CN113221720A - Community security prevention and control method and system based on robot - Google Patents
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Abstract
The invention discloses a community security prevention and control method and a community security prevention and control system based on a robot, wherein community entrance information is obtained, and first owner identification information is obtained according to first owner image information; acquiring first image information through an image acquisition device; acquiring a first image identification level according to the first image information; acquiring first identification rule information according to the first image identification level; inputting the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature; obtaining a first matching degree according to the first identification characteristic and the first image information; and when the first matching degree meets a first preset condition, obtaining a first pass instruction for passing through the image identification of the first owner and generating a first security record, and performing data synchronization processing by using a data processor. The method solves the technical problems that the community security prevention and control is mainly people's air defense, the prevention and control is not comprehensive, and the effective security is influenced due to slow data sharing and transmission speed in the prior art.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to a community safety prevention and control method and system based on a robot.
Background
Along with the rapid development of domestic economy, the living standard of people is remarkably improved, and the requirement of people on the safety of living environment is increased day by day. In many large and medium-sized cities, people select a rental house and a community, and meanwhile, the awareness of home security and even community security is continuously improved. As an indispensable part of the construction of smart cities with hot and sporadic fires, smart communities are continuously closely connected with the lives of people. The security system is used as an important guarantee for community safety. The construction investment cost of the current community defense, civil defense and civil defense is higher and higher, the problem of group defense group control strength aging is more and more serious in the aspect of civil defense, most community security guards are security guards in the age of fifty-six, and the mobility of personnel is high. Meanwhile, the patrol route of the community is mainly based on walking, and is limited by the view and energy particularly in night patrol, so that the prevention dead angle is difficult to be fully covered.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
in the prior art, the community security prevention and control is mainly people's air defense, and the technical problems of incomplete prevention and control, slow data sharing and transmission speed and influence on effective security and protection exist.
Disclosure of Invention
The embodiment of the application provides a community safety prevention and control method and system based on a robot, and solves the technical problems that in the prior art, community safety prevention and control is mainly people's air defense, the prevention and control are not comprehensive, and effective security and protection are affected due to slow data sharing and transmission speed.
In view of the foregoing problems, embodiments of the present application provide a community security prevention and control method and system based on a robot.
In a first aspect, an embodiment of the present application provides a robot-based community security control method, which is applied to a security robot, where the security robot has an image collector and a data processor, the image collector is connected to the data processor, and the method includes: obtaining community entrance information, wherein the community entrance information comprises first owner image information; acquiring first owner identification information according to the first owner image information; acquiring first image information through an image acquisition device; acquiring a first image identification grade according to the first image information; acquiring first identification rule information according to the first image identification level; inputting the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature; obtaining a first matching degree according to the first identification feature and the first image information; judging whether the first matching degree meets a first preset condition or not; and when the first pass instruction is met, obtaining a first pass instruction, wherein the first pass instruction is used for passing through the image identification of the first owner and generating a first security record, and data synchronization processing is carried out by using a data processor.
On the other hand, this application still provides a community safety prevention and control system based on robot, the system includes:
a first obtaining unit configured to obtain community portal information, wherein the community portal information includes first owner image information;
a second obtaining unit configured to obtain first owner identification information based on the first owner image information;
the third obtaining unit is used for acquiring and obtaining first image information;
a fourth obtaining unit configured to obtain a first image recognition level based on the first image information;
a fifth obtaining unit configured to obtain first recognition rule information according to the first image recognition level;
a sixth obtaining unit, configured to input the first identification rule information and the first owner identification information into a feature extraction model, and obtain a first identification feature;
a seventh obtaining unit, configured to obtain a first matching degree according to the first identification feature and the first image information;
a first judging unit, configured to judge whether the first matching degree satisfies a first predetermined condition;
and the eighth obtaining unit is used for obtaining a first passing instruction when the first passing instruction is met, wherein the first passing instruction is used for performing data synchronization processing by using a data processor through image recognition of the first owner and generation of a first security record.
