CN117499621A

CN117499621A - Detection method, device, equipment and medium of video acquisition equipment

Info

Publication number: CN117499621A
Application number: CN202410001644.6A
Authority: CN
Inventors: 李可欣; 李勇
Original assignee: China Mobile Communications Group Co Ltd; China Mobile Suzhou Software Technology Co Ltd
Current assignee: China Mobile Communications Group Co Ltd; China Mobile Suzhou Software Technology Co Ltd
Priority date: 2024-01-02
Filing date: 2024-01-02
Publication date: 2024-02-02
Anticipated expiration: 2044-01-02
Also published as: CN117499621B

Abstract

The present disclosure relates to a detection method, apparatus, device and medium for video acquisition equipment, which effectively solve the technical problems in the prior art that in the prior art, the detection method for video acquisition equipment cannot be overhauled according to the severity of a fault and the association between monitoring cameras, so that the timeliness of the fault repair of the cameras is poor, and a large amount of time and manpower are wasted, and the detection method for video acquisition equipment comprises: acquiring operation and maintenance data of at least one video acquisition device to be detected; determining an operation and maintenance score of each video acquisition device to be detected based on the operation and maintenance data of each video acquisition device to be detected; and determining the video acquisition equipment to be detected, of which the operation and maintenance score is larger than a preset scoring threshold value, as abnormal video acquisition equipment.

Description

Detection method, device, equipment and medium of video acquisition equipment

Technical Field

The disclosure relates to the technical field of monitoring and intelligent operation and maintenance, in particular to a detection method, a detection device and a detection medium of video acquisition equipment.

Background

With the development of video monitoring, the video monitoring camera plays an irreplaceable role in modern security, and the monitoring equipment often fails due to the annual use of the monitoring equipment and abrasion caused by the natural environment, so that the security of a monitoring area is reduced. Currently, the most part of the monitoring overhaul is divided into two types: one is to judge the fault and then overhaul according to the quality detection of the returned image. The other is realized by periodically carrying out inspection of monitoring equipment on the monitoring area by maintenance personnel. The above two maintenance schemes cannot be used for maintenance according to the severity of faults and the association between monitoring cameras, so that the timeliness of the fault restoration of the cameras is poor, and a large amount of time and labor are wasted.

Disclosure of Invention

In order to solve the technical problems, the disclosure provides a detection method, a device, equipment and a medium of video acquisition equipment, which effectively solve the technical problems that in the prior art, maintenance cannot be performed according to the severity of faults and the association between monitoring cameras, so that the timeliness of repairing the faults of the cameras is poor, and a large amount of time and labor are wasted.

In a first aspect, an embodiment of the present disclosure provides a method for detecting a video capturing device, where the method includes:

acquiring operation and maintenance data of at least one video acquisition device to be detected;

determining an operation and maintenance score of each video acquisition device to be detected based on the operation and maintenance data of each video acquisition device to be detected;

and determining the video acquisition equipment to be detected with the operation and maintenance score larger than a preset scoring threshold as abnormal video acquisition equipment.

In a possible implementation manner, in the method provided by the embodiment of the present invention, operation and maintenance data of at least one video acquisition device to be detected is obtained, including:

and acquiring judgment values of a plurality of monitoring indexes of the video acquisition equipment to be detected through a sensor arranged on each video acquisition equipment to be detected.

In a possible implementation manner, in the method provided by the embodiment of the present invention, determining an operation and maintenance score of each video capture device to be detected based on an operation and maintenance data of each video capture device to be detected includes:

Acquiring a judgment value range of each monitoring index;

and calculating to obtain the operation and maintenance scores of the video acquisition equipment to be detected by utilizing the judgment values of the monitoring indexes of the video acquisition equipment to be detected and the judgment value range of the monitoring indexes.

In a possible implementation manner, in the method provided by the embodiment of the present invention, after determining, as an abnormal video capturing device, a video capturing device to be detected whose operation and maintenance score is greater than a preset score threshold, the method further includes:

calculating the association degree of each abnormal video acquisition device;

and for each abnormal video acquisition device, determining the alarm level of the abnormal video acquisition device based on the association degree of the abnormal video acquisition device and the operation and maintenance scores of the abnormal video acquisition device.

