CN115984063A - Community online security monitoring method and device, computer equipment and storage medium - Google Patents
Community online security monitoring method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a method and a device for monitoring community online security, computer equipment and a storage medium. The method comprises the following steps: acquiring a face image shot by a camera deployed in a cell; carrying out big data analysis on the face image in combination with the position information of the cell to obtain an analysis result; storing the analysis results for retrieval and use. By implementing the method provided by the embodiment of the invention, the dynamic data monitoring and statistics of the community real population can be realized, the safety of community residents can be effectively guaranteed, and the standardization, population management dynamics, accurate service management and control and diversification of convenient service of the community are realized.
Description
Technical Field
The invention relates to a community security management method, in particular to a community online security monitoring method, a device, computer equipment and a storage medium.
Background
The number of community personnel is large, the mobility is high, information acquisition is passive, a timely and effective information updating means is lacked, and the accuracy and freshness of data are difficult to guarantee. The urban floating population is large in number and complex in composition, so that the change of floating personnel information is not recorded in time, the management difficulty of the floating population is high for the community, the moving population trend is difficult to master, the security management of a community is difficult, and the management and control measures of a management department are difficult to implement. The consciousness of the floating population is weak, the registration consciousness is not high in active declaration, and the registration procedure is often not applied for part of cell owners for pursuing benefits and tenants for saving expenses, so that the number of registered people is far lower than the number of actually temporarily stored people, and a large number of missing registration phenomena occur. Due to the common defects of long-term management, the management capability of personnel management, floating population management and housing real living condition management is seriously lost, and the modes of visiting, routing inspection, registration and acquisition and the like are generally carried out in a manual mode.
The existing cell management scheme can not actively collect population information of cells, only manual collection can be carried out, and the real-time performance, accuracy and effectiveness of data can not meet the management requirements.
Therefore, it is necessary to design a new method to monitor and count the dynamic data of the real population of the residential area, to more effectively ensure the safety of the residents in the residential area, and to achieve the standardization of the residential area housing management, the dynamic population management, the precision of the service management and control, and the diversification of the convenient service.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a cell online security monitoring method, a cell online security monitoring device, computer equipment and a storage medium.
In order to achieve the purpose, the invention adopts the following technical scheme: the community online security monitoring method comprises the following steps:
acquiring a face image shot by a camera deployed in a cell;
carrying out big data analysis on the face image in combination with the position information of the cell to obtain an analysis result;
storing the analysis results for retrieval and use.
The further technical scheme is as follows: the cameras deployed in the residential area comprise a residential area entrance guard, a door lock and cameras deployed in the elevators.
The further technical scheme is as follows: the big data analysis is carried out on the face image in combination with the position information of the cell to obtain an analysis result, and the big data analysis comprises the following steps:
acquiring the position information of a cell;
inputting the face image into an analysis model for target detection to obtain a detection result;
combining the detection result with the position information of the cell to form an analysis result;
the analysis model is obtained by training a convolutional neural network through a plurality of face images with frame coordinate information labels where the face targets are located.
The further technical scheme is as follows: the acquiring the location information of the cell includes:
and carrying out positioning analysis on the face image to obtain the position information of the cell.
The further technical scheme is as follows: the combining the detection result with the location information of the cell to form an analysis result includes:
integrating the same detection result of the same cell to form information corresponding to the detection results of different time points of the same cell so as to obtain an integrated result;
and performing behavior path analysis on the integration result to obtain an analysis result.
The further technical scheme is as follows: the analyzing the behavior path of the integrated result to obtain an analysis result includes:
and (4) normalizing the integration result by taking the same detection result as a reference according to a time axis sequence to obtain an analysis result.
The further technical scheme is as follows: the storing the analysis results for retrieval and use includes:
and storing the analysis result for calling, and updating the criminal and the personnel residence information according to the analysis result.
