CN112689131B - Gridding-based moving target monitoring method and device and related equipment - Google Patents
Gridding-based moving target monitoring method and device and related equipment Download PDFInfo
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Abstract
The embodiment of the invention provides a grid-based moving target monitoring method, which comprises the following steps: acquiring each piece of snapshot data in a preset area in a current preset time period, wherein the snapshot data comprises archive information, snapshot place information and snapshot time information of the moving target, and the preset area comprises a plurality of grid areas; counting the sum of all moving targets of each grid area in the current preset time period according to all the snapshot data; and performing difference calculation according to the sum of all the activity targets of each grid area in the current preset time period and the sum of all the activity targets in the grid area in the previous preset time period to obtain the number of the newly added activity targets of each grid area in the preset time period. Compared with the existing monitoring mode, the method has the advantages that the grid personnel are not required to be registered at the door, the monitoring efficiency is higher, the manpower and the material resources are saved, and meanwhile, the method can also be used for monitoring except personnel, such as monitoring of vehicles.
Description
Technical Field
The invention relates to the technical field of security and protection, in particular to a grid-based moving target monitoring method and device and related equipment.
Background
A large number of floating population with separated people is generated in the urbanization process of China, and how to manage and service the floating population becomes an important problem in the current social management. With the speed increase of the urbanization process and the formation of a large traffic pattern, the suburban and rural suburb steps are obviously accelerated, so that the population flow is increased, the flow rate is accelerated, the number of flow layers is increased, and the original population management mode cannot adapt to the requirements of social and economic development and public security management.
Along with the practical and rapid spreading of the smart city security system, the population number of the city is increased day by day, the difficulty of public security monitoring is improved along with the increase of the population, and the condition of active personnel appearing in each grid can be monitored only through the registration of grid personnel in the prior art. Therefore, the efficiency is very low, and the data statistics cannot be realized in a short period, so that the monitoring requirement is difficult to achieve.
Disclosure of Invention
The embodiment of the invention provides a grid-based moving target monitoring method, which can improve the efficiency of monitoring urban population.
In a first aspect, an embodiment of the present invention provides a grid-based active target monitoring method, including the following steps:
acquiring each piece of snapshot data in a preset area in a current preset time period, wherein the snapshot data comprises archive information, snapshot place information and snapshot time information of the moving target, and the preset area comprises a plurality of grid areas;
counting the sum of all moving targets of each grid area in the current preset time period according to all the snapshot data;
and performing difference calculation according to the sum of all the activity targets of each grid area in the current preset time period and the sum of all the activity targets in the grid area in the previous preset time period to obtain the number of the newly added activity targets of each grid area in the preset time period.
Preferably, the step of counting the total of all activity targets of each grid region in the current preset time period according to all the snapshot data includes:
establishing activity data based on each activity target according to the snapshot data, wherein the rule for establishing the activity data is one activity data for each activity target in each grid area in each current preset time period;
and counting all the activity data of each grid area to obtain the sum of all the activity targets of the grid area.
Preferably, the step of establishing activity data based on each activity target according to the snapshot data, where the rule of establishing the activity data is that one activity data is provided for each activity target in each grid area in each current preset time period, includes:
judging the occurrence frequency of the moving target in each grid area according to all corresponding snapshot data in the grid area;
and updating the activity data corresponding to the activity target according to the occurrence times.
Preferably, the method further comprises the steps of:
judging whether the occurrence frequency of the activity target is greater than a preset frequency or not according to the activity data;
and if the occurrence frequency of the activity target is greater than the preset frequency, recording the activity target according to a first recording rule.
Preferably, the method further comprises the steps of:
judging whether the movable target is a resident target of the grid area to which the movable target belongs or not according to the file information and the snapshot place information;
if the activity target is a resident target, recording according to a second recording rule;
and if the active target is the non-stationary target, recording according to a third recording rule.
Preferably, the step of acquiring each piece of snapshot data in the current preset time period further includes the steps of:
acquiring a snapshot image of a moving target through a camera within a preset time period;
acquiring snapshot data of the moving target according to the snapshot image and storing the snapshot data in a full-text search engine;
in the step of obtaining each piece of snapshot data in a preset time period, obtaining each piece of snapshot data is obtained from the full-text search engine.
