Pervasive conference, tutorial on Context-Aware Computing

The last tutorial of the conference is Context-aware computing presented by Anind Dey of Carnegie Mellon University. Context is all the stuff that is important for understanding a user's goals and motivation. What is the important part for context is reminders, when and where to deliver context? It is easy to grab context, but more difficult in my opinion, to infer context. Context is a very difficult and slippery word to define because it means different things to different people. Inferring an activity or task as context is difficult. Finding social norms as context is, according to Anind, is slippery. My PhD work is looking at community as a metaphor for finding social context. I believe that there is some way that we can infer social context automatically from the links within the social hypertext. As a pervasive computing community, we need to look at real problems instead of recycling over the same applications like location guides. Anind says that grad students should not do work in context infrastructures because it is extremely difficult to publish your work.

One of the challenges of context is how to leverage real human context and realize that you're not really getting at human intention. Anind showed some videos of examples of context, one video was about an automatic door made in Japan that conforms to the type of body you have and will open that much.