Spatio-Temporal Reasoning and Context Awareness

Smart homes provide many research challenges, but some of the most interesting ones are in dealing with data that monitors human behaviour and that is inherently both spatial and temporal in nature. This means that context becomes all important: a person lying down in front of the fireplace could be perfectly normal behaviour if it was cold and the fire was on, but otherwise it is unusual. In this example, the context can include temporal resolution on various scales (it is winter and therefore probably cold, it is not nighttime when the person would be expected to be in bed rather than the living room) as well as spatial (the person is lying in front of the fireplace) and extra information such as whether or not the fire is lit. It could also include information about how they reached their current situation: if they went from standing to lying very suddenly there would be rather more cause for concern than if they first knelt down and then lowered themselves onto the floor. Representing all of these different temporal and spatial aspects together is a major challenge for smart home research. In this chapter we will provide an overview of some of the methodologies that can be used to deal with these problems. We will also outline our own research agenda in the Massey University Smart Environments (MUSE) group. Our interpretation of the smart home can be seen in Figure 1. We assume that unspecified sensors make observations of the house, and that changes in the observations, and hence the output, of these sensors in some way represent the behaviour of the human inhabitants. We are not directly interested in the signal processing that