INTELLIGENT AGENT TECHNOLOGY FOR CELLULAR-ASSISTED GPS POSITIONING USING BAYESIAN AND SELF-ORGANIZING MAP APPROACHES

An intelligent agent equipped with cellular-assisted Global Positioning System (GPS) positioning has been proposed in this paper. The positioning technique has been enhanced by using Bayesian and Self-Organizing Maps approaches. Due to the overlapping of coverage areas of cellular towers, convention...

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Main Authors: Choo, Wou Onn, Lee, Lam Hong, Tay, Yen Pei, Goh, Khang Wen, Chue, Wen Yeen, Suliman, Mohamed Fati
Format: Article
Language:English
Published: INTI International University 2018
Subjects:
Online Access:http://eprints.intimal.edu.my/1498/
http://eprints.intimal.edu.my/1498/1/v1_2018_28.pdf
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author Choo, Wou Onn
Lee, Lam Hong
Tay, Yen Pei
Goh, Khang Wen
Chue, Wen Yeen
Suliman, Mohamed Fati
author_facet Choo, Wou Onn
Lee, Lam Hong
Tay, Yen Pei
Goh, Khang Wen
Chue, Wen Yeen
Suliman, Mohamed Fati
author_sort Choo, Wou Onn
building INTI Institutional Repository
collection Online Access
description An intelligent agent equipped with cellular-assisted Global Positioning System (GPS) positioning has been proposed in this paper. The positioning technique has been enhanced by using Bayesian and Self-Organizing Maps approaches. Due to the overlapping of coverage areas of cellular towers, conventional cellular-based positioning techniques have been reported to be inaccurate. Current cellular-assisted GPS positioning techniques are cost ineffective as extensive investments on hardware deployments are required in order to achieve the highly accurate positioning performance. A relatively low cost approach is presented in this paper for more economical and satisfactory cellular-assisted GPS positioning. Raw location information, in the form of cellular identity (ID) and GPS coordinate pairs, are acquired by using equipment such as smart phones and GPS trackers. These raw information were categorized into categories according to the distribution patterns of cellular towers. The cellular ID and GPS coordinate pairs were further grouped within each of the individual cellular IDs. An intelligent software agent equipped with data mining capabilities was then deployed to collect and process the device-coordinates in order to predict the optimal GPS coordinates of the cellular ID. This results to the determination of a virtual cellular tower location for each cellular ID, to provide more precise location positioning. Experimental results show that the prediction of location using GPS coordinate of cellular IDs helps in improving the contemporary cellular-assisted GPS positioning technique to sub-kilometre accuracy.
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spelling intimal-14982021-05-10T07:45:09Z http://eprints.intimal.edu.my/1498/ INTELLIGENT AGENT TECHNOLOGY FOR CELLULAR-ASSISTED GPS POSITIONING USING BAYESIAN AND SELF-ORGANIZING MAP APPROACHES Choo, Wou Onn Lee, Lam Hong Tay, Yen Pei Goh, Khang Wen Chue, Wen Yeen Suliman, Mohamed Fati Q Science (General) QA75 Electronic computers. Computer science QA76 Computer software An intelligent agent equipped with cellular-assisted Global Positioning System (GPS) positioning has been proposed in this paper. The positioning technique has been enhanced by using Bayesian and Self-Organizing Maps approaches. Due to the overlapping of coverage areas of cellular towers, conventional cellular-based positioning techniques have been reported to be inaccurate. Current cellular-assisted GPS positioning techniques are cost ineffective as extensive investments on hardware deployments are required in order to achieve the highly accurate positioning performance. A relatively low cost approach is presented in this paper for more economical and satisfactory cellular-assisted GPS positioning. Raw location information, in the form of cellular identity (ID) and GPS coordinate pairs, are acquired by using equipment such as smart phones and GPS trackers. These raw information were categorized into categories according to the distribution patterns of cellular towers. The cellular ID and GPS coordinate pairs were further grouped within each of the individual cellular IDs. An intelligent software agent equipped with data mining capabilities was then deployed to collect and process the device-coordinates in order to predict the optimal GPS coordinates of the cellular ID. This results to the determination of a virtual cellular tower location for each cellular ID, to provide more precise location positioning. Experimental results show that the prediction of location using GPS coordinate of cellular IDs helps in improving the contemporary cellular-assisted GPS positioning technique to sub-kilometre accuracy. INTI International University 2018 Article PeerReviewed text en http://eprints.intimal.edu.my/1498/1/v1_2018_28.pdf Choo, Wou Onn and Lee, Lam Hong and Tay, Yen Pei and Goh, Khang Wen and Chue, Wen Yeen and Suliman, Mohamed Fati (2018) INTELLIGENT AGENT TECHNOLOGY FOR CELLULAR-ASSISTED GPS POSITIONING USING BAYESIAN AND SELF-ORGANIZING MAP APPROACHES. INTI JOURNAL, 2018 (28). ISSN e2600-7320 http://intijournal.intimal.edu.my/intijournal.htm
spellingShingle Q Science (General)
QA75 Electronic computers. Computer science
QA76 Computer software
Choo, Wou Onn
Lee, Lam Hong
Tay, Yen Pei
Goh, Khang Wen
Chue, Wen Yeen
Suliman, Mohamed Fati
INTELLIGENT AGENT TECHNOLOGY FOR CELLULAR-ASSISTED GPS POSITIONING USING BAYESIAN AND SELF-ORGANIZING MAP APPROACHES
title INTELLIGENT AGENT TECHNOLOGY FOR CELLULAR-ASSISTED GPS POSITIONING USING BAYESIAN AND SELF-ORGANIZING MAP APPROACHES
title_full INTELLIGENT AGENT TECHNOLOGY FOR CELLULAR-ASSISTED GPS POSITIONING USING BAYESIAN AND SELF-ORGANIZING MAP APPROACHES
title_fullStr INTELLIGENT AGENT TECHNOLOGY FOR CELLULAR-ASSISTED GPS POSITIONING USING BAYESIAN AND SELF-ORGANIZING MAP APPROACHES
title_full_unstemmed INTELLIGENT AGENT TECHNOLOGY FOR CELLULAR-ASSISTED GPS POSITIONING USING BAYESIAN AND SELF-ORGANIZING MAP APPROACHES
title_short INTELLIGENT AGENT TECHNOLOGY FOR CELLULAR-ASSISTED GPS POSITIONING USING BAYESIAN AND SELF-ORGANIZING MAP APPROACHES
title_sort intelligent agent technology for cellular-assisted gps positioning using bayesian and self-organizing map approaches
topic Q Science (General)
QA75 Electronic computers. Computer science
QA76 Computer software
url http://eprints.intimal.edu.my/1498/
http://eprints.intimal.edu.my/1498/
http://eprints.intimal.edu.my/1498/1/v1_2018_28.pdf