LANDMARC: Indoor Location Sensing Using Active RFID
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
An Improvement Approach of Indoor Location Sensing Using Active RFID
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2
Active RFID-Based Object Management System in Sensor-Embedded Environment
FGCN '07 Proceedings of the Future Generation Communication and Networking - Volume 02
Comparison between Weighted D-KNN and Other Classifiers for Music Emotion Recognition
ICICIC '08 Proceedings of the 2008 3rd International Conference on Innovative Computing Information and Control
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This paper describes a method for localizing objects in an actual living environment. We have developed this method by using a complementary combination of 1) received signal strength indicators (RSSIs) and vibration data acquired from active RFID tags, and 2) human behavior detected from various types of sensors embedded in the environment. Regarding the former, we use a pattern recognition method to select a feature appeared in SSIs received by several radio frequency (RF) readers at different places and to classify them into a particular location. In our work, we regard the estimated location as the most probable location where the object is placed. As for the latter, we use the detected human behavior to support the estimation based on the analysis of RSSIs. Experiment results showed that the proposed method improved the estimation performance from about 50 to 95% compared with using only RSSIs to localize objects. Moreover, the results also suggested that we can estimate object location indoors without sensors for detecting human position. This indoor object localization method can contribute for constructing an indoor object management system that improves living comfort.