Passenger customs inspection method, system and customs inspection device

Abstract

The application provides a passenger customs clearance inspection method, system and customs clearance inspection device. The method comprises arranging a face recognition device and a sensor in a customs clearance area, capturing target facial features of passengers in real time, and collecting position information of the passengers; comparing the target facial features with pre-stored identity information in a background database; analyzing the position information to obtain moving tracks and staying time of the passengers, and continuously evaluating whether there is abnormal behavior; when the identity information comparison result and the abnormal behavior are both qualified, a risk evaluation program is not triggered, and the passenger is automatically guided to a customs clearance port; when either the identity information comparison result or the abnormal behavior is unqualified, the risk evaluation program is triggered. The system comprises a feature extraction module, a behavior evaluation module and a risk evaluation module. The device comprises a camera, a sensor, a background database, a controller, a power supply and a display device. The application establishes a more intelligent, automated and safe customs clearance system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data mining and analysis, and particularly relates to a passenger customs inspection method and system and a customs inspection device. BACKGROUND

[0002] Passenger identity verification refers to a process of confirming and verifying the identity information of a traveler through certain methods and technologies. It usually occurs at immigration, security check or other occasions where personal identity needs to be confirmed to ensure that the passenger's identity is legal and true. The specific content of identity verification includes but is not limited to the following aspects: basic identity information confirmation, biometric technology, background information query and behavior analysis, etc. The significance of passenger identity verification is security protection, improvement of customs efficiency, enhancement of legal compliance, data-driven decision-making and improvement of travel experience, etc. Passenger identity verification is not only an important part of immigration management and security protection, but also an indispensable part of modern intelligent transportation and tourism system; through effective identity verification measures, multiple benefits can be provided for social security, economic development and passenger experience. However, the existing passenger customs relies too much on personnel operation, which not only wastes time and effort and reduces the efficiency of customs inspection, but also easily misses key information.

[0003] Prior art one, application number: CN202410242180.8 discloses a passenger customs inspection management method and device and electronic equipment, the method comprises: acquiring the face image of a target passenger newly entering the inspection channel; based on the wireless signal strength of the mobile device carried by the target passenger, querying a pre-set fingerprint library to determine the position information corresponding to the target passenger; associating the face image and the position information to generate the pedestrian trajectory corresponding to the target passenger, and updating the position information in the pedestrian trajectory in real time; determining the stay time of each target passenger in the inspection channel and the number of people staying in the inspection channel according to the pedestrian trajectory of each target passenger in the inspection channel; determining and executing the corresponding intervention strategy according to the stay time of each target passenger and the number of people staying in the inspection channel. Although it can accurately identify and timely respond to the personnel staying in the inspection channel, thereby improving the efficiency of passenger customs, it does not involve analysis of passenger identity information, resulting in the need to improve the accuracy of obtaining passenger information.

[0004] The prior art two, application number: CN202111677091.9 discloses an airport passenger whole-process customs clearance method based on face recognition technology, establishes a whole customs clearance platform system, the platform system constructs a cloud and each independent airport node, and forms a cloud identity library of each process service point in the cloud and a local identity library of each process service point in each airport node. When customs clearance, the passenger certificate information and the face biometric information are combined to form unique identity information data. Each service point collects the on-site face photo, extracts the face photo feature code, uploads the face photo feature code to the cloud for comparison, perfects the cloud identity library or sends the airport node for comparison and perfects the local identity library, so as to sequentially clear the whole process of check-in, security check and boarding. Although the platform system is a passenger identity information management and control center with unified service, unified standard and unified operation and maintenance, real-time scheduling operation is realized, and the application goal of "one-time registration, lifelong use, smooth and worry-free travel" is realized. However, the operation process is relatively simple, the passenger security check information inspection content is less, and the safety of information query is not conducive to play.

[0005] The prior art three, application number: CN202311746224.2 discloses an inspection system and method, comprising: a passenger information acquisition subsystem configured to acquire the identity information of a passing passenger; a luggage information acquisition subsystem configured to acquire the luggage information of the passenger; a data interface subsystem configured to interface with an associated party to obtain the associated party information of the passenger and / or the luggage; an association binding subsystem connected to the passenger information acquisition subsystem, the luggage information acquisition subsystem and the data interface subsystem, and configured to associate and match the passenger according to the identity information, the luggage information and the associated party information, to form an associated and bound passenger customs clearance data chain; and an identification and interception subsystem configured to determine a target passenger or luggage based on the passenger customs clearance data chain to perform interception prompting. Although the efficiency and accuracy of luggage information matching are improved, the analysis of passenger identity information is not involved, resulting in low intelligence degree of the system.

[0006] At present, the prior art one, the prior art two and the prior art three have problems of low accuracy of data deep mining and analysis in the customs clearance process, and low efficiency of customs clearance process and management. Therefore, the present application provides a passenger customs clearance inspection method, system and customs clearance inspection device. SUMMARY

[0007] In order to solve the above technical problems, the present application provides a passenger customs clearance inspection method, comprising the following steps:

[0008] Arranging face recognition devices and sensors in the customs clearance area to capture the target facial features of the passengers in real time and collect the position information of the passengers;

[0009] The target facial features are compared with pre-stored identity information in a background database; the position information is analyzed to obtain the moving track and stay time of the passenger, and it is continuously evaluated whether there is abnormal behavior;

[0010] When both the identity information comparison result and the abnormal behavior are judged to be qualified, the risk assessment program is not triggered, and the passenger will be automatically guided to the customs clearance port; when either the identity information comparison result or the abnormal behavior is judged to be unqualified, the risk assessment program is triggered, and an alarm is given.

[0011] Preferably, the expression for automatically adjusting the angle, focal length and shooting mode of the lens is:

[0012] C actire = f(L, T, P, V)

[0013] In the formula, C actire represents the activation state of the currently enabled face device, 0 represents not activated, and 1 represents activated, L represents the light intensity, the unit is lx, which represents the light environment of the environment, T represents the time period feature, which represents the influence of the time period on the monitoring demand, and is represented by a discrete value, P represents the passenger flow characteristic, which represents the flow rate of the passenger in a certain time period, reflecting the crowd density and flow situation in the area, and V represents the important area coefficient, taking a value between 0 and 1, representing the importance of the current monitoring area, the closer to 1 representing the more important the area;

[0014] Focal length adjustment equation:

[0015]

[0016] Angle adjustment equation:

[0017]

[0018] Shooting mode selection equation:

[0019] M

[0020] = { "LowLight" if L < L threshold and P > P threshold "Standard" if L ≥ L threshold and P ≤ P threshold "HighDetail" if V ≥ 0.8

[0021] In the formula, F represents the focal length, the unit is mm, the focal length setting of the lens of the face device, A represents the angle of the lens, the unit is degree, the shooting angle setting of the face device, k f , k a , k bL represents the coefficient for adjusting the sensitivity of focal length and angle, which needs to be adjusted according to the characteristics of the system, L threshold P represents the threshold of the light intensity, which is a standard set according to the actual monitoring needs, P threshold L represents the threshold of the passenger flow rate, which is determined according to the monitoring focus, L max L represents the threshold of the passenger flow rate, which is determined according to the monitoring focus, L min P represents the maximum and minimum values of the ambient light to ensure the rationality of the adjustment, P peak L represents the threshold of the passenger flow rate, which is determined according to the monitoring focus, L

[0022] Preferably, the process of continuously evaluating whether there is abnormal behavior includes the following steps:

[0023] The moving trajectory of the passenger is analyzed, the position information of each time node is extracted, the moving path of the passenger is drawn through continuous coordinate points, and the dynamic behavior of each passenger in the customs area is captured;

[0024] The dwell time analysis is used to calculate the dwell time of each key position, the dwell time at the security check, passport check and key monitoring points is identified through mathematical comparison of the timestamp data; if the dwell time at a certain position exceeds the threshold determined through historical data analysis, it will be marked as abnormal; the average moving speed of the passenger is calculated in parallel, the acceleration data and position information are combined to monitor the flow state of the passenger in the customs area in real time;

[0025] The current speed of the passenger is compared with the historical data, if the speed is significantly higher than the normal driving speed or the moving speed fluctuates sharply in a short time in the captured moving data, it is judged as potential abnormal behavior.

[0026] Preferably, the process of capturing the dynamic behavior of each passenger in the customs area includes the following steps:

[0027] The data of each sensor is synchronized through the timestamp, the position information of the passenger captured by the sensor is extracted at each time node, continuous coordinate points are generated, and the coordinate points represent the moving trajectory of the passenger in the customs area;

[0028] The moving path of the passenger is drawn by connecting the continuous coordinate points; based on the drawn moving path, the behavior pattern of the passenger is analyzed, and potential abnormal behavior is identified;

[0029] The drawn moving path is compared with the real-time data to dynamically capture the behavior change of the passenger; through real-time monitoring, abnormal changes in the behavior of the passenger are found.

[0030] Preferably, the process of identifying the dwell time at the security check, passport check and other key monitoring points includes the following steps:

[0031] By arranging sensors and face devices at key locations, the position information and corresponding time stamps of passengers are continuously collected in real time; whenever a passenger passes a certain monitoring point, the coordinates and time information of the position are recorded; the continuous time stamp data are paired, and the time difference between each entry and exit of the key location is obtained by subtraction operation, and then the stay time of the passenger at the location is determined;

[0032] The stay time threshold of each key location is set in advance, and the stay time exceeding the set stay time is automatically marked as abnormal by comparing the stay time with the preset threshold;

[0033] By collecting the position information, combining the acceleration data and position coordinates, the position information corresponding to the time stamp is statistically operated, and the moving speed of the passenger between the key locations is calculated.

