Fire-fighting inspection quality evaluation system and method

Abstract

The invention relates to the technical field of fire-fighting inspection, and discloses a fire-fighting inspection quality evaluation system and method, and the system comprises an obtaining module which is used for obtaining a pre-inspection image of an inspection region, and determining an inspection quality permissible threshold according to the pre-inspection image of the inspection region; the calculation module is used for acquiring the polled image of the polled area and determining a polled quality coefficient according to the polled image of the polled area; the correction module is used for acquiring the inspection process video of the inspection area and correcting the inspection quality coefficient according to the inspection process video of the inspection area; and the evaluation module is used for determining an inspection quality evaluation coefficient according to the corrected inspection quality coefficient and a quality allowable threshold value, and determining a fire-fighting inspection quality grade according to the inspection quality evaluation coefficient. The fire-fighting inspection quality is comprehensively evaluated by combining the inspection images before, during and after the fire-fighting inspection, the probability of omission of the inspection can be effectively reduced, and the fire-fighting inspection quality is improved.

Description

Technical Field

[0001] This application relates to the technical field of fire inspection, and more specifically, to a fire inspection quality assessment system and method. Background Art

[0002] With the continuous advancement of urban construction and industrial development, fire safety issues have become increasingly prominent. Fire safety accidents not only cause property losses, but may also lead to casualties and even have a serious impact on the surrounding environment. Therefore, it is particularly important to improve the quality of fire inspections.

[0003] In the prior art, after the fire inspection is completed, there is no evaluation mechanism for the quality of fire inspections. Inspectors cannot timely discover the fire drawbacks existing in the inspection process, resulting in inspection omissions and even fire safety accidents. Summary of the Invention

[0004] The present invention provides a fire inspection quality assessment system and method to solve the problem of the lack of evaluation of the quality of fire inspections in the prior art, including:

[0005] An acquisition module, configured to acquire the pre-inspection image of the inspection area and determine the inspection quality tolerance threshold according to the pre-inspection image of the inspection area;

[0006] A calculation module, configured to acquire the post-inspection image of the inspection area and determine the inspection quality coefficient according to the post-inspection image of the inspection area;

[0007] A correction module, configured to acquire the inspection process video of the inspection area and correct the inspection quality coefficient according to the inspection process video of the inspection area;

[0008] An evaluation module, configured to determine the inspection quality evaluation coefficient according to the corrected inspection quality coefficient and the quality tolerance threshold, and determine the fire inspection quality level according to the inspection quality evaluation coefficient.

[0009] Further, the acquisition module determines the inspection quality tolerance threshold according to the pre-inspection image of the inspection area, including:

[0010] Dividing the pre-inspection image of each inspection area into a plurality of first image blocks, acquiring the ratio of the area of fire hazardous substances in the first image block to the area of the first image block to obtain the hazardous substance density value;

[0011] Selecting the first hidden danger image blocks with the hazardous substance density value greater than the first preset threshold, and determining the distance attenuation coefficient according to the distance value between each first hidden danger image block and the nearest first hidden danger image block;

[0012] Multiply the dangerous goods density value of each hidden danger first image block by the corresponding distance attenuation coefficient to obtain the corrected dangerous goods density value of the hidden danger first image block;

[0013] Calculate the sum value of the corrected dangerous goods density values of all hidden danger first image blocks in the inspection area to obtain the inspection safety coefficient of the inspection area;

[0014] Cluster each inspection area according to the inspection safety coefficient, and determine the cluster partition to which each inspection area belongs according to the clustering result;

[0015] Standardize the cluster center of the cluster partition to obtain the initial inspection quality tolerance threshold, and multiply the standardized cluster center by the initial inspection quality tolerance threshold to obtain the inspection quality tolerance threshold corresponding to each cluster partition.

[0016] Further, the clustering of each inspection area according to the inspection safety coefficient includes:

[0017] Establish an inspection safety data set according to the inspection safety coefficient, and randomly select k initial cluster centers of the inspection safety data set;

[0018] Calculate the Euclidean distance from the inspection safety coefficient in the inspection safety data set to the initial cluster center, and divide each inspection area into the corresponding cluster according to the Euclidean distance from the inspection safety coefficient in the inspection safety data set to the initial cluster center;

[0019] Calculate the average value of the inspection safety coefficients in each cluster, and re-determine the cluster center according to the average value of the inspection safety coefficients in each cluster;

[0020] Repeat the above steps iteratively until the cluster center no longer changes or the number of iterations reaches the preset iteration threshold to obtain the clustering result of the inspection area.

