Title :
In-building Localization using Neural Networks
Author :
Ahmad, Uzair ; Gavrilov, Andrey ; Nasir, Uzma ; Iqbal, Mahrin ; Cho, Seong Jin ; Lee, Sungyoung
Author_Institution :
Dept. of Comput. Eng., Kyung Hee Univ.
Abstract :
Location awareness is key capability of context-aware ubiquitous environments. Received signal strength (RSS) based localization is increasingly popular choice especially for indoor scenarios after pervasive adoption of IEEE 802.11 wireless LAN. Fundamental requirement of such localization systems is to estimate location from RSS at a particular location. Multi-path propagation effects make RSS to fluctuate in unpredictable manner, introducing uncertainty in location estimation. Moreover, in real life situations RSS values are not available at some locations all the time making the problem more difficult. We employ modular multi-layer perceptron (MMLP) approach to effectively reduce the uncertainty in location estimation system. It provides better location estimation results than other approaches and systematically caters for unavailable signals at estimation time
Keywords :
mobile computing; multilayer perceptrons; wireless LAN; IEEE 802.11 wireless LAN; artificial neural networks; context-aware ubiquitous environments; localization systems; location aware computing; location awareness; location estimation system; modular multilayer perceptron approach; multipath propagation; received signal strength based localization; Artificial neural networks; Calibration; Computer networks; Middleware; Mobile radio mobility management; Neural networks; Pervasive computing; Ubiquitous computing; Uncertainty; Wireless LAN; Artificial Neural Networks; Location Aware Computing; Wireless LAN;
Conference_Titel :
Engineering of Intelligent Systems, 2006 IEEE International Conference on
Conference_Location :
Islamabad
Print_ISBN :
1-4244-0456-8
DOI :
10.1109/ICEIS.2006.1703135
