Accurate indoor visible light positioning system utilizing machine learning technique with height tolerance

Chin Wei Hsu, Siming Liu, Feng Lu, Chi Wai Chow, Chien Hung Yeh, Gee Kung Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

An accurate, low-cost indoor visible light positioning system utilizing machine learning technique is proposed and experimentally demonstrated. The average position resolution of the system can achieve 3.65 cm with height tolerance range of 15 cm.

Original languageEnglish
Title of host publication2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-3
Number of pages3
ISBN (Electronic)9781943580385
StatePublished - 13 Jun 2018
Event2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - San Diego, United States
Duration: 11 Mar 201815 Mar 2018

Publication series

Name2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings

Conference

Conference2018 Optical Fiber Communications Conference and Exposition, OFC 2018
CountryUnited States
CitySan Diego
Period11/03/1815/03/18

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  • Cite this

    Hsu, C. W., Liu, S., Lu, F., Chow, C. W., Yeh, C. H., & Chang, G. K. (2018). Accurate indoor visible light positioning system utilizing machine learning technique with height tolerance. In 2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings (pp. 1-3). (2018 Optical Fiber Communications Conference and Exposition, OFC 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc..