CN112837458A - Personnel supervision method and device based on big data and storage medium - Google Patents
Personnel supervision method and device based on big data and storage medium Download PDFInfo
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- CN112837458A CN112837458A CN202110247209.8A CN202110247209A CN112837458A CN 112837458 A CN112837458 A CN 112837458A CN 202110247209 A CN202110247209 A CN 202110247209A CN 112837458 A CN112837458 A CN 112837458A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/20—Individual registration on entry or exit involving the use of a pass
- G07C9/22—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder
- G07C9/25—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition
- G07C9/257—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition electronically
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
- G06K17/0025—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement consisting of a wireless interrogation device in combination with a device for optically marking the record carrier
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/20—Individual registration on entry or exit involving the use of a pass
- G07C9/27—Individual registration on entry or exit involving the use of a pass with central registration
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Abstract
The invention relates to the technical field, in particular to a personnel supervision method and device based on big data and a storage medium. Acquiring biological characteristic identification information of community visitors; and whether the visiting person is a community person is judged according to the judgment result; if the community is a non-community person, acquiring the information of the relationship between the visiting person and the community where the visiting person appears last time; when the community where the visitor appears last time is judged to be a non-risk area, an access instruction is sent to a community security check terminal, and biological feature identification information and a personnel relation two-dimensional code of the visitor are stored in a database; and when the community where the visitor appears last time is judged to be a dangerous area, sending an early warning instruction to a community security check terminal. The invention can effectively master the personal traceability information of the community commuters so as to judge risks and improve the safety supervision efficiency of the commuters.
Description
Technical Field
The invention relates to the technical field, in particular to a personnel supervision method and device based on big data and a storage medium.
Background
The community is a large group formed by gathering a plurality of social groups or organization members in a certain field and related to each other in life, and is mostly seen in the places of urban resident population. In recent years, with the acceleration of urbanization and the increasing demand of people for high-quality life, community management currently faces a lot of difficulties, the traditional community construction and maintenance and management means are single and extensive, and community managers cannot master information of numerous people in the coming and going. With the development of economy, the urban construction speed is accelerated, so that the population in cities is dense, the number of floating population is increased, the safety management of communities is particularly difficult, and particularly in a special period, such as a period of virus infection epidemic situations, if the effective personal information of each person in the community can not be mastered, the epidemic situations can be further diffused, and the safety threat can be caused to other persons in the community. Therefore, in order to further improve the efficiency of community security management, it is urgently needed to establish an effective supervision means for community commuters.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a personnel supervision method, a personnel supervision device and a storage medium based on big data, and when the personnel supervision device is applied, the personnel traceability information of community commuters can be effectively mastered, so that risk judgment can be conveniently carried out, and the safety supervision efficiency of the commuters can be improved.
In a first aspect, the present invention provides a personnel supervision method based on big data, including:
acquiring biological characteristic identification information of community visitors;
comparing the biological characteristic identification information of the visitor with pre-stored biological characteristic identification information of community personnel, and judging whether the visitor is the community personnel;
when the visitor is judged to be a non-community person, acquiring a person relationship two-dimensional code of the visitor, scanning the person relationship two-dimensional code, and acquiring the person relationship information of the visitor and the community person;
the method comprises the steps that biological characteristic identification information of a visitor is stamped and uploaded to a cloud server;
receiving tracking information of the visitors fed back by the cloud server, and determining a community where the visitors appear recently according to the tracking information of the visitors;
carrying out risk judgment on the communities where the visitors appear last time according to a set risk area division rule;
when the community where the visitor appears last time is judged to be a non-risk area, an access instruction is sent to a community security check terminal, and biological feature identification information and a personnel relation two-dimensional code of the visitor are stored in a database; and when the community where the visitor appears last time is judged to be a dangerous area, sending an early warning instruction to a community security check terminal.
Based on the above invention, whether the visiting person is a community person is judged through big data calculation and comparison by obtaining the biological characteristic identification information of the community visiting person, if not, the personnel relationship between the visiting person and the community person is judged through obtaining the personnel relationship two-dimensional code of the visiting person, and according to the biological characteristic identification information of the visiting person, the community where the visiting person appears last time is determined through big data calculation so as to judge whether the visiting person comes from a risk area, so that corresponding response can be made. By the method, personal traceability information of community commuters can be effectively mastered, so that risk judgment is facilitated, and safety supervision efficiency of the commuters is improved.
