@inproceedings{2b961719ab9a490b8bdc26da1c15c4c6,
title = "DevLoc: Seamless device association using light bulb networks for indoor iot environments",
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.",
keywords = "Machine learning approaches, Mobile ad hoc networks, Network services, Similarity measures, Ubiquitous and mobile devices",
author = "Michael Haus and Jorg Ott and DIng, {Aaron Yi}",
note = "Virtual/online event due to COVID-19 ; 5th ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI 2020 ; Conference date: 21-04-2020 Through 24-04-2020",
year = "2020",
doi = "10.1109/IoTDI49375.2020.00030",
language = "English",
series = "Proceedings - 5th ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI 2020",
publisher = "IEEE",
pages = "231--237",
booktitle = "Proceedings - 5th ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI 2020",
address = "United States",
}