@article {1037,
	title = {Predicting Space Utilization of Buildings through Integrated and Automated Analysis of User Activities and Spaces },
	number = {TR214},
	year = {2013},
	month = {06/2013},
	abstract = {A well-functioning building aligns the types and number of spaces with the activities of the building users. Throughout design, architects have to predict the utilization of spaces quickly and consistently. This study presents a knowledge-based space-use analysis (KSUA) method that integrates user activity and space information. Specific contributions enabling this method are a method for mapping user activities onto appropriate spaces and an ontology for representing user activities for use in space-use analysis. Tests with novice architects show that they can update predictions about space utilization 6.5 times faster with the KSUA method than with today{\textquoteright}s method and do so much more consistently (the standard deviation of predictions across the novice architects was 68\% less with the method). Tests also show that the performance of novice architects with the KSUA method outweighs the performance of expert architects without the method. Deployment of the method in practice should enable better designed buildings and more productive building users. },
	keywords = {Charrette, Knowledge representation and reasoning, Planning, Space-use analysis, User activity, VDC, Virtual Design and Construction},
	attachments = {http://cife.stanford.edu/sites/default/files/TR214.pdf},
	author = {Tae Wan Kim}
}