The invention also provides a community online security monitoring device, which comprises:
the image acquisition unit is used for acquiring a face image shot by a camera deployed in a cell;
the analysis unit is used for carrying out big data analysis on the face image in combination with the position information of the cell to obtain an analysis result;
and the storage unit is used for storing the analysis result for calling and using.
The invention also provides a computer device, which comprises a memory and a processor, wherein the memory is stored with a computer program, and the processor executes the computer program to realize the method.
The invention also provides a storage medium storing a computer program which, when executed by a processor, implements the method described above.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the human face images shot by the cameras deployed in the community are acquired, and the big data analysis is carried out by combining the position information of the community for calling and using, so that the dynamic data monitoring and statistics of the real population of the community are realized, the safety of residents in the community is effectively ensured, and the standardization, population management dynamics, accurate service management and control and diversified convenience service of community housing management are realized.
The invention is further described below with reference to the accompanying drawings and specific embodiments.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic view of an application scenario of a cell online security monitoring method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a method for monitoring security of a community on line according to an embodiment of the present invention;
fig. 3 is a sub-flow diagram of a method for monitoring security of a community on line according to an embodiment of the present invention;
fig. 4 is a schematic flow chart of a method for monitoring security of a community on line according to an embodiment of the present invention;
fig. 5 is a schematic block diagram of an online security monitoring apparatus for a cell according to an embodiment of the present invention;
fig. 6 is a schematic block diagram of an analysis unit of an online security monitoring device for a cell according to an embodiment of the present invention;
fig. 7 is a schematic block diagram of a combination subunit of the online security monitoring apparatus for a cell according to an embodiment of the present invention;
FIG. 8 is a schematic block diagram of a computer device provided by 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 some, but not all, embodiments of the present invention. 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.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, 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, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.
Referring to fig. 1 and fig. 2, fig. 1 is a schematic view of an application scenario of a cell online security monitoring method according to an embodiment of the present invention. Fig. 2 is a schematic flowchart of a cell online security monitoring method provided in an embodiment of the present invention. The community online security monitoring method is applied to a server. The server performs data interaction with the camera, and the server performs big data analysis on the image acquired by the camera arranged at the entrance guard of the community, the door lock and the elevator, and stores the analysis result in a positioning position for calling.
Fig. 2 is a schematic flow chart of a method for monitoring security of a cell online provided by an embodiment of the present invention. As shown in fig. 2, the method includes the following steps S110 to S130.
And S110, acquiring a face image shot by a camera deployed in a cell.
In this embodiment, the cameras deployed in the residential area include cameras deployed in residential area entrance doors, door locks, and elevators.
Specifically, the face image refers to an image with a face captured by a camera deployed in a cell.
And S120, performing big data analysis on the face image in combination with the position information of the cell to obtain an analysis result.
In this embodiment, the analysis result refers to information with a face target frame, a location of a cell, and a behavior path, and the face target frame may carry identity information and the like.
In an embodiment, referring to fig. 3, the step S120 may include steps S121 to S123.
And S121, acquiring the position information of the cell.
In this embodiment, the location information of the cell refers to a geographic location of the cell corresponding to the face image.
Specifically, the face acquisition device has a GPS positioning function, and the face recognition result is bound to the device number, so that corresponding GPS information can be obtained. In order to facilitate searching, each face recognition device has a serial number and an editable name, and the name has character information with high readability, such as a certain street, a certain cell, a certain gate and the like.
Specifically, the face image is positioned and analyzed to obtain the position information of the cell.
The shot geographic position is positioned through the image, the method is convenient and quick, and the accuracy is high.
And S122, inputting the face image into an analysis model for target detection to obtain a detection result.
In this embodiment, the detection result refers to coordinate information of a frame where the face target is located, and the detection result may be further subjected to face recognition and matched with information registered in the cell to form associated information.
The user has already carried out face registration when applying for entrance guard, ladder accuse and gate control system, has deposited user's face information in district property system. The detection result is compared with the community property registration information to know whether the community is a long-term resident or a visitor who has applied for the community, and if the community is the long-term resident or the visitor, early warning information is generated. By counting the detected activity frequency of registered owners in the community property system, a list of the owners which do not appear for a long time can be obtained, and property workers can check help at home according to the conditions of whether the owners are solitary old people or not.
