The Community for Technology Leaders
RSS Icon
Issue No.07 - July (2013 vol.46)
pp: 62-69
Diane J. Cook , Washington State University
Aaron S. Crandall , Washington State University
Brian L. Thomas , Washington State University
Narayanan C. Krishnan , Washington State University
The CASAS architecture facilitates the development and implementation of future smart home technologies by offering an easy-to-install lightweight design that provides smart home capabilities out of the box with no customization or training.
Smart homes, Intelligent sensors, Machine learning, Pervasive computing, Middleware, Computer architecture, Knowledge discovery, smart home, machine learning, pervasive computing, activity recognition, activity discovery
Diane J. Cook, Aaron S. Crandall, Brian L. Thomas, Narayanan C. Krishnan, "CASAS: A Smart Home in a Box", Computer, vol.46, no. 7, pp. 62-69, July 2013, doi:10.1109/MC.2012.328
1. P. Hewitt, “Speech by the Rt Hon Patricia Hewitt MP, Secretary of State for Health,16 May 2007: Long-term Conditions Alliance Annual Conference,” 2007; +/ DH_074812.
2. S. Helal et al., “The Gator Tech Smart House: A Programmable Pervasive Space,” Computer, Mar. 2005, pp. 50-60.
3. B. Logan et al., “A Long-Term Evaluation of Sensing Modalities for Activity Recognition,” Proc. 9th Int'l Conf. Ubiquitous Computing (UbiComp 07), Springer, 2007, pp. 483-500.
4. D.H. Hu, V.W. Zheng, and Q. Yang, “Cross-Domain Activity Recognition Via Transfer Learning,” Pervasive and Mobile Computing, vol. 7, no. 3, 2011, pp. 344-358.
5. T.L.M. van Kasteren,G. Englebienne, and B.J.A. Kröse, “Hierarchical Activity Recognition Using Automatically Clustered Actions,” Proc. 2nd Int'l Conf. Ambient Intelligence (AmI 11), Springer, 2011, pp. 82-91.
6. T. Gu et al., “An Unsupervised Approach to Activity Recognition and Segmentation Based on Object-Use Fingerprinters,” Data & Knowledge Eng., vol. 69, no. 6, 2010, pp. 533-544.
7. D. Cook, N. Krishnan, and P. Rashidi, “Activity Discovery and Activity Recognition: A New Partnership,” to appear in IEEE Trans. Systems, Man, and Cybernetics, Part B, 2013;
8. G.K. Vincent and V.A. Velkoff, “The Next Four Decades—The Older Population in the United States: 2010 to 2050,” US Census Bureau, 2010; .
9. P. Kaushik, S.S. Intille, and K. Larson, “User-Adaptive Reminders for Home-Based Medical Tasks: A Case Study,” Methods of Information in Medicine, vol. 47, no. 3, 2008, pp. 203-207.
10. L. Pérez-Lombard, J. Ortiz, and C. Pout, “A Review of Building Energy Consumption Information,” Energy and Buildings, vol. 40, no. 3, 2008, pp. 394-398.
11. A. Faruqui, S. Sergici, and A. Sharif, “The Impact of Informational Feedback on Energy Consumption—A Survey of the Experimental Evidence,” Energy, vol. 35, no. 4, 2010, pp. 1598-1608.
303 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool