Orientation-Aware Indoor Localization Path Loss Prediction Model for Wireless Sensor Networks

There have been a large amount of research and interest in the area of ubiquitous and indoor location aware computing ill the past decade. Anion g several proposed algorithms, fingerprint algorithm stands as one of the most accurate systems for localization. However, there is a lack of theoretical basis and understanding on the orientation of the user. This paper presents a model for orientation-aware indoor location tracking system using a Zigbee based protocol wireless sensor called Sun's SPOT (Small Programmable Object Technology). Our experiment. shows better accuracy in location tracking when orientation acid attenuation factors are considered for the path loss prediction model than the traditional path loss model. Orientation-aware fingerprint algorithm is also examined in our experiment to have a. basis of comparison on an empirical algorithm.