Community Visitor Management Method and System Based on AI Technology

Abstract

The present invention relates to the field of security technologies, and particularly to a community visitor management method and system based on AI technology. When the method of the present invention uses a front-end interaction device to obtain a first face image of a visitor, it simultaneously uses a matrix pressure sensing device to continuously monitor the pressure matrix of the visitor on the ground. Then, based on a face recognition algorithm, the first face image is matched with the images in a pre-registered face image library. If the match is successful, an opening instruction is sent to the access control device, and the access control opening time is recorded. Then, the pressure gradient difference and modulus value of the pressure matrix after the access control opening time are calculated. Finally, it is continuously determined whether any of the following conditions is satisfied: the pressure gradient difference is less than or equal to 0; the pressure gradient difference is greater than 0 and the modulus value is less than the pressure threshold. If neither is satisfied, a tailgating alarm is issued. Compared with the prior art, the method of the present invention solves the problem of the failure of the tailgating alarm in an outdoor environment.

Description

Technical Field

[0001] The present invention relates to the field of security technologies, and particularly to a community visitor management method and system based on AI technology. Background Art

[0002] A community visitor management system is an intelligent system specifically used to manage the entry and exit of community visitors, which can improve community security. It generally consists of a front-end interaction device, an access control device, a back-end management device, and a mobile application terminal. Before a non-community resident visitor applies to enter the community, they generally need to use the mobile application terminal to register visit information with the back-end management device, and then go to the front-end interaction device to use AI face recognition technology to determine whether it is the person himself. If so, the access control device gate is opened to let the visitor pass. At the moment when the visitor passes through the access control device, multiple groups of infrared sensors are usually installed inside the access control device at upper, middle, and lower positions to detect whether a single person passes. If a single person passes, the characteristic of the infrared signal detection is only a section of infrared distance detection data. At this time, the visitor is safely released. If there are multiple sections of distance detection data in time sequence, a tailing alarm is issued, indicating that there is a suspicious person tailing the visitor into the community.

[0003] However, the application of infrared sensors in outdoor environments has obvious defects and is difficult to meet the actual outdoor needs. Specifically, the outdoor environment is complex and changeable, and factors such as direct sunlight, wind-blown tree shadows, smoke and dust may interfere with the infrared signal, causing the effective detection distance of the infrared sensor to change and affecting the accuracy of the sensor. When a suspicious person tails a visitor into the community, the infrared sensor is affected by such external factors and often fails to detect the suspicious person, resulting in the failure of the tailing alarm, which is a major hidden danger to community security. Summary of the Invention

[0004] The present invention provides a community visitor management method and system based on AI technology to solve the problem of the failure of the tailing alarm in the outdoor environment in the prior art.

[0005] In a first aspect, the present invention discloses a community visitor management method based on AI technology for a community visitor management system provided with a matrix pressure sensing device outdoors. The method of the present invention includes:

[0006] When using the front-end interaction device to obtain the first face image of the visitor, simultaneously use the matrix pressure sensing device to real-time monitor the pressure matrix of the visitor on the ground;

[0007] Based on the face recognition algorithm, match the first face image with the images in the pre-registered face image library. If the match is successful, send an opening instruction to the access control device and record the access control opening time;

[0008] Calculate the pressure gradient difference and its modulus value of the pressure matrix after the access control opening time; the calculation formula for the pressure gradient difference is:

[0009]

[0010] where , is the access control opening time, is the pressure gradient difference, is at moment pressure matrix 's pressure gradient, is at moment pressure matrix 's pressure gradient;

[0011] Continuously determine whether any of the following conditions are met: the pressure gradient difference is less than or equal to 0; the pressure gradient difference is greater than 0 and the modulus value is less than the pressure threshold;

[0012] If neither is satisfied, issue a tailgating alarm.

