Abstract
We present a new dataset, called Orange4Home, of activities of daily living of one inhabitant in a smart home environment. We collected data from 236 heterogeneous sensors in a fully integrated instrumented apartment. Data collection spanned 4 consecutive weeks of working days for a total of around 180 h of recording. 20 classes of varied activities were labeled in situ. We report the methodology adopted to establish a representative, challenging dataset, as well as present the apartment and sensors used to collect this data.
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Acknowledgments
We thank Nicolas Bonnefond and Stan Borkowski for their technical and organizational help. This work benefited from the support of the French State through the Agence Nationale de la Recherche under the Future Investments program referenced ANR-11-EQPX-0002.
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Cumin, J., Lefebvre, G., Ramparany, F., Crowley, J.L. (2017). A Dataset of Routine Daily Activities in an Instrumented Home. In: Ochoa, S., Singh, P., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2017. Lecture Notes in Computer Science(), vol 10586. Springer, Cham. https://doi.org/10.1007/978-3-319-67585-5_43
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DOI: https://doi.org/10.1007/978-3-319-67585-5_43
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