An Adaptive Fingerprint Database Updating Method for Room Localization

Fingerprint-based indoor localization has become one of the most attractive and promising techniques, and however, one primary concern for this technology to be fully practical is to maintain the fingerprint database to combat harsh indoor environmental dynamics, especially for the large-scale and long-term deployment. In this paper, focusing on room localization, we first analyze the effect of different factors on indoor location accuracy, then propose an integrity check algorithm and a fuzzy map mechanism in response to network changes accurately and timely, and then design an accuracy check algorithm and a regional adaptive periodic update approach to update the fingerprint database effectively when an environment changes. Meanwhile, we design the active static data collecting mechanism and the active pin data collecting mechanism to ensure the accuracy and reliability of fingerprints newly captured and reduce the overhead on mobile devices significantly. The experimental results demonstrate that the proposed solution improves the performance of updating the fingerprint database in real time and robustness and maintains the location accuracy over 95% no matter how the indoor environmental changes; meanwhile, it also reduces energy efficiency imposed on the mobile phones by over 50%.