  To enable serendipitous interaction for indoor IoT environments, spontaneous
device associations are of particular interest so that users set up a
connection in an ad-hoc manner. Based on the similarity of light signals, our
system named DevLoc takes advantage of ubiquitous light sources around us to
perform continuous and seamless device grouping. We provide a configuration
framework to control the spatial granularity of user's proximity by managing
the lighting infrastructure through customized visible light communication. To
realize either proximity-based or location-based services, we support two modes
of device associations between different entities: device-to-device and
device-to-area. Regarding the best performing method for device grouping,
machine learning-based signal similarity performs in general best compared to
distance and correlation metrics. Furthermore, we analyze patterns of device
associations to improve the data privacy by recognizing semantic device groups,
such as personal and stranger's devices, allowing automated data sharing
policies.
