CN114022988B - Visitor information management verification system and method based on artificial intelligence - Google Patents
Visitor information management verification system and method based on artificial intelligence Download PDFInfo
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Abstract
The invention discloses a visitor information management verification system based on artificial intelligence, and relates to the technical field of visitor information management verification; the technical problem that real-time visitors cannot be managed and verified in real time in the prior art is solved, visitors entering a campus in real time are analyzed, the safety factor in the campus is increased, and potential safety hazards of teachers, students and equipment in the campus are reduced; judging the access state of the familiar visitor, and preventing the access abnormality of the familiar visitor from causing the reduction of the safety coefficient in the campus; access control is carried out on real-time stranger visitors, random route matching is carried out on the real-time stranger visitors, and the condition that the stranger visitors cannot enter a campus to be controlled in real time and the safety coefficient in the campus is reduced is prevented; and monitoring the real-time access process of the strange visitors, judging whether the access process of the strange visitors in the campus is normal or not, and preventing dangerous accidents in advance.
Description
Technical Field
The invention relates to the technical field of visitor information management verification, in particular to a system and a method for visitor information management verification based on artificial intelligence.
Background
The birth of the intelligent visitor management system is also a revolution in line with the era, the popularization of second-generation identity cards and the emerging concept of the Internet of things are positive as early as 2006, and in addition, the current international security situation changes in a morbid way, so that the number of mobile personnel is increased rapidly under the influence of the large social and economic environment, and multiple security events such as stealing, robbery, cheating and the like easily occur. At present, the management of external visitors of government offices, troops, electric power, communication, enterprises, residential districts, schools, office buildings and other units still mostly stays in the manual management stage of 'looking at, asking by mouth and handwriting'. Aiming at the safety management requirement in the new period, the intelligent visitor management system obtains a booming effect for birth and specially solves the problem of safety management details of visitor registration.
However, in the prior art, the visitor information management efficiency is low because the visitor information cannot be analyzed corresponding to the real-time visitor, and meanwhile, the visitor information verification efficiency is low because the familiar visitor and the strange visitor cannot be accessed and managed; meanwhile, the safety factor of visitor access is reduced.
In view of the above technical drawbacks, a solution is proposed.
Disclosure of Invention
The invention aims to solve the problems and provides a visitor information management verification system based on artificial intelligence, which is used for analyzing visitors entering a campus in real time, increasing the safety factor in the campus and reducing the potential safety hazards of teachers and students and equipment in the campus; judging the access state of the familiar visitor, and preventing the access abnormality of the familiar visitor from causing the reduction of the safety coefficient in the campus; access control is carried out on real-time unfamiliar visitors, random route matching is carried out on the real-time unfamiliar visitors, and the situation that the safety coefficient of a campus is reduced due to the fact that the unfamiliar visitors cannot be controlled in real time when entering the campus is prevented; and monitoring the real-time access process of the real-time unfamiliar visitor, and judging whether the access process of the unfamiliar visitor in the campus is normal or not, so as to prevent dangerous accidents in advance.
The purpose of the invention can be realized by the following technical scheme:
a visitor information management verification system based on artificial intelligence comprises a visitor verification management platform, wherein a server, an identity verification unit, a familiar visitor management platform and a strange visitor management platform are arranged in the visitor verification management platform; a history analysis unit and a data recording unit are arranged in the familiar visitor management platform; an access control unit and a process monitoring unit are arranged in the unfamiliar visitor management platform;
the visitor verification management platform is used for analyzing visitors entering the campus in real time, and when the visitors enter the campus in real time, the server generates an identity verification signal and sends the identity verification signal to the identity verification unit; analyzing the real-time visitor through an identity verification unit, dividing the real-time visitor into a familiar visitor and a strange visitor through analysis, and respectively sending the familiar visitor and the strange visitor to a familiar visitor management platform and a strange visitor management platform; after the familiar visitor management platform receives the familiar access signal and the familiar visitor, the familiar visitor is analyzed through the history analysis unit; data recording is carried out through a data recording unit; after the unfamiliar access management platform receives the unfamiliar access signal and the unfamiliar visitor, an access control signal is generated and sent to the access control unit, and the access control unit is used for performing access control on the unfamiliar visitor in real time; and monitoring the real-time access process of the real-time stranger through a process monitoring unit.
