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- W174139353 abstract "In this paper, we propose a distributed model that recognize ADLs of human can be occurred in daily living places. We collect and analyze user's environmental, location or activity information by simple sensor attached home devices or utensils. Based on these information, we provide a lifecare services by inferring the user's life pattern and health condition. But in order to provide a lifecare services well-refined activity recognition data are required and without enough inferred information it is very hard to build an ADL activity recognition model for high-level situation awareness. The sequence that generated by sensors are very helpful to infer the activities so we utilize the sequence to analyze an activity pattern and propose a distributed linear time inference algorithm. This algorithm is appropriate to recognize activities in small area like home, office or hospital. For performance evaluation, we test with an open data from MIT Media Lab and the recognition result shows over 75% accuracy." @default.
- W174139353 created "2016-06-24" @default.
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- W174139353 date "2009-05-01" @default.
- W174139353 modified "2023-09-26" @default.
- W174139353 title "A Distributed Activity Recognition Algorithm based on the Hidden Markov Model for u-Lifecare Applications" @default.
- W174139353 hasPublicationYear "2009" @default.
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