In a possible implementation manner, in the method provided by the embodiment of the present invention, the calculating the association degree of each abnormal video acquisition device includes:

acquiring position information and shooting angles of each video acquisition device;

determining an overlapping shooting angle of each video acquisition device and the abnormal video acquisition device according to the shooting angle of the abnormal video acquisition device and the shooting angle of each video acquisition device;

And determining the association degree of the abnormal video acquisition equipment based on the position information of the abnormal video acquisition equipment, the shooting angle and the overlapped shooting angle of the abnormal video acquisition equipment.

In a possible implementation manner, in the method provided by the embodiment of the present invention, for each abnormal video capture device, based on the association degree of the abnormal video capture device and the operation and maintenance score of the abnormal video capture device, determining the alarm level of the abnormal video capture device includes:

calculating the association degree of each abnormal video acquisition device and the weighted average value of the operation and maintenance scores of each abnormal video acquisition device;

and determining the alarm level of the abnormal video acquisition equipment based on the weighted average value.

In a possible implementation manner, in the method provided by the embodiment of the present invention, the alarm levels include a level one, a level two and a level three, the alarm level of the level one is higher than the alarm level of the level two, and the alarm level of the level two is higher than the alarm level of the level three, where:

when the weighted average value is in a first threshold value, determining that the alarm grade is grade one;

when the weighted average value is in the second threshold value, determining that the alarm grade is grade two;

and when the weighted average value is at a third threshold value, determining that the alarm level is level three.

In a possible implementation manner, before calculating the association degree of each abnormal video acquisition device, the method provided in the embodiment of the present invention further includes:

if the preset angle of the abnormal video acquisition equipment changes, determining that the alarm grade of the abnormal video acquisition equipment is grade one.

In a possible implementation manner, in the method provided by the embodiment of the present invention, whether the preset angle of the abnormal video acquisition device changes is determined by the following method:

acquiring a shooting image shot by an abnormal video acquisition device;

and determining whether the preset angle changes or not by comparing the shot image with the historical shot image shot by the abnormal video acquisition equipment.

In one possible implementation manner, in the method provided by the embodiment of the present invention, the method further includes:

determining the abnormal type of each abnormal video acquisition device through the operation and maintenance score of each abnormal video acquisition device;

and generating a maintenance work order based on the alarm grade and the abnormality type of each abnormal video acquisition device, wherein the maintenance work order is used for representing the maintenance sequence and the abnormality type of each abnormal video acquisition device.

In a possible implementation manner, in the method provided by the embodiment of the present invention, a repair worksheet of an abnormal video acquisition device is generated based on an alarm level of each abnormal video acquisition device, including:

Determining an influence factor of each anomaly type according to the historical maintenance records;

and sequencing the abnormal video acquisition equipment to be maintained based on the influence factors of each abnormal type and the alarm level of each abnormal video acquisition equipment to obtain a maintenance work order.

In a possible implementation manner, in the method provided by the embodiment of the present invention, a history maintenance record includes an anomaly detection type and an anomaly maintenance type when the history anomaly video capture device is maintained each time, the anomaly detection type is an anomaly type predicted according to a judgment value, the anomaly maintenance type is an anomaly type determined during maintenance, and then an influence factor of each anomaly type is determined according to the history maintenance record, including:

determining the confidence coefficient of each anomaly type according to the anomaly detection type and the anomaly maintenance type;

and determining an influence factor of each anomaly type based on the confidence of each anomaly type and a preset anomaly type weight.

In a possible implementation manner, in the method provided by the embodiment of the present invention, based on the influence factor of each anomaly type and the alarm level of each anomaly video capture device, each anomaly video capture device is sequenced to obtain a maintenance work order, including:

Sequencing each abnormal video acquisition device based on the alarm level of each abnormal video acquisition device to obtain a sequencing result, wherein the abnormal video acquisition device with the high alarm level in the sequencing result is the prior one;

and correcting the sequencing result by using the influence factors of each anomaly type, so that the anomaly video acquisition equipment with high influence factor values in the anomaly video acquisition equipment with the same alarm level is prior.

In a second aspect, an embodiment of the present disclosure provides a detection apparatus for a video capture device, where the apparatus includes:

the acquisition unit is used for acquiring operation and maintenance data of at least one video acquisition device to be detected;

the scoring unit is used for determining the operation and maintenance score of each video acquisition device to be detected based on the operation and maintenance data of each video acquisition device to be detected;

and the determining unit is used for determining the video acquisition equipment to be detected with the operation and maintenance score larger than a preset score threshold value as abnormal video acquisition equipment.

In a possible implementation manner, in the device provided by the embodiment of the present invention, the obtaining unit is specifically configured to:

In a possible implementation manner, in the device provided by the embodiment of the present invention, the scoring unit is specifically configured to:

acquiring a judgment value range of each monitoring index;

In a possible implementation manner, in the apparatus provided by the embodiment of the present invention, the apparatus further includes a processing unit, where the processing unit is configured to:

calculating the association degree of each abnormal video acquisition device;

In a possible implementation manner, in the device provided by the embodiment of the present invention, the processing unit is specifically further configured to:

In a possible implementation manner, in the device provided by the embodiment of the present invention, the alarm levels include a level one, a level two and a level three, the alarm level of the level one is higher than the alarm level of the level two, the alarm level of the level two is higher than the alarm level of the level three, and the processing unit is specifically further configured to:

In a possible implementation manner, in the apparatus provided by the embodiment of the present invention, the processing unit is further configured to:

In a possible implementation manner, in the apparatus provided by the embodiment of the present invention, the processing unit is specifically further configured to determine whether a preset angle of the abnormal video acquisition device changes by:

Acquiring a shooting image shot by an abnormal video acquisition device;

In a possible implementation manner, in the device provided by the embodiment of the present invention, the history maintenance record includes an abnormality detection type and an abnormality maintenance type when the history abnormal video capture device is maintained each time, the abnormality detection type is an abnormality type predicted according to the judgment value, the abnormality maintenance type is an abnormality type determined during maintenance, and the processing unit is specifically configured to:

In a possible implementation manner, in the device provided by the embodiment of the present invention, the processing unit is specifically configured to:

In a third aspect, an embodiment of the present disclosure provides an electronic device, including:

a memory;

a processor; and

a computer program;

wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of detection of the video capture device as described above.

In a fourth aspect, embodiments of the present disclosure provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a method for detecting a video capture device as described above.

The embodiment of the disclosure provides a detection method of video acquisition equipment, which comprises the following steps:

firstly, operation and maintenance data of at least one video acquisition device to be detected are obtained, then operation and maintenance scores of each video acquisition device to be detected are determined based on the operation and maintenance data of each video acquisition device to be detected, and finally the video acquisition device to be detected with the operation and maintenance scores being larger than a preset score threshold value is determined to be an abnormal video acquisition device. According to the method provided by the disclosure, the abnormal video acquisition equipment is determined according to scoring of the video acquisition equipment to be detected, so that the abnormality of the video acquisition equipment can be effectively identified, the accuracy is improved, and the operation and maintenance cost is reduced.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.

In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.

Fig. 1 is a flow chart of a detection method of a video acquisition device according to an embodiment of the disclosure;

fig. 2 is a flowchart of a detection method of another video capture device according to an embodiment of the disclosure;

fig. 3 is a schematic diagram of overlapping shooting angles according to an embodiment of the present disclosure;

fig. 4 is a flowchart illustrating a detection method of still another video capturing apparatus according to an embodiment of the present disclosure;

FIG. 5 is an exemplary diagram of a maintenance personnel log provided by an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of a detection device of a video capturing apparatus according to an embodiment of the present disclosure;

fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.

Detailed Description

In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.

Fig. 1 is a flow chart of a detection method of a video capturing apparatus according to an embodiment of the present disclosure, which specifically includes the following steps S101 to S103 shown in fig. 1:

s101, acquiring operation and maintenance data of at least one video acquisition device to be detected.

In specific implementation, the judgment values of a plurality of monitoring indexes of the video acquisition equipment to be detected are obtained through the sensors arranged on each video acquisition equipment to be detected, for example, when the video acquisition equipment is a camera, the faults of the camera comprise brightness faults, communication states, signal loss, picture color cast, black screen and the like. The monitoring indicators collected by the sensor include signal to noise ratio, power supply voltage, operating temperature, trigger CCD and humidity.

S102, determining the operation and maintenance score of each video acquisition device to be detected based on the operation and maintenance data of each video acquisition device to be detected.

In specific implementation, firstly, the judging value range of each monitoring index is obtained, then the judging values of a plurality of monitoring indexes of each video acquisition device to be detected and the judging value range of each monitoring index are utilized to calculate and obtain the operation and maintenance score of each video acquisition device to be detected, and the specific calculation formula is as follows:

wherein score represents a score calculated from the index score;representing the z-th monitoring index acquired by the acquisition equipmentkJudging values; />Represent the firstzThe first monitoring indexkNormal range of each judgment value;Kabnormal sharing representing a certain monitoring indexKDetermining a judgment value;Zindicating the total number of monitoring indicators.

