Abstract
The development of smart environments is cumbersome and time-consuming compared to traditional software, since lacking a standard development process and according tool support. Smart environments are termed “smart” due to pro-active user assistance: User behavior is anticipated by an “intention analysis” software employing machine learning algorithms. In this paper we present a tool that facilitates the development of intention analysis by guiding the domain expert through the development process. Initially, the tool allows the user-centered design of HCI task models, without taking care of implementation details. Subsequently annotated task models are transformed into low level models, which are applied within the machine learning inference engine. We support both evaluation at early and later development stages. At early stages we evaluate designed models with expert-generated scenarios to simulate artificial low level sensor data. At later stages we evaluate a physical environment on the basis of real sensor data. A comparison between observed behavior and defined expectation allows identifying usability issues. A close connection between development and evaluation should further ensure rapid software changes and reevaluation to access improvements.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bilmes, J.A.: What hmms can do. IEICE - Trans. Inf. Syst. E89-D(3), 869–891 (2006)
Burghardt, C., Kirste, T.: Inferring intentions in generic context-aware systems. In: MUM 2007: Proceedings of the 6th international conference on Mobile and ubiquitous multimedia, pp. 50–54. ACM, New York (2007)
Card, S.K., Mackinlay, J., Shneiderman, B.: Readings in Information Visualization: Using Vision to Think (The Morgan Kaufmann Series in Interactive Technologies). Morgan Kaufmann, San Francisco (1999)
Cuřín, J., Fleury, P., Kleindienst, J., Kessl, R.: Meeting state recognition from visual and aural labels, pp. 24–35 (2008)
Fraley, C., Raftery, A.E.: Bayesian regularization for normal mixture estimation and model-based clustering. Journal of Classification 24(2), 155–181 (2007)
Giersich, M., Forbrig, P., Fuchs, G., Kirste, T., Reichart, D., Schumann, H.: Towards an integrated approach for task modeling and human behavior recognition, pp. 1109–1118 (2007)
Hartmann, B., Klemmer, S.R., Bernstein, M., Abdulla, L., Burr, B., Robinson-Mosher, A., Gee, J.: Reflective physical prototyping through integrated design, test, and analysis. In: UIST 2006: Proceedings of the 19th annual ACM symposium on User interface software and technology, pp. 299–308. ACM Press, New York (2006)
Hein, A.: Echtzeitfähige Merkmalsgewinnung von Beschleunigungswerten und Klassifikation von zyklischen Bewegungen. diploma thesis, Universität Rostock (2007)
Luyten, K., Van den Bergh, J., Vandervelpen, C., Coninx, K.: Designing distributed user interfaces for ambient intelligent environments using models and simulations. Computers & Graphics 30(5), 702–713 (2006)
Maly, I., Curin, J., Kleindienst, J., Slavik, P.: Creation and visualization of user behavior in ambient intelligent environment. International Conference on Information Visualisation 0, 497–502 (2008)
Martin, M., Nurmi, P.: A generic large scale simulator for ubiquitous computing. Annual International Conference on Mobile and Ubiquitous Systems 0, 1–3 (2006)
Nishikawa, H., Yamamoto, S., Tamai, M., Nishigaki, K., Kitani, T., Shibata, N., Yasumoto, K., Ito, M.: UbiREAL: Realistic Smartspace Simulator for Systematic Testing, pp. 459–476 (2006)
Pandian, R.C.: Software Metrics: A Guide to Planning, Analysis, and Application. AUERBACH (September 2003)
Paterno, F.: Model-Based Design and Evaluation of Interactive Applications. Springer, London (1999)
Patterson, D.J., Fox, D., Kautz, H., Philipose, M.: Fine-grained activity recognition by aggregating abstract object usage. In: ISWC 2005: Proceedings of the Ninth IEEE International Symposium on Wearable Computers, Washington, DC, USA, pp. 44–51. IEEE Computer Society, Los Alamitos (2005)
Propp, S., Buchholz, G., Forbrig, P.: Task model-based usability evaluation for smart environments, pp. 29–40 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Burghardt, C., Propp, S., Kirste, T., Forbrig, P. (2009). Rapid Prototyping and Evaluation of Intention Analysis for Smart Environments. In: Tavangarian, D., Kirste, T., Timmermann, D., Lucke, U., Versick, D. (eds) Intelligent Interactive Assistance and Mobile Multimedia Computing. IMC 2009. Communications in Computer and Information Science, vol 53. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10263-9_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-10263-9_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10262-2
Online ISBN: 978-3-642-10263-9
eBook Packages: Computer ScienceComputer Science (R0)