A Study on the Indoor Real-Time Tracking System to Reduce the Interference Problem

The real-time tracking system is an essential component in the development of low cost sensor networks to be used in pervasive and ubiquitous computing. In this paper we address the interference problem of the sensor network platform that uses ultrasonic for location tracking. We also present a novel scheme reducing the error rate caused by interference, which is particularly suited for supporting context-aware computing. It is achieved by considering the speed variance of the mobile node and thereby correcting the interference errors. Performance evaluation using an actually implemented platform, Pharos, reveals that the proposed scheme outperforms the three existing schemes. It also identifies that error rate decreases as the number of packets transmitted for distance estimation increases, while it increases as the speed of the mobile node increases.