Maximizing the utility of situated public displays

Situated public displays are intended to convey important information to a large and heterogeneous population. Because of the heterogeneity of the population, they may risk providing a lot of irrelevant information. Many such important information items presented on public displays are actionables, items that are intended to trigger specific actions. The expected utility that such actionables have for a user depend on the value of the action for the user. A goal should be to provide for each user the actionables with highest utility. This can be achieved by adapting the information presentation to the users currently in front of the display. Adaptation can take place either by identifying individual users, by using statistics about the user groups usually in front of the display or by a combination of both. We present a formal framework based on decision theory that enables the integration of sensor data and statistics and allows to choose the optimal actionable to present based on this data.