Learning from experience: seamless prediction of inhabitants' needs.

According to the vision of Mark Weiser (considered the father of ubiquitous computing), the most advanced technologies are those that disappear: computer technology should become invisible, and all the objects surrounding us must possess sufficient computing capacity to interact with users and their surroundings while the entire physical environment should exhibit intelligent behavior. The objective of our research is to move ahead in this direction by proposing a functional software application able to learn the behavior and habits of home inhabitants in order to anticipate their needs. This software component offers a complete, ready-to-use working application that learns through interaction with the user in order to improve quality of life in a technological living environment, such as a house, a smart city and so on. Although the proposed solution is currently targeting comfort issues, it also represents an opportunity to provide greater autonomy and safety to disabled and elderly occupants, especially in cases of critical illness. The result is an AAL (Ambient Assisted Living) system that can actively contribute to anticipating, and thereby preventing, emergency situations.