In a third aspect, the present invention provides a robot-based community security prevention and control system, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the embodiment of the application provides a community security prevention and control method and system based on a robot, which are applied to a security robot, wherein the security robot is provided with an image collector and a data processor, the image collector is connected with the data processor, and community entrance information is obtained, wherein the community entrance information comprises first owner image information; acquiring first owner identification information according to the first owner image information; acquiring first image information through an image acquisition device; acquiring a first image identification grade according to the first image information; acquiring first identification rule information according to the first image identification level; inputting the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature; obtaining a first matching degree according to the first identification feature and the first image information; judging whether the first matching degree meets a first preset condition or not; and when the first pass instruction is met, obtaining a first pass instruction, wherein the first pass instruction is used for passing through the image identification of the first owner and generating a first security record, and data synchronization processing is carried out by using a data processor. When the person in the first image information passes identification and verification, a corresponding pass instruction is obtained, which indicates that the currently scanned and collected person is safe and can be released, otherwise prompt intervention is carried out, the data, the image information and the analysis result collected in the safety prevention and control process are shared and stored with a centralized processing operation center through a data processor, and are synchronously shared with other robots, so that the robot can know the identification result in time, avoid repeated work, simultaneously can store the data, provide material data for subsequent data analysis and other community work, effectively ensure the security work of the community, improve the timeliness of the data transmission process, form a community security protection large network through a data information construction network, ensure the comprehensiveness of the security monitoring process, and solve the problem that the safety prevention and control of the community in the prior art is mainly based on personal defense, the technical problems of incomplete prevention and control, slow data sharing and transmission speed and influence on effective security and protection exist.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Fig. 1 is a schematic flowchart of a community security control method based on a robot according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a robot-based community security control system according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a fifth obtaining unit 15, a sixth obtaining unit 16, a seventh obtaining unit 17, a first judging unit 18, an eighth obtaining unit 19, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 305.
Detailed Description
The embodiment of the application provides a community safety prevention and control method and system based on a robot, and solves the technical problems that in the prior art, community safety prevention and control is mainly people's air defense, the prevention and control are not comprehensive, and effective security and protection are affected due to slow data sharing and transmission speed. The utility model has the advantages of reached and utilized the security protection system to carry out real-time information acquisition, and carry out information synchronization sharing and storage, accelerate information transmission's efficiency, utilize data to construct information identification's big net, effective identification is carried out to the expert personnel in the community, guarantee the security of community, through the analysis of omnidirectional community personnel, the security protection scope has been enlarged, the blind area that appears in having avoided the civil air defense, omit the scheduling problem, utilize data synchronization simultaneously, carry out information sharing to the robot in the community, make it can in time know the result of discernment, avoid repetitive work, can save data simultaneously, provide material data to subsequent data analysis and the community work in other aspects, the security protection work in community has effectively been ensured, the technological effect of the ageing of data transmission process has been improved. Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.
Summary of the application
Along with the rapid development of domestic economy, the living standard of people is remarkably improved, and the requirement of people on the safety of living environment is increased day by day. In many large and medium-sized cities, people select a rental house and a community, and meanwhile, the awareness of home security and even community security is continuously improved. As an indispensable part of the construction of smart cities with hot and sporadic fires, smart communities are continuously closely connected with the lives of people. The security system is used as an important guarantee for community safety. The construction investment cost of the current community defense, civil defense and civil defense is higher and higher, the problem of group defense group control strength aging is more and more serious in the aspect of civil defense, most community security guards are security guards in the age of fifty-six, and the mobility of personnel is high. Meanwhile, the patrol route of the community is mainly based on walking, and is limited by the view and energy particularly in night patrol, so that the prevention dead angle is difficult to be fully covered. However, in the prior art, the community security prevention and control is mainly people's air defense, and the technical problems of incomplete prevention and control, slow data sharing and transmission speed and influence on effective security and protection exist.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
obtaining community entrance information, wherein the community entrance information comprises first owner image information; acquiring first owner identification information according to the first owner image information; acquiring first image information through an image acquisition device; acquiring a first image identification grade according to the first image information; acquiring first identification rule information according to the first image identification level; inputting the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature; obtaining a first matching degree according to the first identification feature and the first image information; judging whether the first matching degree meets a first preset condition or not; and when the first pass instruction is met, obtaining a first pass instruction, wherein the first pass instruction is used for passing through the image identification of the first owner and generating a first security record, and data synchronization processing is carried out by using a data processor. The utility model has the advantages of reached and utilized the security protection system to carry out real-time information acquisition, and carry out information synchronization sharing and storage, accelerate information transmission's efficiency, utilize data to construct information identification's big net, effective identification is carried out to the expert personnel in the community, guarantee the security of community, through the analysis of omnidirectional community personnel, the security protection scope has been enlarged, the blind area that appears in having avoided the civil air defense, omit the scheduling problem, utilize data synchronization simultaneously, carry out information sharing to the robot in the community, make it can in time know the result of discernment, avoid repetitive work, can save data simultaneously, provide material data to subsequent data analysis and the community work in other aspects, the security protection work in community has effectively been ensured, the technological effect of the ageing of data transmission process has been improved.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, an embodiment of the present application provides a robot-based community security control method, which is applied to a security robot, where the security robot has an image collector and a data processor, and the method includes:
the method is applied to a security robot, security prevention and control management of a community is achieved through the security robot, the security robot is provided with an image collector and a data processor, the image collector is used for achieving collection and monitoring work of surrounding environments and people and objects appearing in the community, the data processor is an operation center for carrying out centralized processing on collected data, is connected with the image collector and a general control center, and carries out basic data processing and operation functions of synchronous uploading, transmission, analysis, storage and the like of the data.
