Mobile Information Systems

Mobile Information Systems / 2014 / Article
Special Issue

Internet of Things

View this Special Issue

Open Access

Volume 10 |Article ID 517486 | https://doi.org/10.1155/2014/517486

Yunchuan Sun, Hongli Yan, Cheng Lu, Rongfang Bie, Zhangbing Zhou, "Constructing the Web of Events from Raw Data in the Web of Things", Mobile Information Systems, vol. 10, Article ID 517486, 21 pages, 2014. https://doi.org/10.1155/2014/517486

Constructing the Web of Events from Raw Data in the Web of Things

Received23 Jul 2013
Accepted23 Jul 2013

Abstract

An exciting paradise of data is emerging into our daily life along with the development of the Web of Things. Nowadays, volumes of heterogeneous raw data are continuously generated and captured by trillions of smart devices like sensors, smart controls, readers and other monitoring devices, while various events occur in the physical world. It is hard for users including people and smart things to master valuable information hidden in the massive data, which is more useful and understandable than raw data for users to get the crucial points for problems-solving. Thus, how to automatically and actively extract the knowledge of events and their internal links from the big data is one key challenge for the future Web of Things. This paper proposes an effective approach to extract events and their internal links from large scale data leveraging predefined event schemas in the Web of Things, which starts with grasping the critical data for useful events by filtering data with well-defined event types in the schema. A case study in the context of smart campus is presented to show the application of proposed approach for the extraction of events and their internal semantic links.

Copyright © 2014 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

 PDF Download Citation Citation
 Order printed copiesOrder
Views445
Downloads871
Citations

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.