CN115862241B - Charging pile area theft monitoring method - Google Patents
Charging pile area theft monitoring method Download PDFInfo
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- CN115862241B CN115862241B CN202310193814.0A CN202310193814A CN115862241B CN 115862241 B CN115862241 B CN 115862241B CN 202310193814 A CN202310193814 A CN 202310193814A CN 115862241 B CN115862241 B CN 115862241B
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Abstract
The invention discloses a charge pile area theft monitoring method, which relates to charge pile monitoring technology and aims at solving the problems that the monitoring mode is not only easily affected by the night state of security personnel, but also can not be found in time due to the night brightness problem, and the technical scheme is as follows: step one, dividing a scene into a white day environment and a night environment according to brightness; step two, collecting a person stealing action image, marking the azimuth of the charging pile, and establishing a suspicious person detection model; detecting in a black night environment through a thermal imaging principle, and judging whether suspected theft personnel act or not; and step four, substituting the detection result of the thermal imaging principle into a suspicious person detection model to judge whether the suspicious person is a theft person or not when the action of the suspicious theft person is monitored. The invention can automatically monitor the charging pile area, eliminate the influence of brightness and personnel and automatically monitor.
Description
Technical Field
The invention relates to a charging pile monitoring technology, in particular to a charging pile area theft monitoring method.
Background
Under the macroscopic regulation of the policy in recent years, the market share of the electric automobile is greatly improved, in order to meet the requirement that the electric quantity is insufficient and the electric automobile needs to be charged in time when the electric automobile is out of service, charging piles of the electric automobile are installed in cities in all places, and accordingly, a part of lawless persons use night time to disassemble, steal and sell the charging piles.
In order to tightly grasp such behaviors, most of the prior art directly carries out video monitoring through a monitoring camera and security personnel, and the problem is completely eradicated through a mode of naked eye observation, but because the monitoring camera needs to keep higher brightness in a monitored field at night, the security personnel can conveniently check the monitoring mode through naked eyes in real time, the monitoring mode is not only easily influenced by the night state of the security personnel, but also can not be found in time due to the night brightness problem of the security personnel, so that a monitoring method capable of discharging personnel factors and environment brightness factors is needed.
There is therefore a need to propose a new solution to this problem.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide the charge pile area theft monitoring method which can shoot the environment in monitoring and discharge the interference of brightness, and detect and analyze the actions and the positions of the personnel through the thermal imaging principle, so that the influence of the environment brightness on the monitoring is reduced, and the requirement on the labor intensity of the personnel is also reduced.
The technical aim of the invention is realized by the following technical scheme: the charge pile area theft monitoring method includes the following steps,
step one, dividing a scene into a white day environment and a night environment according to brightness;
step two, collecting a person stealing action image, marking the azimuth of the charging pile, and establishing a suspicious person detection model;
detecting in a black night environment through a thermal imaging principle, and judging whether suspected theft personnel act or not;
step four, substituting the detection result of the thermal imaging principle into a suspicious person detection model to judge whether the suspicious person is a theft person when the action of the suspicious theft person is monitored;
step five, when the charging pile azimuth is judged to have theft personnel, the content of an early warning picture is sent for verification and early warning;
and step six, when the charging pile azimuth is judged to have the theft personnel, comprehensively judging and alarming after combining the verification result.
The invention is further provided with: the white day environment and the night environment are static monitoring pictures, and coordinate systems are established, and the coordinates of the white day environment and the night environment correspond to each other.
The invention is further provided with: the static monitoring picture comprises a simulation picture of states of zero vehicles in a parking space, full vehicles in the parking space and less than full vehicles in the parking space.
The invention is further provided with: and the suspicious person detection model is established through MATLAB operation according to the azimuth coordinate range of the charging pile in the static monitoring picture and the coordinate range of the person stealing action image.
The invention is further provided with: the character theft action image comprises squatting action, semi-squatting action, horse step action, bowing action, standing and lifting double hands action and lifting action.
The invention is further provided with: the suspicious person detection model establishment step is as follows:
static monitoring picture establishes a planar coordinate system (X a ，Y b ），X a Is the transverse coordinate of the static monitoring picture, Y b For static monitoring of picturesVertical coordinates, and thereby confirm the charging pile azimuth coordinate range axis light (X cmin ，X cmax ，Y cmin ，Y cmax ），X cmin And X cmax Maximum and minimum ranges of transverse axes of the azimuth coordinate range of the charging pile respectively, Y cmin And Y cmax The maximum range and the minimum range of the vertical axis of the azimuth coordinate range of the charging pile are respectively, and the left heel in the person stealing action image is taken as a base point to establish a person stealing action image coordinate range axis light (X dmin ，X dmax ，Y dmin ，Y dmax ），X dmin And X dmax Maximum range and minimum range of transverse axis of human theft action image coordinate range, Y dmin And Y dmax The maximum range and the minimum range of the vertical axis of the coordinate range of the human theft action image are calculated, the relation between the detection result of the thermal imaging principle and the azimuth coordinate range of the charging pile is calculated, the relation between the detection result of the thermal imaging principle and the coordinate range of the human theft action image is calculated,
the region=inter (poly 1, poly 2)
poly1=polyshape([axis tight（X emin ，X emax ，Y emin ，Y emax ）]);
Poly2=polyshape([axis tight（X dmin ，X dmax ，Y dmin ，Y dmax ）])。
The invention is further provided with: step three, the thermal imaging principle detection result is used for establishing a plane coordinate system (X a ，Y b ) Confirming the motion coordinate range axis light (X) emin ，X emax ，Y emin ，Y emax ）,X emin And X emax Maximum range and minimum range of transverse axis of human theft action image coordinate range, Y emin And Y emax The maximum range and the minimum range of the vertical axis of the coordinate range of the human theft action image,
and when inter (poly 1, poly 2)/trapz ([ axis light (X) dmin ，X dmax ，Y dmin ，Y dmax ）]) If the number is more than 70%, the suspected theft is considered to act, otherwise, the suspected theft is not considered.
The invention is further provided with: the fourth step, the azimuth coordinate range of the polyout charging pile and the action coordinate range of the thief;
Poly3=polyshape([axis tight（X cmin ，X cmax ，Y cmin ，Y cmax ）]);
Poly4=polyshape([axis tight（X dmin ，X dmax ，Y dmin ，Y dmax ）]);
when the intersect (poly 3, poly 4)/trapz ([ axis light (X) cmin ，X cmax ，Y cmin ，Y cmax ）]) And when the total frame number/the conventional frame number of the static monitoring picture is more than 1800 seconds, judging as a thief, performing charging pile stealing behavior by the thief, and entering the next step, namely sending to a security room monitoring screen.
The invention is further provided with: the fourth step further comprises the step of positioning the automobile hub in an axis light (X fmin ，X fmax ，Y fmin ，Y fmax ）,X fmin And X fmax Positioning the maximum range and the minimum range of the transverse axis of the coordinate range for the automobile hub, Y fmin And Y fmax The maximum range and the minimum range of the vertical shaft of the automobile hub positioning coordinate range are the same linear fitting formula, and the azimuth coordinate range of the polyout charging pile and the action coordinate range of a thief are the same row of automobile hub positioning coordinate ranges;
Poly5=polyshape([axis tight（X fmin ，X fmax ，Y fmin ，Y fmax ）]);
Poly6=polyshape([axis tight（X dmin ，X dmax ，Y dmin ，Y dmax ）]);
when intersect (poly 5, poly 6)/trapz ([ axis)tight（X fmin ，X fmax ，Y fmin ，Y fmax ）]) When the number is more than 85%, counting the total frame number conforming to the third step and the fourth step by taking the frame number of the static monitoring picture as a reference,
when the total frame number/normal frame number of the static monitoring picture is more than 300s, the system judges that the system is a thief, the thief performs hub stealing and enters the next step, namely, the system is sent to a monitoring screen of a security room.
The automatic monitoring system for the theft of the charging pile area comprises a plurality of monitoring modules, wherein the number of the monitoring modules is several, and the monitoring modules are used for acquiring static monitoring pictures; the thermal imaging modules are equal to the monitoring modules in number and are used for acquiring the action coordinate range of the thief; the processing module is used for importing static monitoring pictures and the action coordinate range of the thief and analyzing and processing the static monitoring pictures and the action coordinate range of the thief; and the monitoring display is connected with the processing module and used for displaying the content of the early warning picture to verify and early warn.
In summary, the invention has the following beneficial effects:
the scene can be shot through the monitoring module, the static monitoring picture is obtained, and meanwhile, the action coordinates of the stolen personnel are obtained through the thermal imaging module, so that the situation in the scene is monitored through the suspicious personnel detection model, the influence of the ambient brightness on the monitoring is eliminated, the requirement on the labor intensity of the personnel can be reduced, and the monitoring on the stolen behavior of the charging pile is more accurate.
Drawings
Fig. 1 is a schematic structural view of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and examples.
Example 1
A charge pile area theft monitoring method, as shown in figure 1, comprises the following steps,
the method comprises the steps that firstly, a scene is divided into a white-day environment and a night environment by brightness, the white-day environment and the night environment are static monitoring pictures, a coordinate system is established for the static monitoring pictures of the white-day environment and the night environment, the coordinates of the white-day environment and the night environment correspond to each other, the static monitoring pictures of the white-day environment and the night environment are matched, the fact that the static monitoring pictures shot during daytime or at night are consistent is ensured, the situation that the charging pile direction or other objects are displaced cannot be said, and people can transfer the white-day environment even in the night environment state when the monitoring camera shoots.
And secondly, collecting the person stealing action image and the azimuth of the charging pile for marking, and establishing a suspicious person detection model, wherein the suspicious person detection model is established through MATLAB operation according to the azimuth coordinate range of the charging pile and the coordinate range of the person stealing action image in the static monitoring picture. The static monitoring picture comprises a simulation picture of a parking space zero vehicle, a parking space full vehicle and states of a parking space not full, and a large number of pictures are imported, so that the static monitoring picture is not limited to the parking space zero vehicle or the parking space full vehicle, after MATLAB is imported through various parameters, a final suspicious person detection model can be obtained through sufficient data parameters, the final formed suspicious person detection model has good accuracy, and when the suspicious person detection model performs data analysis, the final obtained data result is accurate, and requirements on manpower can be reduced.
And thirdly, detecting in a night environment through a thermal imaging principle, and judging whether suspected theft personnel actions exist or not, wherein the figure theft action images comprise squatting actions, semi-squatting actions, horse step actions, bowing actions, standing and lifting double hands and lifting actions. The detection is carried out in the night environment through the thermal imaging principle, the influence of the ambient brightness on the monitoring camera is removed, the heat of a human body can be detected directly through the thermal imaging principle, and the human body is displayed in a picture form, so that the existence of the human body can be detected even in the night environment, the situation that people in a parking lot cannot be clearly obtained due to the problem of the ambient brightness can be avoided, and the accuracy of final monitoring is improved.
And fourthly, substituting the detection result of the thermal imaging principle into a suspicious person detection model to judge whether the suspicious person is a theft person or not when the suspicious person is detected to exist, and automatically judging the situation conforming to the theft behavior, thereby reducing the requirement on the person, and the judgment is not a final result, and only is performed as a primary parameter to perform accounting, so that the final result can have more reference directions, and the judgment cannot be easily performed.
And fifthly, when the charging pile azimuth is judged to have the theft personnel, sending the early warning picture content to carry out verification early warning, and sending the early warning picture content to the security personnel to carry out manual verification aiming at the special situation, so that the occurrence of error early warning is avoided, the accuracy of final result judgment is improved, and meanwhile, the security personnel can only verify under the condition that the first few steps meet the conditions, the working intensity of the security personnel is not increased more, and compared with the common situation, the working intensity of the security personnel is greatly reduced.
And step six, when the charging pile azimuth is judged to have the theft personnel, comprehensively judging and alarming after combining the verification result.
