Dependable visual light-based indoor localization with automatic anomaly detection for location-based service of mobile cyber-physical systems

Abstract

Indoor localization has become popular in recent years due to the increasing need of location-based services in mobile cyber-physical systems (CPS). The massive deployment of light emitting diodes (LEDs) further promotes the indoor localization using visual light. As a key enabling technique for mobile CPS, accurate indoor localization based on visual light communication remains nontrivial due to various non-idealities such as attenuation induced by unexpected obstacles. The anomalies of localization can potentially reduce the dependability of location-based services. In this article, we develop a novel indoor localization framework based on relative received signal strength. Most importantly, an efficient method is derived from the triangle inequality to automatically detect the abnormal LED lamps that are blocked by obstacles. These LED lamps are then ignored by our localization algorithm so that they do not bias the localization results, which improves the dependability of our localization framework. As demonstrated by the simulation results, the proposed techniques can achieve superior accuracy over the conventional approaches, especially when there exist abnormal LED lamps.