In one possible design, the method further includes:
when the visitor is judged to be a community person, an access instruction is sent to the community security check terminal, the biological characteristic identification information of the visitor is stamped, and the biological characteristic identification information is uploaded to the cloud server.
In one possible design, the biometric information includes face image feature information and iris image feature information, and the obtaining biometric information of the community visitor includes:
receiving a face recognition image and an iris recognition image of a visitor sent by a community security check terminal;
extracting the characteristics of the face recognition image and the iris recognition image to obtain the characteristics of the face image and the iris image;
and integrating the facial image characteristics and the iris image characteristics into biological characteristic identification information.
In one possible design, the time stamping the biometric information of the visitor and uploading the biometric information to the cloud server includes:
stamping a time stamp on the biological characteristic identification information of the visitor;
encrypting the biometric feature identification information with the timestamp by using a secret key to obtain an encrypted information packet;
and transmitting the encrypted information packet to a cloud server through a secure encryption channel.
In a second aspect, the present invention provides a personnel supervision method based on big data, including:
acquiring a personnel relationship two-dimensional code, a face recognition image and an iris recognition image of community visitors;
the personnel relation two-dimensional code, the face recognition image and the iris recognition image are transmitted to a management terminal, and an access instruction or an early warning instruction fed back by the management terminal is received;
when an access instruction is received, opening a security inspection access door for releasing; and sending out early warning information when receiving the early warning instruction.
In one possible design, the transmitting the face recognition image and the iris recognition image to the management terminal includes:
carrying out image preprocessing on the face recognition image and the iris recognition image, wherein the preprocessing process comprises image enhancement, image restoration, image coding compression and image segmentation;
packing the preprocessed face recognition image and the preprocessed iris recognition image to obtain an image packet;
and encrypting the image packet by using the key and transmitting the image packet to the management terminal.
In a third aspect, the present invention provides a personnel supervision device based on big data, comprising:
the first acquisition unit is used for acquiring biological characteristic identification information of community visitors;
the comparison unit is used for comparing the biological characteristic identification information of the visitor with the pre-stored biological characteristic identification information of the community personnel and judging whether the visitor is the community personnel or not;
the second acquisition unit is used for acquiring the personnel relationship two-dimensional code of the visitor when the visitor is judged to be a non-community person, scanning the personnel relationship two-dimensional code and acquiring personnel relationship information of the visitor and community personnel;
the transmission unit is used for stamping a time stamp on the biological characteristic identification information of the visitor, uploading the biological characteristic identification information to the cloud server, and receiving the visitor tracking information fed back by the cloud server;
the determining unit is used for determining the community where the visitor appears last time according to the tracking information of the visitor;
the judgment unit is used for carrying out risk judgment on the communities where the visitors appear recently according to the set risk area division rule;
the feedback unit is used for sending an access instruction to the community security check terminal when the community where the visitor appears last time is judged to be a non-risk area, and storing biological characteristic identification information and a personnel relation two-dimensional code of the visitor into a database; and when the community where the visitor appears last time is judged to be a dangerous area, sending an early warning instruction to a community security check terminal.
In a fourth aspect, the present invention provides a personnel supervision device based on big data, including:
the acquisition unit is used for acquiring the personnel relationship two-dimensional code, the face recognition image and the iris recognition image of the community visitor;
the receiving and sending unit is used for transmitting the personnel relationship two-dimensional code, the face recognition image and the iris recognition image to the management terminal and receiving an access instruction or an early warning instruction fed back by the management terminal;
the execution unit is used for opening the security inspection channel door for releasing when the access instruction is received; and sending out early warning information when receiving the early warning instruction.
In a fifth aspect, the present invention provides a big data based personnel supervision apparatus, the apparatus comprising:
a memory to store instructions;
a processor configured to read the instructions stored in the memory and execute the method of any of the first aspects according to the instructions.
In a sixth aspect, the present invention provides a computer-readable storage medium having stored thereon instructions which, when run on a computer, cause the computer to perform the method of any of the above first aspects.
In a seventh aspect, the present invention provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of any of the first aspects above.
The invention has the beneficial effects that:
according to the invention, biological characteristic identification information of community visitors is obtained, whether the visitors are community persons is judged through big data calculation and comparison, if the visitors are not community persons, the relationship between the visitors and the community persons is judged through obtaining a person relationship two-dimensional code of the visitors, and according to the biological characteristic identification information of the visitors, the communities where the visitors appear recently are determined through big data calculation, so that whether the visitors come from a risk area is judged, and corresponding response is made. By the method, personal traceability information of community commuters can be effectively mastered, so that risk judgment is facilitated, and safety supervision efficiency of the commuters is improved.
