David T. Alpert

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Our work involves monitoring and learning methods for inhabitant identification in smart home environments. Inexpensive audio monitoring equipment is used to gather sets of samples of footstep patterns on an interior staircase. Samples are then automatically processed to identify some basic features of the resulting wave pattern. Labeled examples are then(More)
This work involves learning the use schedule of an academic building in order to intelligently control various aspects of the environment. Motion sensors are used to monitor and record the activity of each of the rooms in the building. After a basic preprocessing of the data, a Cyclic Genetic Algorithm (CGA) is used to pick out the patterns of use of the(More)
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