The analysis model is obtained by training a convolutional neural network through a plurality of face images with frame coordinate information labels where the face targets are located.
And S123, combining the detection result with the position information of the cell to form an analysis result.
In this embodiment, the analysis result refers to a result formed after coordinate information of a frame where the face target is located is combined with a position where the cell is located and a behavior path is constructed.
In one embodiment, referring to fig. 4, the step S123 may include steps S1231 to S1232.
And S1231, integrating the same detection result of the same cell to form information corresponding to the detection results of different time points of the same cell so as to obtain an integrated result.
In this embodiment, the integration result refers to information corresponding to detection results of different time points in the same cell.
After the detection results are classified according to the same cell, the detection results are classified and integrated according to the same detection result in the same cell to form corresponding integration results, and the integration can be carried out according to the detection results, the position of the cell (time and the specific position of the shot).
And S1232, performing behavior path analysis on the integration result to obtain an analysis result.
Specifically, the same detection result is used as a reference according to a time axis sequence, and the integration result is normalized to obtain an analysis result.
Specifically, the real-time acquisition system processes the face data in the MQ and stores the processed face data in the OLAP database.
The OLAP database is partitioned according to the day, partitioned according to the hour and partitioned into buckets, and a columnar storage engine and a bitmap index are selected and built according to corresponding dimensionality.
The database middle station provides a data query service API, and can query in various modes such as time interval/people track query, time interval/cell people counting, time interval/user in-out counting and the like.
And S130, storing the analysis result for calling and using.
Specifically, the analysis result is stored for calling, and criminals and personnel residence information are updated according to the analysis result.
In this embodiment, the big data analysis and the early warning are mainly implemented to perform cleaning, deduplication, format conversion, local operation, queue storage, AI analysis and the like on the acquired data, complete analysis on the data through algorithms such as deep machine learning, extract important information in the data, form corresponding instructions to be distributed to a terminal or give an early warning signal, complete corresponding control operations, and form a cloud-side superconcephalon. The superconcephalon uniformly registers and manages all cells, commands are issued to registered cell equipment indiscriminately, a data format is unified, and data are analyzed and stored through various systems to form a calculation basis of the superconcephalon part, so that service data are provided for an upper-layer platform, and data service is analyzed. The passing records of various crowds can be visually checked through the analysis system, the passing time, the image and the position of equipment such as a gate, a unit door and elevator control are included, and accurate data are provided when the personnel pass, audit and trace. The data access provides a uniform interface, classification processing and storage are carried out on different types of data, the service use queue cache technology can simultaneously process more than 100 single-point data return in a single server with 128GB memory, the request can be processed more than 10000 times per second, and the data can be processed and completed in 3 seconds after being received.
The stream media processing system is responsible for SIP registration of cell monitoring NVR or channels, the system deploys ZLMediakit bottom layer video processing application, application such as stream pulling, stream pushing, GB28181 national standard stream, online transcoding, cascade registration and the like can be realized in the system, and bottom layer service can be provided for the video fusion platform through the stream media processing subsystem. The file processing subsystem is responsible for processing and storing unstructured data, classifying and storing image files and video files by using an HDFS (Hadoop distributed file system), performing concurrent retrieval and distributed storage on massive unstructured data in a structured data mode by using HDFS (Hadoop distributed file system) big data processing capacity, and solving the processing flow of massive files by a big data means.
