Dependable Visual Light-Based Indoor Localization with Automatic Anomaly Detection for Location-Based Service of Mobile Cyber-Physical Systems
Authors: 
Yang Liu, Xiaoming Chen, Dileep Kadambi, Ajinkya Bari, Xin Li, Shiyan Hu, Pingqiang ZhouAuthors Info & Claims
Yang Liu, Xiaoming Chen, Dileep Kadambi, Ajinkya Bari, Xin Li, Shiyan Hu, Pingqiang ZhouAuthors Info & ClaimsArticle No.: 5, Pages 1 - 17
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.
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Index Terms
- Dependable Visual Light-Based Indoor Localization with Automatic Anomaly Detection for Location-Based Service of Mobile Cyber-Physical Systems
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January 2019
256 pages
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Publication History
Published: 29 August 2018
Accepted: 01 November 2017
Revised: 01 September 2017
Received: 01 March 2017
Published in TCPS Volume 3, Issue 1
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