AwareKitchen

Intelligent sensor equipped environments can be of much greater help if they are capable of recognizing the actions and activities of their users, and inferring their intentions. Understanding human activities and characterizing them into expressive and detailed activity models is one of the key issues of today's current pervasive computing systems. If such a system could recognize and understand automatically its user's behavior, it could interact in a more efficient and friendly manner. Unfortunately, the current model construction techniques are based on supervised learning and require specifications from their human counterparts, such as labeling the acquired sensor data. Our vision is to build technical cognitive systems that create and use models in a straightforward manner, by combining already existing online information with the system's context history.