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Spectral-Loc: Indoor Localization using Light Spectral Information

Authors :
Wang, Yanxiang
Hu, Jiawei
Jia, Hong
Hu, Wen
Hassan, Mahbub
Uddin, Ashraf
Kusy, Brano
Youssef, Moustafa
Publication Year :
2022

Abstract

For indoor settings, we investigate the impact of location on the spectral distribution of the received light, i.e., the intensity of light for different wavelengths. Our investigations confirm that even under the same light source, different locations exhibit slightly different spectral distribution due to reflections from their localised environment containing different materials or colours. By exploiting this observation, we propose Spectral-Loc, a novel indoor localization system that uses light spectral information to identify the location of the device. With spectral sensors finding their way in latest products and applications, such as white balancing in smartphone photography, Spectral-Loc can be readily deployed without requiring any additional hardware or infrastructure. We prototype Spectral-Loc using a commercial-off-the-shelf light spectral sensor, AS7265x, which can measure light intensity over 18 different wavelength sub-bands. We benchmark the localisation accuracy of Spectral-Loc against the conventional light intensity sensors that provide only a single intensity value. Our evaluations over two different indoor spaces, a meeting room and a large office space, demonstrate that use of light spectral information significantly reduces the localization error for the different percentiles.<br />Comment: 14 pages, 17 figures, 4 tables

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2206.14401
Document Type :
Working Paper