Please read the PlaceLab Data overview document before continuing.
This is about one month of all non-identifying data from a 2.5 month stay in the PlaceLab of a couple. We cannot provide audio and video because it could reveal the identity of the participants.
Sensors included are all the standard PlaceLab wired sensors, described here:
S. S. Intille, K. Larson, E. Munguia Tapia, J. Beaudin, P. Kaushik, J. Nawyn, and R. Rockinson, "Using a live-in laboratory for ubiquitous computing research," in Proceedings of PERVASIVE 2006, vol. LNCS 3968, K. P. Fishkin, B. Schiele, P. Nixon, and A. Quigley, Eds. Berlin Heidelberg: Springer-Verlag, 2006, pp. 349-365.
The mobile stick-on object usage and accelerometer-based sensors are called MITes and are described in this publication:
E. Munguia Tapia, S. S. Intille, L. Lopez, and K. Larson, "The design of a portable kit of wireless sensors for naturalistic data collection," in Proceedings of PERVASIVE 2006, vol. LNCS 3968, K. P. Fishkin, B. Schiele, P. Nixon, and A. Quigley, Eds. Berlin Heidelberg: Springer-Verlag, 2006, pp. 117-134.
The infrared MITes were developed as part of this work at MERL:
C. R. Wren and E. Munguia-Tapia, "Toward Scalable Activity Recognition for Sensor Networks," in Proceedings of The Second International Workshop in Location and Context-Awareness (LoCA '06), vol. 3987 / 2006, M. Hazas, J. Krumm, and T. Strang, Eds. Dublin, Ireland: Springer Berlin / Heidelberg, 2006, pp. 168-185.
RFID tagging is provided using the Intel RFID glove, described in this publication:
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)
About 100 hours of the data are annotated. The annotation was done using custom annotation software called Handlense [Overview of HandLense and executable]. Only the activity of the male subject was annotated. This paper has details about how the 100 hours of annotation was done:
B. Logan, J. Healey, Matthai Philipose, E. Munguia Tapia, and S. Intille, "A long-term evaluation of sensing modalities for activity recognition," in Proceedings of the International Conference on Ubiquitious Computing, vol. LNCS 4717. Berlin Heidelberg: Springer-Verlag, 2007, pp. 483–500.
The data can be found here: http://mhealth.ccs.neu.edu/datasets/PLCouple1/. Look at the README
The collection of this particular dataset was funded by Microsoft Research and the MIT House_n Consortium.