[0034] Preferably, the process of judging potential abnormal behavior includes the following steps:

[0035] When the passenger moves at the monitoring point, the speed is obtained in real time and recorded;

[0036] The speed of the current passenger is compared with the previously established historical average speed to obtain the existing deviation;

[0037] If the current speed is significantly higher than the set normal range, the state is marked as abnormal; if the speed fluctuation of the monitored passenger exceeds the normal fluctuation range, it is also determined as potential abnormal behavior.

[0038] Preferably, the process of obtaining the existing deviation includes the following steps:

[0039] At the monitoring point, the speed data of the passenger is collected in real time, including the instantaneous speed and moving direction of the passenger; the speed information of the passenger is extracted from the historical monitoring data to construct a historical speed database, including the speed distribution of different time periods and different passenger groups; based on the historical data, the historical average speed of different passenger groups is calculated;

[0040] The real-time speed of the current passenger is compared with the historical average speed of the corresponding passenger group, and the difference between the current speed and the historical average speed, i.e. the speed deviation value, is calculated; the speed deviation value is obtained by calculating the difference between the current speed and the historical average speed, and the deviation value reflects the difference between the current speed and the normal speed pattern;

[0041] The speed deviation value is analyzed to determine whether it exceeds the set normal range, and the normal range is determined by statistical analysis of historical data.

[0042] Preferably, if the speed deviation value is significantly higher than the set normal range, it is determined as potential abnormal behavior; at the same time, the speed fluctuation is analyzed, and if the fluctuation exceeds the normal fluctuation range, it is also determined as potential abnormal behavior.

[0043] The application provides a passenger customs clearance inspection system, comprising:

[0044] A feature extraction module is responsible for arranging face recognition equipment and sensors in the customs clearance area, capturing target facial features of passengers in real time, and collecting position information of passengers.

[0045] A behavior evaluation module is responsible for comparing the target facial features with pre-stored identity information in a background database, analyzing the position information to obtain the moving track and stay time of the passenger, and continuously evaluating whether there is abnormal behavior.

[0046] A risk evaluation module is responsible for not triggering the risk evaluation program when the identity information comparison result and the abnormal behavior are both determined as qualified, and the passenger will be automatically guided to the customs clearance port; when either the identity information comparison result or the abnormal behavior is determined as unqualified, the risk evaluation program is triggered, and an alarm is given.

[0047] The application provides a passenger customs clearance inspection device, comprising a camera, a sensor, a background database, a controller, a power supply and a display device.

[0048] The camera, the sensor, the background database and the display device are connected with the controller, and the power supply is connected with the camera, the sensor, the background database, the controller and the display device.

[0049] The data collection and preprocessing of the present application collects the data of passengers in multiple dimensions in real time through multiple facial image capture devices and sensing devices, including facial images, biometric features (such as iris and fingerprint), moving speed, luggage weight and size, etc.; can quickly extract the facial features of passengers and convert them into digital format for subsequent processing; monitor the location information of passengers in the customs area, including the key positions of entry and exit, generate the moving track and stay time of passengers based on the data. Significance: Through real-time data collection in multiple angles and ways, the system improves the comprehensive understanding of passenger identity and behavior, which helps to lay the foundation for subsequent identity verification and risk assessment; makes the passenger customs process more accurate and efficient, which helps to detect potential risk factors. Identity verification and abnormal behavior analysis compare the real-time extracted target facial features with the pre-stored identity information in the background database, adopt fast image matching algorithm to improve efficiency; analyze the location information and moving track of passengers to detect whether there is abnormal behavior, such as long stay at a certain position or irregular moving mode. Significance: Through identity verification, only legal passengers can pass through, preventing identity fraud and related criminal behavior, thereby maintaining the safety of the customs area; behavior analysis enables the system to actively find potential suspicious behavior, combined with the moving history of passengers, to respond in time and improve the overall safety management capability. Risk assessment and guided decision-making: when the identity information comparison and abnormal behavior detection are both qualified, the passenger will be automatically guided to the customs port to simplify the customs process; once any condition of identity information comparison and abnormal behavior detection is unqualified, the system will trigger the risk assessment program and immediately alarm to inform the security personnel for subsequent processing. Significance: The automatic guiding mechanism greatly improves the efficiency of passenger customs, reduces queuing and waiting time, and optimizes the travel experience of passengers; the risk assessment and alarm mechanism ensures the effectiveness of safety management, and prefers to send more alarms to maintain safety awareness, provides timely and reliable information for security personnel to adjust and flexibly respond to potential risks in time.

[0050] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be achieved and obtained by the structure particularly pointed out in the written description and the accompanying drawings.

[0051] The technical solutions of the present application will be further described in detail below by means of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, to explain the present application, and do not constitute a limitation on the present application. In the drawings:

[0053] Figure 1 For the passenger customs inspection method flowchart in the embodiment 1 of the present application;

[0054] Figure 2 For the process of capturing the target facial features of the passengers in real time in the embodiment 2 of the present application;

[0055] Figure 3 For the process of extracting the target facial features and obtaining the moving track and stay time of the passengers in the embodiment 3 of the present application;

[0056] Figure 4 For the process of dynamically adjusting the lens angle, focal length and mode of the face device in the embodiment 4 of the present application;

[0057] Figure 5 For the process of continuously evaluating whether there is abnormal behavior in the embodiment 5 of the present application;

[0058] Figure 6 For the process of capturing the dynamic behavior of each passenger in the customs area in the embodiment 6 of the present application;

[0059] Figure 7 For the process of identifying the stay time at the security check, passport inspection and other key monitoring points in the embodiment 7 of the present application;

[0060] Figure 8 For the process of judging as potential abnormal behavior in the embodiment 8 of the present application;

[0061] Figure 9 For the process of obtaining the existing deviation in the embodiment 9 of the present application;

[0062] Figure 10 For the process of triggering the risk assessment procedure in the embodiment 10 of the present application;

[0063] Figure 11 For the passenger customs inspection system block diagram in the embodiment 11 of the present application;

[0064] Figure 12 For the passenger customs inspection device principle diagram in the embodiment 12 of the present application. DETAILED DESCRIPTION

[0065] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to explain and illustrate the present application, and are not used to limit the present application.

[0066] The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the description of the application and the appended claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It also will be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0067] The following description refers to the accompanying drawings. Wherever possible, the same reference numbers in different drawings refer to the same or similar elements. The implementation described in the following exemplary embodiments is not meant to represent all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application. In the description of the application, it is to be understood that the terminology used is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. It is also to be understood that the use of "a" or "an", that can be preceded by the terms "comprising", "including", "containing", or "consisting of", does not exclude the addition of one or more other items to the description of the elements or limitations. It is further to be understood that the use of certain specific language makes no representation that any claim is intended to be given to that specific language as originally used nor to any formulation of the application given in any summary portion thereof.

[0068] Embodiment 1: As shown in the figure, the embodiment of the application provides a passenger customs inspection method, comprising the following steps: Figure 1

[0069] S100: Arranging a face recognition device and a sensor in a customs area, capturing target facial features of passengers in real time, and collecting location information of the passengers;

[0070] S200: Comparing the target facial features with pre-stored identity information in a background database; analyzing the location information to obtain a moving track and a stay time of the passengers, and continuously evaluating whether there is abnormal behavior;

[0071] S300: When both the identity information comparison result and the abnormal behavior are judged to be qualified, not triggering a risk assessment program, and the passenger will be automatically guided to a customs clearance port; when either the identity information comparison result or the abnormal behavior is judged to be unqualified, triggering the risk assessment program, and an alarm is given.

[0072] ​The working principle and beneficial effects of the above technical solution are as follows: Firstly, facial recognition devices and sensors are deployed in the customs clearance area to capture the target facial features of passengers in real time and collect their location information. Secondly, the target facial features are compared with the pre-stored identity information in the background database. The location information is analyzed to obtain the passenger's movement trajectory and dwell time, continuously assessing whether there is any abnormal behavior. Finally, if both the identity information comparison result and the abnormal behavior are deemed acceptable, the risk assessment procedure is not triggered, and the passenger will be automatically guided to the customs clearance point. If either the identity information comparison result or the abnormal behavior is deemed unacceptable, the risk assessment procedure is triggered, and an alarm is triggered. Step S100 of the above solution involves data acquisition and preprocessing. By deploying multiple facial image capture devices and sensing devices, passenger data is collected in real time across multiple dimensions, including facial images, biometric features (such as iris and fingerprints), movement speed, luggage weight, and size. This allows for rapid extraction of passenger facial features and conversion into a digital format for subsequent processing. It also monitors the passenger's location information within the customs clearance area, including key entry and exit locations, and generates the passenger's movement trajectory and dwell time based on the data. Significance: By collecting real-time data from multiple angles and methods, the system gains a more comprehensive understanding of passenger identity and behavior, laying the foundation for subsequent identity verification and risk assessment. This makes the passenger clearance process more accurate and efficient, and helps detect potential risk factors. Step S200, identity verification and abnormal behavior analysis, compares the real-time extracted target facial features with pre-stored identity information in the background database, using a fast image matching algorithm to improve efficiency. It also analyzes passenger location information and movement trajectories to detect abnormal behavior, such as prolonged stays in a certain location or irregular movement patterns. Significance: Identity verification ensures that only legitimate passengers can pass, preventing identity fraud and related crimes, thereby maintaining the security of the clearance area. Behavioral analysis enables the system to proactively detect potential suspicious behavior, and combined with passenger movement history, allows for timely responses, improving overall security management capabilities. Step S300 involves risk assessment and guidance decision-making. When both identity verification and abnormal behavior detection are deemed satisfactory, passengers are automatically guided to the clearance point, simplifying the clearance process. If either the identity verification or abnormal behavior fails, the system triggers a risk assessment procedure and immediately alarms, notifying security personnel for further processing. Significance: The automated guidance mechanism significantly improves passenger clearance efficiency, reduces queuing and waiting time, and optimizes the passenger travel experience. The risk assessment and alarm mechanism ensures the effectiveness of security management; it's better to issue more alarms than not to maintain security awareness, providing security personnel with timely and reliable information to facilitate timely adjustments and flexible responses to potential risks.