Preferably, the step of acquiring the snapshot data of the moving object according to the snapshot image includes:
carrying out face recognition according to the snap-shot image and acquiring archive information of a moving target corresponding to the snap-shot image;
acquiring snapshot place information according to the position of the camera acquiring the snapshot image; and
and acquiring snapshot time information according to the snapshot image.
In a second aspect, an embodiment of the present invention further provides a grid-based active object monitoring apparatus, where the apparatus includes:
the snapshot data acquisition module is used for acquiring each piece of snapshot data in a preset area in a current preset time period, wherein the snapshot data comprises file information, snapshot place information and snapshot time information of the moving target, and the preset area comprises a plurality of grid areas;
the moving target counting module is used for counting the sum of all moving targets of each grid area in the current preset time period according to all the snapshot data;
and the newly added target counting module is used for performing difference calculation according to the sum of all the active targets of each grid area in the current preset time period and the sum of all the active targets in the grid area in the previous preset time period to obtain the number of the newly added active targets of each grid area in the preset time period.
In a third aspect, an embodiment of the present invention further provides an electronic device, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in the activity goal monitoring method according to any one of the embodiments of the present invention when executing the computer program.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the activity target monitoring method according to any one of the embodiments of the present invention.
In the embodiment of the invention, a monitoring area (a preset area) is divided into a plurality of grid areas, a camera is used for capturing the moving target of each grid area, capturing data aiming at the moving target can be obtained based on a captured image, the sum of the moving targets appearing in each grid area in the current preset time period can be calculated based on the capturing data by obtaining the capturing data, and then difference calculation can be carried out according to the sum of all the moving targets in the grid area in the current preset time period and the last preset time period, so that the number of the newly added moving targets in each grid area is obtained. And monitoring the moving target of each grid area in the preset area. Compared with the existing monitoring mode, the method has the advantages that the grid personnel is not required to be registered at the door, the monitoring efficiency is higher, the manpower and the material resources are saved, and meanwhile, the method can also be used for monitoring other than personnel, such as the monitoring of vehicles.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flowchart of a grid-based active object monitoring method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a grid-based people/vehicle monitoring method provided by an embodiment of the invention;
FIG. 3 is a flow chart of a snapshot data storage manner provided by an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a grid-based active object monitoring apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart of a monitoring method for an activity target based on grid according to an embodiment of the present invention, as shown in fig. 1, the monitoring method for an activity target based on grid includes the following steps:
101. each piece of snapshot data in a preset area in the current preset time period is obtained, wherein the snapshot data comprise archive information, snapshot place information and snapshot time information of the moving target, and the preset area comprises a plurality of grid areas.
In the embodiment of the present invention, as shown in fig. 2, the process of acquiring each piece of snapshot data in the current preset time period is sequentially acquired, and each time one piece of snapshot data is acquired, it is determined whether the piece of snapshot data is the last piece, and if not, the next piece of snapshot data continues to be acquired until all pieces of snapshot data are acquired. The moving target can be a human or a vehicle, and of course, can also be a specific animal, such as a wandering animal and the like. The preset area may include a plurality of grid areas, for example, the preset area may be a city, and the corresponding grid area may be divided into a plurality of blocks according to the division of the roads on the map, and of course, the preset area may also be a partial area of the city. The snapshot data are obtained by shooting through the camera arranged at a specific position in each grid area in the preset area, then the snapshot image is further processed, for example, if the face characteristics of the active personnel can be identified in the face recognition process, corresponding file information can be inquired in a file information system according to the face characteristics, the snapshot place information can be obtained through the serial number or the mark of the camera, and the snapshot time information can be obtained through the generation time of the snapshot image. Taking a vehicle as an example, the archive information of the vehicle can be identified through license plate number identification, the snapshot location information can be obtained through the serial number or mark of the camera, and the snapshot time information can be obtained through the generation time of the snapshot image. As shown in fig. 2, the present embodiment takes a person and a vehicle as examples to explain the overall process of the monitoring method of the present invention.
In this embodiment, the snapshot data may be stored in the full-text search engine server, and written into the full-text search engine server after the camera takes the snapshot image of the moving target.
In this embodiment, the current preset time period may be a day or a custom time interval, and the current preset time period is a time period in which snapshot data needs to be acquired currently.
102. And counting the total sum of all the moving targets of each grid area in the current preset time period according to all the snapshot data.
