A Fine-grained Context-dependent Model for Indoor Spaces

The notion of context has been recently recognised as a key element in the development of context-aware information systems. Context varies according to application constraints, but also integrates the way users act in the environment and the interfaces they use to interact. Amongst many applications, indoor navigation systems strongly rely on context-based information to adapt their services accordingly. Still, these systems need the design and development of flexible and dynamic spatial data models that will be able to provide appropriate data and services to mobile users acting in the environment. The preliminary research presented in this paper introduces a fi ne-grained and multi-layered spatial model that provides a flexible representation of an indoor space, and also takes into account the objects supported and acting in the environment. The modelling approach integrates diff erent levels of granularity, from micro to macro levels, according to available positioning techniques, the infrastructure, device capabilities and user preferences