Early warning systems were interested in captured data of mobile objects. From the 2000s, a new generation of data capture equipment arrives. These capture devices rise large scale trajectory data. How early warning systems can integrate these masses of data? How they can give real-time answers to users queries? In this paper, we present an ontological approach to model the trajectory. The trajectory’s domain knowledge are expressed as rules used by the ontological inference mechanism. We show the important complexity of the inference and we propose optimizations. We evaluate our contributions over real data.
early warning system, trajectory ontology modeling, ontology inference, domain rules, temporal rules, data filter algorithm