Use of active RFID and environment-embedded sensors for indoor object location estimation

Abstract

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.