[0013] Beneficial effects: The method of the present invention is specifically used for outdoor environments. This method first uses a parallel process to obtain the first face image and the pressure matrix in real time. After the face recognition algorithm passes the recognition and issues the access control opening, the pressure gradient difference and its modulus value are continuously calculated. If the pressure gradient difference after the access control opening time is less than or equal to 0, it means that a single person is passing normally or a device with a linearly increasing pressure is passing. If the pressure gradient difference is greater than 0 and the modulus value is less than the pressure threshold, it means that a single person is carrying a child. If neither of the above two conditions is met, it means that there is a possibility of multiple people tailgating, and a tailgating alarm is issued. Compared with the prior art, the method of the present invention uses a matrix pressure sensing device to obtain the detection information related to tailgating, and uses the analysis of the pressure matrix data to judge whether there is a tailgating behavior after the access control is opened. This method is less affected by interference factors in the outdoor environment and solves the problem that the existing infrared sensing technology is prone to tailgating detection failure in the outdoor environment.

[0014] Preferably, at moment pressure matrix 's pressure gradient calculation formula is:

[0015]

[0016] In the formula, represents the pressure gradient of the pressure matrix at moment, represents the pressure matrix at moment, represents at The pressure matrix at a moment, indicating from the time interval to

[0017] Preferably, the calculation formula for the modulus value is:

[0018]

[0019] In the formula, is the modulus of the pressure matrix at the moment , is the number of rows of the pressure matrix, is the number of columns of the pressure matrix.

[0020] Preferably, before calculating the pressure gradient difference and modulus value of the pressure matrix, the method of the present invention further includes:

[0021] If , replace the value of with 1.

[0022] Beneficial effect: Normalize the pressure values greater than 0 in the pressure matrix to exclude the interference caused by different weights of different visitors, which is beneficial to data analysis of the pressure matrix, and further improves the accuracy and reliability of the trailing judgment of the present invention.

[0023] Preferably, the calculation formula for the pressure threshold is:

[0024]

[0025] In the formula, is the pressure threshold, is the number of rows of the pressure matrix, is the number of columns of the pressure matrix, is the pressure matrix at the access control opening time , is the proportionality coefficient.

[0026] Beneficial effect: Through the above algorithm design, the pressure threshold will be adaptively adjusted according to the characteristics of the pressure matrix of the visitor after face recognition, so as to improve the accuracy of trailing detection.

[0027] Preferably, the value range of the proportionality coefficient is 0.25 - 0.5.

[0028] Preferably, the face recognition algorithm adopts a multi-frame recognition algorithm, and matches the first face image with the images in the pre-registered face image library, specifically:

[0029] Calculate the single-frame matching degree of each frame of the first face image and the second face image in the face image library;

[0030] Calculate the matching mean of multiple single-frame matching degrees;

[0031] Determine whether the matching mean is higher than the matching threshold. If so, the matching is successful.

[0032] Beneficial effects: By continuously capturing the face information of visitors, obtaining multiple consecutive frames of first face images, and calculating the matching degrees between the multiple first face images and the second face image, the accuracy of face recognition can be improved, and the problem of insufficient accuracy of single-frame capture recognition can be avoided.

[0033] Preferably, before using the front-end interaction device to obtain the first face image of the visitor, the method of the present invention further includes:

[0034] Identify whether the visitor is located in the visitor passage. If so, obtain the first face image of the visitor; if not, send a suspension service pop-up window to the visitor.

[0035] Beneficial effects: The method of the present invention can weakly guide the visitor to go to the visitor passage for face recognition and stress monitoring. This method realizes dedicated channels and reduces the impact of visitors' inquiries in the community on the daily entry and exit of local community residents.

[0036] Preferably, when matching the first face image with the images in the pre-registered face image library and if the matching fails, the method of the present invention further includes:

[0037] Read the temporary access request of the mobile application terminal;

[0038] Verify whether the information of the temporary access request includes the identity ID, access area, and contact phone number. If so, send an opening instruction to the access control device.

[0039] Beneficial effects: If the visitor has not registered face information in advance, the access control device can be opened by applying for a temporary access request. This method improves the flexibility and convenience of the method of the present invention.

[0040] In a second aspect, the present invention further provides a community visitor management system based on AI technology, including a processor and a memory. The memory stores computer program instructions for implementing the community visitor management method based on AI technology. When the computer program instructions are executed by the processor, the community visitor management method based on AI technology in the first aspect is implemented.

[0041] The beneficial effects of the present invention are as follows:

[0042] (1)Compared with the prior art, the method of the present invention uses a matrix pressure sensing device to obtain detection information related to tailgating, and analyzes the pressure matrix data to determine whether there is a tailgating behavior after the access control is opened. This method is less affected by outdoor environmental interference factors and solves the problem that the existing infrared sensing technology is prone to tailgating detection failure in outdoor environments.