[0073] In summary, the embodiment improves the accuracy and security of customs clearance through effective data collection, identity verification and risk management. Not only does it reduce congestion and waiting time, but it also enhances the early warning capability of potential risks; it lays the foundation for establishing a more intelligent, automated and secure customs clearance system.

[0074] Embodiment 2: As shown in the embodiment 1, on the basis of the embodiment 1, the real-time capturing of the target facial features of the passenger provided by the embodiment of the application comprises the following steps: Figure 2

[0075] S101: High-definition face devices and face recognition devices are installed at multiple key positions in the customs clearance area to capture facial images of passengers in real time and extract facial features such as facial contours and facial textures; a variety of sensors are arranged in the customs clearance area to monitor the moving speed of the passengers, the weight and size of the luggage, and to collect the location information of the passengers in real time;

[0076] S102: The facial images captured by the face recognition devices are analyzed in real time by image processing algorithms to extract target facial features; the location information collected by the sensors is processed by location analysis to obtain the moving track and the staying time of the passengers;

[0077] S103: The extracted facial features and location information are transmitted to the background database in real time through a wireless network; the background database stores and manages the data.

[0078] ​The working principle and beneficial effects of the above technical solution are: first, high-definition face devices and face recognition devices are installed at multiple key positions in the customs clearance area to capture real-time facial images of passengers and extract facial features such as facial contours and textures; various sensors are arranged in the customs clearance area to monitor the moving speed of passengers, the weight and size of luggage, and collect real-time location information of passengers; second, the facial images captured by the face recognition device are analyzed in real time through image processing algorithms to extract target facial features; the location information collected by the sensors is processed through location analysis to obtain the moving track and stay time of the passengers; finally, the extracted facial features and location information are transmitted in real time to the background database through the wireless network; the background database stores and manages the data. The step S101 device installation and data collection in the above scheme installs high-definition face devices and face recognition devices at multiple key positions in the customs clearance area, so that the system can capture facial images of passengers from all directions and multiple angles, ensuring the comprehensiveness and accuracy of the data. At the same time, the arrangement of various sensors enables the system to monitor the moving speed of passengers, the weight and size of luggage, and the location information of passengers in real time, providing a rich data basis for subsequent analysis. The significance achieved is to ensure comprehensive data collection and lay a foundation for accurate identification and analysis. Through real-time capture and monitoring, the system can timely detect abnormal situations and improve customs clearance efficiency and security. Step S102 image processing and location analysis, the facial images captured by the face recognition device are analyzed in real time through advanced image processing algorithms to accurately extract target facial features such as facial contours and textures; at the same time, the location information collected by the sensors is processed through location analysis to accurately depict the moving track and stay time of the passengers. The significance achieved is that through efficient image processing and location analysis, accurate identification and behavior analysis of passengers are realized; not only helps to improve customs clearance efficiency, but also effectively prevents potential security risks to ensure the safety and smoothness of the customs clearance process. Step S103 data transmission and background management, the extracted facial features and location information are transmitted in real time to the background database through the wireless network to ensure the timeliness and integrity of the data; the background database stores and manages the data to provide reliable support for subsequent data analysis and application. The significance achieved is to ensure real-time data transmission and safe storage, providing protection for the continuous operation and optimization of the system; through the management of the background database, the system can realize comprehensive grasp and dynamic monitoring of passenger information, further improving customs clearance efficiency and security.

[0079] In summary, the embodiment realizes comprehensive and accurate identification and behavior analysis of passengers through multi-level and multi-dimensional technical means, improves customs clearance efficiency, and enhances the safety and reliability of the customs clearance process.

[0080] Embodiment 3: as Figure 3As shown, on the basis of Embodiment 2, the process of extracting the target facial features and obtaining the moving track and stay time of the passenger provided by the present embodiment comprises the following steps:

[0081] S1011: performing denoising processing on the captured facial image, and performing image enhancement processing through histogram equalization;

[0082] S1012: using a Haar feature classifier to locate the facial region in the image, determining the position and size of the face in the image; locating the positions of the key points (eyes, nose, mouth) of the five organs in the detected facial region, and determining the coordinates of the key points; extracting the contours of the face and the five organs through edge detection, performing texture analysis on the facial region through a gray level co-occurrence matrix, and extracting facial texture features;

[0083] S1013: performing real-time processing on the passenger moving speed, luggage weight and size, and position information collected by various sensors (such as infrared sensors, pressure sensors, face devices, etc.), real-time tracking the moving path of the passenger in the customs clearance area, and generating a moving track; according to the moving track, calculating the stay time of the passenger in a specific area.

[0084] The working principle and beneficial effects of the above technical solution are: first, the captured face image is denoised, and image enhancement is performed through histogram equalization; second, the Haar feature classifier is used to locate the face region in the image, determine the position and size of the face in the image; in the detected face region, the positions of the key points of the facial features (eyes, nose, mouth) are located, and the coordinates of the key points are determined; the facial contour and the contours of the facial features are extracted through edge detection, the texture of the face region is analyzed through the gray level co-occurrence matrix, and the texture features of the face are extracted; finally, the passenger moving speed, luggage weight and size and position information collected by various sensors (such as infrared sensors, pressure sensors, face devices, etc.) are processed in real time, the moving path of the passenger in the customs area is tracked in real time, and the moving trajectory is generated; according to the moving trajectory, the stay time of the passenger in a specific area is calculated. The image quality is significantly improved through denoising and histogram equalization in step S1011 of the above scheme; denoising eliminates random noise in the image, and histogram equalization enhances the contrast of the image, making the facial features more clear and visible; high-quality image preprocessing lays a solid foundation for subsequent facial feature extraction, ensuring the accuracy and reliability of face recognition. In step S1012, the facial feature extraction uses the Haar feature classifier to accurately locate the face region, and through the positioning of the key points of the facial features and the contour extraction, high-precision features of the face are obtained; texture analysis further enriches the dimension of the facial features, providing more identification basis. Significance: The fine facial feature extraction technology not only improves the accuracy of recognition, but also enhances the robustness of the system, which can cope with various complex environments and lighting conditions. In step S1013, the passenger moving trajectory analysis, through the data fusion and real-time processing of various sensors, the system can accurately track the moving path of the passenger and calculate the stay time in a specific area; such real-time and accuracy is difficult to match by traditional methods. Significance: Real-time tracking and stay time analysis provide valuable data support for security monitoring and traffic management, which helps to optimize the customs process and improve overall efficiency.

[0085] In summary, the embodiment not only realizes efficient and accurate facial feature extraction and passenger moving trajectory analysis in technology, but also shows great value in practical application, providing strong support for modern security management and intelligent services.

[0086] Embodiment 4: as shown in Figure 4 The process of dynamically adjusting the lens angle, focal length and mode of the face device provided by the embodiment of the application based on embodiment 3 includes the following steps:

[0087] S10131: When collecting light data through the mobile device, a comprehensive time series reflecting the light change trend in different time periods is generated in combination with the timestamp of each data point; the passenger aggregation and movement path in different areas are displayed through the liquidity heat map;

[0088] S10132: According to the processed light data and motion trajectory information, the adjustment command of the face device is implemented through the control interface; the currently enabled face device will automatically adjust the angle, focal length and shooting mode of the lens according to the light intensity and passenger flow characteristics;

[0089] Wherein, the expression of automatically adjusting the angle, focal length and shooting mode of the lens is:

[0090] C actire = f (L, T, P, V)

[0091] In the formula, C actire represents the activation state of the currently enabled face device, 0 represents inactivated, and 1 represents activated, L represents the light intensity, the unit is 1x (lux), which represents the light environment of the environment, T represents the time period characteristics, which represents the influence of the time period on the monitoring demand, which can be represented by discrete values (such as 0, 1, 2, representing early peak, late peak and idle time respectively), P represents the passenger flow characteristics, which represents the flow rate of passengers in a certain time period (unit: person / second), reflecting the flow density and flow situation in the area, V represents the important area coefficient, taking value between 0 and 1, representing the importance of the current monitoring area, the closer to 1 represents the more important area;

[0092] Focal length adjustment equation:

[0093]

[0094] Angle adjustment equation:

[0095]

[0096] Shooting mode selection equation:

[0097] M

[0098] = { "LowLight" if L < L threshold and P > P threshold "Standard" if L ≥ L threshold and P ≤ P threshold "HighDetail" if V ≥ 0.8

[0099] In the formula, F represents the focal length, the unit is mm, the focal length setting of the lens of the face device, A represents the lens angle, the unit is degree, the shooting angle setting of the face device, k f, k a , k b represents the coefficient for adjusting the focal length and the sensitivity of the angle, which needs to be adjusted according to the characteristics of the system, L threshola represents the threshold of the light intensity, which is a standard set according to the actual monitoring needs, P threshold represents the threshold of the passenger flow rate, which is determined according to the monitoring focus, L max , L min represents the maximum and minimum values of the ambient light to ensure the rationality of the adjustment, P peak represents the peak value of the passenger flow to determine whether the flow is excessive;

[0100] S10133: After receiving the adjustment command, the pan-tilt control will change the direction of the face device; combined with the electric zoom technology, the distance of the lens is adjusted, and the picture range covers the key monitoring area; when it is monitored that some areas are not covered or there are important blind spots, an alarm will be automatically sent out, and the monitoring layout of the face device will be adjusted again to optimize the monitoring layout, ensuring that no important area is missed.

