Nowadays, with a growing use of location-aware, wirelessly connected, mobile devices, we can easily capture trajec- tories of mobile objects. To exploit these raw trajectories, we need to enhance them with semantic information. Several research fields are currently focusing on semantic trajectories to support inferences and queries to help users validating and discovering more knowledge about mobile objects. The inference mechanism is needed for queries on semantic trajectories connected to other sources of information. Time and space knowledge are fundamental sources of information used by the inference operation on semantic trajectories. This article discusses new approach for inference mechanisms on semantic trajec- tories. The proposed solution is based on an ontological approach for modelling semantic trajectories integrating time concepts and rules. We present a case study with experiments, optimization and evaluation to show the complexity of inference and queries. Then, we introduce a refinement algorithm based on temporal neighbour to enhance the temporal inference. The results show the positive impact of our proposal on reducing the complexity of the inference mechanism.