In the embodiment of the present invention, the sum of all the active targets in each grid region in the current preset time period is counted based on the number of the active targets acquired by the snapshot data.
It should be noted that when an active object moves from one grid area to another grid area, both grid areas will log the active object into the summary data of the active object.
103. And performing difference calculation according to the sum of all the activity targets of each grid area in the current preset time period and the sum of all the activity targets in the grid area in the previous preset time period to obtain the number of the newly added activity targets of each grid area in the preset time period.
In the embodiment of the present invention, the current preset time period and the previous preset time period are two adjacent time periods, and the time intervals of the two time periods are the same in length. The above-mentioned difference calculation is performed on the sum of all the moving targets of each grid area and the sum of all the moving targets in the grid area in the previous preset time period, so as to obtain the newly increased number of the moving targets in two time intervals. For example, as shown in fig. 2, a preset time period is 1 day, the total of the activity targets of the current preset time period is the total of the activity targets of the current day, the total of the activity targets of the previous preset time period is the total of the activity targets of yesterday, and the number of the newly added activity targets of the current day can be obtained by subtracting the total of the activity targets of the current day and the total of the activity targets of the previous day.
104. Further, as an optional implementation, the method further includes the steps of: and outputting the statistical result to a visual interface.
Specifically, if the statistical result is output to the display screen of the monitoring background, the manager can visually know the number of the newly added activity targets in each grid area through the display screen.
In this embodiment, the step 102 further includes:
1021. establishing activity data based on each activity target according to the snapshot data, wherein the rule for establishing the activity data is one activity data for each activity target in each grid area in each current preset time period;
1022. and counting all the activity data of each grid area to obtain the sum of all the activity targets of the grid area.
Specifically, each activity target corresponds to one piece of activity data in one grid area, that is, only one piece of activity data exists in one grid area. When the activity target is active in other grid areas, the activity target also correspondingly has an activity data corresponding to the other grid areas.
Further, in step 1021, establishing an activity data mode based on each of the activity targets includes:
10211. judging the occurrence frequency of the moving target in each grid area according to all corresponding snapshot data in the grid area;
10212. and updating the activity data corresponding to the activity target according to the occurrence times.
Specifically, each activity target corresponds to only one piece of activity data in one grid area, and when the activity target is captured for multiple times in the grid area, new activity data is not established, but the capturing times are updated into the activity data, that is, the activity data includes the capturing times of the activity target in the grid area. As shown in fig. 2, when the number of occurrences of the person or the vehicle increases once, the records in the activity data are accumulated 1 time.
Further, in this embodiment, the method further includes the steps of:
1023. judging whether the occurrence frequency of the activity target is greater than a preset frequency or not according to the activity data;
1024. and if the occurrence frequency of the activity target is greater than the preset frequency, recording the activity target according to a first recording rule.
Specifically, the number of occurrences of the activity target may be determined based on the above-mentioned number of times of capturing, and when the number of occurrences of the activity target is greater than the preset number of times, the activity target is recorded according to a first recording rule, for example, the first recording rule may be "frequent in and out target".
Further, in this embodiment, the method further includes the steps of:
1011. judging whether the movable target is a resident target of the grid area to which the movable target belongs or not according to the file information and the snapshot place information;
1012. if the activity target is a resident target, recording according to a second recording rule;
1013. and if the active target is the non-stationary target, recording according to a third recording rule.
Specifically, the identity of the active target may be identified according to the profile information of the active target, and based on the profile information recorded before the current preset time period, a search is performed in the previously recorded profile information, and if the active target corresponding to the snapshot data cannot be searched in the previously recorded profile information, it is indicated that the active target is a non-resident target, and recording is performed according to a third recording rule, where the third recording rule may be, for example, an "unknown target". If the activity object corresponding to the snapshot data can be retrieved from the previously recorded archive information, and the later activity object is a resident object, recording is performed according to a second recording rule, and the second recording rule may be, for example, a "known object".
Further, as shown in fig. 3, in this embodiment, before step 101, the method further includes the steps of:
0011. acquiring a snapshot image of a moving target through a camera within a preset time period;
0012. and acquiring the snapshot data of the moving target according to the snapshot image and storing the snapshot data in a full-text search engine.
The full-text search engine server is used for providing data storage of the full-text search engine, and is in communication connection with all the cameras to acquire snapshot data.