[0101] The working principle and beneficial effects of the technical solution are: first, when the mobile device collects illumination data, the time stamp of each data point is combined to generate a comprehensive time series, reflecting the light change trend in different time periods; through the liquidity heat map, the passenger aggregation and movement path in different areas are displayed; second, according to the processed illumination data and motion trajectory information, the adjustment command of the face device is implemented through the control interface; the currently enabled face device will automatically adjust the angle, focal length and shooting mode of the lens according to the light intensity and passenger flow characteristics; finally, the pan-tilt control will change the direction of the face device after receiving the adjustment command; combined with the electric zoom technology, the distance of the lens is adjusted, and the picture range covers the key monitoring area; when it is monitored that some areas are insufficiently covered or there are important blind spots, an alarm will be automatically sent out, and the monitoring layout of the face device will be adjusted to optimize the monitoring layout, ensuring that no important area is missed. The step S1031 of the above scheme is illumination data collection and passenger flow analysis, which combines the illumination data collected by the mobile device with the time stamp to generate a detailed time series; the time series accurately reflects the change trend of the light in different time periods, which is convenient for identifying peak periods and abnormal situations; the generated liquidity heat map shows the aggregation and movement path of passengers in a specific area, providing visual data support for understanding passenger dynamic behavior. The significance achieved: the time series extracted from the illumination data provides a basis for subsequent decision-making, enabling the face device to take timely remedial measures when the light is insufficient; the liquidity heat map helps system operators to understand passenger dynamics in real time, identify busy areas, optimize the allocation of monitoring resources, and improve monitoring efficiency. The step S1032 of the control interface adjusts the face device command, which can automatically generate adjustment commands for the face device by processing the illumination data and passenger dynamic characteristics; the automatic process reduces manual intervention and improves response speed and accuracy; the face device dynamically adjusts the angle, focal length and shooting mode of the lens according to the real-time monitored light intensity and passenger flow, ensuring that the captured picture meets the current needs. The significance achieved: the adaptive adjustment capability enhances the adaptability of the monitoring system to the changing environment, effectively improving the attention to important events or areas; the automatic adjustment mechanism can quickly remedy when the light conditions or passenger flow density change, avoiding monitoring dead angles or blurred pictures, and ensuring clear capture of important information. The step S1033 of the pan-tilt control and monitoring layout optimization can quickly change the direction of the face device after receiving the adjustment command, thereby flexibly responding to the needs of different environments; at the same time, through the electric zoom technology, the distance of the lens is adjusted to ensure that the picture covers the key monitoring area; real-time monitoring of the coverage range and blind area, when identifying insufficient monitoring coverage, an alarm will be automatically sent out and corresponding adjustment will be made to ensure the integrity of the monitoring area.The significance achieved: greatly improves the effectiveness of monitoring, ensures that all important areas are not missed, and improves the ability to respond to potential security risks in a timely manner; automatic alarm and readjustment mechanism enhances the intelligent level of the system, making it better adapt to dynamic environmental changes, ensuring the continuity and effectiveness of security monitoring work.

[0102] In summary, the embodiment enables the face device system to have the ability of dynamic adjustment, which can flexibly change according to real-time data, and improves the intelligence and efficiency of the monitoring system. Finally, it makes the security management and monitoring work more accurate and comprehensive, which is an important embodiment of the development of modern monitoring technology.

[0103] Embodiment 5: as shown in Figure 5 On the basis of embodiment 1, the process provided by the embodiment of the application for continuously evaluating whether there is abnormal behavior includes the following steps:

[0104] S201: analyze the moving track of the passenger, extract the position information of each time node, draw the moving path of the passenger through continuous coordinate points, and capture the dynamic behavior of each passenger in the customs clearance area;

[0105] S202: use the stay time analysis to calculate the stay time of each key position, identify the stay time in the security check, passport check and other key monitoring points through mathematical comparison of the time stamp data; if the stay time of a position exceeds the threshold value determined through historical data analysis, it will be marked as abnormal; parallel operation of the average moving speed of the passenger, combined with the acceleration data and position information, real-time monitoring of the flow state of the passenger in the customs clearance area;

[0106] S203: compare the current speed of the passenger with the historical data, if the speed in the captured moving data is significantly higher than the normal driving speed, or the moving speed fluctuates sharply in a short time, it is judged as potential abnormal behavior.

[0107] The working principle and beneficial effects of the technical solution are: first, the moving trajectory of the passenger is analyzed, the position information of each time node is extracted, the moving path of the passenger is drawn through continuous coordinate points, and the dynamic behavior of each passenger in the customs area is captured; second, the stay time analysis is used to calculate the stay time of each key position, the stay time of the passenger in the security check, passport check and other key monitoring points is identified through mathematical comparison of the timestamp data; if the stay time of a certain position exceeds the threshold value determined through historical data analysis, it will be marked as abnormal; the average moving speed of the passenger is calculated in parallel, the acceleration data and position information are combined to monitor the flow state of the passenger in the customs area in real time; finally, the current speed of the passenger is compared with the historical data, and if the speed captured in the moving data is significantly higher than the normal driving speed or the moving speed fluctuates sharply in a short time, it is judged as a potential abnormal behavior. The step S201 moving trajectory analysis of the above scheme analyzes the moving trajectory of the passenger in detail, generates continuous coordinate points by extracting the position information of each time node, and accurately draws the moving path of the passenger in the customs area; the spatial data analysis technology is used to effectively capture the dynamic behavior of the passenger, including the behavior mode of entering and leaving each key position. Significance: by clearly presenting the moving trajectory of the passenger, the activity of the passenger in the customs area is intuitively understood; not only helps to supplement the background data of identity information query, but also lays a foundation for subsequent abnormal behavior identification; accurate trajectory analysis can reveal potential suspicious activities and provide empirical support for security personnel, thereby enhancing the safety and effective monitoring of the customs area. Step S202 stay time analysis: using the stay time analysis method, the stay time of the key position is calculated, and the stay time of the passenger in the security check, passport check and other important monitoring points is identified through mathematical comparison of the timestamp data; once the stay time exceeds the set reasonable threshold value, the behavior will be marked as abnormal; at the same time, the average moving speed of the passenger is calculated in parallel, and the acceleration data and position information are combined to monitor the flow state of the passenger in the customs area in real time. Significance: through comprehensive analysis of the stay time and average speed, the possible abnormal behavior of the passenger can be identified; for example, in the security check link, if the passenger stays at a certain monitoring point for too long or the moving speed deviates significantly from the normal range, it may indicate a security risk or suspicious activity; this analysis result can trigger an alarm in time to improve the rapid response capability to potential risks, thereby ensuring the smoothness and safety of the customs process. Step S203 speed comparison analysis: the current moving speed of the passenger is compared with the historical data, the existing behavior mode is used as a reference to quickly identify the situation that is significantly higher than the normal speed or the behavior that appears sharp speed fluctuation in a short time; statistical analysis method is adopted to ensure accurate capture of abnormalities.Significance: The importance of speed comparison analysis lies in its ability to reliably monitor passenger movements; for individuals with normal behavior, there is a certain range of movement speed; once significant speed anomalies are detected, risk alarms are triggered, enabling precise interception; through this measure, the customs area can strike a balance between dynamics and security, ensuring fast and effective monitoring and reducing the probability of security risks.

[0108] In summary, the process of continuously evaluating abnormal behavior in this embodiment forms a highly integrated dynamic monitoring system through movement trajectory analysis, dwell time analysis, and speed comparison analysis, effectively improving the security and efficiency of passenger customs clearance. This ensures real-time response to potential security threats and provides passengers with faster and safer customs clearance experiences.

[0109] Embodiment 6: As shown in Figure 6 Based on Embodiment 5, the process of capturing the dynamic behavior of each passenger in the customs area provided by the present embodiment includes the following steps:

[0110] S2011: Synchronize data from each sensor through timestamps. For each time node, extract the passenger position information captured by the sensor to generate continuous coordinate points, which represent the movement trajectory of the passenger in the customs area;

[0111] S2012: Draw the movement path of the passenger by connecting the continuous coordinate points; based on the drawn movement path, analyze the passenger's behavior pattern, such as whether there are frequent U-turns, stays, or rapid movements, etc., to identify potential abnormal behavior;

[0112] S2013: Compare the drawn movement path with real-time data to dynamically capture changes in passenger behavior; through real-time monitoring, abnormal changes in passenger behavior are discovered.

