CN119296239A - Anti-theft monitoring and early warning method based on video remote monitoring - Google Patents
Anti-theft monitoring and early warning method based on video remote monitoring Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
- G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
- G08B13/19613—Recognition of a predetermined image pattern or behaviour pattern indicating theft or intrusion
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
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Abstract
本发明属于防盗监控预警技术领域，具体是基于视频远程监控的防盗监测预警方法，包括采集相应目标区域的实时监控视频、判断相应目标区域是否存在盗窃风险、判断存在盗窃风险触发警报以及将相应目标区域的盗窃隐患程度进行分析；本发明通过视频监控并自动识别判断防盗风险，有利于保证所需监测区域的防盗安全性能，且通过将相应目标区域的盗窃隐患程度进行分析以确定巡检区域和监控区域，方便后续针对不同子区域安排相适配的管理模式，以及通过巡检追踪模块将针对相应巡检区域的巡检表现进行分析，以及时加强相应巡检区域的巡检监管和巡检人员培训，进一步保证所需监测区域的防盗管控性能，智能化程度高。
The present invention belongs to the technical field of anti-theft monitoring and early warning, and specifically is an anti-theft monitoring and early warning method based on video remote monitoring, including collecting real-time monitoring video of corresponding target area, judging whether there is a theft risk in the corresponding target area, judging whether there is a theft risk to trigger an alarm, and analyzing the degree of theft hazard in the corresponding target area; the present invention uses video monitoring and automatic identification and judgment of anti-theft risks, which is conducive to ensuring the anti-theft safety performance of the required monitoring area, and by analyzing the degree of theft hazard in the corresponding target area to determine the inspection area and the monitoring area, it is convenient to arrange suitable management modes for different sub-areas later, and analyze the inspection performance of the corresponding inspection area through the inspection tracking module, so as to timely strengthen the inspection supervision and inspection personnel training of the corresponding inspection area, further ensure the anti-theft management and control performance of the required monitoring area, and have a high degree of intelligence.
Description
Technical Field
The invention relates to the technical field of anti-theft monitoring and early warning, in particular to an anti-theft monitoring and early warning method based on video remote monitoring.
Background
With the development of technology and the progress of society, the demands of people for safety protection are increasing, and particularly, how to prevent or reduce the risk of article or property theft, the video remote monitoring technology is widely applied in the field of safety protection in recent years, and the anti-theft performance of corresponding areas is enhanced;
however, at present, comprehensive evaluation and reasonable planning of subsequent anti-theft management and control schemes are difficult to carry out on theft hidden dangers of different subareas in corresponding areas, inspection performance of the subareas to be inspected cannot be reasonably analyzed and accurately fed back, running conditions of all monitoring devices cannot be comprehensively detected and early warned in time, anti-theft safety performance of the corresponding areas is not guaranteed, workload of management staff is reduced, and the intelligent degree is low;
In view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide an anti-theft monitoring early warning method based on video remote monitoring, which solves the problems that the prior art is difficult to comprehensively evaluate and reasonably plan subsequent anti-theft management and control schemes aiming at theft hidden dangers of different subareas in corresponding areas, the inspection performance of the subareas to be inspected cannot be reasonably analyzed and accurately fed back, the running condition of each monitoring device cannot be comprehensively detected and early warned in time, and the anti-theft safety performance of the corresponding areas cannot be guaranteed.
In order to achieve the above purpose, the present invention provides the following technical solutions:
A theft-proof monitoring and early warning method based on video remote monitoring comprises the following steps:
the method comprises the steps that firstly, a monitoring management platform obtains an area to be monitored, monitors to be monitored are divided into a plurality of sub-areas, and the corresponding sub-areas are marked as target areas;
Monitoring all target areas by the video monitoring module through the camera, acquiring real-time monitoring videos of the corresponding target areas, and sending the real-time monitoring videos to the video processing analysis module through the monitoring management platform;
Step three, a video processing analysis module receives a real-time monitoring video, carries out real-time analysis on a video image through an intelligent algorithm, identifies a moving target, and judges whether a corresponding target area has a theft risk according to behavior characteristics of the moving target;
step four, if the theft risk is judged to exist, the anti-theft early warning module automatically triggers an alarm to give out an alarm to the site, alarm information is transmitted to a remote monitoring center through a monitoring management platform, and the remote monitoring center monitors and commands the site situation in real time;
Fifthly, the theft hidden danger assessment module analyzes the theft hidden danger degree of the corresponding target area in the detection period, generates a theft high hidden danger signal or a theft low hidden danger signal through analysis, and sends the theft high hidden danger signal or the theft low hidden danger signal to a remote monitoring center through a monitoring management platform.
Further, in the third step, a specific analysis and judgment process for judging whether the corresponding target area has a theft risk according to the behavior characteristics of the moving target is as follows:
Image preprocessing, namely carrying out noise reduction processing on a received video image, carrying out brightness and contrast enhancement processing on the video image according to ambient illumination conditions, and compensating image jitter caused by camera shake or ambient interference;
The method comprises the steps of detecting a moving target, establishing and updating a background model to distinguish a static background from a dynamic target in an image, and extracting the moving target in a foreground by comparing a current image with the background model;
The target behavior analysis comprises the steps of tracking the identified moving target in continuous frames to generate a motion track of the moving target, extracting key behavior features from the motion track of the corresponding moving target, comparing the extracted behavior features with a preset normal behavior mode, and judging whether the target has abnormal behaviors or not;
And (3) carrying out theft risk assessment, namely carrying out context analysis on the behaviors of the targets by combining the behavior characteristics and scene information of the moving targets, grading the theft risk of the corresponding moving targets according to the context analysis result, and presetting one or more risk thresholds, wherein when the theft risk grade of the targets exceeds a certain threshold, the potential theft risk is considered.
Further, in the fifth step, the specific analysis process of the theft hidden danger assessment module is as follows:
Setting a detection period with the number of days of L1, dividing the detection period into a plurality of detection periods when the number of days reaches L1, marking the corresponding detection period as an abnormal theft period or a safety period through theft period detection analysis, obtaining the number of abnormal theft periods in a corresponding target area in the detection period, marking the number of abnormal theft periods as abnormal theft detection values, marking the number of abnormal theft periods between two adjacent groups of safety periods as abnormal theft continuous values, and carrying out average calculation on all abnormal theft continuous values to obtain abnormal theft continuous condition values;
The total number of times of generating alarm information in the corresponding target area in the detection period is obtained and marked as a theft alarm value, a theft hidden danger assessment value is obtained through numerical calculation of the abnormal theft detection value, the abnormal theft holding condition value and the theft alarm value, the theft hidden danger assessment value is compared with a preset theft hidden danger assessment threshold value, if the theft hidden danger assessment value exceeds the preset theft hidden danger assessment threshold value, a theft high hidden danger signal in the corresponding target area is generated, and if the theft hidden danger assessment value does not exceed the preset theft hidden danger assessment threshold value, a theft low hidden danger signal in the corresponding target area is generated.
Further, the specific analysis process of the theft time-division detection analysis is as follows:
The method comprises the steps of collecting the times of generating alarm information in corresponding detection time periods by corresponding target areas, marking the times as time period alarm values, comparing the time period alarm values with preset time period alarm thresholds, marking the corresponding detection time periods as abnormal theft time periods if the time period alarm values exceed the preset time period alarm thresholds, and marking the corresponding detection time periods as safe time periods if the time period alarm values do not exceed the preset time period alarm thresholds.
And the monitoring management platform is in communication connection with the inspection tracking module, the inspection tracking module analyzes the inspection performance of the corresponding inspection area in the next detection period, generates an inspection qualified signal or an inspection abnormal signal through analysis, and transmits the inspection qualified signal or the inspection abnormal signal of the corresponding inspection area to the remote monitoring center through the monitoring management platform.
Further, the specific operation process of the patrol tracking module comprises:
Acquiring the total number of inspection aiming at a corresponding inspection area in a detection period, marking the total number of inspection aiming at the corresponding inspection area as an inspection total frequency value, judging whether the corresponding inspection process is an inferior table inspection process or not through inspection monitoring analysis, acquiring the number of inferior table inspection processes aiming at the corresponding inspection area in the detection period, and carrying out ratio calculation on the number of inferior table inspection processes aiming at the corresponding inspection area and the inspection total frequency value to obtain an inspection inferior condition value;
And calculating the time difference between the starting time of the corresponding inspection process and the ending time of the adjacent last inspection process to obtain an inspection time difference, comparing the inspection time difference with a corresponding preset inspection time difference threshold value in a numerical mode, marking the corresponding inspection time difference as an inspection abnormal value if the inspection time difference exceeds the preset inspection time difference threshold value, obtaining the quantity of the inspection abnormal value in a detection period, and calculating the ratio of the quantity of the inspection abnormal value to the quantity of the inspection time difference to obtain the inspection abnormal value;
The inspection tracking value is obtained by carrying out numerical calculation on the inspection total frequency value, the inspection interval abnormal value and the inspection inferior condition value, the inspection tracking value is compared with a corresponding preset inspection tracking threshold value in numerical value, an inspection abnormal signal of a corresponding inspection area is generated if the inspection tracking value exceeds the preset inspection tracking threshold value, and an inspection qualified signal of the corresponding inspection area is generated if the inspection tracking value does not exceed the preset inspection tracking threshold value.
Further, the specific analysis process of the inspection monitoring analysis is as follows:
After the corresponding inspection process is finished, acquiring an actual inspection track of the corresponding inspection process, comparing the actual inspection track with a preset standard inspection track, marking the length of an inspection-free track in the standard inspection track in the corresponding inspection process as an inspection-free track value, comparing the inspection-free track value with a corresponding preset inspection-free track threshold value, and marking the corresponding inspection process as an inferior table inspection process if the inspection-free track value exceeds the preset inspection-free track threshold value;
If the non-patrol track value does not exceed the preset non-patrol track threshold value, acquiring a real-time patrol speed in the corresponding patrol process, carrying out numerical comparison on the real-time patrol speed and a corresponding preset patrol speed range, and if the real-time patrol speed is not in the corresponding preset patrol speed range, judging that the corresponding moment is in a different patrol speed state;
And marking the ratio of the non-patrol track value to the corresponding preset non-patrol track threshold value as a non-patrol track occupation value, carrying out numerical calculation on the non-patrol track occupation value, the speed-difference occupation value and the patrol time bias value to obtain a patrol evaluation condition value, carrying out numerical comparison on the patrol evaluation condition value and the preset patrol evaluation condition threshold value, and marking the corresponding patrol process as an inferior table patrol process if the patrol evaluation condition value exceeds the preset patrol evaluation condition threshold value.
Further, the monitoring management platform is in communication connection with the monitoring equipment supervision module, the monitoring equipment supervision module acquires all monitoring equipment in an area to be monitored, monitors corresponding monitoring equipment, acquires real-time temperatures at a plurality of positions in the corresponding monitoring equipment, calculates the average value of the real-time temperatures at all the positions to obtain a monitoring temperature detection value, acquires vibration data and noise data generated by the corresponding monitoring equipment, and marks the vibration data and the noise data as a monitoring vibration detection value and a monitoring noise detection value respectively;
The method comprises the steps of obtaining delay data and definition data of video images acquired by corresponding monitoring equipment, marking the delay data and the definition data as a monitoring delay value and a monitoring definition value respectively, carrying out numerical calculation on a monitoring temperature detection value, a monitoring vibration detection value, a monitoring noise detection value, a monitoring delay value and a monitoring definition value to obtain a monitoring abnormal detection value, carrying out numerical comparison on the monitoring abnormal detection value and a preset monitoring abnormal detection threshold value, generating a monitoring abnormal signal of the corresponding monitoring equipment if the monitoring abnormal detection value exceeds the preset monitoring abnormal detection threshold value, and generating a monitoring normal signal of the corresponding monitoring equipment if the monitoring abnormal detection value does not exceed the preset monitoring abnormal detection threshold value, and sending the monitoring abnormal signal or the monitoring normal signal of the corresponding monitoring equipment to a remote monitoring center through a monitoring management platform.
