify and observe a moving human or object inside a building. Location Fingerprinting is a cost-effective software-based solution utilising the built-in wireless signal of the building to estimate the most probable position of a real-time signal data. In this paper, we apply the Conformal Prediction (CP) algorithm to further enhance the Fingerprinting method. We design a new nonconformity measure with the Weighted K-nearest neighbours (W-KNN) as the underlying algorithm. Empirical results show good performance of the CP algorithm.

AB - Indoor localisation is the state-of-the-art to identify and observe a moving human or object inside a building. Location Fingerprinting is a cost-effective software-based solution utilising the built-in wireless signal of the building to estimate the most probable position of a real-time signal data. In this paper, we apply the Conformal Prediction (CP) algorithm to further enhance the Fingerprinting method. We design a new nonconformity measure with the Weighted K-nearest neighbours (W-KNN) as the underlying algorithm. Empirical results show good performance of the CP algorithm.

U2 - 10.1007/978-3-642-33412-2_22

DO - 10.1007/978-3-642-33412-2_22

M3 - Conference contribution

SN - 9783642334115

T3 - IFIP Advances in Information and Communication Technology

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BT - IFIP Advances in Information and Communication Technology

PB - Springer

ER -