In this embodiment, in the step of obtaining each piece of snapshot data in a preset time period, obtaining each piece of snapshot data is obtained from the full-text search engine.
The step of acquiring the snapshot data of the moving target according to the snapshot image comprises the following steps:
carrying out face recognition according to the snap-shot image and acquiring archive information of a moving target corresponding to the snap-shot image;
acquiring snapshot place information according to the position of the camera acquiring the snapshot image; and
and acquiring snapshot time information according to the snapshot image.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an activity target monitoring apparatus 200 based on grid-based according to an embodiment of the present invention, the apparatus includes:
the snapshot data obtaining module 210 is configured to obtain each piece of snapshot data in a preset area within a current preset time period, where the snapshot data includes file information, snapshot location information, and snapshot time information of the moving target, and the preset area includes multiple mesh areas;
the moving target counting module 220 is configured to count the total sum of all moving targets in each grid region within the current preset time period according to all the snapshot data;
and the newly added target counting module 230 is configured to perform difference calculation according to the sum of all the activity targets of each grid region in the current preset time period and the sum of all the activity targets in the grid region in the previous preset time period, and obtain the number of the newly added activity targets of each grid region in the preset time period.
Further, the activity goal statistics module 220 includes:
the activity data establishing unit is used for establishing activity data based on each activity target according to the snapshot data, wherein the rule for establishing the activity data is one activity data for each activity target in each grid area in each current preset time period;
and the activity data counting unit is used for counting all the activity data of each grid area to obtain the sum of all the activity targets of the grid area.
Further, the activity data creating unit further includes:
the appearance frequency counting unit is used for judging the appearance frequency of the moving target in each grid area according to all corresponding snapshot data in the grid area;
and an activity data updating unit for updating the activity data corresponding to the activity target according to the occurrence number, specifically, for example, as shown in fig. 2, when the occurrence number of the person or the vehicle increases once, the records in the activity data are accumulated for 1 time.
Further, the apparatus further comprises:
the activity frequency judging unit is used for judging whether the occurrence frequency of the activity target is greater than a preset frequency or not according to the activity data;
and the first marking unit is used for recording the activity target according to a first recording rule if the occurrence frequency of the activity target is greater than the preset frequency.
Further, the apparatus further comprises:
the resident target judging unit is used for judging whether the movable target is a resident target of the grid area to which the movable target belongs according to the file information and the snapshot place information;
the second marking unit is used for recording according to a second recording rule if the activity target is a resident target;
and the third marking unit is used for recording according to a third recording rule if the active target is the non-stationary target.
Further, the apparatus further comprises:
the shooting module is used for acquiring a snapshot image of the moving target through the camera within a preset time period;
and the storage module is used for acquiring the snapshot data of the moving target according to the snapshot image and storing the snapshot data in a full-text search engine.
The full-text search engine server is used for providing data storage of the full-text search engine, and is in communication connection with all the cameras to acquire snapshot data.
In the embodiment of the invention, a monitoring area (a preset area) is divided into a plurality of grid areas, a camera is used for capturing the moving target of each grid area, capturing data aiming at the moving target can be obtained based on a captured image, the sum of the moving targets appearing in each grid area in the current preset time period can be calculated based on the capturing data by obtaining the capturing data, and then difference calculation can be carried out according to the sum of all the moving targets in the grid area in the current preset time period and the last preset time period, so that the number of the newly added moving targets in each grid area is obtained. And monitoring the moving target of each grid area in the preset area. Compared with the existing monitoring mode, the method has the advantages that the grid personnel is not required to be registered at the door, the monitoring efficiency is higher, the manpower and the material resources are saved, and meanwhile, the method can also be used for monitoring other than personnel, such as the monitoring of vehicles.
As shown in fig. 5, an electronic device 800 according to an embodiment of the present invention includes: the memory 802, the processor 801, the network interface 803, and a computer program stored in the memory 802 and capable of running on the processor, where the computer program, when executed by the processor, implements each process of the grid-based activity target monitoring method provided in the embodiments of the present invention, and can achieve the same technical effect, and are not described herein again to avoid repetition.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the grid-based activity target monitoring method provided in the embodiment of the present invention, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.