As a preferred embodiment of the present invention, the authentication process of the authentication unit is as follows:
the method comprises the steps of collecting a face photo of a real-time visitor in real time, comparing the real-time visitor face photo collected in real time with a historical visitor face photo in a database, marking the real-time visitor as i, wherein i is a natural number greater than 1, collecting historical access times, frequency and average access time of the real-time visitor, and respectively marking the historical access times, frequency and average access time of the real-time visitor as CSi, PLi and SCi;
by the formula
Acquiring an identity verification coefficient Xi of a real-time visitor, wherein a1, a2 and a3 are all preset proportionality coefficients, and a1 is greater than a2 and is greater than a3 and is greater than 0; comparing the identity verification coefficient of the real-time visitor with an identity verification coefficient threshold:
if the identity authentication coefficient of the real-time visitor is larger than or equal to the identity authentication coefficient threshold value, the opposite real-time visitor is judged as a familiar visitor, a familiar access signal is generated, and the familiar access signal and the familiar visitor are sent to a familiar visitor management platform; if the identity verification coefficient of the real-time visitor is smaller than the identity verification coefficient threshold value, the real-time visitor is judged as an unfamiliar visitor, an unfamiliar access signal is generated, and the unfamiliar access signal and the unfamiliar visitor are sent to an unfamiliar visitor management platform.
As a preferred embodiment of the present invention, the analysis process of the history analysis unit is as follows:
acquiring historical access frequency and historical longest access time of a familiar visitor, and comparing the historical access frequency and the historical longest access time of the familiar visitor with a historical access frequency threshold range and a historical access time threshold range respectively:
if the historical access frequency of the familiar visitor is larger than the threshold range of the historical access frequency and the historical longest access time is larger than the threshold range of the historical access time, judging that the corresponding familiar visitor is abnormal in access, generating a familiar access abnormal signal and sending the familiar access abnormal signal to a data recording unit;
and if the historical access frequency of the familiar visitor is not greater than the threshold range of the historical access frequency and the historical longest access time is not greater than the threshold range of the historical access time, judging that the corresponding familiar visitor has normal access, generating a familiar access normal signal and sending the familiar access normal signal to the data recording unit.
As a preferred embodiment of the present invention, after receiving the familiar visitor abnormal signal and the corresponding familiar visitor, the data recording unit monitors the corresponding familiar visitor, acquires the access position of the corresponding familiar visitor and the access time length of the corresponding position, and if the access position of the familiar visitor is the first access position and the access time length of the corresponding position exceeds the corresponding time length threshold, determines that the familiar visitor needs to perform identity monitoring in real time, generates a real-time monitoring signal, and sends the real-time monitoring signal and the corresponding familiar visitor to the mobile phone terminal of the security personnel; and after receiving the familiar access normal signal and the corresponding familiar visitor, the data recording unit records and saves the access time and the real-time access date of the corresponding familiar visitor.
As a preferred embodiment of the present invention, the control procedure of the access control unit is as follows:
acquiring the access position of a real-time strange visitor, and marking the access position of the real-time strange visitor as a destination position; simultaneously marking the entry position of the real-time strange visitor as a starting position; collecting routes of a starting position and a final position, and marking the routes as preset access routes; acquiring the average pedestrian number per hour in a preset access route and the total station ratio of the camera monitoring area in the preset access route, and respectively marking the average pedestrian number per hour in the preset access route and the total station ratio of the camera monitoring area in the preset access route as RSL and ZZB; obtaining an analysis coefficient LX of a preset access route through a formula LX = beta (RSL multiplied by b1+ ZZB multiplied by b 2), wherein b1 and b2 are both preset proportionality coefficients, b1 is larger than b2 and larger than 0, and beta is an error correction factor and takes a value of 1.36;
comparing the analysis coefficient of the preset access route with an analysis coefficient threshold value:
if the analysis coefficient of the preset access route is larger than or equal to the analysis coefficient threshold value, judging that the corresponding preset access route is qualified, and marking the corresponding preset access route as a selected route; sorting the selected routes according to the sequence of the analysis coefficient values from large to small, marking the selected route sorted first as a preferred route, and marking the selected route sorted second as a standby route; sending the preferred route and the standby route to a mobile phone terminal of a security worker; if the analysis coefficient of the preset access route is smaller than the analysis coefficient threshold value, judging that the corresponding preset access route is unqualified, and marking the corresponding preset access route as an unselected route; and marking the unselected routes as forbidden routes, and sending the forbidden routes to the mobile phone terminal of the security personnel.