The intelligent sensing system for the residential area acquires related data in the public area of the residential area through terminal equipment by laying various intelligent terminals such as various face entrance guards, fingerprint entrance guards, high-altitude parabolic probes, safety monitoring probes, face snapshot equipment, automatic license plate recognition of a vehicle barrier gate, face ladder control and the like, and distributes related instructions to the intelligent terminals or early warning after data processing and analysis are completed through a big data analysis and early warning system, so that unified collection and unified processing of data are realized at high efficiency, and finally, a residential area microcomputer is formed. The microcomputer can efficiently carry out undifferentiated butt joint on all intelligent terminal equipment in a cell, and all the equipment form a network, are interconnected and intercommunicated, and carry out management, data aggregation, instruction issuing and edge calculation in a unified way; and copying the cell architecture aiming at the overall mode, uniformly managing and uniformly butting the massive cells in a uniform mode, and realizing a multipoint registration single-point management mode. The remote SIP signaling video streaming service subsystem is responsible for registering all monitoring probes in a cell, and the NVR recorder registers monitoring in a cell data center in a national standard form, performs signaling interaction through a cascaded superior platform, and serves as a data source of a video screen fusion platform to provide services such as video, SIP registration, directory channels, transcoding, transmission, heartbeat, playback, downloading, back control and the like. In order to improve the performance of the whole system, the intelligent terminal docking service subsystem is responsible for docking intelligent terminal hardware in the forms of an SKD docking library or an API (application program interface) interface and the like, issuing instructions to equipment through services, enabling the equipment to accurately execute required tasks and return data generated by the equipment, monitoring heartbeat of the equipment in real time, and performing indifferent docking on all types of equipment through a docking service framework and performing unified standard on the data through edge calculation. In order to realize the traceability of data, the data checking and reverse tracing service subsystem is responsible for whole-course log recording, accurately records all commands and data flow directions, ensures all operations to be searchable, and can automatically trace the last correct operation after the server is down to ensure that the data and the commands are not lost.
In order to effectively improve the capability of the system for resisting network attacks, the system specially develops an anti-intrusion service module which is responsible for authentication and authorization of an internet interface and ensures that key operations such as command receiving, data sending and the like meet the safety standard, so that tampered data or attack type commands cannot be transmitted and executed. And (4) capturing and returning the attack data and the attack position in real time through an entity firewall, and early warning in real time by a cloud terminal.
According to the method for monitoring the online placement of the residential area, the face image shot by the camera deployed in the residential area is obtained, and big data analysis is carried out by combining the position information of the residential area for calling and using, so that the dynamic data monitoring and statistics of the real population of the residential area are realized, the safety of residents in the residential area is effectively guaranteed, and the standardization, population management dynamics, accurate service management and control and diversified convenience service of residential area house management are realized.
Fig. 5 is a schematic block diagram of an online security monitoring device 300 for a cell according to an embodiment of the present invention. As shown in fig. 5, the present invention further provides an online security monitoring device 300 for a community corresponding to the online security monitoring method for the community. The cell online security monitoring apparatus 300 includes a unit for performing the above-described cell online security monitoring method, and may be configured in a server. Specifically, referring to fig. 5, the cell online security monitoring apparatus 300 includes an image acquisition unit 301, an analysis unit 302, and a storage unit 303.
An image obtaining unit 301, configured to obtain a face image shot by a camera deployed in a cell; an analysis unit 302, configured to perform big data analysis on the face image in combination with the location information of the cell to obtain an analysis result; a storage unit 303, configured to store the analysis result for retrieval and use.
In an embodiment, as shown in fig. 6, the analysis unit 302 comprises a location acquisition subunit 3021, an object detection subunit 3022 and a combination subunit 3023.
A location acquiring subunit 3021, configured to acquire location information of a cell; a target detection subunit 3022, configured to input the face image into an analysis model to perform target detection, so as to obtain a detection result; a combining subunit 3023, configured to combine the detection result with the location information of the cell to form an analysis result.
In an embodiment, the location acquiring subunit 3021 is configured to perform positioning analysis on the face image to obtain location information of a cell.
In one embodiment, as shown in fig. 7, the combining subunit 3023 includes an integrating module 30231 and a path analyzing module 30232.
An integrating module 30231, configured to integrate the same detection result of the same cell to form information corresponding to the detection results of different time points of the same cell, so as to obtain an integrated result; a path analysis module 30232, configured to perform behavior path analysis on the integration result to obtain an analysis result.
