University of Surrey

Test tubes in the lab Research in the ATI Dance Research

IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams

Elsaleh, T., Bermudez-Edo, M., Enshaeifar, S., Acton, S. T., Rezvani, R. and Barnaghi, P. (2019) IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams In: 3rd Global IoT Summit (GIoTS 2019), 17-21 Jun 2019, Aarhus, Denmark.

[img]
Preview
Text
IoT-Stream.pdf - Accepted version Manuscript

Download (913kB) | Preview

Abstract

In recent years, the development and deployment of Internet of Things (IoT) devices has led to the generation of large volumes of real world data. Analytical models can be used to extract meaningful insights from this data. However, most of IoT data is not fully utilised, which is mainly due to interoperability issues and the difficulties to analyse data collected by heterogeneous resources. To overcome this heterogeneity, semantic technologies are used to create common models to share various data originated from heterogeneous sources. However, semantics add further overhead to data delivery, and the processing time to annotate the data with the model can increase the latency and complexity in publishing and querying the annotated data. In this paper, we present a lightweight semantic model to annotate IoT streams. The metadata descriptions that are provided in the models are used for search and discovery of the data using various attributes such as value and type. The proposed model extends commonly used ontologies such as W3C/OGC SSN ontology and its recent lightweight core, SOSA, and includes concepts to describe streaming IoT data. We also show use cases, tools and applications where the proposed model has been used.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Elsaleh, T.T.Elsaleh@surrey.ac.uk
Bermudez-Edo, M.
Enshaeifar, S.s.enshaeifar@surrey.ac.uk
Acton, S. T.s.acton@surrey.ac.uk
Rezvani, R.r.rezvani@surrey.ac.uk
Barnaghi, P.P.Barnaghi@surrey.ac.uk
Date : 2019
Funders : European Union's Horizon 2020
Grant Title : IoTCrawler project
Copyright Disclaimer : © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : IoT; Data model; Ontology; Data stream; Semantic model
Related URLs :
Depositing User : Clive Harris
Date Deposited : 15 May 2019 08:43
Last Modified : 17 Jun 2019 02:08
URI: http://epubs.surrey.ac.uk/id/eprint/851830

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800