[0113] The working principle and beneficial effects of the above technical solution are: first, the time stamp is used to synchronize the data of each sensor. For each time node, the passenger position information captured by the sensor is extracted to generate continuous coordinate points, and the coordinate points represent the moving track of the passenger in the customs area. Second, the moving path of the passenger is drawn by connecting the continuous coordinate points. Based on the drawn moving path, the behavior pattern of the passenger is analyzed, such as whether there is frequent U-turn, stay or fast movement, etc., to identify potential abnormal behavior. Finally, the drawn moving path is compared with real-time data to dynamically capture the behavior change of the passenger. Through real-time monitoring, the abnormal change of passenger behavior is found. Step S2011 of the above scheme ensures the time consistency of the data of each sensor, avoiding errors caused by time deviation. By extracting the passenger position information captured by the sensor, continuous coordinate points are generated, which accurately record the moving track of the passenger in the customs area. The significance achieved is that time stamp synchronization and coordinate point generation ensure the accuracy and integrity of the data, providing a reliable basis for behavior analysis. Through real-time data acquisition, the dynamic behavior of the passenger can be captured in time, providing data support for real-time monitoring and abnormal behavior detection. Step S2012 path drawing and behavior analysis: by connecting the continuous coordinate points, the moving path of the passenger is drawn to intuitively show the behavior of the passenger in the customs area. Based on the drawn moving path, the behavior pattern of the passenger is analyzed, such as frequent U-turn, stay or fast movement, etc., to identify potential abnormal behavior. The significance achieved is that through path drawing, the dynamic behavior of the passenger is visualized, which is convenient for intuitive understanding and analysis. Through behavior pattern recognition, potential abnormal behavior can be found in time to provide a basis for abnormal behavior evaluation. Step S2013 dynamic behavior capture and real-time monitoring: the drawn moving path is compared with real-time data to dynamically capture the behavior change of the passenger, ensuring the real-time and effectiveness of the monitoring. Through real-time monitoring, the abnormal change of passenger behavior can be found in time, such as sudden acceleration, frequent U-turn, etc., to provide real-time feedback for abnormal behavior detection. The significance achieved is that through real-time comparison and monitoring, the abnormal behavior of the passenger can be found and responded in time to improve the safety and management efficiency of the customs area. Through dynamic behavior capture, a warning mechanism can be established to remind the management personnel to pay attention to potential abnormal behavior, ensuring the safety of the customs area.

[0114] In summary, the embodiment can comprehensively and accurately capture the dynamic behavior of each passenger in the customs area, ensuring the accuracy and real-time of the data. Not only does it provide a reliable basis for abnormal behavior evaluation, but also through behavior pattern recognition and real-time monitoring, potential abnormal behavior is found and responded in time to improve the safety and management efficiency of the customs area.

[0115] Embodiment 7: as Figure 7As shown, on the basis of Embodiment 5, the process for identifying the stay duration at security check, passport check and other key monitoring points provided by the present embodiment comprises the following steps:

[0116] S2021: continuously collecting the position information and corresponding time stamp of the passenger in real time through the sensors and face devices arranged at the key positions; whenever the passenger passes through a certain monitoring point, the coordinate of the position and the time information are recorded; the continuous time stamp data are paired, the time difference between each time of entering and leaving the key position is obtained through subtraction operation, and then the stay time of the passenger at the position is determined;

[0117] S2022: the stay duration threshold of each key position is set in advance, and the stay time exceeding the set stay duration is automatically marked as abnormal through the comparison operation of the stay time and the preset threshold;

[0118] S2023: through the collected position information, the statistical operation of the position information corresponding to the time stamp is carried out in combination with the acceleration data and the position coordinate, and the moving speed of the passenger between the key positions is calculated.

[0119] The working principle and beneficial effects of the technical solution are: first, the position information and corresponding time stamp of the passenger are continuously and real-timely collected through the sensors and face devices arranged at key positions; the coordinates and time information of the position are recorded when the passenger passes through a certain monitoring point; the continuous time stamp data are paired, and the time difference between each time of entering and leaving the key position is obtained through subtraction operation, and then the stay time of the passenger at the position is determined; second, the stay time threshold of each key position is set in advance, and the behavior is automatically marked as abnormal through comparison operation of the stay time and the preset threshold when the stay time exceeds the set stay time; finally, the position information corresponding to the time stamp is statistically operated through the collected position information, combined with the acceleration data and position coordinates, and the moving speed of the passenger between the key positions is calculated. The step S2021 of the above scheme collects real-time position information and time stamp, and the sensors and face devices arranged at the key monitoring points can continuously and real-timely collect the position information and time stamp of the passenger; when the passenger passes through a specific monitoring point, the system records the coordinates and accurate time of the position; then, the continuous time stamp data are paired through subtraction operation, and the stay time of the passenger at the position is calculated. Meaning: ensures the accurate recording of all passenger behaviors, forms a monitoring system based on real-time data; provides basic data for subsequent behavior analysis, ensures the accuracy and reliability of the analysis results; through the clear time stamp and corresponding position information, the actual flow of each passenger at the key point can be captured, laying a solid foundation for the identification of abnormal behaviors. The step S2022 sets the stay time threshold and marks the abnormality, and the reasonable stay time threshold of each key position is set in advance, which is usually based on historical data analysis and flow pattern; when comparing the stay time, once the stay time of the passenger exceeds the set threshold, the behavior is automatically marked as abnormal through comparison operation. Meaning: the process of defining and applying the stay time threshold is the key to ensuring the efficient operation of the monitoring system, which quickly identifies possible security risks and abnormal behaviors; the behaviors marked as abnormal are reported to the monitoring personnel in time, so that potential security threats can be responded to in real time; not only improves the safety of the customs, but also effectively reduces the possibility of false positives. The step S2023 calculates the moving speed, and the coordinates between each key position are statistically operated through the position information collected in the early stage, combined with the acceleration data and time stamp, to calculate the moving speed of the passenger; the calculation depends on the change of continuous position information and the accurate measurement of time difference. Meaning: the process of calculating the moving speed provides an important dimension for the analysis of stay time, and through the monitoring of the average moving speed of the passenger, abnormal moving patterns such as rapid movement or abnormal stagnation in a short time can be identified; it is crucial for judging whether there is a potential threat, which can further improve the identification ability of suspicious behaviors; through the comprehensive analysis of speed and stay time, security decisions can be made more effectively in a dynamic environment, ensuring the efficient and safe customs process.

[0120] In summary, through the synergistic effect of the above steps, the monitoring system forms a multi-level monitoring mechanism when analyzing the stay time and behavior of passengers. Not only does it enhance real-time identification of potential abnormal behavior, but it also improves the overall security of the customs area, providing strong data support for subsequent security measures. Each step plays an indispensable role in dynamic monitoring, abnormality identification, and emergency response.

[0121] Embodiment 8: As shown in the embodiment 5, on the basis of the embodiment 5, the process of judging the potential abnormal behavior provided by the embodiment of the application comprises the following steps: Figure 8

[0122] S2031: When the passenger moves at the monitoring point, the speed is acquired in real time and recorded;

[0123] S2032: The speed of the current passenger is compared with the previously established historical average speed to obtain the existing deviation;

[0124] S2033: If the current speed is significantly higher than the set normal range, the state is marked as abnormal; the speed fluctuation of the monitored passenger exceeds the normal fluctuation range, which is also determined as a potential abnormal behavior.

[0125] ​The working principle and beneficial effects of the above technical solution are: first, when the passenger moves at the monitoring point, the speed is acquired in real time and recorded; second, the current passenger's speed is compared with the previously established historical average speed to obtain the existing deviation; finally, if the current speed is significantly higher than the set normal range, the state is marked as abnormal; the speed fluctuation of the monitored passenger exceeds the normal fluctuation range, which is also determined as potential abnormal behavior. The step S2031 of the above scheme acquires the speed in real time, which acquires the moving speed data of the passenger in real time by deploying sensors and face devices at the monitoring points; the sensor has the ability of high-frequency collection, which can quickly and accurately record the speed information of the passenger when passing through the monitoring point. The significance achieved is: timely acquisition of speed data enables quick understanding of the dynamic behavior of passengers, providing first-hand information for subsequent analysis; high-precision speed measurement can eliminate human intervention and delay, ensuring the reliability of the analysis of basic data; through real-time monitoring, the flow state of passengers in the customs area can be understood at any time, and rapid intervention can be made on abnormal situations. The step S2032 of speed comparison and analysis compares the real-time speed of the current passenger with the historical average speed established in the historical database, and calculates the deviation between the two, which helps to identify the abnormal characteristics of passenger behavior. The significance achieved is: through the comparison of historical data, the standard of normal behavior can be set, which provides an objective basis for subsequent judgment; rapid identification of speed deviation phenomenon facilitates early detection of potential problems such as rapid escape, unreasonable arrival time and other abnormal behaviors; comparison and analysis not only focus on static speed, but also combine multiple speed data of passengers at different monitoring points, thereby improving the accuracy of abnormal behavior identification. The step S2033 of abnormal state determination, through comparison and analysis, if the current speed is significantly higher than the normal range or the speed of the passenger fluctuates sharply, the state will be immediately marked as abnormal; various thresholds may also be set to improve the accuracy of discrimination. The significance achieved is: through the marking of abnormal state, the alarm can be generated quickly and fed back to the security personnel, prompting them to take action in time to prevent possible security incidents; through the rapid identification of potential abnormal behavior, the security prevention capability of the customs area is enhanced, thereby reducing risks and potential threats; through the continuous accumulation of data of abnormal cases, the system can optimize the abnormal mode and judgment rules, and improve the effectiveness and accuracy of future monitoring. The step S2031 of real-time speed acquisition measures the moving speed of the passenger in real time by using the sensors installed at these key positions when the passenger passes through the monitoring point. This process includes several important links: first, the system collects the position information and time data of the passenger passing through a specific monitoring point through the sensor; second, by analyzing these position changes, the system accurately calculates the moving speed of the passenger in unit time and records this real-time speed data into the database; the data is not only instantaneous speed measurement, but also forms a dynamically updated speed history record, providing a basis for subsequent analysis.Step S2032 speed comparison analysis, compare the current passenger's speed with the pre-established historical average speed, use the average speed value stored in the historical database as the benchmark. These average speed values are calculated based on the behavior data of passengers in multiple past clearance periods, ensuring accurate reflection of traffic trends under normal circumstances. When the real-time speed of the passenger is recorded, it will be immediately compared with the historical average speed. If a significant deviation is found between the current speed and the historical average speed, this change will be highlighted; not only static comparison, but also considering multiple speed data within 100 meters, by evaluating the passing speed of passengers at repeated monitoring points, the sensitivity to changes is enhanced. Step S2033 abnormal state determination, after speed comparison analysis, it is determined whether there is potential abnormal behavior; if the current passenger's speed is significantly higher than the preset normal range, the system will immediately mark it as abnormal, this abnormal marking is based on the speed threshold set in advance, which is obtained by statistical analysis, aiming to capture dynamic changes beyond normal behavior. In addition, the system will also focus on the speed fluctuation of the passenger; if the speed of the passenger is found to fluctuate sharply within a short period of time during monitoring, such fluctuation will also be judged as potential abnormality; the amplitude and frequency of these speed changes will be recorded to ensure timely feedback to security personnel for further investigation.