As a preferred embodiment of the present invention, the monitoring process of the process monitoring unit is as follows:
acquiring the average moving speed of the real-time strange visitor on the preferred route and the stay time of the real-time strange visitor on the preferred route, and comparing the average moving speed of the real-time strange visitor on the preferred route and the stay time of the real-time strange visitor on the preferred route with a moving speed threshold range and a stay time threshold range respectively:
if the average moving speed of the real-time stranger in the preferred route is not within the moving speed threshold range or the stay time of the real-time stranger in the preferred route is not within the stay time threshold range, judging that the access of the corresponding real-time stranger is abnormal, generating a real-time monitoring signal and sending the real-time monitoring signal to a mobile phone terminal of a security worker, and the security worker receives the real-time monitoring signal and then monitors the stranger in real time through a camera; if the average moving speed of the real-time strange visitor on the preferred route is within the moving speed threshold range or the stay time of the real-time strange visitor on the preferred route is within the stay time threshold range, judging that the corresponding real-time strange visitor has normal access, generating a no-abnormal signal and sending the no-abnormal signal to the mobile phone terminal of the security personnel.
A visitor information management verification method based on artificial intelligence comprises the following steps:
the method comprises the steps that firstly, a visitor verification management platform analyzes a visitor entering a campus in real time, and when the visitor enters the campus in real time, a server generates an identity verification signal and sends the identity verification signal to an identity verification unit;
step two; analyzing the real-time visitor through an identity verification unit, dividing the real-time visitor into a familiar visitor and a strange visitor, and respectively sending the familiar visitor and the strange visitor to a familiar visitor management platform and a strange visitor management platform;
after the familiar visitor management platform receives the familiar access signal and the familiar visitor, the history analysis unit analyzes the familiar visitor and the data recording unit records data;
and step four, after receiving the unfamiliar access signal and the unfamiliar visitor, the unfamiliar access management platform generates an access control signal and sends the access control signal to the access control unit, the access control unit performs access control on the real-time unfamiliar visitor, and the process monitoring unit performs real-time access process monitoring on the real-time unfamiliar visitor.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the visitors entering the campus in real time are analyzed, the safety factor in the campus is increased, and the potential safety hazards of teachers, students and equipment in the campus are reduced; judging the access state of the familiar visitor, and preventing the access abnormality of the familiar visitor from causing the reduction of the safety coefficient in the campus; access control is carried out on real-time unfamiliar visitors, random route matching is carried out on the real-time unfamiliar visitors, and the situation that the safety coefficient of a campus is reduced due to the fact that the unfamiliar visitors cannot be controlled in real time when entering the campus is prevented; and monitoring the real-time access process of the strange visitors, judging whether the access process of the strange visitors in the campus is normal or not, and preventing dangerous accidents in advance.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a functional block diagram of the present invention;
FIG. 2 is a functional block diagram of a familiar guest management platform;
fig. 3 is a functional block diagram of a strange guest management platform.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-3, an artificial intelligence based visitor information management verification system includes a visitor verification management platform, in which a server, an identity verification unit, a familiar visitor management platform and a strange visitor management platform are disposed; a history analysis unit and a data recording unit are arranged in the familiar visitor management platform; an access control unit and a process monitoring unit are arranged in the unfamiliar visitor management platform;
the visitor verification management platform is used for analyzing visitors entering the campus in real time, increasing the safety factor in the campus and reducing the potential safety hazards of teachers, students and equipment in the campus; when the visitor enters in real time, the server generates an authentication signal and sends the authentication signal to the authentication unit, the authentication unit is used for analyzing the real-time visitor and judging the type of the real-time visitor, the type of the real-time visitor comprises a familiar visitor and a strange visitor, and the specific authentication process is as follows:
