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. 2020 Feb 11;20(4):953.
doi: 10.3390/s20040953.

IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services

Tarek Elsaleh  1 , Shirin Enshaeifar  1 , Roonak Rezvani  1 , Sahr Thomas Acton  1   2 , Valentinas Janeiko  1 , Maria Bermudez-Edo  3
Affiliations

IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services

Tarek Elsaleh et al. Sensors (Basel). .

Abstract

With the proliferation of sensors and IoT technologies, stream data are increasingly stored and analyzed, 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.

Keywords: IoT; data model; data stream; linked data; ontology; semantic model.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
An Analogy of Internet of Things (IoT) stream data as waterways derived from other waterways.
Figure 2
Figure 2
IoT-Stream classes and properties.
Figure 3
Figure 3
IoT-Stream linked with the main ontologies.
Figure 4
Figure 4
An instantiation of IoT-Stream.
Figure 5
Figure 5
System entities and interactions for IoT-Stream adoption.
Figure 6
Figure 6
Ontology concepts used in data flow between system entities: (a) A Producer registering an IotStream. (b) A Producer publishing a StreamObservation. (c) A Consumer registering an IotStream derived from an IotStream analysed by an Analytics Service. (d) An Analytics Service publishing an analysed StreamObservation. (e) Another Analytics Service publishing a generated Event.
Figure 7
Figure 7
Smart city traffic analysis.
Figure 8
Figure 8
Annotation process for detecting traffic and air quality levels.
Figure 9
Figure 9
Capturing IoT stream data from Smart Home environments.
Figure 10
Figure 10
Annotation process for detecting indoor activity levels.
Figure 11
Figure 11
Analysed IoT-Streams using KAT service.
Figure 12
Figure 12
IoTCrawler Architecture with the use of IoT-Stream.
See this image and copyright information in PMC

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