Compared with the prior art, the invention has the beneficial effects that:
1. In the invention, the real-time monitoring video of the corresponding target area is acquired through the video monitoring module, the video processing analysis module judges whether the corresponding target area has a theft risk, if so, an alarm is automatically triggered, thereby being beneficial to ensuring the theft safety performance of the required monitoring area;
2. According to the invention, the inspection performance of the corresponding inspection area is analyzed through the inspection tracking module, the inspection qualified signal or the inspection abnormal signal is generated through analysis, inspection supervision and inspection personnel training of the corresponding inspection area are enhanced when the inspection abnormal signal is generated, the subsequent inspection effect is ensured, the anti-theft performance of the area is improved, the operation conditions of all monitoring equipment are analyzed through the monitoring equipment supervision module, the corresponding monitoring equipment is regulated, controlled, inspected and maintained in time, the operation safety of all monitoring equipment is ensured, and the anti-theft management and control performance of the required monitoring area is further ensured.
Drawings
For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
FIG. 1 is a flow chart of a method according to a first embodiment of the invention;
FIG. 2 is a system block diagram of a first embodiment of the present invention;
FIG. 3 is a system block diagram of a second embodiment of the present invention;
fig. 4 is a system block diagram of a third embodiment 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.
1-2, The anti-theft monitoring and early warning method based on video remote monitoring provided by the invention comprises the following steps:
Step one, a monitoring management platform acquires a region to be monitored, divides the region to be monitored into a plurality of sub-regions, and marks the corresponding sub-regions as target regions.
And secondly, the video monitoring module monitors all the target areas through the cameras, acquires real-time monitoring videos of the corresponding target areas, and sends the real-time monitoring videos to the video processing analysis module through the monitoring management platform.
Step three, the video processing analysis module receives the real-time monitoring video, carries out real-time analysis on the video image through an intelligent algorithm, identifies a moving target (a moving target such as a human body, a vehicle and the like), judges whether a corresponding target area has a theft risk according to the behavior characteristics of the moving target, and the specific analysis and judgment process is as follows:
Image preprocessing, namely, noise is possibly generated in the video transmission process, so that noise reduction processing is firstly carried out on the received video image to improve the accuracy of subsequent analysis, enhancement processing such as brightness, contrast and the like is carried out on the video image according to the ambient lighting condition, and image jitter caused by camera shake or ambient interference is compensated to keep the stability of the image;
The method comprises the steps of detecting a moving target, establishing and updating a background model to distinguish a static background from a dynamic target in an image, and extracting the moving target in the foreground by comparing a current image with the background model;
The target behavior analysis comprises the steps of tracking the identified moving target in continuous frames to generate a motion track of the moving target, extracting key behavior features such as speed, acceleration, direction change and the like from the motion track of the corresponding moving target, comparing the extracted behavior features with a preset normal behavior mode, and judging whether the target has abnormal behaviors such as long-time loitering, abrupt acceleration or direction change and the like;
The method comprises the steps of carrying out context analysis on the behavior of a moving target and other information (such as time, weather, illumination conditions and the like) in a scene, grading the theft risk of the corresponding moving target according to the context analysis result, carrying out weighted calculation on the grading based on a plurality of factors, such as the type (human body or vehicle) of the target, the degree of abnormality of the behavior, the distance from a sensitive area and the like, setting one or more risk thresholds in advance, and considering that the potential theft risk exists when the theft risk grading of the target exceeds a certain threshold.
And step four, if the theft risk is judged, the anti-theft early warning module automatically triggers an alarm to give out an alarm to the site, alarm information is transmitted to a remote monitoring center through a monitoring management platform, and the remote monitoring center monitors and commands the site condition in real time.