the method comprises the steps of collecting a real-time visitor face photo in real time, comparing the real-time visitor face photo collected in real time with a historical visitor face photo in a database, marking the real-time visitor as i, wherein i is a natural number larger than 1, collecting historical access times, frequency and average access duration of the real-time visitor, and respectively marking the historical access times, the frequency and the average access duration of the real-time visitor as CSi, PLi and SCi;
by the formula
Obtaining an identity verification coefficient Xi of the real-time visitor, wherein a1, a2 and a3 are all preset proportionality coefficients, and a1 is more than a2 > a3 > 0; the identity authentication coefficient of the real-time visitor is a numerical value used for judging the probability of judging whether the real-time visitor is a familiar visitor or not by carrying out normalization processing on the parameter of the real-time visitor; the larger the historical access times, frequency and average access duration of the real-time visitor can be obtained through a formula, the larger the identity verification coefficient of the real-time visitor is, and the larger the probability that the real-time visitor is a familiar visitor is;
comparing the identity verification coefficient of the real-time visitor with an identity verification coefficient threshold:
if the identity authentication coefficient of the real-time visitor is larger than or equal to the identity authentication coefficient threshold value, the opposite real-time visitor is judged as a familiar visitor, a familiar access signal is generated, and the familiar access signal and the familiar visitor are sent to a familiar visitor management platform; if the identity verification coefficient of the real-time visitor is less than the identity verification coefficient threshold value, judging the real-time visitor as an unfamiliar visitor, generating an unfamiliar access signal and sending the unfamiliar access signal and the unfamiliar visitor to an unfamiliar visitor management platform;
after the familiar visitor management platform receives the familiar access signal and the familiar visitor, the familiar visitor is analyzed through the history analysis unit, the visiting state of the familiar visitor is judged, the visiting abnormality of the familiar visitor is prevented, the safety factor in the campus is reduced, and the specific analysis process is as follows:
acquiring historical access frequency and historical longest access time of a familiar visitor, and comparing the historical access frequency and the historical longest access time of the familiar visitor with a historical access frequency threshold range and a historical access time threshold range respectively:
if the historical access frequency of the familiar visitor is larger than the threshold range of the historical access frequency and the historical longest access time is larger than the threshold range of the historical access time, judging that the corresponding familiar visitor is abnormal in access, generating a familiar access abnormal signal and sending the familiar access abnormal signal to a data recording unit;
if the historical access frequency of the familiar visitor is not greater than the threshold range of the historical access frequency and the historical longest access time is not greater than the threshold range of the historical access time, judging that the corresponding familiar visitor has normal access, generating a familiar access normal signal and sending the familiar access normal signal to a data recording unit;
the data recording unit monitors the corresponding familiar visitor after receiving the familiar access abnormal signal and the corresponding familiar visitor, acquires an access position of the corresponding familiar visitor and an access time length of the corresponding position, judges that the familiar visitor needs to perform identity monitoring in real time if the access position of the familiar visitor is a first access position and the access time length of the corresponding position exceeds a corresponding time length threshold value, generates a real-time monitoring signal and sends the real-time monitoring signal and the corresponding familiar visitor to a mobile phone terminal of a security worker; after the data recording unit receives the familiar visiting normal signal and the corresponding familiar visitor, the data recording unit records and stores the access time and the real-time visiting date of the corresponding familiar visitor;
after receiving the unfamiliar access signal and the unfamiliar visitor, the unfamiliar access management platform generates an access control signal and sends the access control signal to the access control unit, the access control unit is used for performing access control on the real-time unfamiliar visitor and performing random route matching on the real-time unfamiliar visitor, so that the situation that the unfamiliar visitor cannot perform real-time control when entering a campus and safety factors in the campus are reduced is prevented, and the specific control process is as follows:
