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Qualitative Failure Analysis of IoT-enabled Industrial Fire Detection and Prevention System
Rahman, Md M. ; Abdulhamid, A. ;
Rahman, Md M.
Abdulhamid, A.
Publication Date
2023-12
End of Embargo
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Rights
(c) 2023 IEEE. Full-text reproduced in accordance with the publisher's self-archiving policy.
Peer-Reviewed
Yes
Open Access status
embargoedAccess
Accepted for publication
2023-11-13
Institution
Department
Awarded
Embargo end date
2025-04-27
Additional title
Abstract
The Internet of Things (IoT) has improved our lives through various applications such as home automation, smart city monitoring, environmental monitoring, intelligent farming, and a host of others. IoT is increasingly being used for environmental monitoring to prevent fire incidents and other environmental hazards. However, for IoT systems to function effectively in preventing fire incidents, they must operate in a safe, reliable, and dependable manner. The intelligent sensors and devices that constitute the system are prone to different types of failures, which can lead to unsafe or dangerous conditions. Failure of a fire prevention system can pose significant risks to Health, Safety, and the Environment (HSE). To address these concerns, it is essential to understand how component failures can contribute to the overall system failure. This paper adopts Fault Tree Analysis, a widely used framework for failure behaviour analysis in other safety-critical domains, to qualitatively analyse an intelligent fire detection system in an industrial setting. The analysis outlines the ways in which the system can fail and the necessary prevention mechanism to guard against undesired system failure.
Version
Accepted manuscript
Citation
Rahman MM, Abdulhamid A, Kabir S et al (2023) Qualitative Failure Analysis of IoT-enabled Industrial Fire Detection and Prevention System. 26th International Conference on Computer and Information Technology (ICCIT) 13-15 Dec 2023, Cox’s Bazar, Bangladesh.
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Type
Conference paper
Qualification name
Notes
The full-text of this article will be released for public view at the end of the publisher embargo on 27 Apr 2025.