DocumentCode :
2542167
Title :
Adaptive Temporal Radio Maps for Indoor Location Estimation
Author :
Yin, Jie ; Yang, Qiang ; Lionel Ni
Author_Institution :
Dept. of Comput. Sci., Hong Kong Univ. of Sci. & Technol., Kowloon
fYear :
2005
fDate :
8-12 March 2005
Firstpage :
85
Lastpage :
94
Abstract :
In this paper, we present a novel method to adapt the temporal radio maps for indoor location estimation by offsetting the variational environmental factors using data mining techniques and reference points. Environmental variations, which cause the signals to change from time to time even at the same location, present a challenging task for indoor location estimation in the IEEE 802.11b infrastructure. In such a dynamic environment, the radio maps obtained in one time period may not be applicable in other time periods. To solve this problem, we apply a regression analysis to learn the temporal predictive relationship between the signal-strength values received by sparsely located reference points and that received by the mobile device. This temporal prediction model can then be used for online localization based on the newly observed signal-strength values at the client side and the reference points. We show that this technique can effectively accommodate the variations of signal-strength values over different time periods without the need to rebuild the radio maps repeatedly. We also show that the location of mobile device can be accurately determined using this technique with lower density in the distribution of the reference points
Keywords :
IEEE standards; data mining; indoor radio; mobility management (mobile radio); prediction theory; regression analysis; wireless LAN; IEEE 802.11b; adaptive temporal radio maps; data mining techniques; indoor location estimation; mobile device; regression analysis; signal-strength values; temporal prediction model; variational environmental factors; Computer science; Data mining; Environmental factors; Mobile computing; Pervasive computing; Phase estimation; Predictive models; RF signals; Radio frequency; Regression analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing and Communications, 2005. PerCom 2005. Third IEEE International Conference on
Conference_Location :
Kauai Island, HI
Print_ISBN :
0-7695-2299-8
Type :
conf
DOI :
10.1109/PERCOM.2005.7
Filename :
1392745
Link To Document :
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