acquiring the access position of a real-time strange visitor, and marking the access position of the real-time strange visitor as a destination position; simultaneously marking the entry position of the real-time strange visitor as a starting position; collecting routes of a starting position and a final position, and marking the routes as preset access routes; acquiring the average pedestrian number per hour in a preset access route and the total station ratio of the camera monitoring area in the preset access route, and respectively marking the average pedestrian number per hour in the preset access route and the total station ratio of the camera monitoring area in the preset access route as RSL and ZZB; obtaining an analysis coefficient LX of a preset access route through a formula LX = beta (RSL multiplied by b1+ ZZB multiplied by b 2), wherein b1 and b2 are both preset proportionality coefficients, b1 is larger than b2 and larger than 0, and beta is an error correction factor and takes a value of 1.36;
comparing the analysis coefficient of the preset access route with an analysis coefficient threshold value:
if the analysis coefficient of the preset access route is larger than or equal to the analysis coefficient threshold value, judging that the corresponding preset access route is qualified, and marking the corresponding preset access route as a selected route; sorting the selected routes according to the sequence of the analysis coefficient values from large to small, marking the selected route sorted first as a preferred route, and marking the selected route sorted second as a standby route; sending the preferred route and the standby route to a mobile phone terminal of a security worker;
if the analysis coefficient of the preset access route is smaller than the analysis coefficient threshold value, judging that the corresponding preset access route is unqualified, and marking the corresponding preset access route as an unselected route; marking the unselected routes as forbidden routes, and sending the forbidden routes to the mobile phone terminal of the security personnel;
after security personnel set preferred routes for real-time strange visitors, the strange visitor management platform generates process monitoring signals and sends the process monitoring signals to the process monitoring unit, the process monitoring unit is used for carrying out real-time access process monitoring on the real-time strange visitors, whether the access process of the strange visitors in a campus is normal or not is judged, dangerous accidents are prevented in advance, and the specific monitoring process is as follows:
acquiring the average moving speed of the real-time stranger on the preferred route and the stay time of the real-time stranger on the preferred route, and comparing the average moving speed of the real-time stranger on the preferred route and the stay time of the real-time stranger on the preferred route with a moving speed threshold range and a stay time threshold range respectively:
if the average moving speed of the real-time stranger in the preferred route is not within the moving speed threshold range or the stay time of the real-time stranger in the preferred route is not within the stay time threshold range, judging that the access of the corresponding real-time stranger is abnormal, generating a real-time monitoring signal and sending the real-time monitoring signal to a mobile phone terminal of a security worker, and the security worker receives the real-time monitoring signal and then monitors the stranger in real time through a camera; if the average moving speed of the real-time stranger in the preferred route is within the moving speed threshold range or the stay time of the real-time stranger in the preferred route is within the stay time threshold range, judging that the corresponding real-time stranger has normal access, generating an abnormal-free signal and sending the abnormal-free signal to a mobile phone terminal of a security worker.
The formulas are obtained by acquiring a large amount of data and performing software simulation, and the coefficients in the formulas are set by the technicians in the field according to actual conditions;
when the system is used, the visitor verification management platform is used for analyzing visitors entering a campus in real time, and when the visitors enter the campus in real time, the server generates an identity verification signal and sends the identity verification signal to the identity verification unit; the method comprises the steps that a real-time visitor is analyzed through an identity verification unit, the real-time visitor is divided into a familiar visitor and a strange visitor through analysis, and the familiar visitor and the strange visitor are respectively sent to a familiar visitor management platform and a strange visitor management platform; after the familiar visitor management platform receives the familiar access signal and the familiar visitor, the familiar visitor is analyzed through the history analysis unit; data recording is carried out through a data recording unit; after the unfamiliar access management platform receives the unfamiliar access signal and the unfamiliar visitor, an access control signal is generated and sent to the access control unit, and the access control unit is used for performing access control on the unfamiliar visitor in real time; and monitoring the real-time access process of the real-time stranger through a process monitoring unit.