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 diagram of the process of the present invention;
FIG. 2 is a schematic structural diagram of a first apparatus according to the present invention;
FIG. 3 is a schematic structural diagram of a first apparatus according to the present invention;
fig. 4 is a schematic structural diagram of a computer device.
Detailed Description
The invention is further described with reference to the following figures and specific embodiments. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. Specific structural and functional details disclosed herein are merely illustrative of example embodiments of the invention. This invention may, however, be embodied in many alternate forms and should not be construed as limited to the embodiments set forth herein.
It should be understood that the terms first, second, etc. are used merely for distinguishing between descriptions and are not intended to indicate or imply relative importance. Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments of the present invention.
It should be understood that the term "and/or" herein is merely one type of association relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, B exists alone, and A and B exist at the same time, and the term "/and" is used herein to describe another association object relationship, which means that two relationships may exist, for example, A/and B, may mean: a alone, and both a and B alone, and further, the character "/" in this document generally means that the former and latter associated objects are in an "or" relationship.
It is to be understood that in the description of the present invention, the terms "upper", "vertical", "inside", "outside", and the like, refer to an orientation or positional relationship that is conventionally used for placing the product of the present invention, or that is conventionally understood by those skilled in the art, and are used merely for convenience in describing and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and therefore should not be considered as limiting the present invention.
It will be understood that when an element is referred to as being "connected," "connected," or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may be present. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, there are no intervening elements present. Other words used to describe the relationship between elements should be interpreted in a similar manner (e.g., "between … …" versus "directly between … …", "adjacent" versus "directly adjacent", etc.).
In the description of the present invention, it should also be noted that, unless otherwise explicitly specified or limited, the terms "disposed," "mounted," and "connected" are to be construed broadly, e.g., as meaning fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments of the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes," and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, numbers, steps, operations, elements, components, and/or groups thereof.
It should also be noted that, in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed substantially concurrently, or the figures may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In the following description, specific details are provided to facilitate a thorough understanding of example embodiments. However, it will be understood by those of ordinary skill in the art that the example embodiments may be practiced without these specific details. For example, systems may be shown in block diagrams in order not to obscure the examples in unnecessary detail. In other instances, well-known processes, structures and techniques may be shown without unnecessary detail in order to avoid obscuring example embodiments.
Example 1:
the embodiment provides a personnel supervision method based on big data, which can be applied to a system architecture, where the system architecture includes a community security inspection terminal, a management terminal and a cloud server, and the embodiment describes the personnel supervision method based on big data in detail by combining the system architecture, as shown in fig. 1, including the following steps:
s101, obtaining biological characteristic identification information of community visitors.
In specific implementation, the biological feature identification information comprises face image feature information and iris image feature information, and the process of acquiring the biological feature identification information of community visitors by the management terminal comprises the following steps: receiving a face recognition image and an iris recognition image of a visitor sent by a community security check terminal; extracting the characteristics of the face recognition image and the iris recognition image to obtain the characteristics of the face image and the iris image; and integrating the facial image characteristics and the iris image characteristics into biological characteristic identification information.
Face identification image and iris identification image accessible community security check terminal gather and acquire, before community visitor's personnel come to community security check terminal, community security check terminal carries out corresponding image acquisition transmission, and the process includes: collecting a face recognition image and an iris recognition image of a visitor; carrying out image preprocessing on the face recognition image and the iris recognition image, wherein the preprocessing process comprises image enhancement, image restoration, image coding compression and image segmentation; packing the preprocessed face recognition image and the preprocessed iris recognition image to obtain an image packet; and encrypting the image packet by using the key and transmitting the image packet to the management terminal.
