Improving the Semantic Interoperability of IoT Early Warning Systems

An early warning system (EWS) is a distributed system that monitors the physical world and issues warnings if it detects abnormal situations. The Internet of Things (IoT) offers opportunities to improve monitoring capabilities of EWS and to realize (near) real-time warning and response. This paper presents the development of an interoperable IoT-based EWS to detect accident risks with trucks that deliver goods at the Valencia port area. Our solution addresses the semantic integration of a variety of data sources with processing in safety-critical applications for effective emergency response. The solution considers existing domain-specific ontologies and standards, along with their serialization formats. Accident risks are assessed by monitoring the drivers’ vital signs with ECG medical wearables and the trucks’ position with speed and accelerometer data. Use cases include the detection of health issues and vehicle collision with dangerous goods. This EWS is developed with the SEMIoTICS framework, which encompasses a model-driven architecture that guides the application of data representations, transformations, and distributed software components. This framework enables an EWS to act as a semantic broker for situation-aware decision support.