Publication | Closed Access
SQenloT: Semantic query engine for industrial Internet-of-Things gateways
11
Citations
10
References
2016
Year
Unknown Venue
TechnologyThings Query LanguageInformation RetrievalData ScienceIndustrial Internet Of ThingsEngineeringWeb Of ThingSemantic TaggingSemantic TechnologyIndustrial IotData IntegrationInternet Of ThingsSemantic Sensor NetworkSemantic WebIndustrial InformaticsData ManagementSemantic Query EngineIot Interoperability
The Advent of Internet-of-Things (IoT) paradigm has brought exciting opportunities to solve many real-world problems. IoT in industries is poised to play an important role not only to increase productivity and efficiency but also to improve customer experiences. Two main challenges that are of particular interest to industry include: handling device heterogeneity and getting contextual information to make informed decisions. These challenges can be addressed by IoT along with proven technologies like the Semantic Web. In this paper, we present our work, SQenIoT: a Semantic Query Engine for Industrial IoT. SQenIoT resides on a commercial product and offers query capabilities to retrieve information regarding the connected things in a given facility. We also propose a things query language, targeted for resource-constrained gateways and non-technical personnel such as facility managers. Two other contributions include multi-level ontologies and mechanisms for semantic tagging in our commercial products. The implementation details of SQenIoT and its performance results are also presented.
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