Step S100: obtaining community entrance information, wherein the community entrance information comprises first owner image information;
particularly, the community entry is the access way of community, is provided with image collector in each access way mouth department of community and realizes carrying out real-time image, data acquisition to the current situation of entrance, carries out the synchronous analysis of data with the data processor of gathering to carry out the transmission of data, communication connection with system processing operation center, first owner image information is the image acquisition information of the business turn over pedestrian who gathers in the entry promptly, also include the current image information of other visitors, staff etc. including the owner.
Step S200: acquiring first owner identification information according to the first owner image information;
specifically, the feature information which can be recognized in the image is extracted through the first owner image information, which may be different according to the time and angle of acquisition, if the light is enough in the daytime, the definition of the collected image information of the first owner is high, the first owner identification information is more and has a relation with the collection angle, if the front collection is carried out, the first owner identification information is more, can include a plurality of identification information such as face, body state, clothes, pupil, and the like, and under the condition that the collecting time is night or the light condition is not good, the definition of the collected image information is weak, and the corresponding first owner identification information is less at this time, in addition, the collection angle is also closely related, if the back is collected, only the posture and clothing information of the owner is obtained, and the corresponding first owner identification information is less.
Step S300: acquiring first image information through an image acquisition device;
specifically, the first image information is image information acquired by an image acquirer of the security robot, namely acquired information of the security robot in a working state, and includes people, environments, animals, articles and the like. The embodiment of the application mainly aims at identifying and preventing and controlling people, can also be applied to preventing and controlling animals or preventing and controlling abnormal articles, and judges and reminds the abnormal articles by identifying and marking the characteristics of the collected images.
Step S400: acquiring a first image identification grade according to the first image information;
specifically, the recognition level of the first image is determined according to the resolution and angle problems of the first image information acquisition, the image recognition level is higher if the acquired angle is wider with higher resolution, and vice versa, the image recognition level is lower if the resolution difference angle is not good.
Step S500: acquiring first identification rule information according to the first image identification level;
specifically, the rule information that can be identified is determined according to the first image identification level and the corresponding image information content, that is, according to the mode or which feature is identified, the identification degree is high, the matching degree is high, and different identification rule information is corresponding to different image information.
Step S600: inputting the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature;
further, the step S600 of the embodiment of the present application includes inputting the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature:
step S610: taking the first identification rule information as first input information;
step S620: taking the first owner identification information as second input information;
step S630: inputting the first input information and the second input information into a feature extraction model, wherein the feature extraction model is obtained by training a plurality of sets of training data, and each set of the plurality of sets of training data comprises: the first input information, the second input information, and identification information identifying the first recognition feature;
step S640: obtaining output information of the feature extraction model, the output information including the first identifying feature.
Specifically, matching and comparing are performed according to the content in the first identification rule information and the first owner identification information, which are capable of identifying features are determined, the information capable of being used as identification features is the first identification feature, the content in the first identification rule information corresponds to the features capable of being determined in the first owner identification information, effective information capable of comparing features and identification feature information of character analysis are obtained, the number of the first identification features according to different identification rules and corresponding owner identification information is different, in order to identify the accuracy of feature analysis extraction, a neural network model is constructed and processed, arithmetic processing is performed by using a mathematical model to improve the arithmetic speed and improve the accuracy of extraction results, the feature extraction model is a neural network model in machine learning, neural Networks (NN) are complex Neural network systems formed by a large number of simple processing units (called neurons) widely interconnected, reflect many basic features of human brain functions, and are highly complex nonlinear dynamical learning systems. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (Artificial Neural Networks) are a description of the first-order properties of the human brain system. Briefly, it is a mathematical model. And inputting the first input information and the second input information into a neural network model through training of a large amount of training data, and outputting a first recognition characteristic.
More specifically, the training process is essentially a supervised learning process, each group of supervised data includes the first input information, the second input information and identification information for identifying the first identification feature, the first input information and the second input information are input into a neural network model, the neural network model performs continuous self-correction and adjustment according to the identification information for identifying the first identification feature, until an obtained output result is consistent with the identification information, the group of supervised learning is ended, and the next group of data supervised learning is performed; and when the output information of the neural network model reaches the preset accuracy rate/reaches the convergence state, finishing the supervised learning process. Through right the supervision and learning of neural network model, and then make neural network model handles input information is more accurate, and then obtains more accurate, the first identification feature that is fit for, and then effectively carries out the identification analysis of personage's characteristic, and then reaches the identification feature through the personage and effectively discern personage's identity to improve the safety prevention and control effect in community, avoid the security threat that stranger enters the community and cause, avoid security personnel can't make clear of the omission that personage's characteristic or sight blind area caused, add neural network model simultaneously and improved the efficiency and the degree of accuracy of data operation processing result, tamp the basis for providing more accurate safety prevention and control.
Step S700: obtaining a first matching degree according to the first identification feature and the first image information;
specifically, according to a first identification feature determined from the first owner identification information, the first identification feature is compared with the extraction information of the corresponding feature in the first image information, the matching degree between the first identification feature and the extraction information is obtained as a first matching degree, and the higher the matching degree is, the more accurate the person identity is, and the higher the safety is.
Step S800: judging whether the first matching degree meets a first preset condition or not;
specifically, the first predetermined condition may be set according to the corresponding identification requirement in the first identification rule information, and if the identification factors and features that can be determined in different image information are different, the requirement for the matching degree is different, and if the environment, the definition, and the identification features are all high, the requirement for the matching degree is high, and if the environment, the definition, and the identification features are all high, the requirement for the matching degree is low, that is, the first predetermined condition is low.
Step S900: and when the first pass instruction is met, obtaining a first pass instruction, wherein the first pass instruction is used for passing through the image identification of the first owner and generating a first security record, and data synchronization processing is carried out by using a data processor.
Specifically, when the person in the first image information passes identification and verification, a corresponding pass instruction is obtained, which indicates that the currently scanned and collected person is safe and can be released, and on the contrary, prompt intervention is performed, the data, the image information and the analysis result collected in the safety prevention and control process are shared and stored with a centralized processing operation center through a data processor, and are synchronously shared with other robots, so that the data and the image information can be timely known about the identification result, repeated work is avoided, meanwhile, the data can be stored, material data is provided for subsequent data analysis and other community work, the safety protection work of the community is effectively ensured, the timeliness of the data transmission process is improved, a community safety protection large network is formed through construction of the data information, the comprehensiveness of the safety protection monitoring process is ensured, and the problem that the community safety prevention and control is mainly performed by people in the prior art is solved, the technical problems of incomplete prevention and control, slow data sharing and transmission speed and influence on effective security and protection exist. The utility model has reached and has utilized the security protection system to carry out real-time information acquisition, and carry out information synchronization sharing and storage, accelerate information transmission's efficiency, utilize data to establish information identification's big net, effective identification is carried out to the expert personnel in the community, guarantee the security of community, through the personnel analysis of omnidirectional community, the security protection scope has been enlarged, the blind area that appears in having avoided the people's air defense, omit the scheduling problem, utilize data synchronization simultaneously, carry out information sharing to the robot in the community, avoid the technical effect that repetitive work improves work efficiency.
Further, after determining whether the first matching degree satisfies a first predetermined condition, an embodiment of the present application includes:
step S1010: when the first matching degree does not meet the first preset condition, first reminding information is obtained;
step S1020: acquiring first path information according to the first reminding information;
step S1030: acquiring historical path information of a first owner according to the image information of the first owner;
step S1040: obtaining a second matching degree according to the first path information and the first owner historical path information;
step S1050: judging whether the second matching degree meets a second preset condition or not;
step S1060: when satisfied, obtaining the first pass instruction.
Specifically, when the first matching degree does not satisfy the first predetermined condition, in order to avoid the situation that the data matching result does not satisfy the requirement due to the low image acquisition definition, the first owner image information is further tracked, the corresponding first owner image information is determined according to the result of the matching degree, the identity information of the first owner is determined through the first owner image information, the first owner historical path information, namely the daily walking route of the first owner, is called through the identity information of the first owner, the problem that the image identification characteristic is not high is corrected through the matching degree of the historical path through double confirmation of route comparison and image identification characteristic comparison, and if the matching result of the route and the image identification characteristic satisfies the second predetermined condition, the owner identity is determined, for example, the first matching degree determined through the identification characteristic in the image is not high, the matching degree of the matched owner path meets the daily path of the owner, because the path taken by the owner to go home has repetitive and habitual high frequency, if the path is matched with owner information in the characteristics of the owner image, the identity of the owner is identified, if the path is not matched, a prompt is sent, the passing person needs to be further verified, the passing person can enter a building monitoring system through an alarm control center or according to the entered building information, the identity of the passing person is further confirmed through image acquisition of the monitoring system, and corresponding processing is carried out according to the identification result, so that the suspicious condition can be further provided through the identification result of a robot, data are synchronized in real time, data analysis is carried out according to the pertinence of the data reaction result, and no dead angle monitoring of a community is realized, the safety control of the community is guaranteed. The method solves the technical problems that the community security prevention and control is mainly people's air defense, the prevention and control is not comprehensive, and the effective security is influenced due to slow data sharing and transmission speed in the prior art.
