A recurrent neural network for inter-localization of mobile phones

Shuai Li; S. Chen; Y. Lou; B. Lu; Y. Liang

doi:10.1109/IJCNN.2012.6252444

A recurrent neural network for inter-localization of mobile phones

Shuai Li, S. Chen, Y. Lou, B. Lu, Y. Liang

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

8 Citations (Scopus)

Abstract

The fact that most mobile phones are equipped with short-range communication devices, such as Bluetooth, etc., and a portion of mobile phones have GPS embedded enables us to envision to roughly localize GPS-free phones recursively and progressively by exploiting the available information. With the position of GPS equipped phones as beacons, and with the Bluetooth connection between neighbor phones as proximity constraints, we formulate the problem as an inequality problem defined on the Bluetooth network. A recurrent neural network is developed to solve the problem distributively in real time. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. Two applications examples are considered and simulated. Simulations demonstrate the effectiveness of the proposed method.

Original language	English
Title of host publication	2012 International Joint Conference on Neural Networks, IJCNN 2012
DOIs	https://doi.org/10.1109/IJCNN.2012.6252444
Publication status	Published - 22 Aug 2012
Externally published	Yes
Event	2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 - Brisbane, QLD, Australia Duration: 10 Jun 2012 → 15 Jun 2012

Conference

Conference	2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012
Country/Territory	Australia
City	Brisbane, QLD
Period	10/06/12 → 15/06/12

Keywords

Bluetooth
localization
mobile phone
Recurrent neural network

ASJC Scopus subject areas

Software
Artificial Intelligence

More information

10.1109/IJCNN.2012.6252444

Cite this

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title = "A recurrent neural network for inter-localization of mobile phones",

abstract = "The fact that most mobile phones are equipped with short-range communication devices, such as Bluetooth, etc., and a portion of mobile phones have GPS embedded enables us to envision to roughly localize GPS-free phones recursively and progressively by exploiting the available information. With the position of GPS equipped phones as beacons, and with the Bluetooth connection between neighbor phones as proximity constraints, we formulate the problem as an inequality problem defined on the Bluetooth network. A recurrent neural network is developed to solve the problem distributively in real time. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. Two applications examples are considered and simulated. Simulations demonstrate the effectiveness of the proposed method.",

keywords = "Bluetooth, localization, mobile phone, Recurrent neural network",

author = "Shuai Li and S. Chen and Y. Lou and B. Lu and Y. Liang",

year = "2012",

month = aug,

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doi = "10.1109/IJCNN.2012.6252444",

language = "English",

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booktitle = "2012 International Joint Conference on Neural Networks, IJCNN 2012",

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}

Li, S, Chen, S, Lou, Y, Lu, B & Liang, Y 2012, A recurrent neural network for inter-localization of mobile phones. in 2012 International Joint Conference on Neural Networks, IJCNN 2012., 6252444, 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012, Brisbane, QLD, Australia, 10/06/12. https://doi.org/10.1109/IJCNN.2012.6252444

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AU - Li, Shuai

AU - Chen, S.

AU - Lou, Y.

AU - Lu, B.

AU - Liang, Y.

PY - 2012/8/22

Y1 - 2012/8/22

N2 - The fact that most mobile phones are equipped with short-range communication devices, such as Bluetooth, etc., and a portion of mobile phones have GPS embedded enables us to envision to roughly localize GPS-free phones recursively and progressively by exploiting the available information. With the position of GPS equipped phones as beacons, and with the Bluetooth connection between neighbor phones as proximity constraints, we formulate the problem as an inequality problem defined on the Bluetooth network. A recurrent neural network is developed to solve the problem distributively in real time. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. Two applications examples are considered and simulated. Simulations demonstrate the effectiveness of the proposed method.

AB - The fact that most mobile phones are equipped with short-range communication devices, such as Bluetooth, etc., and a portion of mobile phones have GPS embedded enables us to envision to roughly localize GPS-free phones recursively and progressively by exploiting the available information. With the position of GPS equipped phones as beacons, and with the Bluetooth connection between neighbor phones as proximity constraints, we formulate the problem as an inequality problem defined on the Bluetooth network. A recurrent neural network is developed to solve the problem distributively in real time. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. Two applications examples are considered and simulated. Simulations demonstrate the effectiveness of the proposed method.

KW - Bluetooth

KW - localization

KW - mobile phone

KW - Recurrent neural network

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DO - 10.1109/IJCNN.2012.6252444

M3 - Conference article published in proceeding or book

SN - 9781467314909

BT - 2012 International Joint Conference on Neural Networks, IJCNN 2012

T2 - 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012

Y2 - 10 June 2012 through 15 June 2012

ER -

A recurrent neural network for inter-localization of mobile phones

Abstract

Conference

Keywords

ASJC Scopus subject areas

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