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 rooms. The CGA is seen as ideal for such a problem because of its ability to find repetitive cyclic patterns in the data. Our results show that a CGA has the ability to pick out such patterns and construct a schedule of use for a room.