Context enriched patterns of behavior for delivering notifications in ambient-assisted living

Abstract

Ambient Assisted Living (AAL) refers to ambient intelligent environments where health and personal care is monitored to help to ensure elder’s health, safety, and well-being, detecting possible situations that should be watched over. To effectively reason about a current situation and determine its criticality, it should be compared to past patterns. Current systems that learn patterns do not take into account the context in which they occur and we believe adding contextual variables to the description of patterns could improve the reasoning about current situations. Moreover, it can help improve the notification process to dynamically select who and what should be notified, maintaining the privacy of the elder and avoiding spam. In this paper we detail our proposal for a system that adds context to behavior patterns in order to then create personalized messages to the different members of the network of care of an elder living alone.