A probabilistic approach to the anxious home for activity monitoring

This paper describes an approach to representing normal activities in a smart house based on the concept of anxiety. Anxiety is computed as a function of time and is kept low by interactions of an occupant with the various devices in a house. Abnormality is indicated by a lack of activity or the wrong activity which will cause anxiety to rise ultimately raising an alarm, querying the occupant and/or alerting a carer in real-time. Anxiety is formulated using probabilistic models that describe how people interact with devices in combinations. These models can be learnt interactively as the smart house acts pessimistically enquiring of the occupant if what they are doing is normal. Results are presented for a number of kitchen scenarios and for different formulations of anxiety.