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We present a system for activity monitoring and patient tracking in a smart hospital setting. The system aims to reduce the number of falls and cases of wandering from the ward through the use of context aware sensing and behavior prediction and detection algorithms. The system affords multi-sensor data fusion to be carried out in an experimental manner and the best topology for fusion selected on a case by case basis. Our work is based on a joint project with a hospital, where in a geriatric ward, several types of sensors are deployed for monitoring and tracking of elderly patients.
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