CN111352171A - Method and system for realizing artificial intelligence regional shielding security inspection - Google Patents
Method and system for realizing artificial intelligence regional shielding security inspection Download PDFInfo
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- CN111352171A CN111352171A CN202010237647.1A CN202010237647A CN111352171A CN 111352171 A CN111352171 A CN 111352171A CN 202010237647 A CN202010237647 A CN 202010237647A CN 111352171 A CN111352171 A CN 111352171A
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Abstract
The embodiment of the application provides a method and a system for realizing artificial intelligence regional shielding security inspection. The method comprises the following steps: when a pedestrian passes through the first security inspection opening, the pedestrian puts the area authentication material into the area identification device, and the area identification device determines an area with characters and patterns in the area authentication material to obtain character area characteristics in the characters; combining the regional characteristics and the character regional characteristics, and sending the regional characteristics and the character regional characteristics to a data center; the data center carries out data query to obtain the travel information of the pedestrian, carries out region classification according to the travel information and returns the travel information to the region identification device; the region identification device closes an outlet channel of the first security inspection port, performs first security inspection on pedestrians, determines a next channel of the first security inspection port according to region classification, and opens the next channel to allow the pedestrians to pass after the first security inspection is qualified; the pedestrian gets into second safety inspection mouth through next passageway, and second safety inspection mouth prepares second safety inspection equipment according to regional classification simultaneously, carries out the safety inspection to the pedestrian. This application is through the efficiency that has improved the safety inspection.
Description
Technical Field
The application relates to the field of artificial intelligence, in particular to a method and a system for realizing shielding security check of an artificial intelligence area.
Background
In the security inspection of areas with a high frequency of population movement, such as railway stations, airports, etc., there are times when additional inspections are required for persons with specific characteristics (e.g., from a specified area, with a specified trip). In the current security inspection process, people are mainly screened manually by security inspection personnel to be subjected to additional inspection, so that on one hand, the manual labor intensity of the security inspection personnel is high, the information of the inspected personnel can be leaked, and even double-shot conflict can be caused; on the other hand, the accuracy is not high by only depending on the sampling inspection of security personnel, and a large number of inspected personnel are likely to be missed.
With the continuous development of the artificial intelligence technology, the method can effectively help people to reduce the trouble caused by repeated labor. The artificial intelligence technology is applied to the field of security inspection, and the labor intensity of security inspection personnel can be greatly reduced.
Disclosure of Invention
In view of this, an object of the present application is to provide a method and a system for implementing artificial intelligence regional screening security inspection, which improve security inspection efficiency and solve the technical problem that in the current public health incident, different levels of security inspection need to be efficiently performed on pedestrians in different regions.
Based on the above purpose, the present application provides a method for implementing artificial intelligence regional shielding security inspection, which includes:
arranging an area identification device at a first security inspection port, when a pedestrian passes through the first security inspection port, putting an area authentication material into the area identification device by the pedestrian, determining an area with characters and patterns in the area authentication material by the area identification device, obtaining pattern area characteristics in the material through image identification, and obtaining character area characteristics in the characters through named entity identification; combining the region features and the character region features, obtaining the region identification of the pedestrian through semantic expansion, and sending the region identification to a data center;
the data center carries out data query according to the area identification to obtain the travel information of the pedestrian, carries out area classification according to the travel information and returns the area classification to the area identification device;
the area identification device closes an outlet channel of the first security inspection port, performs first security inspection on the pedestrian, determines a next channel of the first security inspection port according to the area classification, and opens the next channel to allow the pedestrian to pass after the first security inspection is qualified;
and the pedestrian enters a second security inspection port through the next channel, and meanwhile, second security inspection equipment is prepared by the second security inspection port according to the region classification to perform security inspection on the pedestrian.
In some embodiments, the method further comprises:
and taking the second security inspection port as a new first security inspection port, taking the second security inspection device as a new first security inspection device, taking the third security inspection port as a new second security inspection port, taking the third security inspection device as a new second security inspection device, and repeating the iteration until the security inspection requirements of all the regions are met.
In some embodiments, the method further comprises:
inquiring historical security check records according to the area identification of the pedestrian, and judging whether the pedestrian has a security check problem record;
and if the safety inspection accident record exists, classifying the pedestrian into an upgrade safety inspection type, and sending a safety inspection prompt.
In some embodiments, the data center performs data query according to the area identifier to obtain the travel information of the pedestrian, and performs area classification according to the travel information, including:
the data center inquires the travel information of the pedestrian in a specified time period according to the area identification;
and sorting according to the residence time of the pedestrian in each area in the journey.
In some embodiments, the area identification device closes an exit passage of the first security inspection opening, performs a first security inspection on the pedestrian, and determines a next passage of the first security inspection opening according to the area classification, and opens the next passage to allow the pedestrian to pass after the first security inspection is qualified, including:
if the pedestrian has a security inspection problem in the first security inspection process, returning the security inspection problem to the data center;
and the data center predicts the next channel of the pedestrian according to the case problem and the area identification of the pedestrian.
In some embodiments, combining the pattern region feature and the text region feature, obtaining the region identifier of the pedestrian through semantic expansion, including:
and recording the characteristic vector of the pattern region characteristic as R ═ R1，r2……，rnAnd n is the dimension of the pattern area feature, and the feature vector of the character area feature is recorded as P ═ P1，p2……，pmAnd m is the dimension of the character area feature, and the R and the P are subjected to place name analysis and duplication removal respectively to obtain a pattern place name feature vector
And literal place name feature vector
For the feature vector of the pattern place name
And literal place name feature vector
And performing intersection operation to obtain the area identification of the pedestrian.
Based on the above-mentioned purpose, this application has still provided a system for realizing regional shielding security check of artificial intelligence, includes:
the identification module is used for arranging an area identification device at a first security inspection port, when a pedestrian passes through the first security inspection port, the pedestrian puts an area authentication material into the area identification device, the area identification device determines an area with characters and patterns in the area authentication material, pattern area characteristics in the material are obtained through image identification, and character area characteristics in the characters are obtained through named entity identification; combining the region features and the character region features, obtaining the region identification of the pedestrian through semantic expansion, and sending the region identification to a data center;
the query module is used for the data center to perform data query according to the area identification to obtain the travel information of the pedestrian, perform area classification according to the travel information and return the area classification to the area identification device;
the releasing module is used for closing an outlet channel of the first security inspection port by the region identification device, performing first security inspection on the pedestrian, determining a next channel of the first security inspection port according to the region classification, and opening the next channel to release the pedestrian after the first security inspection is qualified;
and the rechecking module is used for enabling the pedestrian to enter a second security inspection port through the next channel, and meanwhile, preparing second security inspection equipment by the second security inspection port according to the region classification to perform security inspection on the pedestrian.
In some embodiments, the system further comprises:
and the iteration module is used for taking the second security inspection port as a new first security inspection port, taking the second security inspection equipment as new first security inspection equipment, taking the third security inspection port as a new second security inspection port, taking the third security inspection equipment as new second security inspection equipment, and iterating until the security inspection requirements of all regions are met.
In some embodiments, the system further comprises:
the judging module is used for inquiring historical security check records according to the area identification of the pedestrian and judging whether the pedestrian has security check problem records;
and the prompt module is used for classifying the pedestrian into an upgrade security inspection type if a security inspection accident record exists, and sending a security inspection prompt.
In some embodiments, the passing module comprises:
the return unit is used for returning the security inspection problem to the data center if the pedestrian has the security inspection problem in the first security inspection process;
and the prediction unit is used for predicting the next channel of the pedestrian by the data center according to the case problem and the area identification of the pedestrian.
