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Behavior Analysis for Assisted Living
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DOI：10.1109/TASE.2010.2049840.png)
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Abstract
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In this paper, we describe a model-based behavior analysis system for assisted living. The goal is monitoring the well-being of a single occupant in a home. Behavior is defined as any pattern in a sequence of observations. In analyzing behavior in a smart home, we aim to detect gradual changes in behavior, and atypical (anomalous) behavior. The anomalous behavior may be the result of equipment failure or the result of significant variations in the behavior of the occupant. In the context of a smart home, both situations require human intervention although the response will differ. For the purpose of observing behavior, the smart home is equipped with embedded sensors that unobtrusively record various environmental parameters. Models of behavior are generated from the sensor data. These models are employed to detect trends and infer atypical behavior.
Keywords:
Artificial intelligence
learning system
unsupervised learning
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