Intelligent fire monitoring system based on depth learning and method thereof

An intelligent monitoring system and deep learning technology, applied in the field of image recognition and computer vision, can solve difficult small fire monitoring and other problems, and achieve the effect of improving incomplete feature extraction and strong feature extraction ability

Inactive Publication Date: 2019-06-18
SHANGHAI MARITIME UNIVERSITY
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AI Technical Summary

Problems solved by technology

However, the image processing unit in the monitoring system still uses manual extraction of the morphological and color features of the flame a

Method used

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  • Intelligent fire monitoring system based on depth learning and method thereof
  • Intelligent fire monitoring system based on depth learning and method thereof
  • Intelligent fire monitoring system based on depth learning and method thereof

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Embodiment Construction

[0041] In order to make the present invention more obvious and understandable, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0042] like figure 1 As shown, the present invention discloses a fire intelligent monitoring system based on deep learning, which mainly includes five modules: an image acquisition module, an image analysis module, an alarm module, a flame location module and a fixed-point fire extinguishing module.

[0043]The image acquisition module performs real-time monitoring in different places through the binocular camera, and collects monitoring video image data; the image analysis module mainly uses the trained deep learning model MaskR-CNN to perform real-time monitoring of the flame in the monitoring video image data. Detect and obtain the flame pixel position information; in the alarm module, once the flame is detected, the monitoring room alarm will be triggered to remind the ...

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Abstract

The invention discloses an intelligent fire monitoring system based on depth learning and a method thereof. The system includes an image acquisition module performing real-time monitoring through a binocular camera, an image analysis module utilizing a deep learning model to perform real-time flame detection of monitoring video images, an alarm module used for prompting monitoring personnel to observe the fire in the monitoring video images, a flame positioning module used for receiving the flame pixel position information detected by the deep learning model and mapping the flame pixel position information to the space through the binocular stereo visual positioning algorithm to obtain the flame space position information, and a fixed point fire extinguishing module used for receiving theflame space position information at preset time intervals under the condition that the alarm module has no response and the alarm continues. The system is advantaged in that through combination of depth learning and the camera positioning algorithm for flame identification, a new convolutional kernel module is proposed, feature extraction capability is stronger, alarm can be performed when the flame is detected, and fixed point fire extinguishing for the flame area in the event of no reaction of the monitoring personnel is performed.

Description

technical field [0001] The invention relates to the fields of image recognition and computer vision, in particular to a deep learning-based intelligent fire monitoring system and method thereof. Background technique [0002] Fire is one of the most common disasters. If it cannot be controlled in time in the early stage, it will further cause a large area of ​​fire, which will cause irreparable loss of life and property. Especially in some special non-smoking places, such as bus stations, gas stations, logistics warehouses, etc., once a fire is caused by artificial smoking or other factors, the consequences will be very serious. Therefore, it is very necessary to monitor smoking behavior and detect fires early. [0003] Flame is a physical phenomenon in the early stage of fire. The early flame detection technologies mainly include temperature sensing, smoke sensing and light sensing. They have been widely used, but there are still technical defects such as low sensitivity, e...

Claims

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Application Information

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IPC IPC(8): G08B17/12G06K9/00G06K9/32
Inventor 安超魏海军刘竑武燊梁麒立
Owner SHANGHAI MARITIME UNIVERSITY
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