Advanced Interaction in Context Albrecht Schmidt U , Kofi Asante Aidoo “ , Antti Takaluoma i , Urpo Tuomela i , Kristof Van Laerhoven “ , Walter Van de Velde “ U TecO, University of Karlsruhe, Germany “ Starlab Nv/Sa, Brussels, Belgium i Nokia Mobile Phones, Oulu, Finland albrecht@teco.edu, kofi@starlab.net, Antti.Takaluoma@nokia.com, Urpo.Tuomela@nokia.com, kvlaerho@vub.ac.be, wvdv@starlab.net Abstract. Mobile information appliances are increasingly used in numerous different situations and locations, setting new requirements to their interaction methods. When the user's situation, place or activity changes, the functionality of the device should adapt to these changes. In this work we propose a layered real-time architecture for this kind of context-aware adaptation based on redundant collections of low-level sensors. Two kinds of sensors are distinguished: physical and logical sensors, which give cues from environment parameters and host information. A prototype board that consists of eight sensors was built for experimentation. The contexts are derived from cues using real-time recognition software, which was constructed after experiments with Kohonen's Self-Organizing Maps and its variants. A personal digital assistant (PDA) and a mobile phone were used with the prototype to demonstrate situational awareness. On the PDA font size and backlight were changed depending on the demonstrated contexts while in mobile phone the active user profile was changed. The experiments have shown that it is feasible to recognize contexts using sensors and that context information can be used to create new interaction metaphors. 1 Introduction Current research and development in information technology is moving away from desktop based general purpose computers towards more task specific information appliances. Mobile phones and personal digital assistants (PDAs) dominate the research landscape as their dominance grows commercially. Last year alone there was a 56% increase in the use of mobile phones across Western Europe resulting in approximately 23 million users of cellular technology. The functionality of these appliances is the crucial issue. Users of these devices are not specialists and don’t accept long learning phases. Nevertheless users like advanced functionality, but it is important that this does not compromise the ease of use for these appliances. An important challenge in competition is to develop new functionality with added value for the user and still keep the interaction mechanism simple and straightforward. Answers and ideas can be