Claims (10)
1. A moving target monitoring method based on gridding is characterized by comprising the following steps:
acquiring each piece of snapshot data in a preset area in a current preset time period, wherein the snapshot data comprises archive information, snapshot place information and snapshot time information of the moving target, and the preset area comprises a plurality of grid areas;
counting the sum of all moving targets of each grid area in the current preset time period according to all the snapshot data;
performing difference calculation according to the sum of all the activity targets of each grid area in the current preset time period and the sum of all the activity targets in the grid area in the previous preset time period to obtain the number of the newly added activity targets of each grid area in the preset time period;
the step of counting the total sum of all the moving targets of each grid area in the current preset time period according to all the snapshot data comprises:
establishing activity data based on each activity target according to the snapshot data, wherein the rule for establishing the activity data is one activity data for each activity target in each grid area in each current preset time period, and when the activity target moves from the current grid area to other grid areas, one activity data of the other grid areas is generated;
and counting all the activity data of each grid area to obtain the sum of all the activity targets of the grid area.
2. The method for monitoring the activity targets based on the gridding according to the claim 1, wherein the step of establishing the activity data based on each activity target according to the snapshot data, wherein the rule of establishing the activity data comprises the following steps of:
judging the occurrence frequency of the moving target in each grid area according to all corresponding snapshot data in the grid area;
and updating the activity data corresponding to the activity target according to the occurrence times.
3. The grid-based active object monitoring method of claim 2, further comprising the steps of:
judging whether the occurrence frequency of the activity target is greater than a preset frequency or not according to the activity data;
and if the occurrence frequency of the activity target is greater than the preset frequency, recording the activity target according to a first recording rule.
4. The grid-based active object monitoring method of claim 1, further comprising the steps of:
judging whether the movable target is a resident target of the grid area to which the movable target belongs or not according to the file information and the snapshot place information;
if the activity target is a resident target, recording according to a second recording rule;
and if the active target is the non-stationary target, recording according to a third recording rule.
5. The method for monitoring active targets based on gridding according to claim 1, wherein the step of obtaining each piece of snapshot data in a current preset time period further comprises the steps of:
acquiring a snapshot image of a moving target through a camera within a preset time period;
acquiring snapshot data of the moving target according to the snapshot image and storing the snapshot data in a full-text search engine;
in the step of obtaining each piece of snapshot data in a preset time period, obtaining each piece of snapshot data is obtained from the full-text search engine.
6. The method for monitoring moving targets based on gridding according to claim 5, wherein the step of obtaining the snapshot data of the moving target according to the snapshot image comprises:
carrying out face recognition according to the snap-shot image and acquiring archive information of a moving target corresponding to the snap-shot image;
acquiring snapshot place information according to the position of the camera acquiring the snapshot image; and
and acquiring snapshot time information according to the snapshot image.
7. An active object monitoring apparatus based on meshing, the apparatus comprising:
the snapshot data acquisition module is used for acquiring each piece of snapshot data in a preset area in a current preset time period, wherein the snapshot data comprises file information, snapshot place information and snapshot time information of the moving target, and the preset area comprises a plurality of grid areas;
the moving target counting module is used for counting the sum of all moving targets of each grid area in the current preset time period according to all the snapshot data;
the newly added target counting module is used for calculating the difference according to the sum of all the active targets of each grid area in the current preset time period and the sum of all the active targets in the grid area in the previous preset time period, and acquiring the number of the newly added active targets of each grid area in the preset time period;
the activity goal statistics module comprises:
the activity data establishing unit is used for establishing activity data based on each activity target according to the snapshot data, wherein the rule for establishing the activity data is one activity data for each activity target in each grid area in each current preset time period, and when the activity target moves from the current grid area to other grid areas, one activity data of the other grid areas is generated;
and the activity data counting unit is used for counting all the activity data of each grid area to obtain the sum of all the activity targets of the grid area.
8. The grid-based active object monitoring apparatus of claim 7, wherein the active data creating unit further comprises:
the appearance frequency counting unit is used for judging the appearance frequency of the moving target in each grid area according to all corresponding snapshot data in the grid area;
and the activity data updating unit is used for updating the activity data corresponding to the activity target according to the occurrence times.
9. An electronic device, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in the grid-based activity goal monitoring method according to any of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, carries out the steps in the grid-based activity goal monitoring method according to any one of claims 1 to 6.
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