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Memorias de investigación
Research Publications in journals:
MULTI-AGENT LOCATION SYSTEM IN WIRELESS NETWORKS
Year:2012
Research Areas
  • Artificial intelligence
Information
Abstract
In this paper we propose a flexible Multi-Agent Architecture together with a methodology for indoor location which allows us to locate any mobile station (MS) such as a Laptop, Smartphone, Tablet or a robotic system in an indoor environment using wireless technology. Our technology is complementary to the GPS location finder as it allows us to locate a mobile system in a specific room on a specific floor using the Wi-Fi networks. The idea is that any MS will have an agent known at a Fuzzy Location Software Agent (FLSA) with a minimum capacity processing at its disposal which collects the power received at different Access Points distributed around the floor and establish its location on a plan of the floor of the building. In order to do so it will have to communicate with the Fuzzy Location Manager Software Agent (FLMSA). The FLMSAs are local agents that form part of the management infrastructure of the Wi-Fi network of the Organization. The FLMSA implements a location estimation methodology divided into three phases (measurement, calibration and estimation) for locating mobile stations (MS). Our solution is a fingerprint-based positioning system that overcomes the problem of the relative effect of doors and walls on signal strength and is independent of the network device manufacturer. In the measurement phase, our system collects received signal strength indicator (RSSI) measurements from multiple access points. In the calibration phase, our system uses these measurements in a normalization process to create a radio map, a database of RSS patterns. Unlike traditional radio map-based methods, our methodology normalizes RSS measurements collected at different locations on a floor. In the third phase, we use Fuzzy Controllers to locate an MS on the plan of the floor of a building. Experimental results demonstrate the accuracy of the proposed method. From these results it is clear that the system is highly likely to be able to locate an MS in a room or adjacent room
International
Si
JCR
Si
Title
Expert Systems With Applications
ISBN
0957-4174
Impact factor JCR
2,203
Impact info
Datos JCR del año 2011
Volume
En proceso
http://dx.doi.org/10.1016/j.eswa.2012.10.037
Journal number
En proceso
From page
En proceso
To page
En proceso
Month
SIN MES
Ranking
Q1 (22/111)
Participants
  • Autor: Luis Mengual Galan (UPM)
  • Autor: Oscar Marban Gallego (UPM)
  • Autor: Santiago Eibe Garcia (UPM)
  • Autor: Ernestina Menasalvas Ruiz (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Data Mining Engineering (DaME) Ingeniería de Minería de datos
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