Step five, the theft hidden danger assessment module analyzes the theft hidden danger degree of the corresponding target area in the detection period, generates a theft high hidden danger signal or a theft low hidden danger signal through analysis, and sends the theft high hidden danger signal or the theft low hidden danger signal to a remote monitoring center through a monitoring management platform, wherein the specific analysis process is as follows:
The method comprises the steps of setting a detection period with the number of days of L1, preferably, L1 is thirty-five days, dividing the detection period into a plurality of detection periods when the number of days reaches L1, marking the corresponding detection period as an abnormal theft period or a safety period through detection analysis of the theft sub-period, specifically, collecting the number of times of generating alarm information in the corresponding detection period by a corresponding target area and marking the alarm information as a period alarm value, carrying out numerical comparison on the period alarm value and a preset period alarm threshold, and marking the corresponding detection period as the abnormal theft period if the period alarm value exceeds the preset period alarm threshold and indicates that the theft risk of the target area of the corresponding detection period is lower;
The method comprises the steps of obtaining the number of abnormal theft periods in corresponding target areas in a detection period, marking the number of abnormal theft periods as abnormal theft detection values, marking the number of abnormal theft periods between two adjacent groups of safety periods as abnormal theft continuous values, carrying out average calculation on all abnormal theft continuous values to obtain abnormal theft holding condition values, obtaining the total number of times of alarm information generation of corresponding target areas in the detection period, and marking the total number of times as theft alarm values;
By the formula Carrying out numerical calculation on the abnormal theft detection value QS, the abnormal theft holding condition value QF and the theft alarm value QR to obtain a theft hidden danger evaluation value QP, wherein wq1, wq2 and wq3 are preset proportional coefficients, wq2> wq1> wq3>0, and the larger the numerical value of the theft hidden danger evaluation value QP is, the larger the theft risk of the corresponding target area in the detection period is indicated, and the higher the theft management difficulty is comprehensively aimed at the corresponding target area;
The theft hidden danger evaluation value QP is compared with a preset theft hidden danger evaluation threshold value, if the theft hidden danger evaluation value QP exceeds the preset theft hidden danger evaluation threshold value, the theft hidden danger signal of the corresponding target area is generated if the theft hidden danger evaluation value QP is higher than the preset theft hidden danger evaluation threshold value, and if the theft hidden danger evaluation value QP does not exceed the preset theft hidden danger evaluation threshold value, the theft hidden danger signal of the corresponding target area is generated if the theft hidden danger evaluation value QP is lower than the preset theft hidden danger evaluation threshold value.
Furthermore, when the monitoring management platform receives the theft high hidden danger signal, the corresponding target area is marked as a patrol area, when the corresponding target area is marked as a monitoring area when the theft low hidden danger signal is received, the marking information of the corresponding target area is sent to the remote monitoring center, the patrol area is required to be monitored in a video mode, corresponding patrol personnel are required to be arranged for the patrol area to patrol the patrol area, the corresponding area is required to be monitored in a video mode through monitoring equipment, the follow-up management mode of arranging the adaptation to different subareas is facilitated, the area safety of the required monitoring area is ensured, and the anti-theft performance of the required monitoring area is improved.
In the second embodiment, as shown in fig. 3, the difference between the present embodiment and embodiment 1 is that the monitoring management platform is in communication connection with the inspection tracking module, the monitoring management platform sends the inspection area to the inspection tracking module, the inspection tracking module analyzes the inspection performance of the corresponding inspection area in the next detection period, generates an inspection qualified signal or an inspection abnormal signal through analysis, sends the inspection qualified signal or the inspection abnormal signal of the corresponding inspection area to the remote monitoring center through the monitoring management platform, strengthens inspection supervision of the corresponding inspection area when receiving the inspection abnormal signal, and carries out training education on corresponding inspection staff, ensures the subsequent inspection effect and improves the anti-theft performance of the area, and the specific operation process of the inspection tracking module is as follows:
acquiring the actual inspection track of the corresponding inspection process after the corresponding inspection process is finished, comparing the actual inspection track with a preset standard inspection track, marking the length of the track which is not inspected in the standard inspection track in the corresponding inspection process as an unground track value, comparing the unground track value with a corresponding preset unground track threshold value, and marking the corresponding inspection process as an unground track if the unground track value exceeds the preset unground track threshold value, wherein the inspection result of the corresponding inspection process is poor;