In summary, the idea of the present application is that an area identification device is disposed at a first security inspection opening, when a pedestrian passes through the first security inspection opening, the pedestrian puts an area authentication material into the area identification device, and the area identification device identifies an area identifier of the pedestrian according to the authentication material and sends the area identifier to a data center; the data center carries out data query according to the area identification to obtain the travel information of the pedestrian, carries out area classification according to the travel information and returns the area classification to the area identification device; the area identification device closes an outlet channel of the first security inspection port, performs first security inspection on the pedestrian, sets a next channel of the first security inspection port according to the area classification, and opens the next channel to allow the pedestrian to pass; and the pedestrian enters a second security inspection port through the next channel, and meanwhile, second security inspection equipment is prepared by the second security inspection port according to the region classification to perform security inspection on the pedestrian.
The invention can solve the problems of overlong queue, low accuracy of manual operation of security personnel, high difficulty of contact inspection and epidemic prevention and the like when the pedestrians from different area sources need to be classified and security inspected in the current security inspection process.
Drawings
In the drawings, like reference numerals refer to the same or similar parts or elements throughout the several views unless otherwise specified. The figures are not necessarily to scale. It is appreciated that these drawings depict only some embodiments in accordance with the disclosure and are therefore not to be considered limiting of its scope.
FIG. 1 shows a flowchart of a method for implementing an artificial intelligence regional screening security inspection according to an embodiment of the present invention.
FIG. 2 shows a flowchart of a method for implementing an artificial intelligence regional screening security inspection, according to an embodiment of the invention.
FIG. 3 shows a flowchart of a method for implementing an artificial intelligence regional screening security inspection, according to an embodiment of the invention.
Fig. 4 shows a block diagram of a security inspection system implementing artificial intelligence region screening according to an embodiment of the present invention.
Fig. 5 shows a block diagram of a security inspection system implementing artificial intelligence region screening according to an embodiment of the present invention.
Fig. 6 shows a block diagram of a security inspection system implementing artificial intelligence region screening according to an embodiment of the present invention.
Fig. 7 shows a configuration diagram of a pass module according to an embodiment of the present invention.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
FIG. 1 shows a flowchart of a method for implementing an artificial intelligence regional screening security inspection according to an embodiment of the present invention. As shown in fig. 1, the method for implementing artificial intelligence regional shielding security inspection includes:
step S11, arranging an area identification device at a first security inspection opening, when a pedestrian passes through the first security inspection opening, putting an area authentication material into the area identification device by the pedestrian, determining an area with characters and patterns in the area authentication material by the area identification device, obtaining pattern area characteristics in the material through image identification, and obtaining character area characteristics in the characters through named entity identification; and combining the region features and the character region features, obtaining the region identification of the pedestrian through semantic expansion, and sending the region identification to a data center.
For example, the pedestrian can put his own ticket, travel itinerary or identification card, even the image-text material containing the travel information such as the travel diary, etc. into the area identification device, the area identification device locates the areas of the pattern and the text in the area identification material, and then obtains the characteristics of the pattern and the text area in the area identification material by respectively adopting the pattern and the text identification method. The area identifications are obtained through semantic expansion, for example, if pictures of the old palace in the travel diary are recognized, it can be inferred that the pedestrian goes to Beijing, and if the pedestrian goes to Beijing, the pedestrian possibly also goes to the great wall, so that a plurality of area identifications of the pedestrian are obtained.
In one embodiment, combining the pattern region feature and the character region feature to obtain the region identifier of the pedestrian through semantic expansion, the method includes:
and recording the characteristic vector of the pattern region characteristic as R ═ R1，r2……，rnAnd n is the dimension of the pattern area feature, and the feature vector of the character area feature is recorded as P ═ P1，p2……，pmAnd m is the dimension of the character area feature, and the R and the P are subjected to place name analysis and duplication removal respectively to obtain a pattern place name feature vector
And literal place name feature vector
For the feature vector of the pattern place name
And literal place name feature vector
And performing intersection operation to obtain the area identification of the pedestrian.