Further, the embodiment of the present application further includes:
step S1110: acquiring an owner information database;
step S1120: acquiring a first identification instruction according to the first owner image information and the owner information database;
step S1130: obtaining a first identification result according to the first identification instruction;
step S1140: when the first identification result is a first type result, obtaining a first pass mark;
step S1150: obtaining a third matching result according to the first image information and the first pass mark;
step S1160: and when the third matching result meets a third preset condition, obtaining the first pass instruction.
Further, after obtaining the first recognition result according to the first recognition instruction, the method includes:
step 1210: when the first identification result is a second type result, obtaining a first query instruction;
step S1220: obtaining a first query result according to the first query instruction;
step S1230: generating a second passing mark according to the first query result;
step S1240: obtaining a fourth matching result according to the first image information and the second passing mark;
step S1250: and when the fourth matching result meets the third preset condition, obtaining the first passing instruction.
Specifically, the embodiment of the application also has a function of identifying owner identity, a security robot is arranged at an entrance to collect images of passers at the entrance and compare the images with an owner information database in the system, the owner information database can be collected and constructed through property statistics, and can also be obtained through analyzing daily access data by the security robot, when the collected passers are matched with the owner information database, the passers are marked with the industry owner, the first kind of result is the owner identity, when the security robot identifies the first pass mark, the communication is rapidly carried out, the working efficiency is improved, the service experience of the owner is improved, and the property service contents such as greeting service, property notification, visit feedback, express collection and the like can be provided for the owner through the identification result of the security robot at the entrance, the identification result is marked and synchronized to share information with other robots, so that the work identification efficiency is improved, and the safety of the community is guaranteed. If the identification is not carried out in the main information database, the result is a second type result, a communicator inquiry is required at an entrance of the second type result, if the data registration is carried out on the visitor, a second passing mark is generated for the visitor according to the registration result of the visitor, the second passing mark indicates that the user is a visitor through the personnel registration, the data synchronization is carried out in the same way, when other robots identify the characteristics of the user or link the second passing mark to determine the identity of the user, a first communication instruction is obtained according to the identification result, the user is released, and the whole collected data is subjected to data storage and synchronous uploading, so that the technical problems that the community safety control is mainly people-defense, the prevention and control is incomplete, the data sharing is slow, and the effective security is influenced in the prior art are solved. The utility model has reached and has utilized the security protection system to carry out real-time information acquisition, and carry out information synchronization sharing and storage, accelerate information transmission's efficiency, utilize data to establish information identification's big net, effective identification is carried out to the expert personnel in the community, guarantee the security of community, through the personnel analysis of omnidirectional community, the security protection scope has been enlarged, the blind area that appears in having avoided the people's air defense, omit the scheduling problem, utilize data synchronization simultaneously, carry out information sharing to the robot in the community, avoid the technical effect that repetitive work improves work efficiency.
Further, the embodiment of the present application further includes:
step 1310: generating a visitor information database according to the first query result and the second passing mark, wherein the visitor information database has first time information;
step S1320: acquiring first acquisition time according to the first image information;
step S1330: obtaining a first visitor matching database according to the first acquisition time and the visitor information database;
step S1340: acquiring a fifth matching result according to the first image information, the first visitor matching database and the owner information database;
step S1350: and when the fifth matching result does not meet a fourth preset condition, obtaining first alarm information.
Particularly, for visiting persons, the visitor information database is generated by correspondingly storing the information of the users identified and registered by the population, the visitor information database comprises the registration information of daily visits, since some visitors may not move about the same day, in order to ensure the completeness of the data, the visitor information database includes long-term or recent data content, the specific set time period is set according to specific requirements, can be monthly, quarterly, semiannually and the like, so that the security robot can identify the identities of the communication personnel collected in the security working process, because the entrance of the community collects the information of the passerby, if the person who does not enter the community through the entrance is found in the security process, an alarm is sent out, the identity of the person is suspicious, and the person is indicated to not enter the community according to a normal way.
Further, the embodiment of the present application further includes:
step S1410: obtaining first license plate information;
step S1420: acquiring owner family member information according to the owner information database and the first license plate information;
step S1430: obtaining a first tracking instruction according to the first license plate information;
step S1440: obtaining a first tracking result according to the first tracking instruction;
step S1450: obtaining a first tracking identification result according to the first tracking result;
step S1460: when the first tracking identification result is the first type result, obtaining the first pass mark;
step S1470: and when the first tracking identification result is the second type of result, obtaining the second passing mark.