And S103, determining the video acquisition equipment to be detected with the operation and maintenance score larger than a preset score threshold as abnormal video acquisition equipment.

In specific implementation, if the operation and maintenance score calculated in step S102 is higher than the preset score threshold, the video capture device to be detected is determined to be an abnormal video capture device, and the specific preset score threshold may be set according to actual requirements, which is not limited in the embodiments of the present disclosure.

Fig. 2 is a specific flowchart of a detection method of a video capturing apparatus according to an embodiment of the present disclosure, which specifically includes the following steps S201 to S205 shown in fig. 2:

s201, operation and maintenance data of at least one video acquisition device to be detected are acquired.

S202, determining the operation and maintenance score of each video acquisition device to be detected based on the operation and maintenance data of each video acquisition device to be detected.

And S203, determining the video acquisition equipment to be detected with the operation and maintenance score larger than a preset score threshold as abnormal video acquisition equipment.

Steps S201 to S203 are the same as steps S101 to S103, and are not described here again.

S204, calculating the association degree of each abnormal video acquisition device.

In specific implementation, the position information and the shooting angle of each video acquisition device are firstly obtained, then the overlapping shooting angle of each video acquisition device and the abnormal video acquisition device is determined according to the shooting angle of the abnormal video acquisition device and the shooting angle of each video acquisition device, and finally the association degree of the abnormal video acquisition device is determined based on the position information of the abnormal video acquisition device, the shooting angle of the abnormal video acquisition device and the overlapping shooting angle.

Taking the cameras in the above embodiment as an example, the association degree is to determine the association between the cameras according to the angles and the distances between the cameras, and the calculation method is as follows:

Wherein Rm represents the association degree between a camera with abnormal index grading and other cameras, if the association degree is stronger, the influence of the fault of the monitoring camera on the whole monitoring system is smaller, and if the association degree is weaker, the influence of the fault of the monitoring camera on the whole monitoring system is larger; j represents the total number of monitoring cameras in the monitoring system except for cameras with abnormal index scores;representing the geographic coordinates of the jth monitoring camera relative to the entire monitoring system；/>Geographic coordinates of the monitoring camera, which represent index scoring abnormality, relative to the whole monitoring system; a represents the shooting angle of a monitoring camera with abnormal index grading; />The j-th monitoring camera and the camera with abnormal index scoring are shown to overlap shooting angles; l represents the distance between the camera with the index score abnormality and the monitoring camera with the farthest distance from the camera with the index score abnormality.

Taking two cameras as an example, as shown in fig. 3, each triangle represents one camera, and the area sandwiched by two dotted lines represents a preset shooting angle of the camera, the method for calculating the overlapping shooting angle o between the two cameras is as follows:

the method provided by the embodiment is applied to judging the association degree between the preset angles and the cameras, specifically, the preset shooting angles of the monitoring cameras are judged by constructing a database, the association degree between the monitoring cameras is further determined, and the importance of the cameras is judged.

S205, for each abnormal video acquisition device, determining the alarm level of the abnormal video acquisition device based on the association degree of the abnormal video acquisition device and the operation and maintenance scores of the abnormal video acquisition device.

In specific implementation, firstly, calculating a weighted average value of the association degree of each abnormal video acquisition device and the operation and maintenance scores of each abnormal video acquisition device, then determining alarm grades of the abnormal video acquisition devices based on the weighted average value, wherein the alarm grades comprise a grade one, a grade two and a grade three, the alarm grade of the grade one is higher than the alarm grade of the grade two, the alarm grade of the grade two is higher than the alarm grade of the grade three, when the weighted average value is in a first threshold value, the alarm grade is determined to be the grade one, when the weighted average value is in a second threshold value, the alarm grade is determined to be the grade two, and when the weighted average value is in a third threshold value, the alarm grade is determined to be the grade three.

