For providing the adaptive assistances to determine when and how to make these assistances available according to the surroundings
the entities are built to model the diverse user behaviors(e.g.
sequential and concurrent behaviors)by integrating the capabilities on sensing
inferring and implementing. By computing the entities' interruption degree based on Petri Net
it is practicable to analyze whether an entity can act under the current environment or not
that means to decide whether an effective assistance can be triggered. We introduce the method in building a smart medication system which provides continuous medication monitoring and context-aware reminders. The experimental results show that our system could improve the medication adherence of elderly in a natural way.
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