Title :
Using ZeeBee Sensor Network with artifical neural network for indoor location
Author :
Chen, Rung-Ching ; Lin, Yu-Hsiang
Author_Institution :
Dept. of Inf. Manage., Chaoyang Univ. of Technol., Taichung, Taiwan
Abstract :
In recent years, the expanding of wireless technologies has applied to position location and context-aware computing. The position location methods are divided into indoor and outdoor types. GPS (Global Position System) is usually used in outdoor location but it was not applied to indoor environment. In this paper, we will propose a new method using ZigBee to perform indoor location tracking. This method uses the value of LQI (Link Quality Indicator) and neural network for indoor position location. Experiment results indicated our proposed method is useful.
Keywords :
Global Positioning System; Zigbee; indoor radio; neural nets; ubiquitous computing; GPS; Global Position System; LQI; ZeeBee sensor network; artificial neural network; context aware computing; indoor environment; indoor location tracking; indoor position location; link quality indicator; outdoor location; wireless technology; Neural networks; Radiofrequency identification; Training; Wireless LAN; Wireless communication; Wireless sensor networks; Zigbee; indoor location; lqi; neural network; zigbee;
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-2130-4
DOI :
10.1109/ICNC.2012.6234591