Automation of smart home for ambient assisted living is currently based on a widespread use of sensors. As e cient as it seems to be, this solution can sometimes be problematic when one focus on user acceptability intimately related to cost and intrusivity. In this paper, we propose a context-aware system based on the semantic analysis of each user request at runtime. Our goal is to infer user data usually sensored by using advanced semantic web tools to adapt home automation services to people with special needs. To take up this challenge, an ontology, automatically derived from a model-driven process, rstly de nes user-system interactions. Then, the use of rules allows an inference engine to deduce user location and intention leading to adapted service delivery.