[0126] In summary, the embodiment analyzes the passenger's moving behavior through three steps, from real-time data collection to comparative analysis, to the determination of abnormal state, forming a complete behavior recognition system. Not only enhances the monitoring efficiency of the clearance area, but also improves the response ability to deal with emergencies, which helps to maintain passenger safety and ensure the smoothness of the clearance process.

[0127] Embodiment 9: as shown in embodiment 8, on the basis of embodiment 8, the process of obtaining the existing deviation provided by the embodiment of the application comprises the following steps: Figure 9

[0128] S20321: at the monitoring point, real-time collection of passenger speed data, including the instantaneous speed and moving direction of the passenger; extract the speed information of the passenger from the historical monitoring data, construct a historical speed database, including the speed distribution of different time periods and different passenger groups; based on the historical data, calculate the historical average speed of different passenger groups;

[0129] S20322: compare the real-time speed of the current passenger with the historical average speed of the corresponding passenger group. Calculate the difference between the current speed and the historical average speed, i.e. the speed deviation value; by calculating the difference between the current speed and the historical average speed, the speed deviation value is obtained, which reflects the difference between the current speed and the normal speed pattern;

[0130] ​S20323: Analyze the speed deviation value to determine whether it is outside the set normal range. The normal range is determined by statistical analysis of historical data, such as standard deviation, confidence interval, etc. If the speed deviation value is significantly higher than the set normal range, it is determined to be a potential abnormal behavior. At the same time, the speed fluctuation is analyzed, and if the fluctuation is outside the normal fluctuation range, it is also determined to be a potential abnormal behavior.

[0131] The working principle and beneficial effects of the above technical solution are: Firstly, the speed data of the passenger is collected in real time at the monitoring point, including the instantaneous speed and moving direction of the passenger; the speed information of the passenger is extracted from the historical monitoring data to construct a historical speed database, including the speed distribution of different time periods and different passenger groups; based on the historical data, the historical average speed of different passenger groups is calculated; secondly, the real-time speed of the current passenger is compared with the historical average speed of the corresponding passenger group. The difference between the current speed and the historical average speed, i.e. the speed deviation value, is calculated; by calculating the difference between the current speed and the historical average speed, the speed deviation value is obtained, which reflects the difference between the current speed and the normal speed pattern; finally, the speed deviation value is analyzed to determine whether it is outside the set normal range. The normal range is determined by statistical analysis of historical data, such as standard deviation, confidence interval, etc. If the speed deviation value is significantly higher than the set normal range, it is determined to be a potential abnormal behavior. At the same time, the speed fluctuation is analyzed, and if the fluctuation is outside the normal fluctuation range, it is also determined to be a potential abnormal behavior. The steps S20321 of the above scheme are real-time collection of speed data and construction of historical data. By collecting the speed data of the passenger in real time, the system can capture the immediate dynamic changes. At the same time, by constructing the historical speed database, the system can accumulate a large amount of data to provide a solid foundation for subsequent analysis. The significance achieved is that it provides data support for speed deviation analysis, not only helps the system to understand the current passenger behavior, but also provides a reference framework for normal behavior through historical data, so that the system can more accurately identify abnormalities. The step S20322 of calculating the speed deviation value can calculate the speed deviation value by comparing the speed of the current passenger with the historical average speed, and the numerical value directly reflects the difference between the current speed and the normal pattern. The significance achieved is that the calculation of the speed deviation value is the core step of identifying abnormal behavior, which enables the system to quantify the degree of abnormality and provides a clear basis for judgment, and quantitative analysis improves the accuracy and reliability of identification. The step S20323 of analyzing the speed deviation value and determining the abnormality analyzes the speed deviation value statistically to determine whether it is outside the set normal range, and the analysis is based on the statistical properties of historical data such as standard deviation and confidence interval to ensure the scientificity and reliability of the judgment. The significance achieved is that the system can timely discover and mark potential abnormal behavior, which not only improves the efficiency of monitoring, but also enhances the early warning capability of the system, so that the manager can quickly take measures to cope with possible security threats.

[0132] In summary, the embodiment forms a closed-loop monitoring system through data collection, deviation calculation and anomaly analysis. It not only improves the understanding of passenger behavior, but also significantly enhances the early warning and response capabilities of the system, providing strong technical support for public safety.

[0133] Embodiment 10: As shown in the embodiment 1, on the basis of the embodiment 1, the process of triggering the risk assessment procedure provided by the embodiment of the application comprises the following steps: Figure 10

[0134] S301: Automatically generating detailed risk alarm information, including the identity information of the relevant passenger, the real-time location, the retrieved abnormal behavior description and the assessed risk level;

[0135] S302: Pushing the alarm information to the terminal device of the monitoring personnel, receiving the alarm;

[0136] S303: According to the set emergency response protocol, automatically starting the emergency measures, such as locking a specific passage, enabling video monitoring to strengthen the close monitoring of a certain area, or mobilizing security personnel to deal with the passenger situation.

[0137] ​The working principle and beneficial effects of the above technical solution are: firstly, the embodiment automatically generates detailed risk alarm information, including the identity information of the relevant passenger, real-time location, retrieved abnormal behavior description, and evaluated risk level; secondly, the alarm information is pushed to the terminal device of the monitoring personnel, and the alarm is received; finally, according to the set emergency response protocol, the emergency measures are automatically started, such as locking a specific passage, enabling video monitoring to strengthen close monitoring of a certain area, or mobilizing security personnel to handle the passenger situation. Step S301 of the above scheme automatically generates detailed risk alarm information, and according to the data obtained from identity information comparison and abnormal behavior detection, a detailed risk alarm information is automatically created; the information includes the identity information of the passenger, such as name, ID number and biometric characteristics; real-time location, which refers to the specific location of the passenger in the monitoring area; description of the retrieved abnormal behavior, such as unusual stay time or abnormal movement trajectory; and the evaluated risk level (such as low, medium, and high). The significance achieved is: to ensure the integration of all relevant information, to help monitoring personnel quickly understand the situation and improve processing efficiency; to provide necessary data support, so that monitoring personnel can decide on appropriate processing measures according to the specific situation; to ensure the real-time nature of the information, to reflect potential threats in a timely manner, and to improve security response capabilities. Step S302 pushes the alarm information to the terminal device of the monitoring personnel, and the generated risk-related alarm information will be automatically pushed to the terminal device of the monitoring personnel through the system, which can include a display, a mobile phone or other types of information terminals, to ensure that on-site personnel can receive alarm information in a timely manner. The significance achieved is: through real-time information pushing, monitoring personnel can understand potential security risks in the first time, so as to respond quickly; timely acquisition of alarm information reduces information flow time, making the response process more efficient and enhancing the ability to handle security incidents on site; ensuring smooth information flow between the monitoring center and on-site security personnel facilitates coordination and linkage tasks. Step S303 automatically starts emergency measures according to the set emergency response protocol, and according to the pre-set emergency response protocol, various emergency measures are automatically started; it may include locking a specific passage to prohibit passenger passage; enabling video monitoring to strengthen close observation of a certain specific area; and mobilizing security personnel to the scene to handle potential risk passengers. The significance achieved is: by implementing emergency measures in a timely manner, the occurrence of potential threats is effectively reduced, and suspicious passengers are monitored and controlled as necessary; standardize and systematize the complex emergency response process to improve the consistency and comprehensiveness of security work; provide necessary support for security personnel to ensure that they can respond to potential threats in the first time, and improve the overall security prevention capability.

[0138] In summary, the triggering of the risk assessment procedure of the embodiment can not only improve the ability to identify and respond to potential threats, but also establish a more effective security management mechanism in a complex customs environment, thereby ensuring the safety of passengers and the smoothness of the customs process. In addition, the information-based and automated operation process reduces the need for manual intervention and reduces the probability of errors.