Through semantic understanding, intersection operation is carried out on the pattern place name feature vector and the character place name feature vector, and duplicate removal can be carried out on the same place names in two vector sets. For example, the pedestrian may have text recording of the content of the beijing in the travel diary, or may have taken a photograph of the beijing, which may cause the beijing to be included in both the pattern place name feature vector and the text place name feature vector, and at this time, the duplication eliminating operation is required, thereby reducing the time complexity of the post-processing.
And step S12, the data center carries out data query according to the area identification to obtain the travel information of the pedestrian, carries out area classification according to the travel information, and returns the area classification to the area identification device.
In an embodiment, the data center performs data query according to the area identifier to obtain the travel information of the pedestrian, and performs area classification according to the travel information, including:
the data center inquires the travel information of the pedestrian in a specified time period according to the area identification;
and sorting according to the residence time of the pedestrian in each area in the journey.
For example, the formation of pedestrians can be classified, and the pedestrians who stay in martian in the past 14 days need to be subjected to secondary security inspection.
And S13, closing an outlet channel of the first security inspection port by the region identification device, performing first security inspection on the pedestrian, determining a next channel of the first security inspection port according to the region classification, and opening the next channel to allow the pedestrian to pass after the first security inspection is qualified.
In one embodiment, the area identification device closes an exit passage of the first security inspection opening, performs a first security inspection on the pedestrian, determines a next passage of the first security inspection opening according to the area classification, and opens the next passage to allow the pedestrian to pass after the first security inspection is qualified, and the area identification device includes:
if the pedestrian has a security inspection problem in the first security inspection process, returning the security inspection problem to the data center;
and the data center predicts the next channel of the pedestrian according to the case problem and the area identification of the pedestrian.
Specifically, the first security check may be set to a regular security check, that is, to accept the inspection of the first security check regardless of where the pedestrian comes from and whether shielding is required. Then, multi-level and multi-level security inspection ports can be arranged according to needs, for example, a second security inspection port, a third security inspection port and the like can be arranged, and different security inspection requirements of pedestrians in different areas and different characteristics can be met.
And step S14, enabling the pedestrian to enter a second security inspection port through the next channel, and simultaneously preparing second security inspection equipment by the second security inspection port according to the region classification to perform security inspection on the pedestrian.
FIG. 2 shows a flowchart of a method for implementing an artificial intelligence regional screening security inspection, according to an embodiment of the invention. As shown in fig. 2, the method for implementing artificial intelligence regional shielding security inspection further includes:
and step S15, taking the second security inspection port as a new first security inspection port, taking the second security inspection equipment as new first security inspection equipment, taking the third security inspection port as a new second security inspection port, taking the third security inspection equipment as new second security inspection equipment, and repeating iteration until the security inspection requirements of all regions are met.
Specifically, a multi-level and multi-type security inspection port can be theoretically arranged according to requirements, so that the security inspection requirements of different levels are met.
FIG. 3 shows a flowchart of a method for implementing an artificial intelligence regional screening security inspection, according to an embodiment of the invention. As shown in fig. 3, the method for implementing artificial intelligence regional screening security inspection further includes:
and step S16, according to the area identification of the pedestrian, inquiring historical security check records, and judging whether the pedestrian has security check problem records.
And step S17, if the safety inspection accident record exists, classifying the pedestrian into an upgrade safety inspection type, and sending a safety inspection prompt.
Specifically, the security level of the pedestrian can be improved according to whether the pedestrian has the over-security accident or not in history. For example, a pedestrian has taken dangerous goods to take a public vehicle once, which causes severe safety influence, and at this time, after identifying the historical safety inspection problem record of the pedestrian, the safety inspection type of the pedestrian can be directly upgraded, and attention reminding is given to safety inspection personnel.
