SENSdesc : connect sensor queries and context

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

Generic semantic platform for the user-friendly development of intelligent IoT services

Improving OWL RL reasoning in N3 by using specialized rules

Semantic Web reasoning can be a complex task: depending on the amount of data and the ontologies involved, traditional OWL DL reasoners can be too slow to face problems in real time. An alternative is to use a rule-based reasoner together with the …

User-friendly and scalable platform for the design of intelligent IoT services : a smart office use case

Evaluation and optimized usage of OWL 2 reasoners in an event-based eHealth context

Event-driven rule-based reasoning using EYE