A Real-Time Integration of Semantic Annotations into Air Quality Monitoring Sensor Data

Nowadays, air pollution is one of the most serious problems in the world, therefore the real-time monitoring air quality is considered as necessity. Internet of Things (IoT) devices, such as sensors, enable real-time air quality monitoring, which produce sensed data continuously in the stream data, and transmit these data to a centralized server. Raw sensor stream data is useless unless properly annotated. Hence, the researchers proposed Semantic Sensor Web (SSW), which is a combination of Sensor Web and technologies of Semantic Web. However, how to advance techniques for integration of the semantic annotations in real-time is still an open issue that should be addressed. This research focuses on real-time integration of semantics into heterogeneous sensor stream data with context in the IoT. In this context, an IoT real-time air quality monitoring system and different semantic annotations are developed for sensor stream data in the format of Sensor Observation Service (SOS).