Towards context-free semantic localisation

We propose a context-free semantic localisation approach to visualise and analyse indoor movements. We focus on settings where indoor location or rooms have strongly associated semantics, such as hospitals. We describe an approach that can work with different localisation systems, with little knowledge of the physical space properties, and with minimal bootstrapping required. We propose a movement representation that consists of time-encoded strings, and discuss how our approach can be used for analysing and visualising longitudinal indoor localisation data.