Based on another concept of the same invention, a visitor information management verification method based on artificial intelligence is provided, and the method comprises the following steps:
the method comprises the steps that firstly, a visitor verification management platform analyzes a visitor entering a campus in real time, and when the visitor enters the campus in real time, a server generates an identity verification signal and sends the identity verification signal to an identity verification unit;
step two; analyzing the real-time visitor through an identity verification unit, dividing the real-time visitor into a familiar visitor and a strange visitor, and respectively sending the familiar visitor and the strange visitor to a familiar visitor management platform and a strange visitor management platform;
after the familiar visitor management platform receives the familiar access signal and the familiar visitor, the history analysis unit analyzes the familiar visitor and the data recording unit records data;
and step four, after receiving the unfamiliar access signal and the unfamiliar visitor, the unfamiliar access management platform generates an access control signal and sends the access control signal to the access control unit, the access control unit performs access control on the real-time unfamiliar visitor, and the process monitoring unit performs real-time access process monitoring on the real-time unfamiliar visitor.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (6)
1. A visitor information management verification system based on artificial intelligence is characterized by comprising a visitor verification management platform, wherein a server, an identity verification unit, a familiar visitor management platform and a strange visitor management platform are arranged in the visitor verification management platform; a history analysis unit and a data recording unit are arranged in the familiar visitor management platform; an access control unit and a process monitoring unit are arranged in the unfamiliar visitor management platform;
the visitor verification management platform is used for analyzing visitors entering the campus in real time, and when the visitors enter the campus in real time, the server generates an identity verification signal and sends the identity verification signal to the identity verification unit; analyzing the real-time visitor through an identity verification unit, dividing the real-time visitor into a familiar visitor and a strange visitor through analysis, and respectively sending the familiar visitor and the strange visitor to a familiar visitor management platform and a strange visitor management platform; after the familiar visitor management platform receives the familiar access signal and the familiar visitor, the familiar visitor is analyzed through the history analysis unit; data recording is carried out through a data recording unit; after the unfamiliar access management platform receives the unfamiliar access signal and the unfamiliar visitor, an access control signal is generated and sent to the access control unit, and the access control unit is used for performing access control on the unfamiliar visitor in real time; monitoring a real-time access process of the real-time strange visitor through a process monitoring unit;
the control procedure of the access control unit is as follows:
acquiring the access position of a real-time strange visitor, and marking the access position of the real-time strange visitor as a destination position; simultaneously marking the entry position of the real-time strange visitor as a starting position; collecting routes of a starting position and a final position, and marking the routes as preset access routes; acquiring the average pedestrian number per hour in a preset access route and the total station ratio of the camera monitoring area in the preset access route, and respectively marking the average pedestrian number per hour in the preset access route and the total station ratio of the camera monitoring area in the preset access route as RSL and ZZB; obtaining an analysis coefficient LX of a preset access route through a formula LX = beta (RSL multiplied by b1+ ZZB multiplied by b 2), wherein b1 and b2 are both preset proportionality coefficients, b1 is larger than b2 and larger than 0, and beta is an error correction factor and takes a value of 1.36;
comparing an analysis coefficient of a preset access route with an analysis coefficient threshold:
if the analysis coefficient of the preset access route is larger than or equal to the analysis coefficient threshold value, judging that the corresponding preset access route is qualified, and marking the corresponding preset access route as a selected route; sorting the selected routes according to the sequence of the analysis coefficient values from large to small, marking the selected route sorted first as a preferred route, and marking the selected route sorted second as a standby route; sending the preferred route and the standby route to a mobile phone terminal of a security worker; if the analysis coefficient of the preset access route is smaller than the analysis coefficient threshold value, judging that the corresponding preset access route is unqualified, and marking the corresponding preset access route as an unselected route; and marking the unselected routes as forbidden routes, and sending the forbidden routes to the mobile phone terminal of the security personnel.
