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Learning to Detect User Activity and Availability from a Variety of Sensor Data
Orlando, Florida March 14-March 17
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PERCOM.2004.1276841Second IEEE International Conference ...
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Martin M?hlenbrock, Xerox Research Centre Europe, Meylan, France
Oliver Brdiczka, Xerox Research Centre Europe, Meylan, France
Dave Snowdon, Xerox Research Centre Europe, Meylan, France
Jean-Luc Meunier, Xerox Research Centre Europe, Meylan, France
Using a networked infrastructure of easily available sensors and context-processing components, we are developing applications for the support of workplace interactions. Notions of activity and availability are learned from labeled sensor data based on a Bayesian approach. The higher-level information on the users is then automatically derived from low-level sensor information in order to facilitate informal ad hoc communications between peer workers in an office environment.
Citation:
Martin M?hlenbrock, Oliver Brdiczka, Dave Snowdon, Jean-Luc Meunier, "Learning to Detect User Activity and Availability from a Variety of Sensor Data," percom, pp.13, Second IEEE International Conference on Pervasive Computing and Communications (PerCom'04), 2004
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