Still using the above example, the alarm level is determined according to the fault severity of the camera and the importance level of the camera, that is, the alarm level is determined according to the index score and the association level, and the calculation formula of the G value is specifically determined by calculating the G value as follows:

wherein,g is divided into three value ranges, the corresponding alarm class is divided into 3 classes, and the higher the G value is, the higher the alarm class is. The values of the first threshold, the second threshold and the third threshold can be determined according to the actual requirement, for example, the first threshold is +. >The method comprises the steps of carrying out a first treatment on the surface of the The second threshold is->The method comprises the steps of carrying out a first treatment on the surface of the The third threshold is->。

In the step, before calculating the score, whether the preset angle of the video acquisition equipment changes is judged, and if the preset angle of the abnormal video acquisition equipment changes, the alarm grade of the abnormal video acquisition equipment is directly determined to be grade one. The specific judging step is that firstly, a shooting image shot by the abnormal video acquisition equipment is obtained, and then whether the preset angle changes is determined by comparing the shooting image with a historical shooting image shot by the abnormal video acquisition equipment. Specifically, still taking a camera as an example, the preset angle judgment is preprocessed by constructing a database and image similarity comparison algorithm. Firstly, numbering each monitoring camera, and storing pictures shot by each monitoring camera at a preset angle into a database, wherein the pictures stored into the database comprise pictures in rainy days, cloudy days, sunny days and other days and in various time periods. When the index score of a certain monitoring camera is higher than a threshold value, the index score of the camera is considered to be abnormal, the picture shot by the current frame of the monitoring camera is compared with the picture of the monitoring camera stored in a database through a picture similarity algorithm, so that whether the preset angle of the camera changes or not is judged, and if the preset angle of the camera changes, the relevance between the cameras is calculated according to the angle and the position, and the relevance judgment is inaccurate at the moment, so that primary alarm is directly carried out; if the correlation degree is not changed, the correlation degree is calculated.

Fig. 4 is a specific flowchart of a detection method of a video capturing apparatus according to another embodiment of the present disclosure, where in this embodiment, the cleaning time is determined by using the working parameters, the image data and the humidity information, and specifically includes the following steps as shown in fig. 4:

s401, acquiring operation and maintenance data of at least one video acquisition device to be detected.

S402, determining the operation and maintenance score of each video acquisition device to be detected based on the operation and maintenance data of each video acquisition device to be detected.

S403, determining the video acquisition equipment to be detected with the operation and maintenance score larger than a preset score threshold as abnormal video acquisition equipment.

Steps S401 to S403 are the same as steps S101 to S103, and are not described here again.

S404, determining the abnormal type of each abnormal video acquisition device through the operation and maintenance score of each abnormal video acquisition device.

In specific implementation, as mentioned in step S101, the faults of the video capturing apparatus include a brightness fault, a connection state, a signal loss, a color cast of a picture, a black screen, and the like. Therefore, the operation and maintenance indexes collected by the collection module comprise signal to noise ratio, power supply voltage, working temperature, trigger CCD humidity and the like. By judging the operation and maintenance scores, what index is abnormal can be determined, and then the abnormal type of the abnormal video acquisition equipment can be judged first.

S405, generating a maintenance work order based on the alarm level and the abnormality type of each abnormal video acquisition device.

During implementation, firstly, determining an influence factor of each abnormal type according to a historical maintenance record, and then sequencing the abnormal video acquisition equipment to be maintained based on the influence factor of each abnormal type and the alarm level of each abnormal video acquisition equipment to obtain a maintenance work order, wherein the maintenance work order is used for representing the maintenance sequence and the abnormal type of each abnormal video acquisition equipment. The historical maintenance record comprises an abnormality detection type and an abnormality maintenance type when the historical abnormal video acquisition equipment is maintained each time, wherein the abnormality detection type is an abnormality type predicted according to a judgment value, and the abnormality maintenance type is an abnormality type determined during maintenance, when an influence factor is calculated, the confidence coefficient of each abnormality type is determined according to the abnormality detection type and the abnormality maintenance type, and then the influence factor of each abnormality type is determined based on the confidence coefficient of each abnormality type and a preset abnormality type weight. When the confidence coefficient is calculated specifically, a self-adaptive determination of the confidence coefficient through a negative feedback mechanism is provided. Confidence of each sensor is The confidence is determined by a maintenance person through a log generated by the real situation in the maintenance process, wherein the log of the maintenance person comprises an index anomaly category, an anomaly index acquisition equipment category, an actual anomaly index and an actual anomaly index acquisition equipment category. The confidence level is calculated as follows:

wherein,representing the confidence level of the ith acquisition device; />Indicating the number of times the ith acquisition device did not detect an anomaly; />Representing the number of false detections of the ith acquisition equipment; t represents the number of times that the actual abnormal index category of maintenance is different from the abnormal index category in the log.

