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http://dx.doi.org/10.9718/JBER.2007.28.4.494

Position Recognition and User Identification System Using Signal Strength Map in Home Healthcare Based on Wireless Sensor Networks (WSNs)  

Yang, Yong-Ju (Control & Perception Research Team, Division for Applied Robot Technology, Korea Institute of Industrial Technology(KITECH))
Lee, Jung-Hoon (Department of Biomedical Engineering, Graduate School of Yonsei University)
Song, Sang-Ha (Department of Biomedical Engineering, Graduate School of Yonsei University)
Yoon, Young-Ro (Department of Biomedical Engineering, Graduate School of Yonsei University)
Publication Information
Journal of Biomedical Engineering Research / v.28, no.4, 2007 , pp. 494-502 More about this Journal
Abstract
Ubiquitous location based services (u-LBS) will be interested to an important services. They can easily recognize object position at anytime, anywhere. At present, many researchers are making a study of the position recognition and tracking. This paper consists of postion recognition and user identification system. The position recognition is based on location under services (LBS) using a signal strength map, a database is previously made use of empirical measured received signal strength indicator (RSSI). The user identification system automatically controls instruments which is located in home. Moreover users are able to measures body signal freely. We implemented the multi-hop routing method using the Star-Mesh networks. Also, we use the sensor devices which are satisfied with the IEEE 802.15.4 specification. The used devices are the Nano-24 modules in Octacomm Co. Ltd. A RSSI is very important factor in position recognition analysis. It makes use of the way that decides position recognition and user identification in narrow indoor space. In experiments, we can analyze properties of the RSSI, draw the parameter about position recognition. The experimental result is that RSSI value is attenuated according to increasing distances. It also derives property of the radio frequency (RF) signal. Moreover, we express the monitoring program using the Microsoft C#. Finally, the proposed methods are expected to protect a sudden death and an accident in home.
Keywords
wireless sensor networks (WSNs); received signal strength indicator (RSSI); position recognition; identification; signal strength map;
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