Abstract
We study activity recognition using 104 hours of annotated data collected from a person living in an instrumented home. The home contained over 900 sensor inputs, including wired reed switches, current and water flow inputs, object and person motion detectors, and RFID tags. Our aim was to compare different sensor modalities on data that approached “real world” conditions, where the subject and annotator were unaffiliated with the authors. We found that 10 infra-red motion detectors outperformed the other sensors on many of the activities studied, especially those that were typically performed in the same location. However, several activities, in particular “eating” and “reading” were difficult to detect, and we lacked data to study many fine-grained activities. We characterize a number of issues important for designing activity detection systems that may not have been as evident in prior work when data was collected under more controlled conditions.
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Munguia Tapia, E., Intille, S.S., Lopez, L., Larson, K.: The design of a portable kit of wireless sensors for naturalistic data collection. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, pp. 117–134. Springer, Heidelberg (2006)
Munguia Tapia, E., Intille, S., Larson, K.: Activity recognition in the home using simple and ubiquitous sensors. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 158–175. Springer, Heidelberg (2004)
Philipose, M., Smith, J.R., Jiang, B., Mamishev, A., Roy, S., Sundara-Rajan, K.: Battery-free wireless identification and sensing. IEEE Pervasive Computing 4(1), 37–45 (2005)
Lester, J., Choudhury, T., Kern, N., Borriello, G., Hannaford, B.: A hybrid discriminative/generative approach for modeling human activities. In: IJCAI, pp. 766–772 (2005)
Bao, L., Intille, S.S.: Activity recognition in the home setting using simple and ubiquitous sensors. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 1–17. Springer, Heidelberg (2004)
Wilson, D.H., Atkeson, C.G.: Simultaneous tracking and activity recognition (STAR) using many anonymous, binary sensors. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 62–79. Springer, Heidelberg (2005)
Wang, S., Pentney, W., Popescu, A.-M., Choudhury, T., Philipose, M.: Common sense joint training of human activity recognizers. In: Proceedings of IJCAI 2007 (2007)
Fishkin, K.P., Philipose, M., Rea, A.D.: Hands-On RFID: Wireless wearables for detecting use of objects. In: ISWC, pp. 38–43 (2005)
Intille, S.S., Larson, K., Munguia Tapia, E., Beaudin, J.S., Kaushik, P., Nawyn, J., Rockinson, R.: Using a live-in laboratory for ubiquitous computing research. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, pp. 349–365. Springer, Heidelberg (2006)
Fogarty, J., Au, C., Hudson, S.E.: Sensing from the basement: a feasibility study of unobtrusive and low-cost home activity recognition. In: UIST, pp. 91–100 (2006)
Patterson, D., Fox, D., Kautz, H., Philipose, M.: Fine-Grained Activity Recognition by Aggregating Abstract Object Usage. In: ISWC (2005)
Placelab Data website. Available: architecture.mit.edu/house_n/data/PlaceLab/PlaceLab.htm
Quiet care systems. Available: www.quietcaresystems.com
E-Neighbor system from Healthsense. Available: www.healthsense.com
i-pot from Zojirushi Corporation. Available: www.mimamori.net
Witten, I., Frank, E.: Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann, San Francisco (2005)
Streiner, D.L., Cairney, J.: What’s under the ROC? An introduction to receiver operating characteristic curves. Canadian Journal of Psychiatry 52(2) (2007)
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Logan, B., Healey, J., Philipose, M., Tapia, E.M., Intille, S. (2007). A Long-Term Evaluation of Sensing Modalities for Activity Recognition. In: Krumm, J., Abowd, G.D., Seneviratne, A., Strang, T. (eds) UbiComp 2007: Ubiquitous Computing. UbiComp 2007. Lecture Notes in Computer Science, vol 4717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74853-3_28
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DOI: https://doi.org/10.1007/978-3-540-74853-3_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74852-6
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