Habit monitoring over sensor streams
Résumé
The use of emerging sensing and communication technologies opens new opportunities for helping elderly or frail people continue living in their home. However, the raw data may be overwhelming for the supervisor. In this poster, we present ongoing work aiming at the discovery of habits from the analysis of the sensor data stream. Habits are searched in the form of episodes, that is to say collections of sensor events that exhibit temporal regularities. These regularities are assessed on combinations of interest measures, such as frequency, periodicity, maximal inter-occurrence gap, length, etc. We propose here structures and methods in order to discover and update over time the k most interesting episodes based on the user preferences on the measures of interest.
Origine | Fichiers produits par l'(les) auteur(s) |
---|