[0043] (2)Compared with the prior art, the method of the present invention normalizes the pressure values greater than 0 in the pressure matrix to exclude the interference caused by different weights of different visitors, which is beneficial to the data analysis of the pressure matrix, and further improves the accuracy and reliability of the present invention for tailgating judgment.

[0044] (3)Compared with the prior art, the pressure threshold of the method of the present invention is adaptively adjusted according to the characteristics of the pressure matrix of the visitor himself to improve the accuracy of tailgating detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a flowchart of the community visitor management method based on AI technology in Embodiment 1 of the present invention;

[0046] Figure 2 It is a pressure matrix change diagram of a single person passing through the access control device in Embodiment 1 of the present invention;

[0047] Figure 3 It is a pressure matrix change diagram of a suitcase passing through the access control device in Embodiment 1 of the present invention;

[0048] Figure 4 It is a pressure matrix change diagram of an adult tailgating through the access control device in Embodiment 1 of the present invention;

[0049] Figure 5 It is a structural schematic diagram of the community visitor management device based on AI technology in Embodiment 2 of the present invention;

[0050] Figure 6 It is a structural schematic diagram of the community visitor management system based on AI technology in Embodiment 3 of the present invention.

[0051] Reference numerals: 100, front-end interaction device; 200, matrix pressure sensing device; 300, backend management device; 400, access control device. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments.

[0053] Next, the specific implementation manners of the present invention will be described in detail with reference to the accompanying drawings.

[0054] This embodiment discloses a community visitor management method and system based on AI technology, mainly used to solve the problem of the failure of trailing alarms in outdoor environments in the prior art.

[0055] Embodiment 1

[0056] As Figure 1 shown, this embodiment discloses a community visitor management method based on AI technology, which is used for a community visitor management system equipped with a matrix pressure sensing device outdoors. The method of the present invention includes:

[0057] S10: When acquiring the first face image of a visitor using a front-end interaction device, simultaneously use the matrix pressure sensing device to continuously monitor the pressure matrix of the visitor on the ground.

[0058] S20: Based on the face recognition algorithm, match the first face image with the images in the pre-registered face image library. If the match is successful, send an opening instruction to the access control device and record the access control opening time.

[0059] S30: Calculate the pressure gradient difference and modulus value of the pressure matrix after the access control opening time.

[0060] S40: Continuously determine whether any of the following conditions are met:

[0061] Condition 1: The pressure gradient difference is less than or equal to 0;

[0062] Condition 2: The pressure gradient difference is greater than 0 and the modulus value is less than the pressure threshold;

[0063] S50: If neither is met, send a trailing alarm.

[0064] Through the above technical solutions S10 - S50, the method of the present invention analyzes the pressure matrix data of single-person passage using the time frame after face recognition is passed. If the pressure gradient difference is less than or equal to 0, it indicates single-person passage or passage of a device with linearly increasing pressure change. If the pressure gradient difference is greater than 0, it may indicate passage with a child or multiple people. At this time, the modulus value of the pressure matrix is introduced for comparison with the pressure threshold. If Condition 2 is met, it indicates the situation of carrying a child and passage is allowed; otherwise, it indicates the situation of multiple people trailing and a trailing alarm is sent. Compared with the prior art, the method of the present invention is more suitable for outdoor environments. By using pressure matrix data to analyze trailing scenarios, it is hardly affected by factors such as direct sunlight, wind-blown tree shadows, smoke, and dust outdoors, and solves the problem of the failure of infrared trailing detection in outdoor environments.

[0065] It should be noted that the device with linearly increasing pressure change can be a flatbed cart, a handcart, a luggage case or other load-carrying vehicles. These devices are all equipped with wheels, and their pressure change characteristics generally show linear increase or linear decrease. The front-end interaction device in the above S10 mainly includes a display screen and a camera. The camera continuously captures photos of the visitors, and multiple first face images are extracted based on multiple photos. Among them, the first face image information obtained from a single photo should include information such as the face contour and the three-part and five-eye ratio. The hardware width and length of the matrix pressure sensing device in the above S10 are adaptively designed according to the actual situation. The monitoring of pressure sensing data and the image monitoring of the front-end interaction device belong to the parallel monitoring process.

