Adaptive interaction support in ambient-aware environments based on quality of context information

Ambient-aware environments are technologically augmented with myriad sensors, devices and other emerging services in order to support users. However, users find it complex in interacting with such environments due to the presence of numerous devices and services. In this situation, providing context-aware implicit or automatic interaction support may help reducing the cognitive load of the users and facilitate easy access of the available devices and services. However, due to the imprecision in context information, implicit interactions performed by the environment often leads to mis-automation. The result of such impaired implicitness causes distrust and dissatisfaction to the user. In order to address this issue, we propose a system that considers quality of information to dynamically adjust the level of implicit interaction and allows a system to operate in different modes such as full-automation, action suggestion, simple notification, or null action. We conduct experiment in a smart home scenario in order to elicit users’ acceptance and trust regarding the proposed system. Our experiment shows that dynamic and alternative mode of interaction not only increases the satisfaction of users but also helps to avoid distrust in automated actions carried out by the environment under varying contexts.