Fig. 4 shows a block diagram of a security inspection system implementing artificial intelligence region screening according to an embodiment of the present invention. As shown in fig. 4, the system for implementing artificial intelligence regional screening security inspection includes:
the identification module 41 is configured to set an area identification device at a first security inspection opening, and when a pedestrian passes through the first security inspection opening, the pedestrian puts an area authentication material into the area identification device, the area identification device determines an area with characters and patterns in the area authentication material, obtains pattern area characteristics in the material through image identification, and obtains character area characteristics in the characters through named entity identification; combining the region features and the character region features, obtaining the region identification of the pedestrian through semantic expansion, and sending the region identification to a data center;
the query module 42 is configured to perform data query by the data center according to the area identifier to obtain the travel information of the pedestrian, perform area classification according to the travel information, and return the area classification to the area identification device;
a release module 43, configured to close an exit channel of the first security inspection opening by the area identification device, perform first security inspection on the pedestrian, determine a next channel of the first security inspection opening according to the area classification, and open the next channel to release the pedestrian after the first security inspection is qualified;
and the rechecking module 44 is used for enabling the pedestrian to enter a second security inspection port through the next channel, and meanwhile, preparing second security inspection equipment according to the region classification by the second security inspection port to perform security inspection on the pedestrian.
Fig. 5 shows a block diagram of a security inspection system implementing artificial intelligence region screening according to an embodiment of the present invention. As shown in fig. 5, the system for implementing artificial intelligence regional shielding security inspection further includes:
and the iteration module 45 is configured to use the second security inspection port as a new first security inspection port, use the second security inspection device as a new first security inspection device, use the third security inspection port as a new second security inspection port, use the third security inspection device as a new second security inspection device, and repeat iteration until the security inspection requirements of all the regions are met.
Fig. 6 shows a block diagram of a security inspection system implementing artificial intelligence region screening according to an embodiment of the present invention. As shown in fig. 6, the system for implementing artificial intelligence regional shielding security inspection further includes:
the judging module 46 is configured to query a historical security check record according to the area identifier of the pedestrian, and judge whether the pedestrian has a security check problem record;
and the prompt module 47 is used for classifying the pedestrian into an upgrade security inspection type if a security inspection accident record exists, and sending a security inspection prompt.
Fig. 7 shows a configuration diagram of a pass module according to an embodiment of the present invention. As shown in fig. 7, the releasing module 43 includes:
a returning unit 431, configured to, if a security inspection problem occurs in the process of the first security inspection of the pedestrian, return the security inspection problem to the data center;
and the prediction unit 432 is used for predicting the next channel of the pedestrian by the data center according to the case problem and the area identification of the pedestrian.
The functions of the modules in the systems in the embodiments of the present application may refer to the corresponding descriptions in the above methods, and are not described herein again.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may also be stored in a computer readable storage medium. The storage medium may be a read-only memory, a magnetic or optical disk, or the like.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive various changes or substitutions within the technical scope of the present invention, and these should be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A security inspection method for realizing artificial intelligence region shielding is characterized by comprising the following steps:
arranging an area identification device at a first security inspection port, when a pedestrian passes through the first security inspection port, putting an area authentication material into the area identification device by the pedestrian, determining an area with characters and patterns in the area authentication material by the area identification device, obtaining pattern area characteristics in the material through image identification, and obtaining character area characteristics in the characters through named entity identification; combining the region features and the character region features, obtaining the region identification of the pedestrian through semantic expansion, and sending the region identification to a data center;
the data center carries out data query according to the area identification to obtain the travel information of the pedestrian, carries out area classification according to the travel information and returns the area classification to the area identification device;
the area identification device closes an outlet channel of the first security inspection port, performs first security inspection on the pedestrian, determines a next channel of the first security inspection port according to the area classification, and opens the next channel to allow the pedestrian to pass after the first security inspection is qualified;
and the pedestrian enters a second security inspection port through the next channel, and meanwhile, second security inspection equipment is prepared by the second security inspection port according to the region classification to perform security inspection on the pedestrian.
