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Vision-based smoke detector

Abdullah, Ali Mohammed Noman and Htike@Muhammad Yusof, Zaw Zaw (2019) Vision-based smoke detector. International Journal of Engineering & Technology. ISSN 2227-524X (In Press)

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Abstract

Previous studies have documented the significant applications of the electronic smoke detector. With the capabilities of vision based fire detection and increase in the number of surveillance cameras, a lesser attention is given to the vision-based type smoke detector. Moreover, some drawbacks have been identified in the accuracy and efficiency of smoke detection. The present study proposes a vision based smoke detector to overcome the shortcomings of the current traditional electronic and vision based smoke detectors. A Convolutional Neural Network is used to classify the smoke regions. After testing the proposed method, the accuracy was approximately 94%. When a modern approach of object detection is used to support image classifying, its accuracy increases by 96%.

Item Type: Article (Journal)
Additional Information: 6919/73168
Uncontrolled Keywords: smoke detector
Subjects: T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Depositing User: Dr. Zaw Zaw Htike
Date Deposited: 15 Jul 2019 10:15
Last Modified: 15 Jul 2019 10:15
URI: http://irep.iium.edu.my/id/eprint/73168

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