Method for carrying out environmental protection unorganized emission supervision by using machine learning

An unorganized emission and machine learning technology, applied in machine learning, instruments, data processing applications, etc., can solve problems such as unorganized monitoring difficulties, and achieve the effect of reducing labor monitoring costs and improving monitoring efficiency.

Pending Publication Date: 2021-07-20
MAANSHAN IRON & STEEL CO LTD
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

[0004] Aiming at the deficiencies of the prior art, the present invention provides a method of using machine learning to monitor unorganized emissions for environmental protection, which solves the problem of difficulty in unorganized monitoring

Method used

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  • Method for carrying out environmental protection unorganized emission supervision by using machine learning

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Experimental program
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Embodiment

[0027] The video recognition analysis server uses a physical server, and the specific configuration is as follows:

[0028] DL580 Gen1061262P 32GB 8SFF CN Svr (standard with 2 IntelXeon-Gold 6126 (2.6GHz / 12-core / 120W) processors; 64GB DDR4-2666 MT / s memory). The server is equipped with an rtx2080ti high-performance graphics card, and the video recognition model is based on GPU for high-speed calculation.

[0029] The system's AI video analysis model is based on a neural network object recognition algorithm: YOLO. YOLO is an object recognition and positioning algorithm based on a deep neural network. Its biggest feature is that it runs very fast and can be used in real-time systems.

[0030] Introduction to the model checking process:

[0031] 1. Resize the picture to 448*448.

[0032] 2. Put the pictures on the network for processing.

[0033] 3. Perform non-maximum value suppression processing to obtain the result.

[0034] 4. A single convolutional neural network is use...

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Abstract

The invention discloses a method for carrying out environmental protection unorganized emission supervision by using machine learning, and relates to the technical field of intelligent monitoring identification. According to the method for carrying out environmental protection unorganized emission supervision by using machine learning, video information is effectively learned by utilizing the high efficiency of machine learning, and the types and types of emissions are judged; and meanwhile, a yolk system is adopted for real-time monitoring, so that the manpower monitoring cost is effectively reduced, and the monitoring efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of intelligent monitoring and identification, and specifically relates to a method for using machine learning to supervise environmental fugitive emissions. Background technique [0002] It is an urgent need for iron and steel enterprises to improve the efficiency of unorganized control and avoid environmental emergencies. It is found that traditional methods such as video AI intelligent automatic recognition technology and Bilingoman grayscale recognition can increase management efficiency and have broader application scenarios. Contents of the invention [0003] (1) Solved technical problems [0004] Aiming at the deficiencies of the prior art, the present invention provides a method of using machine learning to supervise the unorganized emission of environmental protection, which solves the problem of difficulty in unorganized monitoring. [0005] (2) Technical solution [0006] In order to achieve t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06F16/25G06F16/28G06N20/00
CPCG06Q10/063114G06F16/252G06F16/287G06N20/00
Inventor 车文华於琪王洋
Owner MAANSHAN IRON & STEEL CO LTD
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