Data, Volume 9, Issue 12
2024 December - 15 articles
Cover Story: The detection of activities of daily living finds application in healthcare monitoring, smart homes, and the energy management of buildings. While many existing datasets of human activities rely on wearable sensors, this study introduces a dataset captured with ambient sensors. These data facilitate use cases in which subjects are unable or unwilling to carry wearable devices. The data were collected in a supervised recording process, where 14 participants performed 25 different activities of daily living individually. Five identical multisensor devices captured the audio, vibration, infrared array data, light color, and environmental measurements, resulting in five multi-modal data channels. The labeled raw recordings are provided in a structured dataset. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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