THESIS
2019
Abstract
With the explosion of the Internet of Things (IoT) and Augmented Reality (AR), the
number of objects to identify grew up exponentially in recent years and solutions such as
visual markers or radio technologies are starting to show their limits. Visible light markers
have been proposed to overcome these limitations. However, visible light communication
(VLC) is very sensitive to interference. As such, if two light markers are overlapping,
the corresponding signals cannot be recovered. In smart homes, this situation is likely
to occur as devices can be placed in very close proximity. In this paper, we design a
protocol based on orthogonal codes to detect and isolate adjacent light markers, and
individually identify several contiguous objects. We implement the algorithms within an...[
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With the explosion of the Internet of Things (IoT) and Augmented Reality (AR), the
number of objects to identify grew up exponentially in recent years and solutions such as
visual markers or radio technologies are starting to show their limits. Visible light markers
have been proposed to overcome these limitations. However, visible light communication
(VLC) is very sensitive to interference. As such, if two light markers are overlapping,
the corresponding signals cannot be recovered. In smart homes, this situation is likely
to occur as devices can be placed in very close proximity. In this paper, we design a
protocol based on orthogonal codes to detect and isolate adjacent light markers, and
individually identify several contiguous objects. We implement the algorithms within an
Android application and evaluate their effect both analytically and experimentally. We
demonstrate the robustness of our protocol in different conditions, both at the transmitter
and the receiver side. Light markers are correctly recovered with low error rates (under
%5), at a pace of 5 frames per second, enough for object identification in most IoT
scenarios.
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