Reducing False Alarm of Video-Based Smoke Detection by Support Vector Machine

Yang, Chan-Yun; Tseng, Wei-Wen; Yang, Jr-Syu

doi:10.1007/978-3-540-69304-8_12

Cited by 2 publications

(2 citation statements)

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“…(a) Support Vector Machine and motion detection to detect the smoke plume contour (Yang, Tseng & Yang, 2008);…”

Section: Figure 12: Dominant Flame Lookup Table Creation Processmentioning

confidence: 99%

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Improving fire safety and asset loss control in mining: Evaluation and development of a video based fire detection system

Mendham¹

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The overall results of this research addressed the question of how increased time for mineworkers to evacuate mines prior to the onset of untenable fire conditions is achievable. Additionally, improved asset loss control for underground mining is feasible through the successful development of Video Based Fire Detection (VBFD) in mining, as it provides more information earlier for mine fire fighters to intervene in the growth and spread of fire, therefore maintainable coal production is achievable. VBFD may also be used to activate automatic fire suppression systems.VBFD is an emerging volume type smoke detection technology that utilises Closed Circuit Television (CCTV) cameras to capture and analyse real time video data for the purpose of smoke recognition. VBFD technology performance was compared with the performance of fire detection methods currently used in underground coalmines to determine whether valuable improvements to fire safety and asset loss control could be made. Monoxide (CO) concurrent at the VBFD alarm activation time. Sensitivity analysis was undertaken by varying the air velocity over the fire source, which affected the smoke plume shape. The other component of the sensitivity analysis involved variations in light levels aimed at testing the VBFD smoke detection sensitivity. The data were subsequently analysed to identify trends in the detection response of both the CO sensors and the VBFD. Some of the tests carried out exceeded the capability of the VBFD system, which was an important aspect in the research and the evolving capability of video smoke detection.iii The experimental fire characteristics were subsequently replicated numerically using Computational Fluid Dynamics (CFD) so it could be used in this research to estimate the evacuation response of mineworkers under more onerous fire conditions, which could not physically be undertaken in an operational mine.A following VBFD field study was proposed to review and utilise the results of installation commissioning data and maintenance testing of a VBFD system at an operational underground mine environment. The purpose of this field-testing was to inform the underground mining industry of limitations that may exist in terms of the VBFD reliability in service, such as potential maintenance issues. During the period of the subject research the Australian resources industry moved from being in a position to readily facilitate and support minor external unfunded research projects within its underground mine assets, to its current position where it was no longer willing or able to assist. As a result of the lack of a trial VBFD system in an underground mine, the subsequent field study opportunistically considered the reliability and performance of VBFD in a very similar and related environment, however this facility was not an underground mine, but a South African coal fired power station. The results of the reliability testing of 360 VBFD devices over a 12 months' period showed that VBFD was very reliable.Future VBFD research might ad...

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“…(a) Support Vector Machine and motion detection to detect the smoke plume contour (Yang, Tseng & Yang, 2008);…”

Section: Figure 12: Dominant Flame Lookup Table Creation Processmentioning

confidence: 99%

“…References: (Litton, 2009) (Guillemant, 2001), (Kessinger, 2008), (Marbach, Loepfe & Brupbacher, 2006), (Schultze & Willms, 2005), (Toreyin et al, 2007), (Yang, Tseng & Yang, 2008), (Yuan, 2007(Yuan, , 2008). …”

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Improving fire safety and asset loss control in mining: Evaluation and development of a video based fire detection system

Mendham¹

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Remote monitoring of an omnidirectional smoke detection system using texture features image processing techniques

Peng

Hsu

Her

et al. 2014

Engineering Computations

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Purpose – The purpose of this paper is to develop an early fire-alarm raising system based on video processing, and combine it with the omnidirectional projecting system. It not only gives alarm immediately in early fire so that people can be able to strive for more time to escape from the spot, but also solves problem of discontinued screen which was presented fire scene. Design/methodology/approach – The smoke detection system is made by image processing. The flowchart of smoke detection is improved, which the method of background updating can filter out the moving objects that only stay for a short time in the image; and avoids these objects being determined to be the background. Moreover, the authors extract the flickering area to separate the non-smoke and smoke from the candidate of smoke regions. Finally, the image processing is applied in omnidirectional projecting system, then presented the 360-degree fire scene. Findings – The results show that the smoke detection system can accurately detect the smoke and mark its location, then combining it with the omnidirectional projecting system, although the resolution of omnidirectional projecting system is not enough, it can present a continued screen and location of smoke on the 360-degree cylindrical screen. Originality/value – This paper develops the smoke detection based on a improved method of image processing, and the control center staff can see the 360-degree fire scene via omnidirectional projecting system, so shorten the time to find the source of smoke.

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Reducing False Alarm of Video-Based Smoke Detection by Support Vector Machine

Cited by 2 publications

References 12 publications

Improving fire safety and asset loss control in mining: Evaluation and development of a video based fire detection system

Improving fire safety and asset loss control in mining: Evaluation and development of a video based fire detection system

Remote monitoring of an omnidirectional smoke detection system using texture features image processing techniques

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