Example two
Step two, the suspicious person detection model establishment steps are as follows:
static monitoring picture establishes a planar coordinate system (X a ，Y b ），X a Is the transverse coordinate of the static monitoring picture, Y b Is the vertical coordinate of the static monitoring picture, and confirms the azimuth coordinate range axis light (X cmin ，X cmax ，Y cmin ，Y cmax ），X cmin And X cmax Maximum and minimum ranges of transverse axes of the azimuth coordinate range of the charging pile respectively, Y cmin And Y cmax The maximum range and the minimum range of the vertical axis of the azimuth coordinate range of the charging pile are respectively, and the left heel in the person stealing action image is taken as a base point to establish a person stealing action image coordinate range axis light (X dmin ，X dmax ，Y dmin ，Y dmax ），X dmin And X dmax Transverse direction of human theft action image coordinate rangeMaximum and minimum ranges of axes, Y dmin And Y dmax The maximum range and the minimum range of the vertical axis of the coordinate range of the human theft action image are calculated, the relation between the detection result of the thermal imaging principle and the azimuth coordinate range of the charging pile is calculated, the relation between the detection result of the thermal imaging principle and the coordinate range of the human theft action image is calculated,
the region=inter (poly 1, poly 2)
poly1=polyshape([axis tight（X emin ，X emax ，Y emin ，Y emax ）]);
Poly2=polyshape([axis tight（X dmin ，X dmax ，Y dmin ，Y dmax ）])。
By establishing a suspicious person detection model on MATLAB, whether the person is in action or not can be judged for the first time only by taking the azimuth coordinate range of the charging pile and the image coordinate range of the person stealing action as two conditions.
Example III
Step three, the thermal imaging principle detection result is used for establishing a plane coordinate system (X) by using a static monitoring picture a ，Y b ) Confirming the motion coordinate range axis light (X) emin ，X emax ，Y emin ，Y emax ）,X emin And X emax Maximum range and minimum range of transverse axis of human theft action image coordinate range, Y emin And Y emax The maximum range and the minimum range of the vertical axis of the coordinate range of the human theft action image,
and when inter (poly 1, poly 2)/trapz ([ axis light (X) dmin ，X dmax ，Y dmin ，Y dmax ）]) If the number is more than 70%, the suspected theft is considered to act, otherwise, the suspected theft is not considered. The thermal imaging principle detection result, namely the motion coordinate range of the thief is established, the motion coordinate range of the thief is put into the suspicious person detection model, the detection result is compared with the human theft motion image, and the detection result is overlapped with the human theft motion imageWhen the area is larger than 70%, the current personnel action can be considered to be consistent with any one of the person theft action images, and the person theft action image can be considered to be a suspected theft personnel action.
Example IV
Fourth, the orientation coordinate range of the polyout charging pile and the action coordinate range of the thief are the area=interphect (poly 3, poly 4)
poly3=polyshape([axis tight（X cmin ，X cmax ，Y cmin ，Y cmax ）]);
poly4=polyshape([axis tight（X dmin ，X dmax ，Y dmin ，Y dmax ）]);
When the intersect (poly 3, poly 4)/trapz ([ axis light (X) cmin ，X cmax ，Y cmin ，Y cmax ）]) When the number is more than 85%, counting the total frame number conforming to the third step and the fourth step by taking the frame number of the static monitoring picture as a reference,
when the total frame number/the conventional frame number of the static monitoring picture is more than 1800s, the system judges that the system is a thief, and the thief performs the theft of the charging pile and enters the next step, namely the system is sent to a monitoring screen of the security room. When a person is judged to be a suspected stolen person, the person acts as the suspected stolen person, then the azimuth of the person is judged, whether the person acts within the azimuth coordinate range of the charging pile is judged, namely, the action coordinate range of the stolen person is brought into a suspicious person detection model, whether the action coordinate range of the stolen person corresponds to the azimuth coordinate range of the charging pile is judged, if the coincidence degree of the action coordinate range of the stolen person and the azimuth coordinate range of the charging pile is more than 85%, the person is judged to be actually stolen by the suspected stolen person to be carried out nearby the azimuth of the charging pile, the person can be judged to be actually stolen according to normal logic, but in order to eliminate the possibility of errors as far as possible, the person is still required to be compared with the conventional frame number of a static monitoring picture of normal shooting 1s according to the total frame number of the shot picture, and when the calculated time is more than 1800s, namely, when the time is 30min, the person is judged to be the person, the time judgment standard is derived from the normal charging pile installation time, and finally the person is finally judged to be transmitted to the security person to carry out final judgment, and the theft is not directly judged to be the final result by the monitoring method, so that the problem is avoided.