2. The method of claim 1, further comprising:
and taking the second security inspection port as a new first security inspection port, taking the second security inspection device as a new first security inspection device, taking the third security inspection port as a new second security inspection port, taking the third security inspection device as a new second security inspection device, and repeating the iteration until the security inspection requirements of all the regions are met.
3. The method of claim 1, further comprising:
inquiring historical security check records according to the area identification of the pedestrian, and judging whether the pedestrian has a security check problem record;
and if the safety inspection accident record exists, classifying the pedestrian into an upgrade safety inspection type, and sending a safety inspection prompt.
4. The method of claim 1, wherein the data center performs data query according to the area identifier to obtain the travel information of the pedestrian, and performs area classification according to the travel information, including:
the data center inquires the travel information of the pedestrian in a specified time period according to the area identification;
and sorting according to the residence time of the pedestrian in each area in the journey.
5. The method of claim 1, wherein the area identification device closes an exit passage of the first security inspection opening, performs a first security inspection on the pedestrian, and determines a next passage of the first security inspection opening according to the area classification, and opens the next passage to let the pedestrian pass after the first security inspection is qualified, comprising:
if the pedestrian has a security inspection problem in the first security inspection process, returning the security inspection problem to the data center;
and the data center predicts the next channel of the pedestrian according to the case problem and the area identification of the pedestrian.
6. The method according to claim 1, wherein obtaining the pedestrian region identifier by semantic expansion in combination with the pattern region feature and the text region feature comprises:
and recording the characteristic vector of the pattern region characteristic as R ═ R1，r2……，rnAnd n is the dimension of the pattern area feature, and the feature vector of the character area feature is recorded as P ═ P1，p2……，pmWherein m is said letterDimension of the region feature, and place name analysis and duplication removal are respectively carried out on the R and the P to obtain pattern place name feature vectors
And literal place name feature vector
For the feature vector of the pattern place name
And literal place name feature vector
And performing intersection operation to obtain the area identification of the pedestrian.
7. The utility model provides a realize regional security check platform who shields of artificial intelligence which characterized in that includes:
the identification module is used for arranging an area identification device at a first security inspection port, when a pedestrian passes through the first security inspection port, the pedestrian puts an area authentication material into the area identification device, the area identification device determines an area with characters and patterns in the area authentication material, pattern area characteristics in the material are obtained through image identification, and character area characteristics in the characters are obtained through named entity identification; combining the region features and the character region features, obtaining the region identification of the pedestrian through semantic expansion, and sending the region identification to a data center;
the query module is used for the data center to perform data query according to the area identification to obtain the travel information of the pedestrian, perform area classification according to the travel information and return the area classification to the area identification device;
the releasing module is used for closing an outlet channel of the first security inspection port by the region identification device, performing first security inspection on the pedestrian, determining a next channel of the first security inspection port according to the region classification, and opening the next channel to release the pedestrian after the first security inspection is qualified;
and the rechecking module is used for enabling the pedestrian to enter a second security inspection port through the next channel, and meanwhile, preparing second security inspection equipment by the second security inspection port according to the region classification to perform security inspection on the pedestrian.
8. The system of claim 7, further comprising:
and the iteration module is used for taking the second security inspection port as a new first security inspection port, taking the second security inspection equipment as new first security inspection equipment, taking the third security inspection port as a new second security inspection port, taking the third security inspection equipment as new second security inspection equipment, and iterating until the security inspection requirements of all regions are met.
9. The system of claim 7, further comprising:
the judging module is used for inquiring historical security check records according to the area identification of the pedestrian and judging whether the pedestrian has security check problem records;
and the prompt module is used for classifying the pedestrian into an upgrade security inspection type if a security inspection accident record exists, and sending a security inspection prompt.
10. The system of claim 7, wherein the clearance module comprises:
the return unit is used for returning the security inspection problem to the data center if the pedestrian has the security inspection problem in the first security inspection process;
and the prediction unit is used for predicting the next channel of the pedestrian by the data center according to the case problem and the area identification of the pedestrian.
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