The quality of the image in the processes of imaging, collecting, transmitting, copying and the like can be degraded to a certain extent, and the visual effect of the digitized image is not very satisfactory. In order to highlight the interesting parts of the image and make the main structure of the image more definite, the image must be improved, i.e. enhanced. Through image enhancement, the noise of the image in the image is reduced, and the parameters of brightness, color distribution, contrast and the like of the original image are changed. The image enhancement improves the definition and the quality of the image, so that the outline of an object in the image is clearer and the details are more obvious. Image restoration is also called image restoration, the image is blurred due to the influence of environmental noise, image blurring caused by movement, light intensity and other reasons when the image is acquired, the image needs to be restored in order to extract a clearer image, and the image restoration mainly adopts a filtering method to restore an original image from a degraded image. Digital images are characterized by large data size and need to occupy considerable storage space. However, the processing, storage and transmission of data images cannot be performed based on the network bandwidth and mass storage of the computer. In order to transmit an image or video in a network environment quickly and conveniently, the image must be encoded and compressed. At present, image compression and encoding forms an international standard, such as the relatively well-known still image compression standard JPEG, which mainly aims at the resolution, color image and gray image of an image and is suitable for aspects of digital photos, color photos and the like transmitted through a network. Image segmentation is to divide an image into sub-regions that do not overlap each other and have respective characteristics, each region being a continuum of pixels, where the characteristics may be color, shape, grayscale, texture, etc. of the image. Image segmentation represents an image as a collection of physically meaningful connected regions based on a priori knowledge of the target and the background. Namely, the target and the background in the image are marked and positioned, and then the target is separated from the background.
S102, comparing the biological characteristic identification information of the visitor with the pre-stored biological characteristic identification information of the community personnel, and judging whether the visitor is the community personnel.
In specific implementation, the biological feature identification information of all the people in the community can be stored in the database of the management terminal in advance, and after the biological feature identification information of the visitor is obtained, the biological feature identification information of the visitor is directly compared with the biological feature identification information of the community people in the database, so that whether the visitor is the community person can be judged quickly.
S103, when the visitor is judged to be a non-community person, the person relationship two-dimensional code of the visitor is obtained, the person relationship two-dimensional code is scanned, and the person relationship information of the visitor and the community person is obtained.
When the community security check terminal is specifically implemented, when the visiting person is judged to be the community person, the management terminal directly sends an access instruction to the community security check terminal, a timestamp is printed on biological characteristic identification information of the visiting person, and the biological characteristic identification information is uploaded to the cloud server to be tracked and retained. If the visiting person is not the community person, the management terminal can feed back corresponding information to the community security check terminal, the community security check terminal collects the personnel relationship two-dimensional code of the visiting person, the personnel relationship two-dimensional code is forwarded to the mobile terminal of the visiting person by the community person through the corresponding mobile terminal, and the personnel relationship two-dimensional code can contain the social relationship between the visiting person and the community person and the personal information of the visiting person. The management terminal can obtain the personnel relationship information of the visitors and the community personnel and the personal information of the visitors by scanning the personnel relationship two-dimensional code.
And S104, stamping a time stamp on the biological characteristic identification information of the visitor and uploading the biological characteristic identification information to a cloud server.
When the method is specifically implemented, the process of stamping a timestamp on the biological characteristic identification information of the visitor and uploading the information to the cloud server comprises the following steps: stamping a time stamp on the biological characteristic identification information of the visitor; encrypting the biometric feature identification information with the timestamp by using a secret key to obtain an encrypted information packet; and transmitting the encrypted information packet to a cloud server through a secure encryption channel. The key encryption algorithm can adopt a symmetric encryption algorithm, such as DES, 3DES, AES, Blowfish and the like; asymmetric encryption algorithms such as RSA, DSA, DSS, ELGamal, etc.; and one-way encryption algorithms such as MD5, sha1, sha224 and the like.
And S105, receiving the tracking information of the visitors fed back by the cloud server, and determining the community where the visitors appear last time according to the tracking information of the visitors.
During concrete implementation, the cloud server can receive the personnel biological characteristic identification information sent by each community management terminal to trace and trace the source of the personnel in each community, when the cloud server receives the personnel biological characteristic identification information sent by a certain community management terminal, the community where the corresponding personnel appears last time is found through big data calculation and comparison according to the personnel biological characteristic identification information and the timestamp, and the tracking information of the visiting personnel is generated and fed back to the corresponding management terminal.
And S106, carrying out risk judgment on the community where the visitor appears last time according to the set risk area division rule.
In specific implementation, the risk area division rule can be adjusted according to actual conditions, and each community follows the corresponding division rule according to the region where the community is located.
S107, when the community where the visitor appears last time is judged to be a non-risk area, an access instruction is sent to a community security check terminal, and biological feature identification information and a personnel relation two-dimensional code of the visitor are stored in a database; and when the community where the visitor appears last time is judged to be a dangerous area, sending an early warning instruction to a community security check terminal.
