Localisation-capable technologies are becoming more readily available as off-the-shelf components. In this paper, we highlight the need for such a service in the field of health and autonomy, especially for disabled people. We then explore this idea through a study that leverages this localisation functionality.

We introduce a model for Semantic Position Description (SPD) (“The pill organiser in on the kitchen table”) as well as various algorithms that transform raw distance estimations to SPD related to proximity, alignment and room identification.

Two measurement campaigns have been conducted. The first one focused on algorithm performance and exploited the LocURa4IoT testbed. The second confronted the system's output (SPDs) to real user perception in a smart-home environment. This experiment involved ten human participants in the Maison Intelligente de Blagnac. The results indicate that both processes (human and machine perception) converge 90% of the time. This convergence confirms the relevance of our locaisation-based approach and encourages future explorations of its application to various domains.