Adaptive and automated ambiance surveillance and event detection for Ambient Assisted Living

In this paper, we discuss an event detection system using a wireless sensor network in the Ambient Assisted Living context. The sensors measure the environment in which the patients live, not vital parameters of the patient him- or herself, which is important in order to respect the privacy and informational self-determination of the patient. The major difficulties of the given setup with sensors in the environment are that the measurements are taken in an irregular fashion (as opposed to regular sampling) and that some of the sensors may be unreliable. To tackle these problems, we propose an event-detection framework that is based on the theory of conditional random fields [1]. We conduct experiments on real-life sensor data collected from a set of eight households. The experiments show that the conditional random field is well suited for ambiance surveillance.