2. The system as claimed in claim 1, wherein the authentication process of the authentication unit is as follows:
the method comprises the steps of collecting a real-time visitor face photo in real time, comparing the real-time visitor face photo collected in real time with a historical visitor face photo in a database, marking the real-time visitor as i, wherein i is a natural number larger than 1, collecting historical access times, frequency and average access duration of the real-time visitor, and respectively marking the historical access times, the frequency and the average access duration of the real-time visitor as CSi, PLi and SCi;
by the formula
Acquiring an identity verification coefficient Xi of a real-time visitor, wherein a1, a2 and a3 are all preset proportionality coefficients, and a1 is greater than a2 and is greater than a3 and is greater than 0; comparing the identity verification coefficient of the real-time visitor with an identity verification coefficient threshold:
if the identity authentication coefficient of the real-time visitor is larger than or equal to the identity authentication coefficient threshold value, the opposite real-time visitor is judged as a familiar visitor, a familiar access signal is generated, and the familiar access signal and the familiar visitor are sent to a familiar visitor management platform; if the identity verification coefficient of the real-time visitor is smaller than the identity verification coefficient threshold value, the real-time visitor is judged as an unfamiliar visitor, an unfamiliar access signal is generated, and the unfamiliar access signal and the unfamiliar visitor are sent to an unfamiliar visitor management platform.
3. The system as claimed in claim 1, wherein the history analysis unit analyzes as follows:
acquiring historical access frequency and historical longest access time of a familiar visitor, and comparing the historical access frequency and the historical longest access time of the familiar visitor with a historical access frequency threshold range and a historical access time threshold range respectively:
if the historical access frequency of the familiar visitor is larger than the threshold range of the historical access frequency and the historical longest access time is larger than the threshold range of the historical access time, judging that the access of the corresponding familiar visitor is abnormal, generating a familiar access abnormal signal and sending the familiar access abnormal signal to a data recording unit;
and if the historical access frequency of the familiar visitor is not greater than the threshold range of the historical access frequency and the historical longest access time is not greater than the threshold range of the historical access time, judging that the corresponding familiar visitor has normal access, generating a familiar access normal signal and sending the familiar access normal signal to the data recording unit.
4. The visitor information management and verification system based on artificial intelligence as claimed in claim 3, wherein the data recording unit monitors the corresponding familiar visitor after receiving the familiar visitor abnormal signal and the corresponding familiar visitor, acquires the visiting position of the corresponding familiar visitor and the visiting duration of the corresponding position, determines that the familiar visitor needs to perform identity monitoring in real time if the visiting position of the familiar visitor is the first visiting position and the visiting duration of the corresponding position exceeds the corresponding duration threshold, generates a real-time monitoring signal and sends the real-time monitoring signal and the corresponding familiar visitor to the mobile phone terminal of the security personnel; and after receiving the familiar access normal signal and the corresponding familiar visitor, the data recording unit records and saves the access time and the real-time access date of the corresponding familiar visitor.
5. The system as claimed in claim 1, wherein the monitoring process of the process monitoring unit is as follows:
acquiring the average moving speed of the real-time strange visitor on the preferred route and the stay time of the real-time strange visitor on the preferred route, and comparing the average moving speed of the real-time strange visitor on the preferred route and the stay time of the real-time strange visitor on the preferred route with a moving speed threshold range and a stay time threshold range respectively:
if the average moving speed of the real-time stranger in the preferred route is not within the moving speed threshold range or the stay time of the real-time stranger in the preferred route is not within the stay time threshold range, judging that the access of the corresponding real-time stranger is abnormal, generating a real-time monitoring signal and sending the real-time monitoring signal to a mobile phone terminal of a security worker, and the security worker monitors stranger in real time through a camera after receiving the real-time monitoring signal; if the average moving speed of the real-time strange visitor on the preferred route is within the moving speed threshold range or the stay time of the real-time strange visitor on the preferred route is within the stay time threshold range, judging that the corresponding real-time strange visitor has normal access, generating a no-abnormal signal and sending the no-abnormal signal to the mobile phone terminal of the security personnel.
