IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/4/953 |
| _version_ | 1811278598937509888 |
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| author | Tarek Elsaleh Shirin Enshaeifar Roonak Rezvani Sahr Thomas Acton Valentinas Janeiko Maria Bermudez-Edo |
| author_facet | Tarek Elsaleh Shirin Enshaeifar Roonak Rezvani Sahr Thomas Acton Valentinas Janeiko Maria Bermudez-Edo |
| author_sort | Tarek Elsaleh |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T00:38:48Z |
| format | Article |
| id | doaj.art-41223e5652334f4790d24c0a1f639098 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T00:38:48Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-41223e5652334f4790d24c0a1f6390982022-12-22T03:10:15ZengMDPI AGSensors1424-82202020-02-0120495310.3390/s20040953s20040953IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection ServicesTarek Elsaleh0Shirin Enshaeifar1Roonak Rezvani2Sahr Thomas Acton3Valentinas Janeiko4Maria Bermudez-Edo5Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UKCentre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UKCentre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UKSchool of Computer Science, University of St Andrews, St Andrews KY16 9SX, UKCentre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UKSoftware Engineering Department, University of Granada, 18012 Granada, SpainWith 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.https://www.mdpi.com/1424-8220/20/4/953iotdata modelontologydata streamsemantic modellinked data |
| spellingShingle | Tarek Elsaleh Shirin Enshaeifar Roonak Rezvani Sahr Thomas Acton Valentinas Janeiko Maria Bermudez-Edo IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services Sensors iot data model ontology data stream semantic model linked data |
| title | IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services |
| title_full | IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services |
| title_fullStr | IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services |
| title_full_unstemmed | IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services |
| title_short | IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services |
| title_sort | iot stream a lightweight ontology for internet of things data streams and its use with data analytics and event detection services |
| topic | iot data model ontology data stream semantic model linked data |
| url | https://www.mdpi.com/1424-8220/20/4/953 |
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