[0139] Embodiment 11: As shown in the figure, the embodiment of the application provides a passenger customs inspection system, comprising: Figure 11 a feature extraction module responsible for arranging face recognition devices and sensors in the customs area, capturing target facial features of passengers in real time, and collecting location information of passengers;

[0140] a behavior assessment module responsible for comparing the target facial features with the pre-stored identity information in the background database; analyzing the location information to obtain the moving track and the staying time of the passenger, and continuously assessing whether there is abnormal behavior;

[0141] a risk assessment module responsible for not triggering the risk assessment procedure when both the identity information comparison result and the abnormal behavior are judged to be qualified, and the passenger will be automatically guided to the customs port; triggering the risk assessment procedure when either the identity information comparison result or the abnormal behavior is judged to be unqualified, and issuing an alarm.

[0142]

[0143] ​The working principle and beneficial effects of the above technical solution are: the feature extraction module of the embodiment arranges face recognition devices and sensors in the customs clearance area, captures the target facial features of passengers in real time, and collects the location information of passengers; the behavior evaluation module compares the target facial features with the pre-stored identity information in the background database; the location information is analyzed to obtain the moving track and stay time of the passenger, and whether there is abnormal behavior is continuously evaluated; when the identity information comparison result and the abnormal behavior are both judged to be qualified, the risk assessment module does not trigger the risk assessment program, and the passenger will be automatically guided to the customs clearance port; when either the identity information comparison result or the abnormal behavior is judged to be unqualified, the risk assessment program is triggered, and an alarm is given. The feature extraction module of the above scheme can extract the biological features (such as facial features, iris, fingerprint) of passengers in real time by arranging multiple high-performance face image capture devices and sensor devices in the customs clearance area; the device can also collect the location information of passengers in the customs clearance area, including moving speed, activity path, key positions of entry and exit, and stay time. The technical means of this module for feature extraction usually include high-resolution image acquisition, sensor data analysis and real-time updating. The significance achieved is: through high-precision devices and algorithms, the biological features and behavior data of passengers are captured to provide an accurate information basis; the dynamic changes of passengers can be monitored in real time, so that the system can quickly respond to potential risks; the collected location information and activity path provide necessary data support for subsequent behavior evaluation and anomaly detection, forming a complete passenger portrait. The behavior evaluation module analyzes the data provided by the feature extraction module, compares the real-time extracted target facial features with the identity information stored in the background database; analyzes the location information of the passenger to obtain the moving track and stay time, and evaluates whether there is abnormal behavior; usually includes efficient data matching algorithm and anomaly detection algorithm. The significance achieved is: through the comparison of biological features, the authenticity of the passenger's identity is ensured, and identity fraud behavior is effectively prevented; abnormal behavior patterns of passengers can be discovered in time to help security personnel conduct further investigation and judgment; dynamic analysis of the moving behavior of passengers can assess potential risks in real time, so as to respond to abnormal situations more quickly. The risk assessment module integrates the identity information comparison result and the evaluation result of abnormal behavior; when both are judged to be qualified, the system will not trigger the risk assessment program, and the passenger will be automatically guided to the customs clearance port; otherwise, if either is judged to be unqualified, the risk assessment program will be triggered quickly and an alarm signal will be given. The significance achieved is: to reduce the customs clearance delay of normal passengers, improve the customs clearance efficiency, and ensure the efficient use of resources; to judge the risk through clear standards, handle potential threats in time, and improve the safety of the customs clearance area; to provide an emergency response framework that can quickly notify security personnel when a risk is found to ensure the accuracy and timeliness of the handling measures.

[0144] In summary, the embodiment realizes efficient and safe customs clearance management. The feature extraction module ensures the real-time and accuracy of data; the behavior evaluation module strengthens the monitoring of passenger identity and behavior, and discovers abnormalities in time; the risk evaluation module formulates standardized emergency response measures to quickly and effectively respond to potential risks. The safety management level of the customs clearance area is significantly improved, ensuring the safety and smoothness of passenger flow.

[0145] Embodiment 12: As shown in the embodiment 1-embodiment 10, on the basis of the passenger customs clearance inspection device provided by the present embodiment, comprising: a camera, a sensor, a background database, a controller, a power supply, a display device; Figure 12

[0146] The camera, the sensor, the background database and the display device are connected with the controller, and the power supply is connected with the camera, the sensor, the background database, the controller and the display device;

[0147] The camera is used to capture the facial image of the passenger, the sensor is used to monitor the moving speed of the passenger and obtain the weight and size data of the luggage, etc.; the background database pre-stores the identity information; the controller is used to control the coordinated control of the camera, the sensor, the background database and the display device, analyzes the position information, obtains the moving track and the stay time of the passenger, and continuously evaluates whether there is abnormal behavior; when any one of the identity information comparison result and the abnormal behavior is judged as unqualified, the risk evaluation program is triggered to alarm; the power supply is used to provide the energy of the camera, the sensor, the background database, the controller and the display device; the display device is used to display the processing result of the controller.

[0148] ​The working principle and beneficial effects of the above technical solution are: the working principle of the embodiment is that the camera captures the face image of the passenger through the camera installed in the customs clearance area for subsequent identity comparison; the sensor works in parallel with the camera, and the sensor is responsible for monitoring the moving speed, position change of the passenger, and obtaining the weight and size data of the luggage, etc., to evaluate the passenger behavior; all collected images and sensor data are sent to the background database through the connected controller, and the background database pre-stores the identity information and corresponding biometric features of the passenger, such as fingerprint and iris information; the controller receives the data transmitted by the sensor and the camera, first compares the identity information, judges whether the captured facial features are consistent with the information in the background database; at the same time, the controller also analyzes the position information of the passenger to generate the moving track and stay time of the passenger, and judges whether these behaviors are abnormal; according to the identity comparison result and behavior evaluation, if any item is judged as unqualified, the controller will trigger the risk assessment program and issue an alarm signal; the alarm information will be recorded and can be presented to the security personnel through the display device to inform them of further processing measures. The power supply provides stable energy supply for the entire device to ensure that the camera, sensor, background database, controller and display device operate normally and realize real-time data processing.

[0149] The embodiment can collect the face and behavior data of the passenger in real time through the combination of the camera and the sensor, ensure the timeliness of information processing, and thus quickly identify potential risks and abnormal behaviors; by using the pre-stored identity information in the background database and through accurate comparison algorithm, the authenticity of the passenger's identity is ensured, the risk of identity fraud is reduced, and a reliable basis is provided for security inspection; the sensor not only monitors the moving speed of the passenger and the luggage information, but also analyzes the behavior pattern of the passenger to identify abnormal activity track and enhance the reaction ability of security; when risks are identified, the system can automatically trigger an alarm and present the processing result to relevant personnel through the display device, improving the response speed and processing efficiency of on-site security; combined with the camera, sensor, database, controller and display device, no manual intervention is needed, efficient and stable operation can be realized, manpower and operating costs are saved, and the possibility of human error is reduced; it can be configured according to different customs clearance environments and needs, has strong scalability, and is suitable for different security demand application scenarios.

[0150] In summary, the design and implementation of the passenger customs clearance inspection device of the embodiment effectively improve the accuracy and efficiency of security inspection, and provide important support for improving the level of public security management.

[0151] It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application cover modifications and variations of this application provided they come within the scope of the appended claims and their equivalents.

Claims

1. A passenger customs inspection method, characterized by, The method comprises the following steps: Arranging a face recognition device and a sensor in the customs clearance area to capture the target facial features of the passenger in real time and collect the location information of the passenger; Comparing the target facial features with the pre-stored identity information in the background database; Analyzing the location information to obtain the moving track and the staying time of the passenger and continuously evaluating whether there is abnormal behavior; If both the identity information comparison result and the abnormal behavior are qualified, the risk assessment procedure is not triggered, and the passenger will be automatically guided to the customs clearance port; if either the identity information comparison result or the abnormal behavior is unqualified, the risk assessment procedure is triggered, and an alarm is given; The expression for automatically adjusting the angle, focal length and shooting mode of the lens is: C active = f(L, T, P, V) In the formula, C active indicates the activation state of the current face-enabled device, 0 indicates not activated, 1 indicates activated, L indicates the light intensity, the unit is lx, indicates the light environment of the environment, T indicates the time period feature, indicates the influence of the time period on the monitoring demand, is represented by a discrete value, P indicates the passenger flow characteristic, indicates the flow rate of passengers in a specific time period, reflects the flow density and flow situation in the region, V indicates the important area coefficient, the value is between 0 and 1, indicates the importance of the current monitoring area, the closer to 1 indicates that the area is more important; Focal length adjustment equation: Angle adjustment equation: Shooting mode selection equation: M = {"LowLight" if L < L threshold and P > P threshold "Standard" if L ≥ L threshold and P ≤ P threshold "HighDetail" if V ≥ 0.8} In the formula, F represents the focal length, with the unit of mm, the lens focal length setting of the face device, A represents the lens angle, with the unit of degree, the shooting angle setting of the face device, k f , k a , k b represents the coefficient, used to adjust the sensitivity of the focal length and the angle, the value needs to be adjusted according to the system characteristics, L threshold represents the threshold of the light intensity, the standard set according to the actual monitoring needs, P threshold represents the threshold of the passenger flow rate, decided according to the monitoring focus, L max , L min represents the maximum and minimum values of the environmental light, to ensure the rationality of the adjustment, P peak represents the peak value of the passenger flow, so as to judge whether the flow is excessive or not; The process of continuously evaluating whether there is abnormal behavior comprises the following steps: Analyzing the moving track of the passenger, extracting the location information at each time node, drawing the moving path of the passenger through continuous coordinate points, and capturing the dynamic behavior of each passenger in the customs clearance area; Using the staying time analysis to calculate the staying time at each key location, identifying the staying time at the security check, passport check and other key monitoring points through mathematical comparison of the timestamp data; if the staying time at a certain location exceeds the threshold value determined through historical data analysis, it will be marked as abnormal; and parallelly operating the average moving speed of the passenger, combining the acceleration data and the location information to monitor the flow state of the passenger in the customs clearance area in real time; Comparing the current speed of the passenger with the historical data, if the speed captured in the moving data is significantly higher than the normal driving speed or the moving speed fluctuates sharply in a short time, it is judged as potential abnormal behavior.