6. A visitor information management verification method based on artificial intelligence is characterized by comprising the following steps:
the method comprises the steps that firstly, a visitor verification management platform analyzes visitors entering a campus in real time, and when the visitors enter the campus in real time, a server generates an identity verification signal and sends the identity verification signal to an identity verification unit;
step two; analyzing the real-time visitor through an identity verification unit, dividing the real-time visitor into a familiar visitor and a strange visitor, and respectively sending the familiar visitor and the strange visitor to a familiar visitor management platform and a strange visitor management platform;
thirdly, after the familiar visitor management platform receives the familiar access signal and the familiar visitor, the history analysis unit analyzes the familiar visitor and the data recording unit records data;
step four, after the unfamiliar access management platform receives the unfamiliar access signal and the unfamiliar visitor, an access control signal is generated and sent to an access control unit, the access control unit performs access control on the real-time unfamiliar visitor, and a process monitoring unit performs real-time access process monitoring on the real-time unfamiliar visitor; the control procedure of the access control unit is as follows:
acquiring the access position of a real-time strange visitor, and marking the access position of the real-time strange visitor as a destination position; simultaneously marking the entry position of the real-time strange visitor as a starting position; collecting routes of a starting position and a final position, and marking the routes as preset access routes; acquiring the average pedestrian number per hour in a preset access route and the total station ratio of the camera monitoring area in the preset access route, and respectively marking the average pedestrian number per hour in the preset access route and the total station ratio of the camera monitoring area in the preset access route as RSL and ZZB; obtaining an analysis coefficient LX of a preset access route through a formula LX = beta (RSL multiplied by b1+ ZZB multiplied by b 2), wherein b1 and b2 are both preset proportionality coefficients, b1 is larger than b2 and larger than 0, and beta is an error correction factor and takes a value of 1.36;
comparing the analysis coefficient of the preset access route with an analysis coefficient threshold value:
if the analysis coefficient of the preset access route is larger than or equal to the analysis coefficient threshold value, judging that the corresponding preset access route is qualified, and marking the corresponding preset access route as a selected route; sorting the selected routes according to the sequence of the analysis coefficient values from large to small, marking the selected route sorted first as a preferred route, and marking the selected route sorted second as a standby route; sending the preferred route and the standby route to a mobile phone terminal of a security worker; if the analysis coefficient of the preset access route is smaller than the analysis coefficient threshold value, judging that the corresponding preset access route is unqualified, and marking the corresponding preset access route as an unselected route; and marking the unselected routes as forbidden routes, and sending the forbidden routes to the mobile phone terminal of the security personnel.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102445933A (en) * | 2011-10-14 | 2012-05-09 | 兰泽华 | System for monitoring, alarming and managing farmland greenhouses based on Internet of things |
| CN107576311A (en) * | 2017-08-23 | 2018-01-12 | 长江水利委员会长江科学院 | A kind of reservoir inspection method of real-time based on three-dimension GIS |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9405978B2 (en) * | 2013-06-10 | 2016-08-02 | Globalfoundries Inc. | Prioritization of facial recognition matches based on likely route |
| CN107911653B (en) * | 2017-11-16 | 2021-01-01 | 王磊 | Intelligent video monitoring module, system, method and storage medium for residence |
| CN110807344A (en) * | 2018-08-01 | 2020-02-18 | 深圳云天励飞技术有限公司 | Special user monitoring method and equipment based on image analysis and storage medium |
| CN109243026B (en) * | 2018-09-03 | 2022-01-11 | 日立楼宇技术（广州）有限公司 | Visitor management method and system |
| CN110634211A (en) * | 2019-08-05 | 2019-12-31 | 深圳市大拿科技有限公司 | Visiting reminding method and related equipment |
| CN111212385A (en) * | 2020-01-15 | 2020-05-29 | 浙江博诚信息技术有限公司 | Visitor management method based on positioning of Internet of things |
| CN112527934A (en) * | 2020-12-09 | 2021-03-19 | 深圳市天彦通信股份有限公司 | Visitor travel analysis method and device, electronic equipment and storage medium |
-
2021
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102445933A (en) * | 2011-10-14 | 2012-05-09 | 兰泽华 | System for monitoring, alarming and managing farmland greenhouses based on Internet of things |
| CN107576311A (en) * | 2017-08-23 | 2018-01-12 | 长江水利委员会长江科学院 | A kind of reservoir inspection method of real-time based on three-dimension GIS |
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