[0066] In order to realize the guidance for visitors to enter and exit, before S10, the method of the present invention further includes:

[0067] Identifying whether the visitor is located in the visitor passage. If so, execute S10.

[0068] If not, a pop-up window for suspending service is sent to the visitor.

[0069] It should be further noted that the above pop-up window for suspending service is displayed on the display screen of the front-end interaction device. When a visitor wants to enter the community through a non-visitor passage, the corresponding passage will deny service until the visitor goes to the visitor passage to participate in face recognition, so as to achieve weak guidance.

[0070] In this embodiment, the face recognition algorithm in the above S20 adopts a multi-frame recognition algorithm. The specific process of matching the first face image with the images in the pre-registered face image library in the above S20 is as follows:

[0071] S21: Calculate the single-frame matching degree between each frame of the first face image and the second face image in the face image library;

[0072] S22: Calculate the matching mean value of multiple single-frame matching degrees;

[0073] S23: Judge whether the matching mean value is higher than the matching threshold. If so, the matching is successful.

[0074] Through the above S21-S23 scheme, the method of the present invention continuously captures the face information of the visitor to obtain multiple consecutive frames of the first face image, then calculates the matching degree between the multiple first face images and the second face image, and then adds up the multiple matching degrees and takes the average value as the final matching mean value output. This way can improve the accuracy of face recognition to avoid the problem of insufficient accuracy of single-frame capture recognition. In addition, the above scheme can also provide assistance for extending the steady state time of the matrix pressure sensing device to a certain extent.

[0075] Furthermore, if the face image information fails to match, the method of the present invention further includes:

[0076] S200: Read the temporary access request from the mobile application terminal.

[0077] S201: Verify whether the information of the temporary access request includes the identity ID, access area, and contact phone number. If so, send an opening instruction to the access control device.

[0078] It should be noted that in some special cases, a face matching degree lower than the preset threshold does not necessarily mean that the visitor is a suspicious person. It is also possible that the visitor forgot to register the face information in advance. For this situation, the above technical solutions S200 - S201 can provide a temporary access application channel for the visitor to meet the actual needs of the visitor.

[0079] In this embodiment, after the access control device is opened, it closes 3s after the matrix pressure sensing device stops being stressed.

[0080] Further, calculate the pressure gradient difference of the pressure matrix after the access control opening time in the above S30, specifically:

[0081] (1)

[0082] In the formula, , is the access control opening time, is the pressure gradient difference, is the pressure gradient of the pressure matrix at the moment pressure matrix , is the pressure gradient of the pressure matrix at the moment pressure matrix .

[0083] Further, the calculation formula for the pressure gradient of the pressure matrix at the moment pressure matrix is:

[0084] (2)

[0085] In the formula, represents the pressure gradient of the pressure matrix at the moment , represents the pressure matrix at the moment , represents the pressure matrix at the moment , represents to time interval.

[0086] Further, the calculation formula for the modulus value in S30 above is:

[0087] (3)

[0088] In the formula, is the modulus of the pressure matrix at moment, is the number of rows of the pressure matrix, is the number of columns of the pressure matrix.

[0089] Further, the calculation formula for the pressure threshold in S40 above is:

[0090] (4)

[0091] In the formula, is the pressure threshold, is the number of rows of the pressure matrix, is the number of columns of the pressure matrix, is the pressure matrix at the access control opening time , is the proportionality coefficient.

[0092] It should be added that during the process of obtaining the pressure values of the pressure matrix, the pressure values of each matrix unit are different, which is mainly affected by factors such as the center of gravity or weight of the human body. In order to eliminate the influence of the center of gravity and weight factors, in this embodiment, as Figures 2 - 4 shown, before calculating the pressure gradient difference and modulus value of the pressure matrix, the method of the present invention further includes: if , replace the value of with 1. This way of normalizing the pressure values is beneficial to data analysis of the change trend of the pressure matrix, and thus improves the accuracy and reliability of the method of the present invention for trailing judgment.

[0093] Combining Figure 2 shown, it can be seen that during the process of a single person passing through the access control device, the change of its pressure matrix shows a non-linear sudden drop trend. Therefore, the overall pressure gradient shows a downward trend, and the corresponding gradient difference is negative or 0 (0 represents a constant speed decrease or no change).