In an embodiment, the path analysis module 30232 is configured to normalize the integration result according to a time axis sequence based on the same detection result to obtain an analysis result.
In an embodiment, the storage unit 303 is configured to store the analysis result for retrieval, and update criminals and living information according to the analysis result.
It should be noted that, as can be clearly understood by those skilled in the art, for the specific implementation processes of the cell online security monitoring apparatus 300 and each unit, reference may be made to the corresponding description in the foregoing method embodiment, and for convenience and simplicity of description, details are not repeated here.
The above-described cell online security monitoring apparatus 300 may be implemented in the form of a computer program that can be run on a computer device as shown in fig. 8.
Referring to fig. 8, fig. 8 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device 500 may be a server, where the server may be an independent server or a server cluster composed of a plurality of servers.
Referring to fig. 8, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.
The non-volatile storage medium 503 may store an operating system 5031 and computer programs 5032. The computer programs 5032 include program instructions that, when executed, cause the processor 502 to perform a method of cell online security monitoring.
The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.
The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503, and when the computer program 5032 is executed by the processor 502, the processor 502 can be enabled to execute an online cell security monitoring method.
The network interface 505 is used for network communication with other devices. Those skilled in the art will appreciate that the configuration shown in fig. 8 is a block diagram of only a portion of the configuration relevant to the present teachings and does not constitute a limitation on the computer device 500 to which the present teachings may be applied, and that a particular computer device 500 may include more or less components than those shown, or combine certain components, or have a different arrangement of components.
Wherein the processor 502 is configured to run the computer program 5032 stored in the memory to implement the following steps:
acquiring a face image shot by a camera deployed in a cell; carrying out big data analysis on the face image in combination with the position information of the cell to obtain an analysis result; storing the analysis results for retrieval and use.
The cameras deployed in the residential area comprise residential area entrance doors, door locks and cameras deployed in elevators.
In an embodiment, when the processor 502 implements the step of performing big data analysis on the face image in combination with the location information of the cell to obtain the analysis result, the following steps are specifically implemented:
acquiring the position information of a cell; inputting the face image into an analysis model for target detection to obtain a detection result; combining the detection result with the position information of the cell to form an analysis result;
the analysis model is obtained by training a convolutional neural network through a plurality of face images with frame coordinate information labels where the face targets are located.
In an embodiment, when the processor 502 implements the step of obtaining the location information of the cell, the following steps are specifically implemented:
and carrying out positioning analysis on the face image to obtain the position information of the cell.
In an embodiment, when the processor 502 implements the step of combining the detection result with the location information of the cell to form the analysis result, the following steps are specifically implemented:
integrating the same detection result of the same cell to form information corresponding to the detection results of different time points of the same cell so as to obtain an integrated result; and performing behavior path analysis on the integration result to obtain an analysis result.
In an embodiment, when implementing the step of performing behavior path analysis on the integration result to obtain an analysis result, the processor 502 specifically implements the following steps:
and normalizing the integration results by taking the same detection result as a reference according to a time axis sequence to obtain an analysis result.
In an embodiment, when the processor 502 implements the step of storing the analysis result for retrieval and use, the following steps are specifically implemented:
and storing the analysis result for calling, and updating the criminal and the personnel residence information according to the analysis result.
It should be understood that in the embodiment of the present Application, the Processor 502 may be a Central Processing Unit (CPU), and the Processor 502 may also be other general-purpose processors, digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It will be understood by those skilled in the art that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program instructing relevant hardware. The computer program includes program instructions, and the computer program may be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program, when executed by a processor, causes the processor to perform the steps of:
acquiring a face image shot by a camera deployed in a cell; carrying out big data analysis on the face image in combination with the position information of the cell to obtain an analysis result; storing the analysis results for retrieval and use.
The cameras deployed in the residential area comprise residential area entrance doors, door locks and cameras deployed in elevators.
