Constellation, le dépôt institutionnel de l'Université du Québec à Chicoutimi

Résumé

We apply artificial intelligence techniques to perform data analysis and activity recognition in smart homes. Sensors embedded in smart home provide primary data to reason about observations and provide appropriate assistance for residents to complete their Activities Daily Livings (ADLs). These residents may suffer from different levels of Alzheimer disease. In this paper, we introduce a qualitative approach that considers spatiotemporal specifications of activities in the Activity Recognition Agent (ARA) to do knowledge representation and reasoning about the observations. In this paper, we consider different existing uncertainties within sensors observations and Observed Agent?s activities. In the introduced approach if the more details about environment context be provided, the less activity recognition process complexity and more precise functionality is expected.