Specifically, in order to improve the information of people passing through the database, people entering through the parking lot also acquire and register identity information, the data acquired by the parking lot are also stored, an owner information database and a visitor information database are supplemented to ensure the integrity of the data, early warning is accurately performed, and if the monitored people are not in the owner information database or the visitor information database, the situation that the user does not enter through a normal path can only be explained, and an alarm is directly performed. The image collector is arranged in the parking lot to identify and divide personnel appearing in the parking lot, personnel identification is mainly carried out according to license plate information, vehicles entering the parking lot can pass through identity verification of an entrance, personnel identification is further carried out according to the license plate information registered in the entrance of the parking lot and the corresponding personnel information, a monitoring system in the parking lot is used for determining members appearing in the vehicles corresponding to the license plate numbers, the members are identified, and the members are owners or visitors, if no identified personnel appear, the members are registered according to the license plate information and the personnel information corresponding to the license plate at the entrance of the parking lot and stored in a visitor information database, so that the information of people passing through the parking lot is perfected, the passing condition of the community can be comprehensively mastered, and the safe visitor work of the community can be comprehensively and effectively carried out through real-time synchronization and transmission of data, the safety of the community is improved, and the technical problems that in the prior art, the safety control of the community is mainly people's air defense, the control is not comprehensive, and the effective security is influenced due to slow data sharing and transmission speed are further solved.
Example two
Based on the same inventive concept as the community safety prevention and control method based on the robot in the foregoing embodiment, the present invention further provides a community safety prevention and control system based on the robot, as shown in fig. 2, the system includes:
a first obtaining unit 11, configured to obtain community portal information, where the community portal information includes first owner image information;
a second obtaining unit 12, the second obtaining unit 12 being configured to obtain first owner identification information based on the first owner image information;
a third obtaining unit 13, where the third obtaining unit 13 is configured to acquire and obtain first image information;
a fourth obtaining unit 14, wherein the fourth obtaining unit 14 is configured to obtain a first image recognition level according to the first image information;
a fifth obtaining unit 15, where the fifth obtaining unit 15 is configured to obtain first identification rule information according to the first image identification level;
a sixth obtaining unit 16, where the sixth obtaining unit 16 is configured to input the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature;
a seventh obtaining unit 17, where the seventh obtaining unit 17 is configured to obtain a first matching degree according to the first identification feature and the first image information;
a first judging unit 18, wherein the first judging unit 18 is used for judging whether the first matching degree meets a first preset condition;
an eighth obtaining unit 19, configured to obtain, when the first pass instruction is satisfied, a first pass instruction, where the first pass instruction is used to perform data synchronization processing by using a data processor through image recognition of the first owner and generating a first security record.
Further, the system further comprises:
a ninth obtaining unit, configured to obtain first reminding information when the first matching degree does not satisfy the first predetermined condition;
a tenth obtaining unit, configured to obtain first path information according to the first prompting information;
an eleventh obtaining unit configured to obtain first owner history path information based on the first owner image information;
a twelfth obtaining unit, configured to obtain a second matching degree according to the first path information and the first owner historical path information;
a second judging unit configured to judge whether the second matching degree satisfies a second predetermined condition;
a thirteenth obtaining unit configured to obtain the first passage instruction when satisfied.
Further, the system further comprises:
a fourteenth obtaining unit configured to obtain an owner information database;
acquiring a first identification instruction according to the first owner image information and the owner information database;
a fifteenth obtaining unit, configured to obtain a first recognition result according to the first recognition instruction;
a sixteenth obtaining unit, configured to obtain a first pass flag when the first identification result is a first type result;
a seventeenth obtaining unit, configured to obtain a third matching result according to the first image information and the first pass flag;
an eighteenth obtaining unit, configured to obtain the first pass instruction when the third matching result satisfies a third predetermined condition.
Further, the system further comprises:
a nineteenth obtaining unit, configured to obtain a first query instruction when the first identification result is a second type result;
a twentieth obtaining unit, configured to obtain a first query result according to the first query instruction;
the first execution unit is used for generating a second passing mark according to the first query result;
a twenty-first obtaining unit, configured to obtain a fourth matching result according to the first image information and the second access mark;
a twenty-second obtaining unit configured to obtain the first pass instruction when the fourth matching result satisfies the third predetermined condition.
Further, the system further comprises:
a second execution unit, configured to generate a visitor information database according to the first query result and the second pass flag, where the visitor information database has first time information;
a twenty-third obtaining unit, configured to obtain a first acquisition time according to the first image information;
a twenty-fourth obtaining unit, configured to obtain a first visitor matching database according to the first acquisition time and the visitor information database;
a twenty-fifth obtaining unit, configured to obtain a fifth matching result according to the first image information, the first visitor matching database, and the owner information database;
a twenty-sixth obtaining unit, configured to obtain first alarm information when the fifth matching result does not satisfy a fourth predetermined condition.