If the non-patrol track value does not exceed the preset non-patrol track threshold value, acquiring a real-time patrol speed in the corresponding patrol process, carrying out numerical comparison on the real-time patrol speed and a corresponding preset patrol speed range, and if the real-time patrol speed is not in the corresponding preset patrol speed range, judging that the corresponding moment is in a different patrol speed state;
And marking the ratio of the non-patrol track value to the corresponding preset non-patrol track threshold value as a non-patrol track occupation value, and carrying out numerical calculation on the non-patrol track occupation value HF, the fast abnormal occupation value HS and the patrol time bias value HK through a formula HX=y1+y2+y3 to obtain a patrol evaluation value HX, wherein ey1, ey2 and ey3 are preset proportional coefficients with values larger than zero, and the larger the value of the patrol evaluation value HX is, the worse the patrol effect of the corresponding patrol process is indicated;
Comparing the inspection evaluation condition value HX with a preset inspection evaluation condition threshold value, and if the inspection evaluation condition value HX exceeds the preset inspection evaluation condition threshold value, indicating that the inspection effect of the corresponding inspection process is poor, marking the corresponding inspection process as an inferior table inspection process;
And calculating the time difference between the starting time of the corresponding inspection process and the ending time of the adjacent last inspection process to obtain an inspection time difference, comparing the inspection time difference with a corresponding preset inspection time difference threshold value in a numerical mode, marking the corresponding inspection time difference as an inspection abnormal value if the inspection time difference exceeds the preset inspection time difference threshold value, obtaining the quantity of the inspection abnormal value in a detection period, and calculating the ratio of the quantity of the inspection abnormal value to the quantity of the inspection time difference to obtain the inspection abnormal value;
By the formula Carrying out numerical calculation on the inspection total frequency value TY, the inspection interval difference value TW and the inspection condition value TP to obtain an inspection tracking value TF, wherein fp1, fp2 and fp3 are preset proportion coefficients, and the values of fp1, fp2 and fp3 are positive numbers;
And comparing the patrol tracking value TF with a corresponding preset patrol tracking threshold value, if the patrol tracking value TF exceeds the preset patrol tracking threshold value, indicating that the patrol performance synthesis of the corresponding patrol area is poor, generating a patrol abnormal signal of the corresponding patrol area, and if the patrol tracking value TF does not exceed the preset patrol tracking threshold value, indicating that the patrol performance synthesis of the corresponding patrol area is good, generating a patrol qualified signal of the corresponding patrol area.
The third embodiment is that, as shown in fig. 4, the monitoring management platform is in communication connection with the monitoring device supervision module, and the monitoring device supervision module acquires all monitoring devices existing in the area to be monitored, monitors the corresponding monitoring devices, acquires real-time temperatures at a plurality of positions in the corresponding monitoring devices, calculates the average value of the real-time temperatures at all positions to obtain a monitoring temperature detection value, acquires vibration data (i.e. vibration amplitude) and noise data (i.e. noise decibel value) generated by the corresponding monitoring devices and marks the vibration data and the noise data as a monitoring vibration detection value and a monitoring noise detection value respectively;
The method comprises the steps of carrying out numerical calculation on a monitoring temperature detection value YW, a monitoring vibration detection value YN, a monitoring noise detection value YK, a monitoring delay value YS and a monitoring clear value YF through a formula YP=a1+a2 xYN+a3 xYK+a4 xYS+a5/(YF+0.826) to obtain a monitoring abnormal detection value YP, wherein a1, a2, a3, a4 and a5 are preset proportion coefficients with values larger than zero, and the larger the numerical value of the monitoring abnormal detection value YP is, the worse the current running condition of corresponding monitoring equipment is, the more processing measures such as checking maintenance and the like are needed to be carried out on the corresponding monitoring equipment in time;
And if the monitoring abnormal detection value YP does not exceed the preset monitoring abnormal detection threshold, the monitoring normal signal of the corresponding monitoring equipment is generated, the monitoring abnormal signal or the monitoring normal signal of the corresponding monitoring equipment is sent to a remote monitoring center through a monitoring management platform, and the remote monitoring center sends corresponding early warning when receiving the monitoring abnormal signal, timely regulates, controls, inspects and maintains the corresponding monitoring equipment, ensures the operation safety of all the monitoring equipment, and is beneficial to further ensuring the anti-theft management and control performance of a required monitoring area.
