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Web-of-Objects (WoO)-based context aware emergency fire management systems for the Internet of Things

Ara, Safina Showkat, Ush-Shamszaman, Z, Chong, Ilyoung and Jeong, Youn Kwae (2014) Web-of-Objects (WoO)-based context aware emergency fire management systems for the Internet of Things. Sensors, 14 (2). pp. 2944-2966. ISSN 1424-8220

Item Type: Article

Abstract

Recent advancements in the Internet of Things (IoT) and the Web of Things (WoT) accompany a smart life where real world objects, including sensing devices, are interconnected with each other. The Web representation of smart objects empowers innovative applications and services for various domains. To accelerate this approach, Web of Objects (WoO) focuses on the implementation aspects of bringing the assorted real world objects to the Web applications. In this paper; we propose an emergency fire management system in the WoO infrastructure. Consequently, we integrate the formation and management of Virtual Objects (ViO) which are derived from real world physical objects and are virtually connected with each other into the semantic ontology model. The charm of using the semantic ontology is that it allows information reusability, extensibility and interoperability, which enable ViOs to uphold orchestration, federation, collaboration and harmonization. Our system is context aware, as it receives contextual environmental information from distributed sensors and detects emergency situations. To handle a fire emergency, we present a decision support tool for the emergency fire management team. The previous fire incident log is the basis of the decision support system. A log repository collects all the emergency fire incident logs from ViOs and stores them in a repository.

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Uncontrolled Keywords: Internet of Things (IoT); Web of Things (WoT); emergency fire management; context awareness; ViOs; semantic ontology
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Depositing User: Safina Ara

Identifiers

Item ID: 18336
Identification Number: https://doi.org/10.3390/s140202944
ISSN: 1424-8220
URI: http://sure.sunderland.ac.uk/id/eprint/18336
Official URL: https://www.mdpi.com/1424-8220/14/2/2944

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Catalogue record

Date Deposited: 27 Sep 2024 12:27
Last Modified: 27 Sep 2024 12:30

Contributors

Author: Safina Showkat Ara
Author: Z Ush-Shamszaman
Author: Ilyoung Chong
Author: Youn Kwae Jeong

University Divisions

Faculty of Technology > School of Computer Science

Subjects

Computing > Artificial Intelligence
Computing

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