CN111065044B - Big data based data association analysis method and device and computer storage medium - Google Patents
Big data based data association analysis method and device and computer storage medium Download PDFInfo
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Abstract
The invention provides a data association analysis method and device based on big data, which are applied to the technical field of data association analysis of the big data, and the method comprises the following steps: acquiring geographical position information of a portrait in each video frame image and portrait identification information thereof based on face snapshot equipment; capturing mobile terminal data and geographical position information thereof connected with each WIFI probe device based on the WIFI probe devices; determining whether the portrait and the mobile terminal are in the same place for snapshot behavior according to the geographic position information of the portrait snapshot device and the geographic position information of the target WIFI probe device; and determining whether the portrait is associated with the mobile terminal or not based on the number of times the portrait and the mobile terminal are simultaneously snapped in different places. And a computer storage medium is provided, which analyzes the multi-dimensional motion trail through big data analysis collision, and further excavates the basis of the scheme and clues for solving the scheme.
Description
Technical Field
The invention relates to the technical field of big data association analysis processing, in particular to a big data-based data association analysis method and device and a computer storage medium.
Background
With the rapid increase of traffic flow and people flow, the construction of vehicle bayonets, human face bayonets and WIFI probes is increasing day by day, and huge vehicle, human face snapshot and WIFI probe data can be generated every day.
A large amount of traffic flow, people flow and WIFI probe data are put into a database to form big data, so that the corresponding vehicles or people are associated with the mobile terminal under the induction of the WIFI probe in an effective analysis mode, and analysis of complex cases is facilitated. However, in the prior art, since people cannot be associated with corresponding devices, such as mobile devices, or personal information cannot be completely and correctly identified by face capture, data cannot be associated, massive data cannot be effectively processed, and the purpose of associating data with different dimensions is achieved.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a data association analysis method and device based on big data and a computer storage medium, and aims to solve the problem that the mobile terminal cannot be associated with people through big data analysis in the prior art through association of the people and the mobile terminal of WIFI, and meanwhile, vehicles and mobile equipment carried with the vehicles can be associated.
The invention is realized by the following steps:
the embodiment of the invention discloses a data association analysis method based on big data, which comprises the following steps:
acquiring geographical position information of a portrait in each video frame image and portrait identification information thereof based on face snapshot equipment;
capturing mobile terminal data and geographical position information thereof connected with each WIFI probe device based on the WIFI probe devices;
determining whether the portrait and the mobile terminal are in the same place for snapshot behavior according to the geographic position information of the portrait snapshot device and the geographic position information of the target WIFI probe device;
and determining whether the portrait is associated with the mobile terminal or not based on the number of times the portrait and the mobile terminal are simultaneously snapped in different places.
Further, the step of acquiring the geographical location information of the portrait in each video frame image and the portrait identification information thereof based on the face snapshot device includes:
and acquiring longitude and latitude information and portrait identification information of the portrait in each video frame image according to the geographic position of the face snapshot device.
Further, based on the WIFI probe equipment, the step of obtaining the mobile terminal data and the geographical position information thereof connected with each WIFI probe equipment comprises the following steps:
and acquiring data and geographical position information of each mobile terminal connected with the WIFI probe equipment according to the geographical position of the WIFI probe equipment.
Further, the step of determining whether the portrait and the mobile terminal are the snapshot behavior of the same place according to the geographic position information of the portrait snapshot device and the geographic position information of the target WIFI probe device includes:
calculating the corresponding distance of the face snapshot equipment according to the geographic position information of the face snapshot equipment and the geographic position information of the WIFI probe equipment;
and determining the snapshot behavior that the portrait and the mobile terminal are in the same place under the condition that the distance is not less than the preset distance threshold.
Further, the step of determining whether the portrait is associated with the mobile terminal based on the number of times the portrait and the mobile terminal are simultaneously snapped in different places includes:
acquiring the times that the portrait and the mobile terminal have the same place snapshot behavior;
judging whether the acquired times are not less than preset times;
if so, determining that the mobile terminal is associated with the portrait.
Further, the method further comprises:
for any mobile terminal, determining the time and place of the last capture of the mobile terminal by the WIFI probe equipment;
determining whether there is a history of the mobile terminal being captured at the location;
if yes, the occurrence number of the mobile terminal is increased once, and the latest place is updated to the last captured place.
In addition, the invention also discloses a data association analysis device based on big data, which comprises a processor and a memory connected with the processor through a communication bus; wherein the content of the first and second substances,
the memory is used for storing a data association analysis program based on big data;
the processor is configured to execute the big data based data association analysis program to implement any one of the steps of the big data based data association analysis method.
Also, a computer storage medium is disclosed that stores one or more programs executable by one or more processors to cause the one or more processors to perform the steps of any of the big data based data correlation analysis methods.