When the community is a non-risk area, the management terminal of the community sends an access instruction to the community security check terminal, biological characteristic identification information and a personnel relation two-dimensional code of the visitor are stored in the database for keeping a file, the biological characteristic identification information and the personnel relation two-dimensional code are convenient to look up at any time, and when the community security check terminal receives the access instruction, the security check passage door is opened to allow the visitor to pass. When a community in which visitors appear recently is a risk area, the management terminal of the community sends an early warning instruction to the community security check terminal, and the community security check terminal sends corresponding early warning information when receiving the early warning instruction, so that community managers can timely deal with the early warning information.
Example 2:
the embodiment provides a personnel supervision device based on big data, as shown in fig. 2, including:
the first acquisition unit is used for acquiring biological characteristic identification information of community visitors;
the comparison unit is used for comparing the biological characteristic identification information of the visitor with the pre-stored biological characteristic identification information of the community personnel and judging whether the visitor is the community personnel or not;
the second acquisition unit is used for acquiring the personnel relationship two-dimensional code of the visitor when the visitor is judged to be a non-community person, scanning the personnel relationship two-dimensional code and acquiring personnel relationship information of the visitor and community personnel;
the transmission unit is used for stamping a time stamp on the biological characteristic identification information of the visitor, uploading the biological characteristic identification information to the cloud server, and receiving the visitor tracking information fed back by the cloud server;
the determining unit is used for determining the community where the visitor appears last time according to the tracking information of the visitor;
the judgment unit is used for carrying out risk judgment on the communities where the visitors appear recently according to the set risk area division rule;
the feedback unit is used for sending an access instruction to the community security check terminal when the community where the visitor appears last time is judged to be a non-risk area, and storing biological characteristic identification information and a personnel relation two-dimensional code of the visitor into a database; and when the community where the visitor appears last time is judged to be a dangerous area, sending an early warning instruction to a community security check terminal.
Example 3:
the embodiment provides a personnel supervision device based on big data, as shown in fig. 3, including:
the acquisition unit is used for acquiring the personnel relationship two-dimensional code, the face recognition image and the iris recognition image of the community visitor;
the receiving and sending unit is used for transmitting the personnel relationship two-dimensional code, the face recognition image and the iris recognition image to the management terminal and receiving an access instruction or an early warning instruction fed back by the management terminal;
the execution unit is used for opening the security inspection channel door for releasing when the access instruction is received; and sending out early warning information when receiving the early warning instruction.
Example 4:
the present embodiment provides a computer device, as shown in fig. 4, including:
a memory to store instructions;
and the processor is used for reading the instructions stored in the memory and executing the personnel supervision method based on the big data in the embodiment 1 according to the instructions.
The Memory may include, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Flash Memory (Flash Memory), a First In First Out (FIFO), a First In Last Out (FILO), and/or the like; the processor may include, but is not limited to, a single chip, an ARM processor, and the like.
Example 5:
the present embodiment provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to execute the big data based personnel supervision method described in embodiment 1. The computer-readable storage medium refers to a carrier for storing data, and may include, but is not limited to, floppy disks, optical disks, hard disks, flash memories, flash disks and/or Memory sticks (Memory sticks), etc., and the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
Example 6:
the present embodiment provides a computer program product containing instructions, which when run on a computer, cause the computer to execute the big data based personnel supervision method described in embodiment 1. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable devices.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the embodiments of the method may be implemented by hardware related to program instructions, the program may be stored in a computer-readable storage medium, and when executed, the program performs the steps including the embodiments of the method, and the storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention 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 invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus, and storage media of embodiments. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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.
The present invention is not limited to the above-described alternative embodiments, and various other forms of products can be obtained by anyone in light of the present invention. The above detailed description should not be taken as limiting the scope of the invention, which is defined in the claims, and which the description is intended to be interpreted accordingly.
Claims (10)
1. Personnel supervision method based on big data, characterized by comprising:
acquiring biological characteristic identification information of community visitors;
comparing the biological characteristic identification information of the visitor with pre-stored biological characteristic identification information of community personnel, and judging whether the visitor is the community personnel;
when the visitor is judged to be a non-community person, acquiring a person relationship two-dimensional code of the visitor, scanning the person relationship two-dimensional code, and acquiring the person relationship information of the visitor and the community person;
the method comprises the steps that biological characteristic identification information of a visitor is stamped and uploaded to a cloud server;
receiving tracking information of the visitors fed back by the cloud server, and determining a community where the visitors appear recently according to the tracking information of the visitors;
carrying out risk judgment on the communities where the visitors appear last time according to a set risk area division rule;
when the community where the visitor appears last time is judged to be a non-risk area, an access instruction is sent to a community security check terminal, and biological feature identification information and a personnel relation two-dimensional code of the visitor are stored in a database; and when the community where the visitor appears last time is judged to be a dangerous area, sending an early warning instruction to a community security check terminal.