In one example, as shown in fig. 5, the log of the maintenance personnel is shown in the graph, the abnormality detection type is the abnormality index type in the graph, the abnormality maintenance type is the actual abnormality index type in the graph, and in the sample, only one abnormality index is used each time, and only three indexes are collected. The acquisition index is exemplified by signal-to-noise ratio, working temperature and power supply voltage, and the confidence coefficients of the acquisition equipment video measuring instrument, the temperature sensor and the voltage detector are respectively set as、/>、/>. The number of anomalies which are not detected by the video measuring instrument (namely, the number of times that the actual anomaly index is the signal to noise ratio and the anomaly index category is the non-signal to noise ratio) can be known according to the maintenance log >1, the number of false detections of the video measuring instrument (namely, the number of times that the video measuring instrument is actually in a non-signal-to-noise ratio and the abnormal index type is in a signal-to-noise ratio)>Is 2; of temperature sensor2->3; voltage detector->2->Is 0; total of repairs in logThe number T is 5. The confidence coefficient calculation formula is as follows: />，/>，/>。

After the confidence coefficient is calculated, the influence factor is calculated according to the confidence coefficient, and the formula is as follows:

wherein,an influence factor indicating a certain abnormality index; />Representing the confidence level of the abnormal index collection device; />Impact weight indicating an abnormality index; n represents a total of n acquisition devices; />Representing the confidence of the ith collector; />Indicating the impact weight of the i-th index.

The embodiment of the disclosure provides a method for adaptively determining the confidence coefficient of acquisition equipment through a negative feedback mechanism. By establishing a negative feedback mechanism, the confidence level of the monitoring acquisition equipment is self-adaptively determined according to the log generated by the maintenance personnel in the maintenance process, the index scoring accuracy is improved, and the accuracy of identifying the abnormal monitoring cameras is further improved.

Still using the above example, the priority of maintenance is set by the influence of the alarm level and the abnormality index, the influence weight of the picture loss failure such as the signal loss, the black screen, etc. is set to 2W, and the picture quality failure influence weight of the picture not lost such as the brightness failure, the picture color shift, etc. is set to W.

And then judging the maintenance priority of the monitoring camera according to the influence factors of the abnormal indexes and the alarm level, wherein the priority judgment is specifically obtained by comparing priority scores, and the calculation formula of the priority scores is as follows:

wherein,indicating a certain monitoring camera priority score, < >>The larger indicates the higher the maintenance priority; />The number of the abnormal indexes of the camera is represented; />A G value representing the monitoring camera; />The influence factor indicating the mth abnormality index.

And finally, sequencing each abnormal video acquisition device based on the alarm level of each abnormal video acquisition device to obtain a sequencing result, wherein the abnormal video acquisition device with the high alarm level in the sequencing result is the first, and then correcting the sequencing result by using the influence factor of each abnormal type, so that the abnormal video acquisition devices with the high influence factor value in the abnormal video acquisition devices with the same alarm level are the first. In the process of judging the priority, if the alarm level is one level and the alarm level is caused by the change of the preset angle, the maintenance priority is set to be the highest. And in other cases, all the camera priority scores are ranked, and the higher the score is, the higher the order of maintenance work orders is.

In the embodiment of the disclosure, the maintenance work order is generated according to the severity of the camera fault and the priority of the important camera, so that the problems of serious fault and untimely maintenance of the important camera are solved, and the safety of the monitoring system is improved.

Fig. 6 is a schematic structural diagram of a detection device of a video capturing apparatus according to an embodiment of the present disclosure. The detection apparatus 600 of a video capturing device provided in the embodiment of the present disclosure may execute the processing flow provided in the detection method embodiment of a video capturing device, as shown in fig. 6, where the detection apparatus 600 of a video capturing device includes an obtaining unit 601, an output unit 602, and a processing unit 603, where:

an obtaining unit 601, configured to obtain operation and maintenance data of at least one video acquisition device to be detected;

a scoring unit 602, configured to determine an operation and maintenance score of each video capture device to be detected based on the operation and maintenance data of each video capture device to be detected;

the determining unit 603 is configured to determine a video capture device to be detected, whose operation and maintenance score is greater than a preset score threshold, as an abnormal video capture device.