A twenty-seventh obtaining unit, configured to further include:
a twenty-eighth obtaining unit configured to obtain first license plate information;
a twenty-ninth obtaining unit, configured to obtain owner family member information according to the owner information database and the first license plate information;
a thirtieth obtaining unit, configured to obtain a first tracking instruction according to the first license plate information;
a thirty-first obtaining unit, configured to obtain a first tracking result according to the first tracking instruction;
a thirty-second obtaining unit, configured to obtain a first tracking identification result according to the first tracking result;
a thirty-third obtaining unit, configured to obtain the first pass flag when the first tracking identification result is the first type result;
a thirty-fourth obtaining unit, configured to obtain the second passing flag when the first tracking identification result is the second type of result.
Further, the system further comprises:
a third execution unit configured to take the first identification rule information as first input information;
a fourth execution unit configured to take the first owner identification information as second input information;
a first input unit, configured to input the first input information and the second input information into a feature extraction model, where the feature extraction model is obtained by training multiple sets of training data, and each of the multiple sets of training data includes: the first input information, the second input information, and identification information identifying the first recognition feature;
a thirty-fifth obtaining unit configured to obtain output information of the feature extraction model, the output information including the first identification feature.
Various changes and specific examples of the robot-based community security prevention and control method in the first embodiment of fig. 1 are also applicable to the robot-based community security prevention and control system in the present embodiment, and through the foregoing detailed description of the robot-based community security prevention and control method, those skilled in the art can clearly know the implementation method of the robot-based community security prevention and control system in the present embodiment, so for the brevity of the description, detailed descriptions are omitted here.
Exemplary electronic device
The electronic device of the embodiment of the present application is described below with reference to fig. 3.
Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the robot-based community security prevention and control method in the foregoing embodiments, the present invention further provides a robot-based community security prevention and control system, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of any one of the foregoing robot-based community security prevention and control methods.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other systems over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the embodiment of the application provides a community security prevention and control method and system based on a robot, which are applied to a security robot, wherein the security robot is provided with an image collector and a data processor, the image collector is connected with the data processor, and community entrance information is obtained, wherein the community entrance information comprises first owner image information; acquiring first owner identification information according to the first owner image information; acquiring first image information through an image acquisition device; acquiring a first image identification grade according to the first image information; acquiring first identification rule information according to the first image identification level; inputting the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature; obtaining a first matching degree according to the first identification feature and the first image information; judging whether the first matching degree meets a first preset condition or not; and when the first pass instruction is met, obtaining a first pass instruction, wherein the first pass instruction is used for passing through the image identification of the first owner and generating a first security record, and data synchronization processing is carried out by using a data processor. When the person in the first image information passes identification and verification, a corresponding pass instruction is obtained, which indicates that the currently scanned and collected person is safe and can be released, otherwise prompt intervention is carried out, the data, the image information and the analysis result collected in the safety prevention and control process are shared and stored with a centralized processing operation center through a data processor, and are synchronously shared with other robots, so that the robot can know the identification result in time, avoid repeated work, simultaneously can store the data, provide material data for subsequent data analysis and other community work, effectively ensure the security work of the community, improve the timeliness of the data transmission process, form a community security protection large network through a data information construction network, ensure the comprehensiveness of the security monitoring process, and solve the problem that the safety prevention and control of the community in the prior art is mainly based on personal defense, the technical problems of incomplete prevention and control, slow data sharing and transmission speed and influence on effective security and protection exist.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. 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 (systems), and computer program products according to embodiments of the invention. 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 a system 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 an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. A community safety prevention and control method based on a robot is applied to a security robot, the security robot is provided with an image collector and a data processor, the image collector is connected with the data processor, and the method comprises the following steps:
obtaining community entrance information, wherein the community entrance information comprises first owner image information;
acquiring first owner identification information according to the first owner image information;
acquiring first image information through an image acquisition device;
acquiring a first image identification grade according to the first image information;
acquiring first identification rule information according to the first image identification level;
inputting the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature;
obtaining a first matching degree according to the first identification feature and the first image information;
judging whether the first matching degree meets a first preset condition or not;
and when the first pass instruction is met, obtaining a first pass instruction, wherein the first pass instruction is used for passing through the image identification of the first owner and generating a first security record, and data synchronization processing is carried out by using a data processor.
2. The method of claim 1, wherein said determining whether the first degree of match satisfies a first predetermined condition comprises:
when the first matching degree does not meet the first preset condition, first reminding information is obtained;
acquiring first path information according to the first reminding information;
acquiring historical path information of a first owner according to the image information of the first owner;
obtaining a second matching degree according to the first path information and the first owner historical path information;
judging whether the second matching degree meets a second preset condition or not;
when satisfied, obtaining the first pass instruction.
