IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Service
Metadatos
Mostrar el registro completo del ítemAutor
Elsaleh, Tarek; Enshaeifar, Shirin; Rezvani, Roonak; Acton, Sahr Thomas; Janeiko, Valentinas; Bermúdez Edo, María del CampoEditorial
MDPI
Materia
Data model Data stream Semantic model Linked data
Fecha
2020-02-11Referencia bibliográfica
Elsaleh, T., Enshaeifar, S., Rezvani, R., Acton, S. T., Janeiko, V., & Bermudez-Edo, M. (2020). IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services. Sensors, 20(4), 953.
Patrocinador
This work has been funded by the EU Horizon 2020 Research and Innovation programme, through projects IoTCrawler (contract no. 779852) and ACTIVAGE (contract no. 732679).Resumen
With the proliferation of sensors and IoT technologies, stream data are increasingly stored
and analysed, but rarely combined, due to the heterogeneity of sources and technologies. Semantics
are increasingly used to share sensory data, but not so much for annotating stream data. Semantic
models for stream annotation are scarce, as generally, semantics are heavy to process and not ideal
for Internet of Things (IoT) environments, where the data are frequently updated. We present a
light model to semantically annotate streams, IoT-Stream. It takes advantage of common knowledge
sharing of the semantics, but keeping the inferences and queries simple. Furthermore, we present
a system architecture to demonstrate the adoption the semantic model, and provide examples of
instantiation of the system for different use cases. The system architecture is based on commonly used
architectures in the field of IoT, such as web services, microservices and middleware. Our system
approach includes the semantic annotations that take place in the pipeline of IoT services and sensory
data analytics. It includes modules needed to annotate, consume, and query data annotated with
IoT-Stream. In addition to this, we present tools that could be used in conjunction to the IoT-Stream
model and facilitate the use of semantics in IoT.