When the anti-theft monitoring system is used, the area to be monitored is divided into a plurality of sub-areas through the monitoring management platform, the corresponding sub-areas are marked as target areas, the video monitoring module collects real-time monitoring videos of the corresponding target areas, the video processing analysis module judges whether the corresponding target areas have theft risks according to the behavior characteristics of the moving targets, if the theft risks are judged to exist, the alarm is automatically triggered, the anti-theft safety performance of the required monitoring areas is guaranteed, the anti-theft hidden danger evaluation module analyzes the anti-theft hidden danger degree of the corresponding target areas in the detection period, and a high hidden danger signal or a low hidden danger signal is generated through analysis, so that the follow-up management mode adapted to different sub-areas is convenient, the area safety of the required monitoring areas is guaranteed, the anti-theft performance of the required monitoring areas is improved, and the intelligent degree is high.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (6)
1. The anti-theft monitoring and early warning method based on video remote monitoring is characterized by comprising the following steps of:
The method comprises the steps that firstly, a monitoring management platform obtains a region to be monitored, the region to be monitored is divided into a plurality of sub-regions, and the corresponding sub-regions are marked as target regions;
Monitoring all target areas by the video monitoring module through the camera, acquiring real-time monitoring videos of the corresponding target areas, and sending the real-time monitoring videos to the video processing analysis module through the monitoring management platform;
Step three, a video processing analysis module receives a real-time monitoring video, carries out real-time analysis on a video image through an intelligent algorithm, identifies a moving target, and judges whether a corresponding target area has a theft risk according to behavior characteristics of the moving target;
step four, if the theft risk is judged to exist, the anti-theft early warning module automatically triggers an alarm to give out an alarm to the site, alarm information is transmitted to a remote monitoring center through a monitoring management platform, and the remote monitoring center monitors and commands the site situation in real time;
Step five, the theft hidden danger assessment module analyzes the theft hidden danger degree of the corresponding target area in the detection period, generates a theft high hidden danger signal or a theft low hidden danger signal through analysis, and sends the theft high hidden danger signal or the theft low hidden danger signal to a remote monitoring center through a monitoring management platform;
The specific analysis process of the theft hidden danger assessment module is as follows:
Setting a detection period with the number of days of L1, dividing the detection period into a plurality of detection periods when the number of days reaches L1, marking the corresponding detection period as an abnormal theft period or a safety period through theft period detection analysis, obtaining the number of abnormal theft periods in a corresponding target area in the detection period, marking the number of abnormal theft periods as abnormal theft detection values, marking the number of abnormal theft periods between two adjacent groups of safety periods as abnormal theft continuous values, and carrying out average calculation on all abnormal theft continuous values to obtain abnormal theft continuous condition values;
The total number of times of generating alarm information in the corresponding target area in the detection period is obtained and marked as a theft alarm value, a theft hidden danger evaluation value is obtained through numerical calculation of the abnormal theft detection value, the abnormal theft holding condition value and the theft alarm value, and a theft high hidden danger signal in the corresponding target area is generated if the theft hidden danger evaluation value exceeds a preset theft hidden danger evaluation threshold value;
the specific analysis process of the theft time-interval detection analysis is as follows:
The method comprises the steps of collecting the times of generating alarm information in corresponding detection time periods by corresponding target areas, marking the corresponding detection time periods as abnormal theft time periods if the time period alarm values exceed preset time period alarm thresholds, and marking the corresponding detection time periods as safe time periods if the time period alarm values do not exceed the preset time period alarm thresholds.
2. The anti-theft monitoring and early warning method based on video remote monitoring according to claim 1, wherein in the third step, a specific analysis and judgment process for judging whether a theft risk exists in a corresponding target area according to the behavior characteristics of a moving target is as follows:
Image preprocessing, namely carrying out noise reduction processing on a received video image, carrying out brightness and contrast enhancement processing on the video image according to ambient illumination conditions, and compensating image jitter caused by camera shake or ambient interference;
The method comprises the steps of detecting a moving target, establishing and updating a background model to distinguish a static background from a dynamic target in an image, and extracting the moving target in a foreground by comparing a current image with the background model;
The target behavior analysis comprises the steps of tracking the identified moving target in continuous frames to generate a motion track of the moving target, extracting key behavior features from the motion track of the corresponding moving target, comparing the extracted behavior features with a preset normal behavior mode, and judging whether the target has abnormal behaviors or not;
And (3) carrying out theft risk assessment, namely carrying out context analysis on the behaviors of the targets by combining the behavior characteristics and scene information of the moving targets, grading the theft risk of the corresponding moving targets according to the context analysis result, and presetting one or more risk thresholds, wherein when the theft risk grade of the targets exceeds a certain threshold, the potential theft risk is considered.