By applying the big data-based data association analysis method, the big data-based data association analysis device and the computer storage medium, firstly, the geographical position information of the portrait and the human appearance feature information in the captured video image are obtained through the face capture device, and then the mobile terminal data and the geographical position information connected with each WIFI probe device are captured through the device identification of the WIFI probe device; then determining whether the portrait and the mobile terminal are in the same place for snapshot behavior according to the geographical position information of the portrait snapshot device and the geographical position information of the target WIFI probe device; and then determining whether the portrait has association with the mobile terminal or not according to the snapshot morphemes of different places. Therefore, the fact that the portrait and the mobile terminal are simultaneously present near the WIFI probe device is indicated by the snapshot behavior of the geographical position information of the portrait and the geographical position information of the WIFI probe device in the video frame image in the same place is determined, when the snapshot behavior that the portrait and the mobile terminal belong to the same place is determined for multiple times by taking other WIFI probe devices as main bodies, the fact that the portrait and the mobile terminal are simultaneously present near the WIFI probe devices for multiple times is indicated, the fact that the mobile terminal is the handheld device of the portrait is determined, and therefore correlation is conducted. The problem that the mobile terminal and a person cannot be associated through big data analysis in the prior art is solved.
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 schematic flow chart of a big data-based data association analysis method according to an embodiment of the present invention;
fig. 2 is a schematic view of an application scenario of the data association analysis apparatus based on big data according to the 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, an embodiment of the present invention provides a data association analysis method based on big data, including the following steps:
s101, acquiring geographical position information of the portrait in each video frame image and portrait identification information thereof based on face snapshot equipment.
It can be understood that, because the face capturing device is usually fixedly arranged at a position, the obvious reference objects in the surrounding images acquired by the face capturing device are also fixed, for example, buildings are taken as reference objects, and then the longitude and latitude of the buildings can be obtained. Because the proportion of the objects on the photo is the same, the distance between the task corresponding to the portrait and the reference object can be converted according to the distance between the portrait and the reference object on the photo, and the direction between the portrait and the reference object can be obtained from the image, so the actual longitude and latitude of the person corresponding to the portrait can be obtained according to the direction, the distance and the longitude and latitude of the reference object.
Illustratively, the latitude and longitude of the reference object is: north latitude N22 ° 31 '40.86 ", east longitude E114 ° 03' 10.40", sequentially as an origin, and a distance as a radius, and drawing a circle, which is taken as a final determined target point on the circumference according to the direction, where the target point is the point where the portrait is located, so that the longitude and latitude corresponding to the target point can be obtained, the calculation process is the prior art, and details are not repeated in the embodiments of the present invention.
In addition, basic appearance feature information of the portrait, such as height, gender and other appearance features, such as hair length, clothes features and the like, can be obtained according to the portrait on the image. Specifically, the ID of the person may be established, and the appearance feature information may be used as information corresponding to the ID to form a one-to-one correspondence relationship between the person ID and the feature information.
And S102, capturing mobile terminal data and geographical position information thereof connected with each WIFI probe device based on the WIFI probe devices.
It will be appreciated that each WIFI probe device has its corresponding device representation, such as a device ID, and thus, in the big data, each WIFI probe device may be obtained by extracting each device ID, as shown in table 1.
TABLE 1
In the embodiment of the invention, the big data can be stored in KAFKA, and each WIFI probe device can capture the mobile terminal connected with the WIFI probe device, and particularly represents different mobile terminals through the MAC address of the mobile terminal and the time for connecting the mobile terminal. And the position of the WIFI probe device is often fixed, so a connection location can be obtained, so that the mobile terminal within the radiation range can be connected with the WIFI probe device, so that the connection time of the mobile terminal connected with the WIFI probe device can be captured, for example, when the mobile terminal is captured and disconnected from the mobile terminal, as shown in table 2, the corresponding address of the WIFI probe device is also included.
It can be understood that, with the WIFI probe device as the main body, the mobile terminal and the connection information connected thereto can be obtained, and then with this as the premise, with the mobile terminal as the main body, the WIFI probe device corresponding to the mobile terminal and the connection time with each WIFI probe device can be obtained. It can be understood that the mobile terminal is connected with the WIFI probe device, the WIFI probe device captures the MAC address of the mobile terminal, and one mobile terminal corresponds to one MAC address, so that the mobile terminal is represented by the MAC address in the big data. Data search is performed through the MAC address of the mobile terminal, and at least the WIFI probe device connected correspondingly, connection start time and disconnection time can be obtained, as shown in table 2 below.
TABLE 2
It can be understood that, according to the connection time of the mobile terminal and the WIFI probe device, if surrounding images are obtained within this time range, it is possible to find a target person holding the mobile terminal.
