Modelling Spatio-temporal Relevancy in Context-aware Systems Using Multi-interval Algebra

In our everyday life, we communicate with each other within a certain context; our actions are also within a certain context. Events affect every aspect of human life. The importance of the context also influences how we interact with the environment and how technologies provide services for us. The Context is generally regarded as data or information which describes the situation that is relevant. The major challenge of context-aware systems is a separation of relevant and irrelevant information by finding an acceptable degree of information reduction to the relevant one, i.e. presenting as much information as needed and as little as required. In this way, spatial and temporal relationships between the users and objects are two dominant factors for selecting appropriate relevant objects or "spatio-temporal relevant objects". So introducing and applying a comprehensive model for spatio-temporal relationships would help us to find spatio-temporal relevant contexts. In this research we aim to introduce a spatio-temporal relationship model which could support context-aware services. The main contribution of this paper is applying Multi Interval Algebra to model spatio-temporal relevancy for context-aware systems. We assumed that both user and related contexts have an influence interval in time and space. We defined four intervals for user and context; two spatial and temporal intervals for the user and two spatial and temporal intervals for the contexts. Their relationships would assist to model spatiotemporal relevancy. The proposed model is implemented and tested in a context-aware tourist guide system. The achieved results proved the efficiency of the model.