In an embodiment, when the processor executes the computer program to implement the step of performing big data analysis on the face image in combination with the location information of the cell to obtain an analysis result, the following steps are specifically implemented:
acquiring the position information of a cell; inputting the face image into an analysis model for target detection to obtain a detection result; combining the detection result with the position information of the cell to form an analysis result;
the analysis model is obtained by training a convolutional neural network through a plurality of face images with frame coordinate information labels where the face targets are located.
In an embodiment, when the processor executes the computer program to implement the step of obtaining the location information of the cell, the following steps are specifically implemented:
and carrying out positioning analysis on the face image to obtain the position information of the cell.
In an embodiment, when the processor executes the computer program to implement the step of combining the detection result with the location information of the cell to form an analysis result, the following steps are specifically implemented:
integrating the same detection result of the same cell to form information corresponding to the detection results of different time points of the same cell so as to obtain an integrated result; and performing behavior path analysis on the integration result to obtain an analysis result.
In an embodiment, when the processor executes the computer program to implement the step of performing the behavior path analysis on the integrated result to obtain the analysis result, the following steps are specifically implemented:
and normalizing the integration results by taking the same detection result as a reference according to a time axis sequence to obtain an analysis result.
In an embodiment, when the processor executes the computer program to realize the step of storing the analysis result for retrieval and use, the following steps are specifically realized:
and storing the analysis result for calling, and updating the criminal and the personnel residence information according to the analysis result.
The storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, which can store various computer readable storage media.
Those of ordinary skill in the art will appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the components and steps of the various examples have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, various elements or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented.
The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be merged, divided and deleted according to actual needs. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a storage medium. Based on such understanding, the technical solution of the present invention essentially or partly contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. The online security protection monitoring method of the residential area, characterized by, including:
acquiring a face image shot by a camera deployed in a cell;
carrying out big data analysis on the face image in combination with the position information of the cell to obtain an analysis result;
storing the analysis results for retrieval and use.
2. The online security monitoring method for the residential area according to claim 1, wherein the cameras deployed in the residential area comprise residential entrance doors, door locks and cameras deployed in elevators.
3. The online security monitoring method for the residential area according to claim 1, wherein the step of performing big data analysis on the face image in combination with the information of the location of the residential area to obtain an analysis result comprises the steps of:
acquiring the position information of a cell;
inputting the face image into an analysis model for target detection to obtain a detection result;
combining the detection result with the position information of the cell to form an analysis result;
the analysis model is obtained by training a convolutional neural network through a plurality of face images with frame coordinate information labels where the face targets are located.
4. The method for monitoring the online security of the community according to claim 3, wherein the acquiring the location information of the community comprises:
and carrying out positioning analysis on the face image to obtain the position information of the cell.
5. The method for monitoring community online security and protection according to claim 3, wherein the step of combining the detection result with the location information of the community to form an analysis result comprises:
integrating the same detection result of the same cell to form information corresponding to the detection results of different time points of the same cell so as to obtain an integrated result;
and performing behavior path analysis on the integration result to obtain an analysis result.
6. The method for monitoring community online security and protection according to claim 5, wherein the performing behavior path analysis on the integrated result to obtain an analysis result comprises:
and normalizing the integration results by taking the same detection result as a reference according to a time axis sequence to obtain an analysis result.
7. The method of claim 1, wherein the storing the analysis results for retrieval and use comprises:
and storing the analysis result for calling, and updating the criminals and the living information of the criminals according to the analysis result.
8. Online security protection monitoring device in district, its characterized in that includes:
the system comprises an image acquisition unit, a face image acquisition unit and a face image acquisition unit, wherein the image acquisition unit is used for acquiring a face image shot by a camera deployed in a cell;
the analysis unit is used for carrying out big data analysis on the face image in combination with the position information of the cell to obtain an analysis result;
and the storage unit is used for storing the analysis result for calling and using.
9. A computer device, characterized in that it comprises a memory, on which a computer program is stored, and a processor, which when executing the computer program, implements the method according to any one of claims 1 to 7.
10. A storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.
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