[0094] Specifically, the data monitoring table for a single person passing through the access control device is:

[0095] Table 1

[0096]

[0097] As Figure 3As shown, during the forward movement of the luggage, the changing trend of its pressure matrix is first linear increase, then constant, and then linear decrease. The change of the pressure matrix generated during its movement conforms to the above Condition 1 and Condition 2. Specifically, the data monitoring table of the luggage is as follows:

[0098] Table 2

[0099]

[0100] As Figure 4 shown, if there are other adults passing through after the face recognition object has passed through, the pressure matrix will increase non-linearly. At this time, the pressure gradient difference will suddenly become a positive value. Specifically, the data monitoring table of the adult trailing behavior is as follows:

[0101] Table 3

[0102]

[0103] As shown in Table 3, when there is an adult trailing, at the moment when a single foot steps into the matrix pressure sensing device, neither the pressure gradient difference nor the pressure modulus value meets Conditions 1 and 2, and at this time, a trailing alarm will be triggered.

[0104] Through the above formulas (1)-(4), more accurate data analysis of the pressure matrix change can be carried out to obtain more accurate calculation results. Among them, the pressure threshold calculated in formula (4) can be adaptively adjusted according to the face recognition object itself. The pressure threshold is based on the modulus when the recognition object stands on both feet, and then multiplied by the pressure coefficient as its threshold. This method can combine the proportional coefficient to adaptively adjust the threshold, which is approximately equivalent to identifying and limiting the threshold according to the foot size of the recognition object. This method is beneficial to improving the accuracy of trailing detection.

[0105] Preferably, the above proportional coefficient has a value range of 0.25 - 0.5. Generally, in order to improve the accuracy of the method of the present invention, the above takes 0.5. This proportional coefficient can basically be used to distinguish the adult foot sole area and the child foot sole area. Generally, the single foot sole range of an adult is , and the height is in . The single foot sole area of a 3 - 6-year-old child is , and the height is in . Children with a height lower than generally enjoy free ticket discounts or exemption from real-name authentication, and basically do not require face recognition authentication. Therefore, they should be released under the accompaniment of an adult. Considering the different contact areas of adults and 3 - 6-year-old children when stepping into the matrix pressure sensing device with a single foot, the foot sole area of a 3 - 6-year-old child is , so based on the above proportionality coefficient and the above formula (4), adult following access and child following access can be distinguished.

[0106] Embodiment 2

[0107] As Figure 5 shown, this embodiment discloses a community visitor management device based on AI technology. This device uses the community visitor management method based on AI technology described in Embodiment 1 to implement visitor face recognition and trailing detection alarm. The device of the present invention includes a front-end interaction device 100, a matrix pressure sensing device 200, a back-end management device 300, and an access control device 400.

[0108] Specifically, the front-end interaction device 100 is composed of a camera and a display screen. It is set at the front end of the access control device 400 and is used to obtain the first face image of the visitor. The matrix pressure sensing device 200 is set at the front end of the visitor passage and is used to monitor the pressure matrix of the visitor on the ground in real time. The back-end management device 300 is composed of a face recognition module, a pressure gradient difference calculation module, and a trailing alarm module. Its face recognition module is used to match the first face image with the images in the pre-registered face image database based on the face recognition algorithm. If the match is successful, an opening instruction is sent to the access control device 400, and the access control opening time is recorded. The pressure gradient difference calculation module is used to calculate the pressure gradient difference and modulus value of the pressure matrix after the access control opening time. As for the trailing alarm module, it is used to continuously judge whether any of the following conditions is met: whether the pressure gradient difference is less than or equal to 0; the pressure gradient difference is greater than 0 and the modulus value is less than the pressure threshold; if neither is met, a trailing alarm is issued. The access control device 400 is used to open the gate when receiving the opening instruction.

[0109] In this embodiment, the matrix pressure sensing device 200 can adopt an 8×8 flexible thin-film pressure sensor, and its model can be M0808M. Its size can be customized according to actual needs. The periphery of the matrix pressure sensing device 200 can be wrapped with elastic resin to achieve the effect of waterproof protection. In addition, grooves adapted to the shoe surface can be opened at the top of the matrix pressure sensing device 200.