Example five
Step four also includes, the automobile hub positioning coordinate range axis light (X fmin ，X fmax ，Y fmin ，Y fmax ）,X fmin And X fmax Positioning the maximum range and the minimum range of the transverse axis of the coordinate range for the automobile hub, Y fmin And Y fmax The maximum range and the minimum range of the vertical shaft are the automobile hub positioning coordinate ranges, the automobile hub positioning coordinate ranges of the same row are in the same linear fitting formula, and the azimuth coordinate range of the polyout charging pile and the action coordinate range of a thief person
Poly5=polyshape([axis tight（X fmin ，X fmax ，Y fmin ，Y fmax ）]);
Poly6=polyshape([axis tight（X dmin ，X dmax ，Y dmin ，Y dmax ）]);
When the intersect (poly 5, poly 6)/trapz ([ axis light (X) fmin ，X fmax ，Y fmin ，Y fmax ）]) When the number is more than 85%, counting the total frame number conforming to the third step and the fourth step by taking the frame number of the static monitoring picture as a reference,
when the total frame number/normal frame number of the static monitoring picture is more than 300s, the system judges that the system is a thief, the thief performs hub stealing and enters the next step, namely, the system is sent to a monitoring screen of a security room. Meanwhile, in the detection process of the fourth step, once the detection azimuth is the automobile hub positioning coordinate range, whether the tire is stolen or not can be judged on the premise of the theft action, and finally, after the theft time is 5min, the tire is confirmed to be stolen, and finally, the tire is still verified by security personnel, and the final fixed capture is not directly performed by the monitoring method, so that the working intensity of the security personnel is greatly reduced, and the accuracy of the final result is also improved.
Example six
The automatic monitoring system for the area theft of the charging pile comprises a plurality of monitoring modules, wherein the number of the monitoring modules is a plurality of the monitoring modules, and the monitoring modules are used for acquiring static monitoring pictures, and particularly can be monitoring cameras; the thermal imaging modules are equal to the monitoring modules in number and are used for acquiring the action coordinate range of the thief, and the thermal imaging modules can be specifically infrared thermal imagers; the processing module is used for importing static monitoring pictures and the action coordinate range of the thief and analyzing and processing, and can be specifically a CPU; and the monitoring display is connected with the processing module and used for displaying the content of the early warning picture to verify and early warn.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the present invention may occur to one skilled in the art without departing from the principles of the present invention and are intended to be within the scope of the present invention.
Claims (8)
1. The automatic monitoring method for the regional theft of the charging pile is characterized by comprising the following steps of: comprises the following steps of the method,
step one, dividing a scene into a white day environment and a night environment according to brightness;
step two, collecting a person stealing action image, marking the azimuth of the charging pile, and establishing a suspicious person detection model;
the suspicious person detection model establishment steps are as follows:
static monitoring picture establishes a planar coordinate system (X a ，Y b )，X a Is the transverse coordinate of the static monitoring picture, Y b Is the vertical coordinate of the static monitoring picture, and confirms the azimuth coordinate range axis light (X cmin ，X cmax ，Y cmin ，Y cmax )，X cmin And X cmax Maximum and minimum ranges of transverse axes of the azimuth coordinate range of the charging pile respectively, Y cmin And Y cmax The maximum range and the minimum range of the vertical axis of the azimuth coordinate range of the charging pile are respectively established by taking the heel of the left foot in the person stealing action image as a base pointHuman theft action image coordinate range axis light (X dmin ，X dmax ，Y dmin ，Y dmax )，X dmin And X dmax The maximum range and the minimum range of the transverse axis of the coordinate range of the human theft action image, ydmin and Ydmax are the maximum range and the minimum range of the vertical axis of the coordinate range of the human theft action image, the relation between the detection result of the thermal imaging principle and the azimuth coordinate range of the charging pile is calculated, the relation between the detection result of the thermal imaging principle and the coordinate range of the human theft action image is calculated,
the region=inter (poly 1, poly 2)
poly1＝polyshape([axis tight(X emin ，X emax ，Y emin ，Y emax )])；
Poly2＝polyshape([axis tight(X dmin ，X dmax ，Y dmin ，Y dmax )])
Detecting in a black night environment through a thermal imaging principle, and judging whether suspected theft personnel act or not;
step four, substituting the detection result of the thermal imaging principle into a suspicious person detection model to judge whether the suspicious person is a theft person when the action of the suspicious theft person is monitored;
step five, when the charging pile azimuth is judged to have theft personnel, the content of an early warning picture is sent for verification and early warning;
and step six, when the charging pile azimuth is judged to have the theft personnel, comprehensively judging and alarming after combining the verification result.