It can be understood that the WIFI probe device with the radiation range including the point can be obtained according to the longitude and latitude where the portrait is located. It will be appreciated that the mobile terminal held by the portrait may only be captured if the WIFI probe device is able to radiate to the point.
Therefore, the radiation distance of the WIFI probe equipment is used as the radius, the obtained geographic position is used as the center of a circle to draw a circle, and the WIFI probe equipment contained in the circle is determined to be target WIFI probe equipment.
It will be appreciated that the target WIFI probe device may be absent, or one WIFI probe device, or two or more WIFI probe devices, depending on the distance and radiation range over which the WIFI probe devices are disposed.
S103, determining whether the portrait and the mobile terminal are in the same place for snapshot behavior according to the geographic position information of the portrait snapshot device and the geographic position information of the target WIFI probe device.
Specifically, longitude and latitude information of WIFI probe equipment corresponding to target WIFI probe equipment is obtained; determining longitude and latitude information of portrait snapshot equipment in the video frame image; acquiring longitude and latitude information of the WIFI probe equipment and a distance corresponding to the longitude and latitude information of the portrait capturing equipment; and under the condition that the distance is not smaller than a preset distance threshold value, determining that the portrait and the first mobile terminal are in the same place.
The embodiment of the invention specifically calculates the distance between a person and the WIFI probe equipment, and exemplarily judges whether the distance is smaller than 100m or not, and if the distance is smaller than 100m, the person is regarded as the snapshot behavior of the same snapshot point. And then checking the next WIFI probe device to confirm whether the mobile terminal is captured, if so, continuing to execute the following steps, and confirming whether the portrait and the mobile terminal are the same snapshot behavior of the same snapshot point.
And S104, determining whether the portrait is associated with the mobile terminal or not based on the number of times that the portrait and the mobile terminal are simultaneously snapped in different places.
If the person and the WIFI probe device are captured for multiple times by different capturing points, illustratively, the number of the capturing points is not less than three, the person and the WIFI probe device are considered to be the behavior of the same person holding the mobile terminal, and then an association relation table of the task and the mobile terminal can be generated; if the number is more than 100m, the calculation of the association relationship is abandoned.
Therefore, the track of the person can be obtained through the track of the mobile terminal, the track of the person is associated with the track of the person through the track of the mobile terminal, and then the association is carried out through the MAC of the mobile terminal in the WIFI probe equipment table.
In the specific embodiment of the invention, the method also comprises MAC filing, namely acquiring WIFI structural data in real time, extracting MAC and basic information, filing for the MAC (the MAC is unique), and updating the existing data fields such as the latest occurrence time and place.
Specifically, data can be obtained from KAFKA in real time; filtering out MAC of the mobile terminal and bound basic information such as QQ number, micro signal, micro blog number and the like from the data received by KAFKA; whether an MAC file exists is inquired through the MAC of the mobile terminal, if yes, the MAC file exists according to the obtained MAC recent appearance time and the recent appearance place, then the statistical information of the MAC is obtained, the statistical information comprises 10 places with the most active MAC and the time and the frequency corresponding to the places, and if the statistical information comprises the place where the MAC appears, the time and the frequency corresponding to the place are updated. Example (c): the MAC is 'AABB', the latest appearing time of the MAC at the place a is 2019-08-0112:00:00, the frequency is 10, the MAC received this time is 'AABB', the place is also a, but the time is 2019-08-0215:30:00, the latest time needs to be updated to be 2019-08-0215:30:00, and the frequency is added by 1 to be 11. If the MAC address does not exist, the basic information of the MAC is directly extracted for filing, and specifically, the basic information is information such as connection time, appearance place and the like of the MAC of the mobile terminal.
It can be understood that partial statistical information in the MAC file can be completed offline, such as calculating 10 locations, times and times with the highest frequency of occurrence of MAC in the last month; the frequency of occurrence of the MAC is calculated (points 0-6, 6-12, 12-18, 18-24) and updated into the MAC file.
The embodiment of the invention also comprises the steps of associating the vehicle with the mobile terminal, for example, obtaining the connection information of the terminal through the steps S101-S103, obtaining the video frame image of the face snapshot device according to the connection information, and then obtaining the geographic position information of the vehicle in each video frame image; determining corresponding WIFI probe equipment based on the acquired vehicle geographic position information; determining whether the vehicle and a second mobile terminal are snap-shot behaviors of the same place or not according to the determined geographic position information of the WIFI probe device and the acquired geographic position information of the vehicle, wherein the second mobile terminal is any one mobile terminal; and determining whether the second mobile terminal is associated with the vehicle or not based on the number of times the vehicle and the second mobile terminal have the same-place snapshot behavior.
The process is similar to the snapshot behavior of confirming whether the person and the mobile terminal are at the same snapshot point, and only the processing of the person is used as the processing of the vehicle, so that the association between the vehicle and the mobile terminal is obtained.