3. The method of claim 1, wherein the method comprises:
acquiring an owner information database;
acquiring a first identification instruction according to the first owner image information and the owner information database;
obtaining a first identification result according to the first identification instruction;
when the first identification result is a first type result, obtaining a first pass mark;
obtaining a third matching result according to the first image information and the first pass mark;
and when the third matching result meets a third preset condition, obtaining the first pass instruction.
4. The method of claim 3, wherein obtaining the first recognition result according to the first recognition instruction comprises:
when the first identification result is a second type result, obtaining a first query instruction;
obtaining a first query result according to the first query instruction;
generating a second passing mark according to the first query result;
obtaining a fourth matching result according to the first image information and the second passing mark;
and when the fourth matching result meets the third preset condition, obtaining the first passing instruction.
5. The method of claim 4, wherein the method comprises:
generating a visitor information database according to the first query result and the second passing mark, wherein the visitor information database has first time information;
acquiring first acquisition time according to the first image information;
obtaining a first visitor matching database according to the first acquisition time and the visitor information database;
acquiring a fifth matching result according to the first image information, the first visitor matching database and the owner information database;
and when the fifth matching result does not meet a fourth preset condition, obtaining first alarm information.
6. The method of claim 4, wherein the method comprises:
obtaining first license plate information;
acquiring owner family member information according to the owner information database and the first license plate information;
obtaining a first tracking instruction according to the first license plate information;
obtaining a first tracking result according to the first tracking instruction;
obtaining a first tracking identification result according to the first tracking result;
when the first tracking identification result is the first type result, obtaining the first pass mark;
and when the first tracking identification result is the second type of result, obtaining the second passing mark.
7. The method of claim 1, wherein the inputting the first identification rule information and the first owner identification information into a feature extraction model to obtain a first identification feature comprises:
taking the first identification rule information as first input information;
taking the first owner identification information as second input information;
inputting the first input information and the second input information into a feature extraction model, wherein the feature extraction model is obtained by training a plurality of sets of training data, and each set of the plurality of sets of training data comprises: the first input information, the second input information, and identification information identifying the first recognition feature;
obtaining output information of the feature extraction model, the output information including the first identifying feature.
8. A robot-based community security prevention and control system applied to the method of any one of claims 1 to 7, wherein the system comprises:
a first obtaining unit configured to obtain community portal information, wherein the community portal information includes first owner image information;
a second obtaining unit configured to obtain first owner identification information based on the first owner image information;
the third obtaining unit is used for acquiring and obtaining first image information;
a fourth obtaining unit configured to obtain a first image recognition level based on the first image information;
a fifth obtaining unit configured to obtain first recognition rule information according to the first image recognition level;
a sixth obtaining unit, configured to input the first identification rule information and the first owner identification information into a feature extraction model, and obtain a first identification feature;
a seventh obtaining unit, configured to obtain a first matching degree according to the first identification feature and the first image information;
a first judging unit, configured to judge whether the first matching degree satisfies a first predetermined condition;
and the eighth obtaining unit is used for obtaining a first passing instruction when the first passing instruction is met, wherein the first passing instruction is used for performing data synchronization processing by using a data processor through image recognition of the first owner and generation of a first security record.
9. A robot-based community security prevention and control system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1-7 when executing the program.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202110497345.2A CN113221720A (en) | 2021-05-07 | 2021-05-07 | Community security prevention and control method and system based on robot |
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| CN202110497345.2A CN113221720A (en) | 2021-05-07 | 2021-05-07 | Community security prevention and control method and system based on robot |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113643286A (en) * | 2021-10-12 | 2021-11-12 | 南通海美电子有限公司 | Electronic component assembly detection method and system |
| CN116030662A (en) * | 2023-01-05 | 2023-04-28 | 中承信达(天津)技术股份公司 | Intelligent safety detection system and method based on big data |
-
2021
- 2021-05-07 CN CN202110497345.2A patent/CN113221720A/en not_active Withdrawn
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113643286A (en) * | 2021-10-12 | 2021-11-12 | 南通海美电子有限公司 | Electronic component assembly detection method and system |
| CN113643286B (en) * | 2021-10-12 | 2023-06-13 | 南通海美电子有限公司 | Electronic component assembly detection method and system |
| CN116030662A (en) * | 2023-01-05 | 2023-04-28 | 中承信达(天津)技术股份公司 | Intelligent safety detection system and method based on big data |
| CN116030662B (en) * | 2023-01-05 | 2023-09-29 | 弘泰信息技术(天津)有限公司 | Intelligent safety detection system and method based on big data |
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Application publication date: 20210806 |