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 |
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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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More Information
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 |
Author: | Safina Showkat Ara |
Author: | Z Ush-Shamszaman |
Author: | Ilyoung Chong |
Author: | Youn Kwae Jeong |
University Divisions
Faculty of Technology > School of Computer ScienceSubjects
Computing > Artificial IntelligenceComputing
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