DevLoc

Seamless device association using light bulb networks for indoor iot environments

Conference paper (2020)

Authors

Michael Haus Technische Universität München
Jorg Ott Technische Universität München
Copyright: © 2020 Michael Haus, Jorg Ott, Aaron Yi Ding
DOI
help_outline
https://doi.org/10.1109/IoTDI49375.2020.00030
Similarity measures Mobile ad hoc networks Machine learning approaches Network services Ubiquitous and mobile devices
More Info
expand_more

Published Date

2020

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

For indoor IoT environments, spontaneous device associations are of particular interest where users establish a connection in an ad-hoc manner to enable serendipitous interaction. For instance, between a user's personal device and devices the user encounters in the surrounding environment. Our system for device grouping named DevLoc takes advantage of ubiquitous light sources around us to perform continuous device grouping based on the similarity of light signals. To control the spatial granularity of user's proximity, we provide a configuration framework to manage the lighting infrastructure through customized visible light communication. We support two modes of device associations to achieve a binding between different entities: device-to-device and device-to-area allowing either proximity-based or location-based services. Our device grouping includes several methods where in general the machine learning based signal similarity performs best compared to distance and correlation metrics.

Files

DevLoc.pdf
(.pdf | 0.411 Mb)