2. The big-data based personnel supervision method according to claim 1, characterized in that the method further comprises:
when the visitor is judged to be a community person, an access instruction is sent to the community security check terminal, the biological characteristic identification information of the visitor is stamped, and the biological characteristic identification information is uploaded to the cloud server.
3. The personnel supervision method based on big data as claimed in claim 1, wherein the biometric information includes face image feature information and iris image feature information, and the obtaining of the biometric information of community visitors includes:
receiving a face recognition image and an iris recognition image of a visitor sent by a community security check terminal;
extracting the characteristics of the face recognition image and the iris recognition image to obtain the characteristics of the face image and the iris image;
and integrating the facial image characteristics and the iris image characteristics into biological characteristic identification information.
4. The big data based personnel supervision method according to claim 1, wherein the time stamping the biometric information of the visiting personnel and uploading the biometric information to a cloud server comprises:
stamping a time stamp on the biological characteristic identification information of the visitor;
encrypting the biometric feature identification information with the timestamp by using a secret key to obtain an encrypted information packet;
and transmitting the encrypted information packet to a cloud server through a secure encryption channel.
5. Personnel supervision method based on big data, characterized by comprising:
acquiring a personnel relationship two-dimensional code, a face recognition image and an iris recognition image of community visitors;
the personnel relation two-dimensional code, the face recognition image and the iris recognition image are transmitted to a management terminal, and an access instruction or an early warning instruction fed back by the management terminal is received;
when an access instruction is received, opening a security inspection access door for releasing; and sending out early warning information when receiving the early warning instruction.
6. The personnel supervision method based on big data according to claim 5, wherein the transmitting the face recognition image and the iris recognition image to the management terminal comprises:
carrying out image preprocessing on the face recognition image and the iris recognition image, wherein the preprocessing process comprises image enhancement, image restoration, image coding compression and image segmentation;
packing the preprocessed face recognition image and the preprocessed iris recognition image to obtain an image packet;
and encrypting the image packet by using the key and transmitting the image packet to the management terminal.
7. Personnel supervision device based on big data, its characterized in that includes:
the first acquisition unit is used for acquiring biological characteristic identification information of community visitors;
the comparison unit is used for comparing the biological characteristic identification information of the visitor with the pre-stored biological characteristic identification information of the community personnel and judging whether the visitor is the community personnel or not;
the second acquisition unit is used for acquiring the personnel relationship two-dimensional code of the visitor when the visitor is judged to be a non-community person, scanning the personnel relationship two-dimensional code and acquiring personnel relationship information of the visitor and community personnel;
the transmission unit is used for stamping a time stamp on the biological characteristic identification information of the visitor, uploading the biological characteristic identification information to the cloud server, and receiving the visitor tracking information fed back by the cloud server;
the determining unit is used for determining the community where the visitor appears last time according to the tracking information of the visitor;
the judgment unit is used for carrying out risk judgment on the communities where the visitors appear recently according to the set risk area division rule;
the feedback unit is used for sending an access instruction to the community security check terminal when the community where the visitor appears last time is judged to be a non-risk area, and storing biological characteristic identification information and a personnel relation two-dimensional code of the visitor into a database; and when the community where the visitor appears last time is judged to be a dangerous area, sending an early warning instruction to a community security check terminal.
8. Personnel supervision device based on big data, its characterized in that includes:
the acquisition unit is used for acquiring the personnel relationship two-dimensional code, the face recognition image and the iris recognition image of the community visitor;
the receiving and sending unit is used for transmitting the personnel relationship two-dimensional code, the face recognition image and the iris recognition image to the management terminal and receiving an access instruction or an early warning instruction fed back by the management terminal;
the execution unit is used for opening the security inspection channel door for releasing when the access instruction is received; and sending out early warning information when receiving the early warning instruction.
9. A computer device, comprising:
a memory to store instructions;
a processor for reading the instructions stored in the memory and executing the method of any one of claims 1-4 in accordance with the instructions.
10. A computer-readable storage medium having stored thereon instructions which, when executed on a computer, cause the computer to perform the method of any one of claims 1-4.
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