In a possible implementation manner, in the apparatus provided by the embodiment of the present invention, the obtaining unit 601 is specifically configured to:

In one possible implementation manner, in the apparatus provided by the embodiment of the present invention, the scoring unit 602 is specifically configured to:

acquiring a judgment value range of each monitoring index;

In a possible implementation manner, in an apparatus provided by an embodiment of the present invention, the apparatus further includes a processing unit 604, where the processing unit 604 is configured to:

calculating the association degree of each abnormal video acquisition device;

In a possible implementation manner, in the apparatus provided by the embodiment of the present invention, the processing unit 604 is specifically further configured to:

In a possible implementation manner, in the device provided by the embodiment of the present invention, the alert levels include a level one, a level two and a level three, where the alert level of the level one is higher than the alert level of the level two, and the alert level of the level two is higher than the alert level of the level three, and the processing unit 604 is specifically further configured to:

In one possible implementation manner, in the apparatus provided by the embodiment of the present invention, the processing unit 604 is further configured to:

In a possible implementation manner, in the apparatus provided by the embodiment of the present invention, the processing unit 604 is specifically further configured to determine whether the preset angle of the abnormal video acquisition device changes by:

acquiring a shooting image shot by an abnormal video acquisition device;

In a possible implementation manner, in the apparatus provided by the embodiment of the present invention, the history maintenance record includes an abnormality detection type and an abnormality maintenance type when the history abnormal video capturing device is maintained each time, the abnormality detection type is an abnormality type predicted according to the judgment value, and the abnormality maintenance type is an abnormality type determined during maintenance, and the processing unit 604 is specifically configured to:

In one possible implementation manner, in the apparatus provided by the embodiment of the present invention, the processing unit 604 is specifically configured to:

The detection device of the video capturing apparatus in the embodiment shown in fig. 6 may be used to implement the technical solution of the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein again.

In addition, the detection method and apparatus of the video capture device of the embodiments of the present application described in connection with fig. 1 to 6 may be implemented by an electronic device. Fig. 7 shows a schematic hardware structure of an electronic device according to an embodiment of the present application.

As shown in fig. 7, the electronic apparatus 700 may include a processing device (e.g., a central processor, a graphic processor, etc.) 701, which may perform various suitable actions and processes according to a program stored in a Read Only Memory (ROM) 702 or a program loaded from a storage device 708 into a Random Access Memory (RAM) 703 to implement a detection method of a video capture device according to an embodiment of the present disclosure. In the RAM 703, various programs and data required for the operation of the electronic device 700 are also stored. The processing device 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.

In general, the following devices may be connected to the I/O interface 705: input devices 706 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, and the like; an output device 707 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 708 including, for example, magnetic tape, hard disk, etc.; and a communication device 709. The communication means 709 may allow the electronic device 700 to communicate wirelessly or by wire with other devices to exchange data. While fig. 7 shows an electronic device 700 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.

In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a non-transitory computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts, thereby implementing the speech control method as described above. In such an embodiment, the computer program may be downloaded and installed from a network via communication device 709, or installed from storage 708, or installed from ROM 702. The above-described functions defined in the methods of the embodiments of the present disclosure are performed when the computer program is executed by the processing device 701.

It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.

The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to:

Alternatively, the electronic device may perform other steps described in the above embodiments when the above one or more programs are executed by the electronic device.

Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.

It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims

1. A method for detecting a video acquisition device, the method comprising:

and determining the video acquisition equipment to be detected, of which the operation and maintenance score is larger than a preset scoring threshold value, as abnormal video acquisition equipment.

2. The method of claim 1, wherein the acquiring operation and maintenance data of at least one video capture device to be detected comprises:

3. The method of claim 2, wherein said determining an operation dimension score for each of said video capture devices to be detected based on an operation dimension of each of said video capture devices to be detected comprises:

acquiring a judgment value range of each monitoring index;

4. A method according to claim 3, wherein after the video capture device to be detected having the operation and maintenance score greater than a preset score threshold is determined to be an abnormal video capture device, the method further comprises:

Calculating the association degree of each abnormal video acquisition device;

and for each abnormal video acquisition device, determining an alarm level of the abnormal video acquisition device based on the association degree of the abnormal video acquisition device and the operation and maintenance score of the abnormal video acquisition device.

5. The method of claim 4, wherein said calculating a degree of association for each of said anomalous video capture devices comprises:

and determining the association degree of the abnormal video acquisition equipment based on the position information of the abnormal video acquisition equipment, the shooting angle of the abnormal video acquisition equipment and the overlapped shooting angle.

6. The method of claim 4, wherein for each of the anomalous video capture devices, determining an alert level for the anomalous video capture device based on a degree of association of the anomalous video capture device and an operation-to-maintenance score of the anomalous video capture device comprises:

and determining the alarm grade of the abnormal video acquisition equipment based on the weighted average value.

