Passenger customs clearance checking method, system and device

Abstract

The invention provides a passenger customs clearance checking method, system and device, and the method comprises the steps: arranging a face recognition device and a sensor in a customs clearance region, capturing the target facial features of a passenger in real time, and collecting the position information of the passenger; comparing the target facial features with identity information pre-stored in a background database; analyzing the position information to obtain a moving track and staying time of the passenger, and continuously evaluating whether an abnormal behavior exists or not; when the identity information comparison result and the abnormal behavior are judged to be qualified, a risk assessment program is not triggered, and the passenger is automatically guided to a customs clearance; and when any one of the identity information comparison result and the abnormal behavior is judged to be unqualified, triggering a risk assessment program. 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. According to the invention, a more intelligent, automatic and safe customs clearance system is established.

Description

Technical Field

[0001] The present invention relates to the technical field of data mining and analysis, and in particular to a passenger customs inspection method, system and customs inspection device. Background Art

[0002] Passenger identity verification refers to the process of confirming and verifying the identity information of travelers through certain methods and technologies. It usually occurs at entry and exit, security inspection or other occasions where personal identity needs to be confirmed to ensure that the identity of the passenger is legal and authentic. 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. The significance of passenger identity verification includes security assurance, improving customs clearance efficiency, enhancing legal compliance, data-driven decision-making and improving travel experience. Passenger identity verification is not only an important part of entry and exit management and security assurance, but also an indispensable part of the modern intelligent transportation and tourism system; through effective identity verification measures, it can provide multiple benefits for social security, economic development and passenger experience. However, the existing passenger clearance relies too much on human operations, which is not only time-consuming and labor-intensive, reduces the efficiency of customs clearance inspection, but also easily misses key information.

[0003] Prior art 1, application number: CN202410242180.8 discloses a passenger clearance waiting management method, device and electronic device, the method includes: obtaining a facial image of a target passenger who has just entered the waiting 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 location information corresponding to the target passenger; associating the facial image and the location information, generating a pedestrian trajectory corresponding to the target passenger, and updating the location information in the pedestrian trajectory in real time; according to the pedestrian trajectory of each target passenger in the waiting channel, determining the stay time of each target passenger in the waiting channel and the number of stranded people in the waiting channel; according to the stay time of each target passenger and the number of stranded people in the waiting channel, determining and executing the corresponding intervention strategy. Although it can accurately identify and promptly respond to the stranded personnel in the waiting channel, thereby improving the efficiency of passenger clearance. However, there is no analysis of passenger identity information, resulting in the need to improve the accuracy of obtaining passenger information.

[0004] Prior art 2, application number: CN202111677091.9 discloses a full-process customs clearance method for airport passengers based on face recognition technology, and establishes a full customs clearance platform system. The platform system constructs the cloud and each independent airport node, and forms a cloud identity library for each process service point in the cloud, and forms a local identity library for each process service point in each airport node. When clearing customs, the passenger's certificate information is combined with the facial biometric information to form a unique identity information data. Each service point collects on-site facial photos, extracts facial photo feature codes, and uploads the facial photo feature codes to the cloud for comparison, improves the cloud identity library, or sends them to the airport node for comparison, improves the local identity library, and then clears the entire process of check-in, security inspection, boarding, etc. Although the platform system is a passenger identity information control center with unified services, unified standards, and unified operation and maintenance, it dispatches and calculates in real time to achieve the application goal of "register once, benefit for life, smooth all the way, and worry-free travel". However, the operation process is relatively simple, and the content of passenger security inspection information inspection is relatively small, which is not conducive to the security of information query.

[0005] Prior art three, application number: CN202311746224.2 discloses a security inspection system and method, including: a passenger information collection subsystem, configured to collect the identity information of the passing passengers; a luggage information collection subsystem, configured to collect the luggage information of the passengers; a data docking subsystem, configured to dock with the related parties to obtain the related party information of the passengers and / or luggage; an association binding subsystem, connected to the passenger information collection subsystem, the luggage information collection subsystem, and the data docking subsystem, and configured to perform association matching based on the passenger's identity information, luggage information, and related party information to form an associated and bound passenger clearance data chain; and an identification and interception subsystem, configured to determine the target passenger or luggage based on the passenger clearance data chain for interception prompts. Although the efficiency and accuracy of luggage information matching are improved; but there is no analysis of passenger identity information, resulting in a low degree of intelligence in the system.

