Abstract
A key application of sensor networks in smart environments is in monitoring activities of people. We develop several scenarios in which ultrasonic sensors are used for monitoring of patients and the elderly. In each scenario, we apply different algorithms for data fusion and sensor selection using quality-based or time division approaches. We have devised trajectory-matching algorithms to classify trajectories of movement of people in indoor environments. The trajectories are divided into several routine classes and the current trajectory is compared against the known routine trajectories. The initial results are quite promising, and show the potential usability of ultrasonic sensors in monitoring indoor movements of people, and in capturing and classifying trajectories.
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