Smartphone-Based Real-Time Indoor Location Tracking With 1-m Precision.

Abstract

Monitoring the activities of daily living of the elderly at home is widely recognized as useful for the detection of new or deteriorating health conditions. However, the accuracy of existing indoor location tracking systems remains unsatisfactory. The aim of this study was, therefore, to develop a localization system that can identify a patient's real-time location in a home environment with maximum estimation error of 2 m at a 95% confidence level. A proof-of-concept system based on a sensor fusion approach was built with considerations for lower cost, reduced intrusiveness, and higher mobility, deployability, and portability. This involved the development of both a step detector using the accelerometer and compass of an iPhone 5, and a radio-based localization subsystem using a Kalman filter and received signal strength indication to tackle issues that had been identified as limiting accuracy. The results of our experiments were promising with an average estimation error of 0.47 m. We are confident that with the proposed future work, our design can be adapted to a home-like environment with a more robust localization solution.