[0110] In other embodiments, the matrix pressure sensing device 200 can be composed of a plurality of pressure sensors (strain gauges) distributed in a matrix.

[0111] It should be added that the more the number of rows and columns of the matrix pressure sensing device 200, the higher the accuracy of detecting trailing by the method of the present invention. In other embodiments, flexible thin-film pressure sensors with more rows and columns can be selected.

[0112] Preferably, the device of the present invention can be applied to application scenarios such as nurseries, kindergartens, medical care communities, or ticket check platforms that require "one person per gate".

[0113] Compared with the prior art, the device of the present invention is equipped with a face recognition algorithm and a pressure tailing detection algorithm, which can accurately identify visitors and issue an alarm for tailing behavior, with stronger reliability and higher security.

[0114] Embodiment III

[0115] As Figure 6 shown, this embodiment provides a community visitor management system based on AI technology, including a processor and a memory. The memory stores computer program instructions for implementing the community visitor management method based on AI technology. When the computer program instructions are executed by the processor, the community visitor management method based on AI technology in the first aspect is implemented.

Claims

1. A community visitor management method based on AI technology, characterized in that: include: When the front-end interactive device (100) is used to obtain a first facial image of a visitor, a matrix pressure sensing device (200) is simultaneously used to monitor in real time the pressure matrix of the visitor on the ground; Based on a face recognition algorithm, the first face image is matched with an image in a pre-registered face image library, and if the match is successful, an opening instruction is sent to the access control device (400), and the access control opening time is recorded; Calculate the pressure gradient difference and modulus of the pressure matrix after the access control opening time; the calculation formula of the pressure gradient difference is: ,in, , The access control opening time. is the pressure gradient difference, For time Pressure Matrix The pressure gradient, For time Pressure Matrix The pressure gradient; The calculation formula of the modulus value is: , where For The modulus of the moment pressure matrix, is the number of rows in the pressure matrix, is the number of columns of the pressure matrix; Before calculating the pressure gradient difference and the modulus of the pressure matrix, the method further comprises: if ,Will The value of is replaced with 1; Continuously judging whether any of the following conditions is met: the pressure gradient difference is less than or equal to 0; the pressure gradient difference is greater than 0 and the modulus value is less than a pressure threshold; If none of the conditions are met, a tailing alarm will be issued.

2. The community visitor management method based on AI technology according to claim 1 is characterized in that: exist time Pressure Matrix The pressure gradient is calculated as: In the formula, Represents the pressure matrix exist The pressure gradient at that moment, Indicated in The pressure matrix of the moment, Indicated in The pressure matrix of the moment, express arrive time interval.

3. The community visitor management method based on AI technology according to claim 1 is characterized in that: The calculation formula of the pressure threshold is: In the formula, is the pressure threshold, is the number of rows in the pressure matrix, is the number of columns of the pressure matrix, The time when the door is opened The pressure matrix, is the proportionality coefficient.

4. The community visitor management method based on AI technology according to claim 3 is characterized in that: The proportionality factor The value range is 0.25-0.

5.

5. The community visitor management method based on AI technology according to claim 1 is characterized in that: The face recognition algorithm uses a multi-frame recognition algorithm to match the first face image with images in a pre-registered face image library, specifically: Calculate the single frame matching degree between each frame of the first face image and the second face image in the face image library; Calculate the matching mean of multiple single-frame matching degrees; It is determined whether the matching mean is higher than the matching threshold, and if so, the matching is successful.

6. The community visitor management method based on AI technology according to claim 1 is characterized in that: Before using the front-end interactive device (100) to obtain the first facial image of the visitor, the method further comprises: Identify whether the visitor is in the visitor channel. If so, obtain the visitor's first facial image; if not, send a service suspension pop-up window to the visitor.

7. The community visitor management method based on AI technology according to claim 1 is characterized in that: Matching the first face image with images in a pre-registered face image library, if the match fails, the method further includes: Read the temporary access request from the mobile application terminal; Verify whether the information of the temporary access request contains the identity ID, access area and contact number, and if so, send an opening command to the access control device (400).

8. A community visitor management system based on AI technology, characterized in that: It includes a processor and a memory, the memory stores computer program instructions for implementing a community visitor management method based on AI technology, and when the computer program instructions are executed by the processor, the community visitor management method based on AI technology as described in any one of claims 1-7 is implemented.

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