[0021] Further, the calculation module determines the inspection quality coefficient according to the post-inspection image of the inspection area, including:

[0022] Perform grayscale processing on the post-inspection image to obtain the post-inspection grayscale image;

[0023] Divide the post-inspection grayscale image into several second image blocks on average, and calculate the difference between the grayscale value of each pixel point in the second image block and the preset fire-fighting equipment grayscale value;

[0024] Count the number of pixel points in each second image block whose difference between the grayscale value and the preset fire-fighting equipment grayscale value is less than the second preset threshold, and screen out the second image blocks with a quantity greater than the third preset threshold;

[0025] Perform mean filtering on the selected second image block to obtain the fire equipment image after image enhancement, and determine the inspection quality coefficient according to the fire equipment image after image enhancement.

[0026] Further, the determining the inspection quality coefficient according to the fire equipment image after image enhancement includes:

[0027] Obtain a preset standard fire equipment image, and determine the matching degree between the fire equipment after inspection and the preset standard fire equipment according to the fire equipment image after image enhancement;

[0028] Determine the distance values between each fire equipment and its adjacent fire equipment according to the fire equipment image after image enhancement, and determine the distance weights of each fire equipment according to the distance values between each fire equipment and its adjacent fire equipment;

[0029] Multiply the matching degree between the fire equipment after inspection and the preset standard fire equipment by the distance weight to obtain the inspection quality coefficient.

[0030] Further, the correction module corrects the inspection quality coefficient according to the inspection process video of the inspection area, including:

[0031] Obtain the historical inspection data of the inspection area, and determine the standard inspection time of each inspection point in the inspection area according to the historical inspection data;

[0032] Obtain the best moving trajectory of the inspection point, and determine the optimal inspection plan according to the best moving trajectory of the inspection point and the standard inspection time;

[0033] Determine the moving trajectory of the inspection personnel according to the inspection process video of the inspection area, and establish a trajectory curve according to the moving trajectory coordinate values and the time used by the inspection personnel;

[0034] Calculate the correlation coefficient between the trajectory curve of the inspection personnel and the trajectory curve of the optimal inspection plan, and correct the inspection quality coefficient according to the correlation coefficient to obtain the corrected inspection quality coefficient.

[0035] Further, the correcting the inspection quality coefficient according to the correlation coefficient includes:

[0036] Correct the inspection quality coefficient according to the inspection quality correction formula, and the inspection quality correction formula is specifically:

[0037]

[0038] where, Q c is the corrected inspection quality coefficient, Q0 is the inspection quality coefficient before correction, R is the correlation coefficient between the trajectory curve of the inspection personnel and the trajectory curve of the optimal inspection plan, and R0 is the preset standard correlation coefficient.

[0039] Further, the evaluation module determines a fire inspection quality evaluation coefficient based on the corrected inspection quality coefficient and the quality tolerance threshold, including:

[0040] Calculate the difference between the corrected inspection quality coefficient and the inspection quality tolerance threshold, and set the difference between the corrected inspection quality coefficient and the inspection quality tolerance threshold as the inspection quality evaluation coefficient.

[0041] Further, the evaluation module determines the fire inspection quality level based on the inspection quality evaluation coefficient, including:

[0042] Judge whether the inspection quality evaluation coefficient is greater than the fourth preset threshold. If the inspection quality evaluation coefficient is greater than the fourth preset threshold, set the first level as the fire inspection quality level;

[0043] If the inspection quality evaluation coefficient is less than or equal to the fourth preset threshold, judge whether the inspection quality evaluation coefficient is greater than the fifth preset threshold;

[0044] If the inspection quality evaluation coefficient is greater than the fifth preset threshold, set the second level as the fire inspection quality level;

[0045] If the inspection quality evaluation coefficient is less than or equal to the fifth preset threshold, set the third level as the fire inspection quality level.

[0046] To achieve the above object, the present invention also provides a method for evaluating fire inspection quality, including:

[0047] Obtain the pre-inspection image of the inspection area, and determine the inspection quality tolerance threshold according to the pre-inspection image of the inspection area;

[0048] Obtain the post-inspection image of the inspection area, and determine the inspection quality coefficient according to the post-inspection image of the inspection area;

[0049] Obtain the inspection process video of the inspection area, and correct the inspection quality coefficient according to the inspection process video of the inspection area;

[0050] Determine the inspection quality evaluation coefficient according to the corrected inspection quality coefficient and the quality tolerance threshold, and determine the fire inspection quality level according to the inspection quality evaluation coefficient.

[0051] The beneficial effects of the present invention are as follows:

[0052] By applying the above technical solutions, the present invention can comprehensively evaluate the fire inspection quality by combining the video image data of the inspection area before, during, and after the inspection, can effectively reduce the probability of inspection omission, improve the fire inspection quality, and reduce the probability of occurrence of fire safety accidents. Description of the Drawings

[0053] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0054] Figure 1 It shows the overall structure diagram of a fire inspection quality assessment system proposed in an embodiment of the present invention;

[0055] Figure 2 It shows the schematic flowchart of a fire inspection quality assessment method proposed in an embodiment of the present invention. Specific embodiments

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0057] The embodiments of the present application provide a fire inspection quality assessment system, as Figure 1 shown, including:

[0058] An acquisition module, configured to acquire the pre-inspection image of the inspection area and determine the inspection quality tolerance threshold according to the pre-inspection image of the inspection area; a calculation module, configured to acquire the post-inspection image of the inspection area and determine the inspection quality coefficient according to the post-inspection image of the inspection area; a correction module, configured to acquire the inspection process video of the inspection area and correct the inspection quality coefficient according to the inspection process video of the inspection area; an evaluation module, configured to determine the inspection quality evaluation coefficient according to the corrected inspection quality coefficient and the quality tolerance threshold, and determine the fire inspection quality level according to the inspection quality evaluation coefficient.

[0059] In this embodiment, multiple fire inspection areas are preset in advance. After the inspection personnel perform fire inspections in their respective inspection areas, they use high-definition cameras to record the pre-inspection image, inspection process video, and post-inspection image of the inspection area in real time.

[0060] In some embodiments of the present application, the obtaining module determines the inspection quality tolerance threshold according to the pre-inspection image of the inspection area, including: evenly dividing the pre-inspection images of each inspection area into several first image blocks, obtaining the ratio of the area of the fire hazardous substances in the first image block to the area of the first image block to obtain the hazardous substances density value; screening out the first hazard image blocks with the hazardous substances density value greater than the first preset threshold, and determining the distance attenuation coefficient according to the distance value between each first hazard image block and the nearest first hazard image block; multiplying the hazardous substances density value of each first hazard image block by the corresponding distance attenuation coefficient to obtain the corrected hazardous substances density value of the first hazard image block; calculating the sum value of the corrected hazardous substances density values of all the first hazard image blocks in the inspection area to obtain the inspection safety coefficient of the inspection area; clustering each inspection area according to the inspection safety coefficient, and determining the clustering partition to which each inspection area belongs according to the clustering result; performing normalization processing on the clustering center of the clustering partition to obtain the initial inspection quality tolerance threshold, and multiplying the normalized clustering center by the initial inspection quality tolerance threshold to obtain the inspection quality tolerance threshold corresponding to each clustering partition.

[0061] In this embodiment, the distance attenuation coefficient is determined according to the distance value between each first hazard image block and the nearest first hazard image block. The larger the distance value, the smaller the corresponding distance attenuation coefficient, and the higher the attenuation degree of the hazardous substances density value. The hazardous substances density value is corrected by the distance attenuation coefficient, so as to obtain the inspection quality tolerance threshold corresponding to the inspection area.

[0062] In some embodiments of the present application, the clustering of each inspection area according to the inspection safety coefficient includes: establishing an inspection safety data set according to the inspection safety coefficient, and randomly selecting k initial clustering centers of the inspection safety data set; calculating the Euclidean distance from the inspection safety coefficient in the inspection safety data set to the initial clustering center, and dividing each inspection area into the corresponding clustering cluster according to the Euclidean distance from the inspection safety coefficient in the inspection safety data set to the initial clustering center; calculating the average value of the inspection safety coefficients in each clustering cluster, and re-determining the clustering center according to the average value of the inspection safety coefficients in each clustering cluster; repeating the above steps iteratively until the clustering center no longer changes or the number of iterations reaches the preset iteration threshold, to obtain the clustering result of the inspection area.

[0063] In this embodiment, each inspection area is clustered based on the k-means clustering algorithm, and the k value is set according to the number of inspection areas. The more the inspection areas, the larger the corresponding k value.

[0064] In some embodiments of the present application, the calculation module determines the inspection quality coefficient according to the post-inspection image of the inspection area, including: performing grayscale processing on the post-inspection image to obtain a post-inspection grayscale image; dividing the post-inspection grayscale image into several second image blocks evenly, and calculating the difference between the grayscale values of each pixel point in the second image block and the preset grayscale value of the fire-fighting equipment; counting the number of pixel points in each second image block whose difference between the grayscale value and the preset grayscale value of the fire-fighting equipment is less than the second preset threshold, and screening out the second image blocks with the number greater than the third preset threshold; performing mean filtering on the screened second image blocks to obtain a fire-fighting equipment image after image enhancement, and determining the inspection quality coefficient according to the fire-fighting equipment image after image enhancement.

[0065] In this embodiment, the second image blocks with fire-fighting equipment are screened out by the number of pixel points in each second image block whose difference between the grayscale value and the preset grayscale value of the fire-fighting equipment is less than the second preset threshold, and the second image blocks are subjected to image enhancement, so as to facilitate the subsequent calculation of the inspection quality coefficient.

[0066] In some embodiments of the present application, determining the inspection quality coefficient according to the fire-fighting equipment image after image enhancement includes: obtaining a preset standard fire-fighting equipment image, and determining the matching degree between the post-inspection fire-fighting equipment and the preset standard fire-fighting equipment according to the fire-fighting equipment image after image enhancement; determining the distance value between each fire-fighting equipment and its adjacent fire-fighting equipment according to the fire-fighting equipment image after image enhancement, and determining the distance weight of each fire-fighting equipment according to the distance value between each fire-fighting equipment and its adjacent fire-fighting equipment; multiplying the matching degree between the post-inspection fire-fighting equipment and the preset standard fire-fighting equipment by the distance weight to obtain the inspection quality coefficient.

[0067] In this embodiment, the distance weight of each fire-fighting equipment is determined by the distance value between each fire-fighting equipment and its adjacent fire-fighting equipment. The larger the distance value is, the smaller the corresponding distance weight is.

[0068] In some embodiments of the present application, the correction module corrects the inspection quality coefficient according to the inspection process video of the inspection area, including: obtaining the historical inspection data of the inspection area, and determining the standard inspection time of each inspection point in the inspection area according to the historical inspection data; obtaining the best movement trajectory of the inspection point, and determining the optimal inspection plan according to the best movement trajectory of the inspection point and the standard inspection time; determining the movement trajectory of the inspection personnel according to the inspection process video of the inspection area, and establishing a trajectory curve according to the movement trajectory coordinate values and the time used by the inspection personnel; calculating the correlation coefficient between the trajectory curve of the inspection personnel and the trajectory curve of the optimal inspection plan, and correcting the inspection quality coefficient according to the correlation coefficient to obtain the corrected inspection quality coefficient.

[0069] In some embodiments of the present application, the correction of the inspection quality coefficient according to the correlation coefficient includes: correcting the inspection quality coefficient according to the inspection quality correction formula, and the inspection quality correction formula is specifically as follows:

[0070]

[0071] where Q c is the corrected inspection quality coefficient, Q0 is the inspection quality coefficient before correction, R is the correlation coefficient between the trajectory curve of the inspection personnel and the trajectory curve of the optimal inspection plan, and R0 is the preset standard correlation coefficient.

[0072] In this embodiment, by establishing a trajectory curve based on the moving trajectory coordinate values and the time used by the inspection personnel, with the time used as the abscissa and converting the moving trajectory coordinate values of the inspection personnel into a curve according to a preset ratio, the trajectory curve is obtained, and the corrected inspection quality coefficient is calculated through the correlation coefficient between the trajectory curve of the inspection personnel and the trajectory curve of the optimal inspection plan.

[0073] In some embodiments of the present application, the evaluation module determines the inspection quality evaluation coefficient according to the corrected inspection quality coefficient and the quality tolerance threshold, including: calculating the difference between the corrected inspection quality coefficient and the inspection quality tolerance threshold, and setting the difference between the corrected inspection quality coefficient and the inspection quality tolerance threshold as the inspection quality evaluation coefficient.

[0074] In some embodiments of the present application, the evaluation module determines the fire inspection quality level according to the inspection quality evaluation coefficient, including: judging whether the inspection quality evaluation coefficient is greater than the fourth preset threshold. If the inspection quality evaluation coefficient is greater than the fourth preset threshold, the first level is set as the fire inspection quality level; if the inspection quality evaluation coefficient is less than or equal to the fourth preset threshold, it is judged whether the inspection quality evaluation coefficient is greater than the fifth preset threshold; if the inspection quality evaluation coefficient is greater than the fifth preset threshold, the second level is set as the fire inspection quality level; if the inspection quality evaluation coefficient is less than or equal to the fifth preset threshold, the third level is set as the fire inspection quality level.

[0075] Based on the same technical concept, as Figure 2 shown, the present invention also provides a method for evaluating fire inspection quality, including:

[0076] S101, obtaining the pre-inspection image of the inspection area and determining the inspection quality tolerance threshold according to the pre-inspection image of the inspection area;

[0077] S102, obtaining the post-inspection image of the inspection area and determining the inspection quality coefficient according to the post-inspection image of the inspection area;

[0078] S103. Obtain the inspection process video of the inspection area, and correct the inspection quality coefficient according to the inspection process video of the inspection area;

[0079] S104. Determine the inspection quality evaluation coefficient according to the corrected inspection quality coefficient and the quality tolerance threshold, and determine the fire inspection quality level according to the inspection quality evaluation coefficient.

[0080] By applying the above technical solutions, the present invention obtains the pre-inspection image of the inspection area, determines the inspection quality tolerance threshold according to the pre-inspection image of the inspection area; obtains the post-inspection image of the inspection area, determines the inspection quality coefficient according to the post-inspection image of the inspection area; obtains the inspection process video of the inspection area, and corrects the inspection quality coefficient according to the inspection process video of the inspection area; determines the inspection quality evaluation coefficient according to the corrected inspection quality coefficient and the quality tolerance threshold, and determines the fire inspection quality level according to the inspection quality evaluation coefficient.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims

1. A fire inspection quality assessment system, characterized in that: include: An acquisition module is used to acquire a pre-inspection image of the inspection area and determine an inspection quality allowable threshold value based on the pre-inspection image of the inspection area; A calculation module is used to obtain a post-inspection image of the inspection area and determine an inspection quality coefficient according to the post-inspection image of the inspection area; A correction module is used to obtain the inspection process video of the inspection area and correct the inspection quality coefficient according to the inspection process video of the inspection area; The evaluation module is used to determine the inspection quality evaluation coefficient according to the revised inspection quality coefficient and the quality tolerance threshold, and determine the fire inspection quality level according to the inspection quality evaluation coefficient.

2. The fire inspection quality assessment system according to claim 1, characterized in that: The acquisition module determines the inspection quality tolerance threshold according to the pre-inspection image of the inspection area, including: Divide the pre-inspection image of each inspection area into a plurality of first image blocks, obtain the ratio of the area of ​​fire-fighting hazardous materials in the first image block to the area of ​​the first image block, and obtain the density value of the hazardous materials; Screen out hidden danger first image blocks whose dangerous goods density value is greater than a first preset threshold, and determine the distance attenuation coefficient according to the distance value between each hidden danger first image block and the hidden danger first image block closest to it; Multiply the dangerous goods density value of the first image block of each hidden danger by the corresponding distance attenuation coefficient to obtain the corrected dangerous goods density value of the first image block of the hidden danger; Calculate the sum of the corrected dangerous goods density values ​​of the first image blocks of all hidden dangers in the inspection area to obtain the inspection safety factor of the inspection area; Cluster each inspection area according to the inspection safety factor, and determine the cluster partition to which each inspection area belongs based on the clustering results; The cluster centers of the cluster partitions are standardized to obtain an initial inspection quality allowable threshold, and the standardized cluster centers are multiplied by the initial inspection quality allowable threshold to obtain an inspection quality allowable threshold corresponding to each cluster partition.

3. The fire inspection quality assessment system according to claim 2, characterized in that: The clustering of each inspection area according to the inspection safety factor includes: Establish an inspection safety data set according to the inspection safety factor, and randomly select k initial cluster centers of the inspection safety data set; Calculate the Euclidean distance from the inspection safety factor in the inspection safety data set to the initial cluster center, and divide each inspection area into a corresponding cluster cluster according to the Euclidean distance from the inspection safety factor in the inspection safety data set to the initial cluster center; Calculate the average value of the inspection safety factor within each cluster, and re-determine the cluster center based on the average value of the inspection safety factor within each cluster; Repeat the above steps until the cluster center no longer changes or the number of iterations reaches a preset iteration threshold, and obtain the clustering result of the inspection area.

4. The fire inspection quality assessment system according to claim 1, characterized in that: The calculation module determines the inspection quality coefficient according to the post-inspection image of the inspection area, including: Grayscale processing is performed on the image after inspection to obtain a grayscale image after inspection; The grayscale image after inspection is evenly divided into a plurality of second image blocks, and the difference between the grayscale value of each pixel in the second image block and the grayscale value of the preset fire-fighting equipment is calculated; Counting the number of pixel points in each second image block whose difference between the grayscale value and the preset fire-fighting equipment grayscale value is less than a second preset threshold, and screening out second image blocks whose number is greater than a third preset threshold; The screened second image block is subjected to mean filtering to obtain an image of fire-fighting equipment after image enhancement, and the inspection quality coefficient is determined according to the image of fire-fighting equipment after image enhancement.

5. The fire inspection quality assessment system according to claim 4, characterized in that: Determining the inspection quality coefficient according to the fire-fighting equipment image after image enhancement includes: Obtain a preset standard fire-fighting equipment image, and determine the matching degree between the fire-fighting equipment after inspection and the preset standard fire-fighting equipment according to the fire-fighting equipment image after image enhancement; Determine the distance value between each fire-fighting equipment and adjacent fire-fighting equipment according to the fire-fighting equipment image after image enhancement, and determine the distance weight of each fire-fighting equipment according to the distance value between each fire-fighting equipment and adjacent fire-fighting equipment; The inspection quality coefficient is obtained by multiplying the matching degree between the fire-fighting equipment after inspection and the preset standard fire-fighting equipment by the distance weight.

6. The fire inspection quality assessment system according to claim 1, characterized in that: The correction module corrects the inspection quality coefficient according to the inspection process video of the inspection area, including: Obtain historical inspection data of the inspection area, and determine the standard inspection time of each inspection point in the inspection area based on the historical inspection data; Obtain the optimal movement trajectory of the inspection points, and determine the optimal inspection plan based on the optimal movement trajectory of the inspection points and the standard inspection time; Determine the movement trajectory of the inspectors based on the inspection process video of the inspection area, and establish a trajectory curve based on the coordinate values ​​of the movement trajectory of the inspectors and the time used; The correlation coefficient between the trajectory curve of the inspection personnel and the trajectory curve of the optimal inspection plan is calculated, and the inspection quality coefficient is corrected according to the correlation coefficient to obtain the corrected inspection quality coefficient.

7. The fire inspection quality assessment system according to claim 6, characterized in that: The correction of the inspection quality coefficient according to the correlation coefficient includes: The inspection quality coefficient is corrected according to the inspection quality correction formula, and the inspection quality correction formula is specifically: Among them, Q c is the inspection quality coefficient after correction, Q0 is the inspection quality coefficient before correction, R is the correlation coefficient between the trajectory curve of the inspection personnel and the trajectory curve of the optimal inspection plan, and R0 is the preset standard correlation coefficient.

8. The fire inspection quality assessment system according to claim 1, characterized in that: The evaluation module determines the inspection quality evaluation coefficient according to the corrected inspection quality coefficient and the quality tolerance threshold, including: The difference between the corrected inspection quality coefficient and the inspection quality allowable threshold is calculated, and the difference between the corrected inspection quality coefficient and the inspection quality allowable threshold is set as the inspection quality evaluation coefficient.

9. The fire inspection quality assessment system according to claim 8, characterized in that: The evaluation module determines the fire inspection quality level according to the inspection quality evaluation coefficient, including: Determine whether the inspection quality evaluation coefficient is greater than a fourth preset threshold value, and if the inspection quality evaluation coefficient is greater than the fourth preset threshold value, set the first level as the fire inspection quality level; If the inspection quality evaluation coefficient is less than or equal to the fourth preset threshold, determining whether the inspection quality evaluation coefficient is greater than the fifth preset threshold; If the inspection quality evaluation coefficient is greater than the fifth preset threshold, the second level is set as the fire inspection quality level; If the inspection quality evaluation coefficient is less than or equal to the fifth preset threshold, the third level is set as the fire inspection quality level.

10. A fire inspection quality assessment method, characterized in that: include: Acquire a pre-inspection image of the inspection area, and determine an inspection quality allowable threshold value based on the pre-inspection image of the inspection area; Obtaining a post-inspection image of the inspection area, and determining an inspection quality coefficient according to the post-inspection image of the inspection area; Obtain the inspection process video of the inspection area, and correct the inspection quality coefficient according to the inspection process video of the inspection area; The inspection quality evaluation coefficient is determined based on the revised inspection quality coefficient and the quality tolerance threshold, and the fire inspection quality level is determined based on the inspection quality evaluation coefficient.

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