Ontology-Based Event Modeling and High-Confidence Processing in IoT-Enabled High-Speed Train Control System

The rapid development of various types of real-time control systems raise new challenges on their heterogeneity and knowledge explicitly sharing issues. In this study, we propose an ontology-based model, named OntoEvent, to define and detect complex event in high-speed train control system. OntoEvent defines control logics using ontology structure and describes functionalities using logical, temporal operators and attribute relations. This ontology-based event processing model supports dynamic reconfiguration of functions and sharing between different components of the railway system. A pipelined construction framework is designed to transform OntoEvent model into semantic-consistent detection model. We implement a prototype control system, to evaluate the efficiency and performance of OntoEvent. Experimental results on this prototype system prove that OntoEvent-based event detection model outperforms other two selected models in results correctness, processing throughput and real-time performance, especially when processing a large amount of complex events.