7. The method of claim 6, wherein the alert levels include a level one, a level two, and a level three, the alert level of the level one being higher than the alert level of the level two, the alert level of the level two being higher than the alert level of the level three, wherein:

when the weighted average value is at a first threshold value, determining the alarm grade as the grade one;

when the weighted average value is at a second threshold value, determining that the alarm grade is the grade two;

and when the weighted average value is at a third threshold value, determining that the alarm grade is the grade three.

8. The method of claim 7, wherein prior to said calculating the relevance of each of the anomalous video capture devices, the method further comprises:

and if the preset angle of the abnormal video acquisition equipment changes, determining that the alarm grade of the abnormal video acquisition equipment is the grade I.

9. The method of claim 8, wherein determining whether the preset angle of the abnormal video acquisition device has changed is performed by:

acquiring a shooting image shot by the abnormal video acquisition equipment;

10. The method according to claim 4, wherein the method further comprises:

11. The method of claim 10, wherein the generating a repair order for the anomalous video capture device based on the alert level for each anomalous video capture device comprises:

and sequencing the abnormal video acquisition equipment to be maintained based on the influence factors of each abnormal type and the alarm level of each abnormal video acquisition equipment to obtain the maintenance work order.

12. The method according to claim 11, wherein the history maintenance record includes an abnormality detection type and an abnormality maintenance type each time the history abnormality video capture device is maintained, the abnormality detection type being an abnormality type predicted from the determination value, the abnormality maintenance type being an abnormality type determined at the time of maintenance, and the determining the influence factor of each abnormality type from the history maintenance record includes:

determining the confidence of each anomaly type according to the anomaly detection type and the anomaly maintenance type;

and determining an influence factor of each anomaly type based on the confidence coefficient of each anomaly type and a preset anomaly type weight.

13. The method of claim 10, wherein the ranking each of the abnormal video capture devices based on the impact factors of each of the abnormal types and the alert level of each of the abnormal video capture devices to obtain the repair order comprises:

sequencing each abnormal video acquisition device based on the alarm level of each abnormal video acquisition device to obtain a sequencing result, wherein the abnormal video acquisition device with the high alarm level in the sequencing result is prior;

And correcting the sequencing result by using the influence factors of each abnormal type, so that the abnormal video acquisition equipment with high influence factor value is in front of the abnormal video acquisition equipment with the same alarm level.

14. A detection apparatus for a video acquisition device, the apparatus comprising:

and the determining unit is used for determining the video acquisition equipment to be detected, of which the operation and maintenance score is larger than a preset score threshold value, as abnormal video acquisition equipment.

15. The apparatus according to claim 14, wherein the acquisition unit is specifically configured to:

16. The apparatus according to claim 15, wherein the scoring unit is specifically configured to:

acquiring a judgment value range of each monitoring index;

17. The apparatus of claim 16, further comprising a processing unit to:

calculating the association degree of each abnormal video acquisition device;

18. The apparatus according to claim 17, wherein the processing unit is further specifically configured to:

19. The apparatus according to claim 17, wherein the processing unit is further specifically configured to:

20. The apparatus of claim 19, wherein the alert levels include a level one, a level two and a level three, the alert level of the level one being higher than the alert level of the level two, the alert level of the level two being higher than the alert level of the level three, the processing unit being further operable to:

21. The apparatus of claim 20, wherein the processing unit is further configured to:

22. The apparatus of claim 21, wherein the processing unit is further specifically configured to determine whether the preset angle of the abnormal video acquisition device is changed by:

Acquiring a shooting image shot by the abnormal video acquisition equipment;

23. The apparatus of claim 17, wherein the processing unit is further configured to:

24. The apparatus according to claim 23, wherein the processing unit is further specifically configured to:

25. The apparatus according to claim 24, wherein the history maintenance record includes an abnormality detection type and an abnormality maintenance type each time the history abnormal video capturing device is maintained, the abnormality detection type being an abnormality type predicted according to the determination value, the abnormality maintenance type being an abnormality type determined at the time of maintenance, the processing unit being specifically configured to:

26. The apparatus according to claim 23, wherein the processing unit is specifically configured to:

27. An electronic device, comprising:

a memory;

a processor; and

a computer program;

wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of detection of a video capture device according to any of claims 1 to 13.

28. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement a method of detecting a video capture device according to any of claims 1-13.