Vision-based smoke detector
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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English English |
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Science Publishing Corporation
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/73168/ http://irep.iium.edu.my/73168/1/Vision%20Based%20Smoke%20detector%20%282%29.pdf http://irep.iium.edu.my/73168/2/Vision-based%20acceptance.pdf |
| _version_ | 1848787750048759808 |
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| author | Abdullah, Ali Mohammed Noman Htike@Muhammad Yusof, Zaw Zaw |
| author_facet | Abdullah, Ali Mohammed Noman Htike@Muhammad Yusof, Zaw Zaw |
| author_sort | Abdullah, Ali Mohammed Noman |
| building | IIUM Repository |
| collection | Online Access |
| description | 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%. |
| first_indexed | 2025-11-14T17:29:53Z |
| format | Article |
| id | iium-73168 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:29:53Z |
| publishDate | 2019 |
| publisher | Science Publishing Corporation |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-731682019-07-15T02:15:50Z http://irep.iium.edu.my/73168/ Vision-based smoke detector Abdullah, Ali Mohammed Noman Htike@Muhammad Yusof, Zaw Zaw T Technology (General) 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%. Science Publishing Corporation 2019 Article PeerReviewed application/pdf en http://irep.iium.edu.my/73168/1/Vision%20Based%20Smoke%20detector%20%282%29.pdf application/pdf en http://irep.iium.edu.my/73168/2/Vision-based%20acceptance.pdf 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) |
| spellingShingle | T Technology (General) Abdullah, Ali Mohammed Noman Htike@Muhammad Yusof, Zaw Zaw Vision-based smoke detector |
| title | Vision-based smoke detector |
| title_full | Vision-based smoke detector |
| title_fullStr | Vision-based smoke detector |
| title_full_unstemmed | Vision-based smoke detector |
| title_short | Vision-based smoke detector |
| title_sort | vision-based smoke detector |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/73168/ http://irep.iium.edu.my/73168/1/Vision%20Based%20Smoke%20detector%20%282%29.pdf http://irep.iium.edu.my/73168/2/Vision-based%20acceptance.pdf |