| 摘要 |
Methods and a system for mobile device activity classification or context determination. The device compresses and sends sensor data to a remote server together with a selected activity label during a training phase. The remote server receives labeled sensor data from a number of devices and generates a classification model. The model may be reduced to a subspace that represents the dominant model parameters. The subspace data structure, which may be a small matrix, is transmitted to the mobile device. The mobile device uses the subspace data structure to classify device activity as indicated by the device sensors. In one example, the sensor data is projected onto the subspace matrix, which results in estimates of state probabilities for the various predefined states, the dominant one of which is selected as the current state, or estimated state.
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