A dataset of ambient sensors in a meeting room for activity recognition.

ABSTRACT: As IoT technology advances, using machine learning to detect user activities emerges as a promising strategy for delivering a variety of smart services. It is essential to have access to high-quality data that also respects privacy concerns and data streams from ambient sensors in the surrounding environment meet this requirement. However, despite growing interest in research, there is a noticeable lack of datasets from ambient sensors designed for public spaces, as opposed to those for private settings. To bridge this gap, we design the DOO-RE dataset within an actual meeting room environment, equipped with three types of ambient sensors: those triggered by actuators, users, and the environment itself. This dataset is compiled from the activities of over twenty students throughout a perio

SUBMITTER: Kim H 

PROVIDER: S-EPMC11109118 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature