CN116757496A - Fire disaster early warning method for coordination of real-time city monitoring based on monitoring scene - Google Patents
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Abstract
The invention relates to the technical field of urban safety monitoring. The invention relates to a fire early warning method for coordinating real-time city monitoring based on a monitoring scene. Which comprises the following steps: s1, defining an area to be monitored, collecting image information of the area, and simultaneously monitoring road condition data of the area in real time; according to the invention, the automatic monitoring of the city is realized through image acquisition, the fire target is identified in real time, the fire detection and early warning efficiency is greatly improved, the image is processed and analyzed by utilizing an image processing technology and a fire detection algorithm, the fire target can be accurately identified, the interference of other moving targets is eliminated, the fire center can judge the fire condition and allocate personnel according to the image information through uploading the image information, the fire extinguishing work is more efficient and safe, the adaptability and the expandability are stronger, and meanwhile, the data is formulated by the improvement scheme through the feedback of fire fighters, and the use effect of the formulated scheme is improved.
Description
Technical Field
The invention relates to the technical field of urban safety monitoring, in particular to a fire early warning method for coordinating real-time urban monitoring based on a monitoring scene.
Background
The urban fire disaster is a serious safety threat, the fire disaster is quickly found and timely measures are important for reducing the loss of the fire disaster, the urban safety monitoring system relies on manual patrol and alarm telephone to find the fire disaster, the problems of slow response, low accuracy and high labor cost exist, and meanwhile, the fire disaster alarm system cannot accurately identify a fire disaster target, so that the conditions of misinformation and misinformation of the fire disaster are easy to occur, and therefore, the fire disaster early warning method for monitoring the urban in real time based on coordination of monitoring scenes is provided.
Disclosure of Invention
The invention aims to provide a fire early warning method for coordinating real-time city monitoring based on a monitoring scene so as to solve the problems in the background technology.
In order to achieve the above purpose, the fire early warning method for coordinating real-time city monitoring based on monitoring scenes is provided, and comprises the following steps:
s1, defining an area to be monitored, collecting image information of the area, and simultaneously monitoring road condition data of the area in real time;
s2, preprocessing based on the image information acquired in the step S1, and detecting abnormality of the preprocessed image information;
s3, detecting abnormal data based on the S2, analyzing the abnormal data, marking the abnormal data according to the analysis result, and uploading the marked abnormal data to an early warning center;
s4, analyzing the abnormal data marking information in combination with the road condition data acquired in the S1 according to the S3, and making a fire extinguishing scheme according to an analysis result and uploading the fire extinguishing scheme to a fire control center;
and S5, evaluating according to the implementation result of the fire extinguishing work and the fire extinguishing scheme appointed in the S3, and uploading the fire extinguishing work to an early warning center to update data according to the evaluation result.
As a further improvement of the technical scheme, the step of S1 monitoring the road condition data of the area in real time is as follows:
s1.1, defining an area to be monitored according to the influence of fire on a market;
s1.2, collecting road information around the delimited area of the S1.1, collecting image information in the area at the same time, and evaluating the image information.
As a further improvement of the present technical solution, the step of evaluating the image information by S1.2 is as follows:
s1.2.1, evaluating path distribution data of the monitoring area;
s1.2.2, evaluating the people flow data of the monitoring area;
s1.2.3, evaluating inflammable cargo data of the monitored area;
s1.2.4, collecting the evaluation result of the monitoring area, and integrating the evaluation result to obtain the fire rescue difficulty of the specific area.
As a further improvement of the technical scheme, the S2 detects the abnormality of the preprocessed image information;
s2.1, carrying out image quality enhancement according to the image information acquired in the S1.2 through an image processing technology, and evaluating the abnormal state of the image information;
s2.2, judging a moving target of the image information which is extracted and processed by using the background difference technology according to the evaluation result of the S2.1, and obtaining a fire target and other targets.
As a further improvement of the technical scheme, the step of S2.2 for acquiring the fire target and other targets is as follows:
extracting background contrast statistical information from the preprocessed image information to obtain a background image;
the background, the object target area and the noise element are separated by utilizing the extracted background image and the real-time image to carry out differential operation;
the background and the fire moving target area are separated by dividing the image into two parts by using a threshold segmentation algorithm.
As a further improvement of the technical scheme, the step of marking and uploading the abnormal data to the early warning center in the step S3 is as follows:
s3.1, analyzing the fire disaster target acquired by the S2.2 by combining a plurality of image information in the area acquired by the S1.2;
and S3.2, judging to send fire information to the early warning center according to the analysis result of the step S3.1, and simultaneously, identifying and analyzing a fire target by utilizing a fire detection algorithm to obtain a fire extinguishing distribution scheme.
As a further improvement of the present technical solution, the step of S3.2 obtaining the location of the fire occurrence is as follows:
extracting features of a fire target, including colors, shapes, textures and motion features;
the degree of the fire can be evaluated and judged through the feature extraction;
and analyzing the fire targets obtained by target detection and segmentation, the data related to the monitored physical parameters and the meteorological parameters, and analyzing the direction, the speed, the range size and the fire source height information of the fire diffusion.
As a further improvement of the technical scheme, the step of S4 uploading to the completion of the fire extinguishing work is as follows:
s4.1, analyzing the surrounding road information acquired in the S1.2;
and S4.2, carrying out combined analysis on the road analysis result of the S4.1 and the fire extinguishing distribution scheme acquired in the S3.2 to acquire a road scheme reaching the fire place.
As a further improvement of the technical scheme, the step of uploading the fire extinguishing work to the early warning center to update the data according to the evaluation result is as follows:
s5.1, sending a scheme satisfaction questionnaire to a fire user, collecting questionnaire information and evaluating;
and S5.2, analyzing the road scheme of the S4.1 and the fire extinguishing distribution scheme of the S3.2 by combining questionnaire information according to the evaluation result of the S5.1, and uploading analysis data to a cloud for subsequent use.
Compared with the prior art, the invention has the beneficial effects that:
according to the fire early warning method based on the coordination of the monitoring scene and the real-time monitoring of the city, the automatic monitoring of the city is realized through image acquisition, the fire target is identified in real time, the detection and early warning efficiency of the fire is greatly improved, the image is processed and analyzed by utilizing an image processing technology and a fire detection algorithm, the fire target can be accurately identified, the interference of other moving targets is eliminated, the fire center can judge the fire and allocate the personnel according to the image information through uploading the image information, the fire extinguishing work is more efficient and safe, the adaptability and the expandability are stronger, meanwhile, the data is formulated by the feedback of the firefighters, and the use effect of the formulated scheme is improved.
Drawings
FIG. 1 is an overall flow diagram of the present invention;
FIG. 2 is a block flow chart of the present invention for monitoring road condition data of the area in real time;
FIG. 3 is a block flow diagram of anomaly detection of pre-processed image information in accordance with the present invention;
FIG. 4 is a block flow chart of marking and uploading abnormal data to an early warning center according to the present invention;
FIG. 5 is a block flow diagram of the present invention uploaded to a fire center;
FIG. 6 is a block diagram of a process for updating data by the pre-alarm center of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1-6, the present embodiment is directed to providing a fire early warning method for coordinating real-time city monitoring based on a monitoring scene, comprising the following steps:
s1, defining an area to be monitored, collecting image information of the area, and simultaneously monitoring road condition data of the area in real time;
the step of S1 monitoring the road condition data of the area in real time is as follows:
s1.1, defining an area to be monitored according to the influence of fire on a market; installing a high-resolution monitoring camera at a key position of a commercial complex and a people stream dense area, and connecting the high-resolution monitoring camera with the system through network connection to obtain static image information;
s1.2, collecting road information around the delimited area of the S1.1, collecting image information in the area at the same time, and evaluating the image information. The real-time traffic condition of the road is obtained by connecting with a traffic department through a network;
the step of evaluating the image information by the S1.2 is as follows:
s1.2.1, evaluating path distribution data of the monitoring area; the structural design and layout mode, the channel arrangement and the fire-fighting facility configuration in the shopping mall are related to the influence range caused by fire and the difficulty of fire evacuation;
s1.2.2, evaluating the people flow data of the monitoring area; the flow rate, the blocking state and the goods overstock condition of people in the market can directly influence the fire spreading speed, so that the rescue efficiency is influenced, and the rescue difficulty is greatly increased if the people in the market gather, and the evacuation is not in order;
s1.2.3, evaluating inflammable cargo data of the monitored area; articles and facilities in the market are not the same, and uncertainty of the position of a fire source can also bring difficulty and danger to rescue; the area of the market is usually larger, and if the number of substances for igniting the combustible materials is large and the fire is large, the rescue difficulty is increased;
s1.2.4, collecting the evaluation result of the monitoring area, and integrating the evaluation result to obtain the fire rescue difficulty of the specific area.
S2, preprocessing based on the image information acquired in the step S1, and detecting abnormality of the preprocessed image information;
s2, carrying out anomaly detection on the preprocessed image information;
s2.1, carrying out image quality enhancement according to the image information acquired in the S1.2 through an image processing technology, and evaluating the abnormal state of the image information; noise removing and enhancing treatment is carried out on the image so as to improve the image quality;
the steps of denoising, removing and enhancing the image are as follows:
denoising an image: noise removal of the image is required before the image enhancement process is performed. The common denoising method comprises the following steps: the average filtering can reduce the influence of high-frequency noise and improve the image quality. The formula of the mean value filtering is to average a rectangle with a fixed size around the pixel point and then replace the gray value of the pixel point with the average value. Assuming that the size of the rectangle is n×m and the value of the pixel point at the (i, j) position is f (i, j), the formula of the mean filtering is:
f'(i,j)＝1/(N*M)*sum(f(x,y))
where (x, y) is the coordinates of the pixel points around (i, j).
Image enhancement: the histogram equalization technique can be used to improve the contrast, brightness and color aspects of the image so as to more clearly represent the content of the image. The formula of the histogram equalization technique is:
let f (x, y) be the original image, the range of values is [0, L-1], the total number of pixels is MxN, and the histogram is h (r), where r is [0, L-1]. Assuming that the pixel value after equalization is g (x, y), the processing method is as follows for each pixel point (x, y):
calculating the gray level r=f (x, y) where the pixel point is located; calculating a cumulative distribution function CDF:
C(r)＝∑h(i),i∈[0,r]
calculating new pixel values:
g(x,y)＝L-1×CDF(r)/(M×N)
where L is the maximum value of the pixel value. The processed pixel values are returned to the corresponding positions of the original image, and then the image with balanced histogram can be obtained;
s2.2, judging a moving target of the image information which is extracted and processed by using the background difference technology according to the evaluation result of the S2.1, and obtaining a fire target and other targets.
The step of S2.2 obtaining the fire target and other targets is as follows:
extracting background contrast statistical information from the preprocessed image information to obtain a background image;
by performing a differential operation using the extracted background image and the real-time image,
the formula of the differential operation is:
delta(n)＝x(n)-x(n-1)
where delta (n) represents the differential result at the current time n, x (n) represents the signal value at time n, and x (n-1) represents the signal value at time n-1. The result of the differential operation represents the difference between the signal value at the current time and the signal value at the previous time. If the differential result is positive, the signal value is gradually increased; if the differential result is negative, it means that the signal value is gradually decreasing. The differential operation can be utilized to carry out edge detection, motion detection and sound processing operation on the signals so as to separate the background, the object target area and the noise element; the image after difference contains brightness variation information, and the place with larger brightness difference is the moving target;
the background and the fire moving target area are separated by dividing the image into two parts by using a threshold segmentation algorithm.
The threshold segmentation algorithm sets the original image as f (x, y), and the segmentation threshold as T. Each pixel value in f (x, y) is converted to 0 or 1 in the following manner:
iff(x,y)>T:g(x,y)＝1else:g(x,y)＝0
where g (x, y) represents the binarized image pixel value, which takes on a value of 0 or 1. The selection of the threshold value can generally adopt a method based on an image histogram;
the threshold segmentation may divide the image into two parts, one part being the target region and the other part being the background region;
s3, detecting abnormal data based on the S2, analyzing the abnormal data, marking the abnormal data according to the analysis result, and uploading the marked abnormal data to an early warning center;
and S3, marking the abnormal data and uploading the abnormal data to an early warning center, wherein the step is as follows:
s3.1, analyzing the fire disaster target acquired by the S2.2 by combining a plurality of image information in the area acquired by the S1.2;
and shooting images of the fire source targets from a plurality of angles and a plurality of positions, and preprocessing the images to obtain high-quality images and obtain descriptive information of the fire source targets.
Feature matching: comparing and analyzing the obtained characteristics of the target fire source with known fire source characteristic models, judging whether the fire source is a real fire target or not by calculating the similarity of the characteristics, and judging that the fire source is a fire target if the matching degree is high;
and S3.2, judging to send fire information to the early warning center according to the analysis result of the step S3.1, and simultaneously, identifying and analyzing a fire target by utilizing a fire detection algorithm to obtain a fire extinguishing distribution scheme.
The step of S3.2 obtaining the fire disaster occurrence position is as follows:
extracting features of a fire target, including colors, shapes, textures and motion features;
the degree of the fire can be evaluated and judged through the feature extraction;
and analyzing the fire targets obtained by target detection and segmentation, the data related to the monitored physical parameters and the meteorological parameters, and analyzing the direction, the speed, the range size and the fire source height information of the fire diffusion.
S4, analyzing the abnormal data marking information in combination with the road condition data acquired in the S1 according to the S3, and making a fire extinguishing scheme according to an analysis result and uploading the fire extinguishing scheme to a fire control center;
the step of uploading the S4 to the completion of the fire extinguishing work is as follows:
s4.1, analyzing the surrounding road information acquired in the S1.2;
and S4.2, carrying out combined analysis on the road analysis result of the S4.1 and the fire extinguishing distribution scheme acquired in the S3.2 to acquire a road scheme reaching the fire place.
And obtaining the shortest route through a path planning algorithm by using the map and the road data, wherein the shortest route comprises the steps of selecting the most suitable road, calculating travel time and distance information in consideration of traffic jam conditions, and obtaining a fire truck travel scheme.
The path planning algorithm formula is:
let the start point be S, the end point be G, the Open node set be Open, the Close node set be Close. For any node n, the following values need to be calculated:
g (n) represents the cost from the starting node S to node n; h (n) represents the estimated cost from node n to target node G;
f (n) represents the composite cost of node n, f (n) =g (n) +h (n). The basic idea of the algorithm a is:
initializing an Open and Close set, and adding a starting point S into the Open set;
calculating f (n) values for all nodes n in the Open set; finding out a node m with the minimum f (n) value in the Open set, and ending the search if the node is a target node G;
otherwise, moving the node m from the Open set to the Close set, traversing all adjacent nodes n of the node m, and calculating values of g (n) and f (n); if node n is already in the Close set, ignore;
if the node n is not in the Open set, adding the node n into the Open set, and recording the father node of the node n as the node m;
if node n is already in the Open set, the current g value of n is compared with the g value from m to n, and the g value of n is updated with the smaller one. Updating the father node of n as node m at the same time, and recalculating the f (n) value; repeating the steps 2-7 until the Open set is empty or the target node G is found;
updating road data: and updating road information in real time, and adjusting a running scheme in consideration of traffic conditions, construction and vehicle congestion information.
Guiding: real-time monitoring is carried out on the planned running scheme and road traffic conditions, and the fire truck is assisted to drive to a fire scene, including navigation and traffic guidance, so that the fire truck can be ensured to quickly arrive at the fire scene;
and S5, evaluating according to the implementation result of the fire extinguishing work and the fire extinguishing scheme appointed in the S3, and uploading the fire extinguishing work to an early warning center to update data according to the evaluation result.
And S5, uploading the fire extinguishing work to an early warning center according to the evaluation result to update the data, wherein the step is as follows:
s5.1, sending a scheme satisfaction questionnaire to a fire user, collecting questionnaire information and evaluating; collecting the evaluation and suggestion of the fire fighter on the fire extinguishing action by a network information transmission mode;
and S5.2, analyzing the road scheme of the S4.1 and the fire extinguishing distribution scheme of the S3.2 by combining questionnaire information according to the evaluation result of the S5.1, and uploading analysis data to a cloud for subsequent use.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and their equivalents.
Claims (9)
1. The fire disaster early warning method for coordinating real-time city monitoring based on the monitoring scene is characterized in that: the method comprises the following steps:
s1, defining an area to be monitored, collecting image information of the area, and simultaneously monitoring road condition data of the area in real time;
s2, preprocessing based on the image information acquired in the step S1, and detecting abnormality of the preprocessed image information;
s3, detecting abnormal data based on the S2, analyzing the abnormal data, marking the abnormal data according to the analysis result, and uploading the marked abnormal data to an early warning center;
s4, analyzing the abnormal data marking information in combination with the road condition data acquired in the S1 according to the S3, and making a fire extinguishing scheme according to an analysis result and uploading the fire extinguishing scheme to a fire control center;
and S5, evaluating according to the implementation result of the fire extinguishing work and the fire extinguishing scheme appointed in the S3, and uploading the fire extinguishing work to an early warning center to update data according to the evaluation result.
2. The fire early warning method based on coordination of monitoring scenes and real-time monitoring of cities according to claim 1, wherein the fire early warning method is characterized in that: the step of S1 monitoring the road condition data of the area in real time is as follows:
s1.1, defining an area to be monitored according to the influence of fire on a market;
s1.2, collecting road information around the delimited area of the S1.1, collecting image information in the area at the same time, and evaluating the image information.
3. The fire early warning method based on coordination of monitoring scenes for real-time city monitoring according to claim 2, wherein the method comprises the following steps: the step of evaluating the image information by the S1.2 is as follows:
s1.2.1, evaluating path distribution data of the monitoring area;
s1.2.2, evaluating the people flow data of the monitoring area;
s1.2.3, evaluating inflammable cargo data of the monitored area;
s1.2.4, collecting the evaluation result of the monitoring area, and integrating the evaluation result to obtain the fire rescue difficulty of the specific area.
4. The fire early warning method based on coordination of monitoring scenes for real-time city monitoring according to claim 2, wherein the method comprises the following steps: s2, carrying out anomaly detection on the preprocessed image information;
s2.1, carrying out image quality enhancement according to the image information acquired in the S1.2 through an image processing technology, and evaluating the abnormal state of the image information;
s2.2, judging a moving target of the image information which is extracted and processed by using the background difference technology according to the evaluation result of the S2.1, and obtaining a fire target and other targets.
5. The fire early warning method based on coordination of monitoring scenes for real-time city monitoring according to claim 4, wherein the method comprises the following steps: the step of S2.2 obtaining the fire target and other targets is as follows:
extracting background contrast statistical information from the preprocessed image information to obtain a background image;
the background, the object target area and the noise element are separated by utilizing the extracted background image and the real-time image to carry out differential operation;
the background and the fire moving target area are separated by dividing the image into two parts by using a threshold segmentation algorithm.
6. The fire early warning method based on coordination of monitoring scenes for real-time city monitoring according to claim 4, wherein the method comprises the following steps: and S3, marking the abnormal data and uploading the abnormal data to an early warning center, wherein the step is as follows:
s3.1, analyzing the fire disaster target acquired by the S2.2 by combining a plurality of image information in the area acquired by the S1.2;
and S3.2, judging to send fire information to the early warning center according to the analysis result of the step S3.1, and simultaneously, identifying and analyzing a fire target by utilizing a fire detection algorithm to obtain a fire extinguishing distribution scheme.
7. The fire early warning method based on coordination of monitoring scenes for real-time city monitoring according to claim 6, wherein the method comprises the following steps: the step of S3.2 obtaining the fire disaster occurrence position is as follows:
extracting features of a fire target, including colors, shapes, textures and motion features;
the degree of the fire can be evaluated and judged through the feature extraction;
and analyzing the fire targets obtained by target detection and segmentation, the data related to the monitored physical parameters and the meteorological parameters, and analyzing the direction, the speed, the range size and the fire source height information of the fire diffusion.
8. The fire early warning method based on coordination of monitoring scenes for real-time city monitoring according to claim 6, wherein the method comprises the following steps: the step of uploading the S4 to the completion of the fire extinguishing work is as follows:
s4.1, analyzing the surrounding road information acquired in the S1.2;
and S4.2, carrying out combined analysis on the road analysis result of the S4.1 and the fire extinguishing distribution scheme acquired in the S3.2 to acquire a road scheme reaching the fire place.
9. The fire early warning method based on coordination of monitoring scenes for real-time city monitoring according to claim 7, wherein the method comprises the following steps: and S5, uploading the fire extinguishing work to an early warning center according to the evaluation result to update the data, wherein the step is as follows:
s5.1, sending a scheme satisfaction questionnaire to a fire user, collecting questionnaire information and evaluating;
and S5.2, analyzing the road scheme of the S4.1 and the fire extinguishing distribution scheme of the S3.2 by combining questionnaire information according to the evaluation result of the S5.1, and uploading analysis data to a cloud for subsequent use.
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