Spatial and Temporal Reasoning for Ambient Intelligence Systems

Spatio-temporal outliers are occurrences that can reveal significant information about the phenomena under investigation. They are detected after comparing their non-spatial attributes with their spatio-temporal neighbours. One of the important definitions that need to be made is the spatio-temporal neighbourhood of an instance. There can be no universally applicable definition of the spatio-temporal neighbourhood (STN), but rather the definition should be based on empirical results in order to improve the quality of the decision making related to the spatial phenomena. Here we address this issue by defining STNs using Space-Time Autoregressive Integrated Moving Average (STARIMA). The method is illustrated using spatio-temporal outlier detection in Chinese annual temperature data.