Stream Reasoning

C-Sprite : efficient hierarchical reasoning for rapid RDF stream processing

DIVIDE : adaptive context-aware query derivation for IoT data streams

In the Internet of Things, it is a challenging task to inte-grate & analyze high velocity sensor data with domain knowledge &context information in real-time. Semantic IoT platforms typically con-sist of stream processing …

Efficiënte verwerking van heterogene IoT-data aan de hand van expressieve redeneertechnieken

Subset reasoning for event-based systems

In highly dynamic domains such as the Internet of Things (IoT), smart industries, smart manufacturing, pervasive health or social media, data is being continuously generated. By combining this generated data with background knowledge and performing …

A query model for ontology-based event processing over RDF streams

Context-aware patient monitoring through sensor streams

Streaming MASSIF : cascading reasoning for efficient processing of iot data streams

In the Internet of Things (IoT), multiple sensors and devices are generating heterogeneous streams of data. To perform meaningful analysis over multiple of these streams, stream processing needs to support expressive reasoning capabilities to infer …

Towards a cascading reasoning framework to support responsive ambient-intelligent healthcare interventions

In hospitals and smart nursing homes, ambient-intelligent care rooms are equipped with many sensors. They can monitor environmental and body parameters, and detect wearable devices of patients and nurses. Hence, they continuously produce data …

The MASSIF platform : a modular and semantic platform for the development of flexible IoT services

In the Internet of Things (IoT), data-producing entities sense their environment and transmit these observations to a data processing platform for further analysis. Applications can have a notion of context awareness by combining this sensed data, or …

Towards ontology based event processing