Abstract
An important problem in intelligent environments is how the system can identify and model users’ activities. This paper describes a new technique for identifying correlations between sensors and activities in an intelligent environment. Intelligent systems can then use these correlations to recognize the activities in a space. The proposed approach is motivated by the need for distinguishing the critical set of sensors that identifies a specific activity from others that do not. We compare several correlation techniques and show that logistic regression is a suitable solution. Finally, we describe our approach and report preliminary results.
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References
Balachandran, A., Voelker, G., Bahl, P., Rangan, P.: Characterizing User Behavior and Network Performance in a Public Wireless LAN. In: Proc. ACM SIGMETRICS (2002)
Barthelmess, P., Anderson, K.: View of Software Development Environments Based on Activity Theory. Computer Supported Cooperative Work 11(1-2) (2002)
Brumitt, B., Meyers, B., Krumm, J., Kern, A., Shafer, S.: EasyLiving: Technologies for Intelligent Environments. In: Thomas, P., Gellersen, H.-W. (eds.) HUC 2000. LNCS, vol. 1927, p. 12. Springer, Heidelberg (2000)
Dey, A., Mankoff, J., Abowd, G., Carter, S.: Distributed mediation of ambiguous context in aware environments. In: Proc. of UIST, pp. 121–130 (2002)
Dix, A.: Human Issues in the Use of Pattern Recognition Techniques. In: Workshop on Neural Networks and Pattern Recognition in Human Computer Interaction, King’s Manor, York (1991)
Dix, A.: Managing the Ecology of Interaction. In: Proc. of Tamodia, First International Workshop on Task Models and User Interface Design, Bucharest, Romania (2002)
Dix, A., Finaly, J., Abowd, G., Beale, R.: Human-Computer Interaction. Prentice-Hall, Englewood Cliffs (1998)
Elrod, S., Hall, G., Costanza, R., Dixon, M., Des Rivieres, J.: Responsive Office Environments. Communications ACM 36(7), 84–85 (1993)
Engeström, Y.: Learning by Expanding: An Activity-Theoretical Approach to Developmental Research. Orienta-Konsultit, Helsinki (1987)
Hosmer, D., Lemeshow, S.: Applied Logistic Regression, 2nd edn. John Wiley & Sons, Chichester (2000)
Kulkarni, A.: A Reactive Behavioral System for the Intelligent Room. Master’s Thesis in Computer Science and Engineering at the Massachusetts Institute of Technology, Cambridge, MA (2002)
Mozer, M.C.: The Neural Network House: An Environment that Adapts to its Inhabitants. In: Proc. of AAAI Spring Symposium, Menlo Park, CA, pp. 110–114 (1998)
Roman, M., Ziebart, B., Campbell, R.: Dynamic Application Composition: Customizing the Behavior of an Active Space. In: PerCom 2003, Dallas-Fort Worth, Texas (2003)
Weiser M.: The Computer for the Twenty-First Century. Scientific American (1991)
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Al-Bin-Ali, F., Boddupalli, P., Davies, N., Friday, A. (2003). Correlating Sensors and Activities in an Intelligent Environment: A Logistic Regression Approach. In: Aarts, E., Collier, R.W., van Loenen, E., de Ruyter, B. (eds) Ambient Intelligence. EUSAI 2003. Lecture Notes in Computer Science, vol 2875. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39863-9_24
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DOI: https://doi.org/10.1007/978-3-540-39863-9_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20418-3
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