3. The anti-theft monitoring and early warning method based on the video remote monitoring according to claim 1 is characterized in that when a monitoring management platform receives a theft high hidden danger signal, a corresponding target area is marked as a patrol area, when the monitoring management platform receives a theft low hidden danger signal, the corresponding target area is marked as a monitoring area, the monitoring management platform is in communication connection with a patrol tracking module, the monitoring management platform sends the patrol area to the patrol tracking module, the patrol tracking module analyzes patrol performance aiming at the corresponding patrol area in the next detection period, a patrol qualification signal or a patrol abnormality signal is generated through analysis, and the patrol qualification signal or the patrol abnormality signal of the corresponding patrol area is sent to a remote monitoring center through the monitoring management platform.
4. The anti-theft monitoring and early warning method based on video remote monitoring according to claim 3, wherein the specific operation process of the patrol tracking module comprises:
Acquiring the total number of inspection aiming at a corresponding inspection area in a detection period, marking the total number of inspection aiming at the corresponding inspection area as an inspection total frequency value, judging whether the corresponding inspection process is an inferior table inspection process or not through inspection monitoring analysis, acquiring the number of inferior table inspection processes aiming at the corresponding inspection area in the detection period, and carrying out ratio calculation on the number of inferior table inspection processes aiming at the corresponding inspection area and the inspection total frequency value to obtain an inspection inferior condition value;
Calculating the time difference between the starting time of the corresponding inspection process and the ending time of the adjacent last inspection process to obtain an inspection time difference, marking the corresponding inspection time difference as an inspection abnormal value if the inspection time difference exceeds a preset inspection time difference threshold, obtaining the quantity of the inspection abnormal value in the detection period, and calculating the ratio of the quantity of the inspection abnormal value to the quantity of the inspection time difference to obtain the inspection abnormal value;
And (3) carrying out numerical calculation on the inspection total frequency value, the inspection interval abnormal value and the inspection inferior condition value to obtain an inspection tracking value, generating an inspection abnormal signal of a corresponding inspection area if the inspection tracking value exceeds a preset inspection tracking threshold value, and generating an inspection qualified signal of the corresponding inspection area if the inspection tracking value does not exceed the preset inspection tracking threshold value.
5. The anti-theft monitoring and early warning method based on video remote monitoring according to claim 4, wherein the specific analysis process of the patrol monitoring analysis is as follows:
After the corresponding inspection process is finished, marking the corresponding inspection process as an inferior table inspection process if the non-inspection track value exceeds a preset non-inspection track threshold value, acquiring real-time inspection speed in the corresponding inspection process if the non-inspection track value does not exceed the preset non-inspection track threshold value, comparing the real-time inspection speed with a corresponding preset inspection speed range in a numerical mode, and judging that the corresponding moment is in an inspection speed different state if the real-time inspection speed is not in the corresponding preset inspection speed range;
The method comprises the steps of collecting the time length in the abnormal state of the inspection speed in the corresponding inspection process, carrying out ratio calculation on the time length and the total time length when the inspection is carried out to obtain an abnormal speed occupation value, marking the deviation value of the total time length when the inspection is compared with the preset standard inspection time length as an inspection time deviation value, marking the ratio of the non-inspection track value compared with the corresponding preset non-inspection track threshold value as a non-inspection track occupation value, carrying out numerical calculation on the non-inspection track occupation value, the abnormal speed occupation value and the inspection time deviation value to obtain an inspection evaluation value, and marking the corresponding inspection process as an inferior table inspection process if the inspection evaluation value exceeds the preset inspection evaluation threshold value.
6. The anti-theft monitoring and early warning method based on video remote monitoring according to claim 1 is characterized in that a monitoring management platform is in communication connection with a monitoring equipment supervision module, the monitoring equipment supervision module acquires all monitoring equipment existing in an area to be monitored, monitors the corresponding monitoring equipment, calculates a monitoring abnormal detection value through numerical calculation of a monitoring temperature detection value, a monitoring vibration detection value, a monitoring noise detection value, a monitoring delay value and a monitoring clear value, generates a monitoring abnormal signal of the corresponding monitoring equipment if the monitoring abnormal detection value exceeds a preset monitoring abnormal detection threshold value, generates a monitoring normal signal of the corresponding monitoring equipment if the monitoring abnormal detection value does not exceed the preset monitoring abnormal detection threshold value, and transmits the monitoring abnormal signal or the monitoring normal signal of the corresponding monitoring equipment to a remote monitoring center through the monitoring management platform.
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