2. The automatic monitoring method for regional theft of charging piles according to claim 1, wherein the method comprises the following steps: the white day environment and the night environment are static monitoring pictures, and coordinate systems are established, and the coordinates of the white day environment and the night environment correspond to each other.
3. The automatic monitoring method for regional theft of charging piles according to claim 1, wherein the method comprises the following steps: the static monitoring picture comprises a simulation picture of states of zero vehicles in a parking space, full vehicles in the parking space and less than full vehicles in the parking space.
4. A charging pile area theft automatic monitoring method according to any one of claims 1 to 3, characterized in that: and the suspicious person detection model is established through MATLAB operation according to the azimuth coordinate range of the charging pile in the static monitoring picture and the coordinate range of the person stealing action image.
5. The automatic monitoring method for regional theft of charging piles according to claim 4, wherein the method comprises the following steps: the character theft action image comprises squatting action, semi-squatting action, horse step action, bowing action, standing and lifting double hands action and lifting action.
6. The automatic monitoring method for regional theft of charging piles according to claim 4, wherein the method comprises the following steps: step three, the thermal imaging principle detection result is used for establishing a plane coordinate system (X a ，Y b ) Confirming the motion coordinate range axis light (X) emin ，X emax ，Y emin ，Y emax ),X emin And X emax Maximum range and minimum range of transverse axis of human theft action image coordinate range, Y emin And Y emax The maximum range and the minimum range of the vertical axis of the coordinate range of the human theft action image,
and when inter (poly 1, poly 2)/trapz ([ axis light (X) dmin ，X dmax ，Y dmin ，Y dmax )]) If the number is more than 70%, the suspected theft is considered to act, otherwise, the suspected theft is not considered.
7. The automatic monitoring method for regional theft of charging piles according to claim 4, wherein the method comprises the following steps: fourth, the azimuth coordinate range of the polyout charging pile and the action coordinate range of the thief, area=interphect (poly 3, poly 4)
Poly3＝polyshape([axis tight(X cmin ，X cmax ，Y cmin ，Y cmax )])；
Poly4＝polyshape([axis tight(X dmin ，X dmax ，Y dmin ，Y dmax )])；
When the intersect (poly 3, poly 4)/trapz ([ axis light (X) cmin ，X cmax ，Y cmin ，Y cmax )]) When the number is more than 85%, counting the total frame number conforming to the third step and the fourth step by taking the frame number of the static monitoring picture as a reference,
when the total frame number/the conventional frame number of the static monitoring picture is more than 1800s, the system judges that the system is a thief, and the thief performs the theft of the charging pile and enters the next step, namely the system is sent to a monitoring screen of the security room.
8. The automatic monitoring method for regional theft of charging piles according to claim 4, wherein the method comprises the following steps: the fourth step further comprises the step of positioning the automobile hub in an axis light (X fmin ，X fmax ，Y fmin ，Y fmax ),X fmin And X fmax Positioning the maximum range and the minimum range of the transverse axis of the coordinate range for the automobile hub, Y fmin And Y fmax The maximum range and the minimum range of the vertical shaft are the automobile hub positioning coordinate ranges, the automobile hub positioning coordinate ranges of the same row are in the same linear fitting formula, and the azimuth coordinate range of the polyout charging pile and the action coordinate range of a thief person
poly5＝polyshape([axis tight(X fmin ，X fmax ，Y fmin ，Y fmax )])；
poly6＝polyshape([axis tight(X dmin ，X dmax ，Y dmin ，Y dmax )])；
When the intersect (poly 5, poly 6)/trapz ([ axis light (X) fmin ，X fmax ，Y fmin ，Y fmax )]) When the number is more than 85%, counting the total frame number conforming to the third step and the fourth step by taking the frame number of the static monitoring picture as a reference,
when the total frame number/normal frame number of the static monitoring picture is more than 300s, the system judges that the system is a thief, the thief performs hub stealing and enters the next step, namely, the system is sent to a monitoring screen of a security room.
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