Fuzzy topographic modeling in wireless signal tracking analysis

Eddie C.L. Chan; George Baciu; S. C. Mak

Fuzzy topographic modeling in wireless signal tracking analysis

Eddie C.L. Chan
, George Baciu
, S. C. Mak

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

2 Citations (Scopus)

Abstract

Fuzzy logic modelling can be applied to evaluate the behaviour of Wireless Local Area Networks (WLAN) received signal strength (RSS). The behavior study of WLAN signal strength is a pivotal part of WLAN tracking analysis. Previous analytical model has not been addressed effectively for analyzing how the WLAN infrastructure affected the accuracy of tracking. In this paper, we propose a novel fuzzy spatiotemporal topographic model. We implemented the proposed model with a large (9.34 hectare), built-up university, over 2,000 access points to survey and collect WLAN received signal strength (RSS). We applied the Nelder-Mead (NM) method to simplify our previous work on fuzzy color map into a topographic (line-based) map. The new model can provide a detail and quantitative strong representation of WLAN RSS. Finally, it serves as a quicker reference and efficient analysis tool for improving the design of WLAN infrastructure.

Original language	English
Title of host publication	IJCCI 2009 - International Joint Conference on Computational Intelligence, Proceedings
Pages	17-24
Number of pages	8
Publication status	Published - 1 Dec 2009
Event	1st International Joint Conference on Computational Intelligence, IJCCI 2009 - Funchal, Madeira, Portugal Duration: 5 Oct 2009 → 7 Oct 2009

Conference

Conference	1st International Joint Conference on Computational Intelligence, IJCCI 2009
Country/Territory	Portugal
City	Funchal, Madeira
Period	5/10/09 → 7/10/09

Keywords

Fuzzy logic
Received signal strength
Topographic mapping
Wireless signal tracking

ASJC Scopus subject areas

Artificial Intelligence
Computational Theory and Mathematics

Cite this

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title = "Fuzzy topographic modeling in wireless signal tracking analysis",

abstract = "Fuzzy logic modelling can be applied to evaluate the behaviour of Wireless Local Area Networks (WLAN) received signal strength (RSS). The behavior study of WLAN signal strength is a pivotal part of WLAN tracking analysis. Previous analytical model has not been addressed effectively for analyzing how the WLAN infrastructure affected the accuracy of tracking. In this paper, we propose a novel fuzzy spatiotemporal topographic model. We implemented the proposed model with a large (9.34 hectare), built-up university, over 2,000 access points to survey and collect WLAN received signal strength (RSS). We applied the Nelder-Mead (NM) method to simplify our previous work on fuzzy color map into a topographic (line-based) map. The new model can provide a detail and quantitative strong representation of WLAN RSS. Finally, it serves as a quicker reference and efficient analysis tool for improving the design of WLAN infrastructure.",

keywords = "Fuzzy logic, Received signal strength, Topographic mapping, Wireless signal tracking",

author = "Chan, \{Eddie C.L.\} and George Baciu and Mak, \{S. C.\}",

year = "2009",

month = dec,

day = "1",

language = "English",

isbn = "9789896740146",

pages = "17--24",

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note = "1st International Joint Conference on Computational Intelligence, IJCCI 2009 ; Conference date: 05-10-2009 Through 07-10-2009",

}

TY - GEN

T1 - Fuzzy topographic modeling in wireless signal tracking analysis

AU - Chan, Eddie C.L.

AU - Baciu, George

AU - Mak, S. C.

PY - 2009/12/1

Y1 - 2009/12/1

N2 - Fuzzy logic modelling can be applied to evaluate the behaviour of Wireless Local Area Networks (WLAN) received signal strength (RSS). The behavior study of WLAN signal strength is a pivotal part of WLAN tracking analysis. Previous analytical model has not been addressed effectively for analyzing how the WLAN infrastructure affected the accuracy of tracking. In this paper, we propose a novel fuzzy spatiotemporal topographic model. We implemented the proposed model with a large (9.34 hectare), built-up university, over 2,000 access points to survey and collect WLAN received signal strength (RSS). We applied the Nelder-Mead (NM) method to simplify our previous work on fuzzy color map into a topographic (line-based) map. The new model can provide a detail and quantitative strong representation of WLAN RSS. Finally, it serves as a quicker reference and efficient analysis tool for improving the design of WLAN infrastructure.

AB - Fuzzy logic modelling can be applied to evaluate the behaviour of Wireless Local Area Networks (WLAN) received signal strength (RSS). The behavior study of WLAN signal strength is a pivotal part of WLAN tracking analysis. Previous analytical model has not been addressed effectively for analyzing how the WLAN infrastructure affected the accuracy of tracking. In this paper, we propose a novel fuzzy spatiotemporal topographic model. We implemented the proposed model with a large (9.34 hectare), built-up university, over 2,000 access points to survey and collect WLAN received signal strength (RSS). We applied the Nelder-Mead (NM) method to simplify our previous work on fuzzy color map into a topographic (line-based) map. The new model can provide a detail and quantitative strong representation of WLAN RSS. Finally, it serves as a quicker reference and efficient analysis tool for improving the design of WLAN infrastructure.

KW - Fuzzy logic

KW - Received signal strength

KW - Topographic mapping

KW - Wireless signal tracking

UR - https://www.scopus.com/pages/publications/77955446296

M3 - Conference article published in proceeding or book

SN - 9789896740146

SP - 17

EP - 24

BT - IJCCI 2009 - International Joint Conference on Computational Intelligence, Proceedings

T2 - 1st International Joint Conference on Computational Intelligence, IJCCI 2009

Y2 - 5 October 2009 through 7 October 2009

ER -

Fuzzy topographic modeling in wireless signal tracking analysis

Abstract

Conference

Keywords

ASJC Scopus subject areas

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