Pervasive Adaptation for Enhancing Quality of Experience

A visit to a public collection is potentially one of the most effective and entertaining ways of knowledge acquisition open to the general public. Such collections are nevertheless under increasing pressure, for various commercial and technical reasons, to improve the qualaity of experience (QoE) afforded to users. In this work, we propose to (try to) enhance QoE in a visit to a museum through a combination of a sensor-saturated environment with intelligent decision-making and policy-based computing, to deliver personalised, context-sensitive services to the visitor. The fusion of sensor data and user actions to adapt the behaviour of, for example, displays and exhibits is addressing a specific challenge of pervasive adaptation, i.e. how to coordinate the complex interaction of users, devices, and sensors to deliver an improved service or experience.