Bellur, Umesh, Patel, Pankesh, Chauhan, Saurabh and Qin, Yongrui (2017) A Semantic-enabled Framework For Future Internet Of Things Applications. In: 2017 IEEE World Congress on Services (SERVICES). IEEE, pp. 106-113. ISBN 97815386-20021
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Abstract
While the challenge of connecting Internet of Things (IoT) devices at the lowest layer has been widely studied, integrating and interoperating huge amounts of sensed data of heterogeneous IoT devices is becoming increasingly important because of the possibility of consuming such data in supporting many potential novel IoT applications. A common approach to processing and consuming IoT data is a centralized paradigm: sensor data is sent over the network to a comparatively powerful central server or a cloud service, where all processing takes place. However, this approach has some limitations as it requires devices to interact directly with a cloud which is not cost effective. First, it has high demands on the device's storage and computational capabilities. Second, as devices grow rapidly in a deployment area, sending all the data to a centralized cloud server requires high network bandwidth. Moreover, this often creates data privacy concerns as all raw data will be sent to a centralized place. To address the above limitations for building future Internet of Things applications, we present an early design of a novel framework that combines Internet of Things, Semantic Web, and Big Data concepts. We not only present the core components to build an IoT system, but also list existing alternatives with their merits. This framework aims to incorporate open standards to address the potential challenges in building future IoT applications. Therefore, our discussion revolves around open standards to build the framework, rather than proprietary standards.
Item Type: | Book Chapter |
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Additional Information: | © © 2017 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. |
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Schools: | School of Computing and Engineering School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge |
Related URLs: | |
Depositing User: | Yongrui Qin |
Date Deposited: | 31 Jul 2017 14:35 |
Last Modified: | 28 Aug 2021 15:49 |
URI: | http://eprints.hud.ac.uk/id/eprint/32453 |
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