M. Kurosu (Ed.): Human-Computer Interaction, Part I, HCII 2013, LNCS 8004, pp. 340–349, 2013. © Springer-Verlag Berlin Heidelberg 2013 Special Challenges for Models and Patterns in Smart Environments Peter Forbrig, Christian Märtin, and Michael Zaki University of Rostock, Department of Computer Science, Albert Einstein Str. 21, 18055 Rostock, Germany {peter.forbrig,christian.maertin,michael.zaki}@uni-rostock.de Abstract. Smart environments aim at inferring the intention of the user and based on that information, they offer optimal assistance for the users while per- forming their tasks. This paper discusses the role of supportive user interfaces for explicitly interacting with the environment in such cases where implicit inte- ractions of the users fail or the users want to get informed about the state of the environment. It will be shown by small examples how patterns help to specify the intended support with implicit and explicit interactions. A notation for pres- entation patterns will be introduced that allows users dynamically to change the presentation style. It will be discussed how extended task models can be com- bined with presentation patterns and how this information can be used in sup- portive user interfaces on mobile devices. Keywords: Smart Environment, model-based design, pattern, supportive user interface, task migratability, task pattern, presentation patter. 1 Introduction During the last few decades a lot of work has been accomplished by different research teams to study prototypes of environments of assisting users performing their daily life tasks. This research was often focused on elderly people but sometimes also focuses on children (e.g. [3] and [16]). Our paper is based on research within our graduate school MuSAMA (Multimodal Smart Appliance Ensembles for Mobile Applications). The experimental basis is a smart meeting room. The room is equipped with a lot of sensors, projectors and cinema screens (see Fig. 1.). Bayesian algorithms are informed by sensors and try to infer next possible actions of the users. Based on that information, convenient assistance has to be provided. “This creates complex and unpredictable interactive computing environments that are hard to understand. Users thus have difficulties to build up their mental model of such interactive systems. To address this issue users need possibilities to evaluate the state of these systems and to adapt them according to their needs.” [13]