2. The passenger customs inspection method according to claim 1, characterized by, The process of capturing the dynamic behavior of each passenger in the customs clearance area comprises the following steps: Synchronizing the data of each sensor through the timestamp, extracting the passenger location information captured by the sensor at each time node, generating continuous coordinate points, and the coordinate points represent the moving track of the passenger in the customs clearance area; Drawing the moving path of the passenger by connecting the continuous coordinate points; Analyzing the behavior pattern of the passenger based on the drawn moving path, and identifying potential abnormal behavior; Comparing the drawn moving path with real-time data to dynamically capture the behavior change of the passenger; through real-time monitoring, the abnormal change of the passenger behavior is found.

3. The passenger customs inspection method according to claim 1, characterized by, The process of identifying the staying time at the security check, passport check and other key monitoring points comprises the following steps: Continuously and real-timely collecting the location information and the corresponding timestamp of the passenger through the sensors and face devices arranged at the key locations; whenever the passenger passes through a monitoring point, the coordinate and time information of the location are recorded; the continuous timestamp data are paired, the time difference between each time of entering and leaving the key location is obtained through subtraction operation, and then the staying time of the passenger at the location is determined; Pre-setting the staying time threshold of each key location, and if the staying time exceeds the set staying time, the behavior will be automatically marked as abnormal through comparison operation of the staying time and the pre-set threshold value; Through the collected position information, combined with acceleration data and position coordinates, the position information corresponding to the time stamp is statistically operated to calculate the moving speed of the passenger between the key positions.

4. The passenger customs inspection method according to claim 1, characterized by, The process of judging potential abnormal behavior includes the following steps: When the passenger moves at the monitoring point, the speed is acquired in real time and recorded; The current speed of the passenger is compared with the previously established historical average speed to obtain the existing deviation; If the current speed is significantly higher than the set normal range, the state is marked as abnormal; If the speed fluctuation of the passenger monitored exceeds the normal fluctuation range, it is also determined as potential abnormal behavior.

5. The passenger customs inspection method according to claim 4, characterized by, The process of obtaining the existing deviation includes the following steps: Real-time collection of passenger speed data at the monitoring point, including the instantaneous speed and moving direction of the passenger; extraction of passenger speed information from historical monitoring data to construct a historical speed database, including speed distribution of different time periods and different passenger groups; based on historical data, the historical average speed of different passenger groups is calculated; The real-time speed of the current passenger is compared with the historical average speed of the corresponding passenger group to calculate the difference between the current speed and the historical average speed, i.e. the speed deviation value; the speed deviation value is obtained by calculating the difference between the current speed and the historical average speed, and the deviation value reflects the difference between the current speed and the normal speed pattern; The speed deviation value is analyzed to determine whether it exceeds the set normal range, which is determined through statistical analysis of historical data.

6. The passenger customs inspection method according to claim 5, wherein, If the speed deviation value is significantly higher than the set normal range, it is determined as potential abnormal behavior; at the same time, the speed fluctuation is analyzed, and if the fluctuation exceeds the normal fluctuation range, it is also determined as potential abnormal behavior.

7. A passenger customs inspection system, characterized by, It includes: The feature extraction module is responsible for arranging face recognition devices and sensors in the customs area, capturing the target facial features of passengers in real time, and collecting the position information of passengers; The behavior evaluation module is responsible for comparing the target facial features with the pre-stored identity information in the background database; The position information is analyzed to obtain the moving track and stay time of the passenger, and whether there is abnormal behavior is continuously evaluated; The risk assessment module is responsible for triggering the risk assessment program and issuing an alarm when either the identity information comparison result or the abnormal behavior is judged as unqualified; The expression for automatically adjusting the angle, focal length and shooting mode of the lens is: C active = f(L, T, P, V) In the formula, C active indicates the activation state of the current face-enabled device, 0 indicates not activated, 1 indicates activated, L indicates the light intensity, the unit is lx, indicates the light environment of the environment, T indicates the time period feature, indicates the influence of the time period on the monitoring demand, is represented by a discrete value, P indicates the passenger flow characteristic, indicates the flow rate of passengers in a specific time period, reflects the flow density and flow situation in the region, V indicates the important area coefficient, the value is between 0 and 1, indicates the importance of the current monitoring area, the closer to 1 indicates that the area is more important; Focal length adjustment equation: Angle adjustment equation: Shooting mode selection equation: M = {"LowLight" if L < L threshold and P > P threshold "Standard" if L ≥ L threshold and P ≤ P threshold "HighDetail" if V ≥ 0.8} In the formula, F represents the focal length, with the unit of mm, the lens focal length setting of the face device, A represents the lens angle, with the unit of degree, the shooting angle setting of the face device, k f , k a , k b represents the coefficient, used to adjust the sensitivity of the focal length and the angle, the value needs to be adjusted according to the system characteristics, L threshold represents the threshold of the light intensity, the standard set according to the actual monitoring needs, P threshold represents the threshold of the passenger flow rate, decided according to the monitoring focus, L max , L min represents the maximum and minimum values of the environmental light, to ensure the rationality of the adjustment, P peak represents the peak value of the passenger flow, so as to judge whether the flow is excessive or not; Continuous evaluation of whether there is abnormal behavior includes: The moving track of the passenger is analyzed to extract the position information at each time node, and the moving path of the passenger is drawn through consecutive coordinate points to capture the dynamic behavior of each passenger in the customs area; The residence time of each key position is calculated by using residence time analysis, and the residence time length at security check, passport check and key monitoring points is identified by mathematical comparison of timestamp data; if the residence time of a position exceeds the threshold value determined by historical data analysis, it will be marked as abnormal; the average moving speed of passengers is calculated in parallel, and the flow state of passengers in the customs area is monitored in real time by combining acceleration data and position information; The current speed of passengers is compared with historical data, and if the speed is significantly higher than the normal driving speed or the moving speed fluctuates sharply in a short time, it is judged as a potential abnormal behavior.

8. A passenger customs inspection apparatus characterized by comprising: It comprises a camera, a sensor, a background database, a controller, a power supply and a display device. The camera, the sensor, the background database and the display device are connected with the controller, and the power supply is connected with the camera, the sensor, the background database, the controller and the display device. The expression for automatically adjusting the angle, focal length and shooting mode of the lens is: C active = f(L, T, P, V) In the formula, C active indicates the activation state of the current face-enabled device, 0 indicates not activated, 1 indicates activated, L indicates the light intensity, the unit is lx, indicates the light environment of the environment, T indicates the time period feature, indicates the influence of the time period on the monitoring demand, is represented by a discrete value, P indicates the passenger flow characteristic, indicates the flow rate of passengers in a specific time period, reflects the flow density and flow situation in the region, V indicates the important area coefficient, the value is between 0 and 1, indicates the importance of the current monitoring area, the closer to 1 indicates that the area is more important; Focal length adjustment equation: Angle adjustment equation: Shooting mode selection equation: M = {"LowLight" if L < L threshold and P > P threshold "Standard" if L ≥ L threshold and P ≤ P threshold "HighDetail" if V ≥ 0.8} In the formula, F represents the focal length, with the unit of mm, the lens focal length setting of the face device, A represents the lens angle, with the unit of degree, the shooting angle setting of the face device, k f , k a , k b represents the coefficient, used to adjust the sensitivity of the focal length and the angle, the value needs to be adjusted according to the system characteristics, L threshold represents the threshold of the light intensity, the standard set according to the actual monitoring needs, P threshold represents the threshold of the passenger flow rate, decided according to the monitoring focus, L max , L min represents the maximum and minimum values of the ambient light, to ensure the rationality of the adjustment, P peak represents the peak value of the passenger flow, so as to judge whether the flow is excessive or not; The process of continuously evaluating whether there is an abnormal behavior by the controller comprises: The moving track of passengers is analyzed, the position information of each time node is extracted, the moving path of passengers is drawn by continuous coordinate points, and the dynamic behavior of each passenger in the customs area is captured; The residence time of each key position is calculated by using residence time analysis, and the residence time length at security check, passport check and key monitoring points is identified by mathematical comparison of timestamp data; if the residence time of a position exceeds the threshold value determined by historical data analysis, it will be marked as abnormal; the average moving speed of passengers is calculated in parallel, and the flow state of passengers in the customs area is monitored in real time by combining acceleration data and position information; The current speed of passengers is compared with historical data, and if the speed is significantly higher than the normal driving speed or the moving speed fluctuates sharply in a short time, it is judged as a potential abnormal behavior.

Images