Specifically, the number of times of determining whether the vehicle and the mobile terminal are in the same place for capturing behaviors and the determination method of whether the vehicle and the mobile terminal are associated are the same as the above-mentioned manner of processing the vehicle and the mobile terminal, and the details of the embodiment of the present invention are not repeated herein.
The invention can provide better data support for positioning the information of people or vehicles, can more accurately position the behavior track of people, and improves the working efficiency of public security policemen.
In addition, the system is based on a big data distributed computing and storing frame, can analyze, process and store massive pedestrian tracks, vehicle data and WIFi probe data, can ensure high availability, and is more efficient and stable than the traditional application system.
In addition, as shown in fig. 2, the present invention also discloses a big data based data association analysis apparatus 200, wherein the apparatus 200 includes a processor 210, and a memory 220 connected to the processor 210 via a communication bus 230; wherein the content of the first and second substances,
the memory 220 is used for storing a data association analysis program based on big data;
the processor 210 is configured to execute the big data based data association analysis program to implement any of the steps of the big data based data association analysis method.
And a computer storage medium storing one or more programs executable by one or more processors 210 as shown in fig. 2 to cause the one or more processors 210 to perform any of the steps of the big data based data correlation analysis method is disclosed.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (5)
1. A big data-based data association analysis method is characterized by comprising the following steps:
acquiring geographical position information of a portrait in each video frame image and portrait identification information thereof based on face snapshot equipment; the step of acquiring the geographical position information of the portrait in each video frame image and the portrait identification information thereof based on the face snapshot device comprises the following steps:
acquiring longitude and latitude information and portrait identification information of a portrait in each video frame image according to the geographic position of the face snapshot device;
based on the WIFI probe equipment, acquiring mobile terminal data and geographical position information thereof connected with each WIFI probe equipment; based on WIFI probe equipment, the step of obtaining mobile terminal data and geographical position information thereof connected with each WIFI probe equipment includes:
acquiring data and geographical position information of each mobile terminal connected with the WIFI probe equipment according to the geographical position of the WIFI probe equipment;
determining whether the portrait and the mobile terminal are in the same place for snapshot behavior according to the geographic position information of the portrait snapshot device and the geographic position information of the target WIFI probe device; the step of determining whether the portrait and the mobile terminal are the snapshot behavior of the same place or not according to the geographic position information of the portrait snapshot device and the geographic position information of the target WIFI probe device comprises the following steps:
calculating the corresponding distance of the face snapshot equipment according to the geographic position information of the face snapshot equipment and the geographic position information of the WIFI probe equipment;
determining the snapshot behavior that the portrait and the mobile terminal are in the same place under the condition that the distance is not smaller than a preset distance threshold;
and determining whether the portrait is associated with the mobile terminal or not based on the number of times the portrait and the mobile terminal are simultaneously snapped in different places.
2. The big data-based data association analysis method according to claim 1, wherein the step of determining whether the portrait is associated with the mobile terminal based on the number of times the portrait and the mobile terminal are simultaneously snapped at different locations comprises:
acquiring the times that the portrait and the mobile terminal have the same place snapshot behavior;
judging whether the acquired times are not less than preset times;
if so, determining that the mobile terminal is associated with the portrait.
3. The big-data-based data association analysis method of claim 2, wherein the method further comprises:
for any mobile terminal, determining the time and place of the last capture of the mobile terminal by the WIFI probe equipment;
determining whether there is a history of the mobile terminal being captured at the location;
if yes, the occurrence number of the mobile terminal is increased once, and the latest place is updated to the last captured place.
4. A big data-based data association analysis apparatus, comprising a processor, and a memory connected to the processor through a communication bus; wherein the content of the first and second substances,
the memory is used for storing a data association analysis program based on big data;
the processor is configured to execute the big data based data association analysis program to implement the steps of the big data based data association analysis method according to any one of claims 1 to 3.
5. A computer storage medium storing one or more programs, the one or more programs being executable by one or more processors to cause the one or more processors to perform the steps of the big data based data correlation analysis method as claimed in any one of claims 1 to 3.
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| CN112637548B (en) * | 2020-11-12 | 2023-11-24 | 佳都科技集团股份有限公司 | Information association early warning method and device based on camera |
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| US9380411B2 (en) * | 2012-06-21 | 2016-06-28 | Broadcom Corporation | Proximity detection |
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| CN106874347A (en) * | 2016-12-26 | 2017-06-20 | 深圳市深网视界科技有限公司 | A kind of method and system for matching characteristics of human body and MAC Address |
| CN106934773A (en) * | 2017-03-03 | 2017-07-07 | 中国民航大学 | Video frequency motion target and Mac addresses matching process |
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