[0006] At present, the existing technologies 1, 2 and 3 have the problem that the accuracy of deep mining and analysis of data in the customs clearance process needs to be improved, and the customs clearance process and management efficiency are low. Therefore, the present invention provides a passenger customs clearance inspection method, system and customs clearance inspection device. Summary of the invention

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

[0008] Facial recognition equipment and sensors are deployed in the customs clearance area to capture the target facial features of passengers in real time and collect the location information of passengers;

[0009] Compare the target's facial features with the identity information pre-stored in the backend database; analyze the location information to obtain the passenger's movement trajectory and stay time, and continuously evaluate whether there is any abnormal behavior;

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

[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 Indicates the activation status of the currently enabled face recognition device, 0 indicates inactive, 1 indicates activated, L indicates light intensity, the unit is lx, indicating the lighting environment of the environment, T indicates the time period characteristics, indicating the impact of the time period on the monitoring demand, expressed in discrete values, P indicates the passenger mobility characteristics, indicating the flow rate of passengers in a specific time period, reflecting the density and flow of people in the area, V indicates the important area coefficient, the value is between 0 and 1, indicating the importance of the current monitoring area, the closer to 1, the more important the area;

[0014] Focus adjustment equation:

[0015]

[0016] Angle adjustment equation:

[0017]

[0018] Shooting mode selection equation:

[0019] M

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

[0021] Where F is the focal length in mm, which is the lens focal length setting of the face device. A is the lens angle in degrees, which is the shooting angle setting of the face device. f , k a , k bIndicates the coefficient, which is used to adjust the sensitivity of focal length and angle. The value needs to be adjusted according to the system characteristics. L threshold Indicates the threshold of light intensity, which is set according to the actual monitoring needs. threshold The threshold of passenger flow rate is determined according to the monitoring focus. max , L min Indicates the maximum and minimum values ​​of ambient light to ensure the rationality of adjustment, P peak Indicates the peak value of passenger flow in order to determine whether the flow exceeds the standard.

[0022] Preferably, the process of continuously evaluating whether abnormal behavior exists comprises the following steps:

[0023] Analyze the passenger's movement trajectory, extract the location information of each time node, draw the passenger's movement path through continuous coordinate points, and capture the dynamic behavior of each passenger in the customs clearance area;

[0024] The dwell time analysis is used to calculate the dwell time at each key location. The dwell time at security check, passport control and key monitoring points is identified through mathematical comparison of timestamp data. If the dwell time at a certain location exceeds the threshold determined by historical data analysis, it will be marked as abnormal. The average movement speed of passengers is calculated in parallel, and the flow status of passengers in the customs clearance area is monitored in real time by combining acceleration data and location information.

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

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

[0027] The data of each sensor is synchronized through timestamps. For each time node, the passenger location information captured by the sensor is extracted to generate continuous coordinate points, which represent the movement trajectory of the passenger in the customs clearance area.

[0028] By connecting consecutive coordinate points, the passenger's movement path is drawn; based on the drawn movement path, the passenger's behavior pattern is analyzed to identify potential abnormal behavior;

[0029] Compare the drawn movement path with real-time data to dynamically capture changes in passenger behavior; through real-time monitoring, detect abnormal changes in passenger behavior.

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

[0031] Through sensors and facial recognition devices placed at key locations, the location information and corresponding timestamps of passengers are continuously collected in real time; whenever a passenger passes a monitoring point, the location coordinates and time information are recorded; the continuous timestamp data are paired, and the time difference between each entry and exit of the key location is obtained through subtraction operations, thereby determining the passenger's stay time at the location;

[0032] Preset the dwell time threshold for each key location. If the dwell time exceeds the set dwell time, the behavior will be automatically marked as abnormal by comparing the dwell time with the preset threshold.

[0033] By combining the collected location information with the acceleration data and location coordinates, the location information corresponding to the timestamp is statistically calculated to calculate the passenger's movement speed between key locations.

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

[0035] When passengers move at the monitoring point, their speed is obtained in real time and recorded;

[0036] Compare the current passenger speed 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 status will be marked as abnormal; if the speed fluctuation of the passenger is monitored and exceeds the normal fluctuation range, it will also be judged as potential abnormal behavior.

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

[0039] At the monitoring point, the speed data of passengers is collected in real time, including the instantaneous speed and moving direction of passengers; the speed information of passengers is extracted from the historical monitoring data to build 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] Compare the real-time speed of the current passenger with the historical average speed of the corresponding passenger group, and calculate the difference between the current speed and the historical average speed, that is, the speed deviation value; obtain the speed deviation value 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 mode;

[0041] The speed deviation value is analyzed to determine whether it exceeds the set normal range. 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 to be a 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 to be a potential abnormal behavior.

[0043] The present invention provides a passenger clearance inspection system, comprising:

[0044] The feature extraction module is responsible for arranging facial recognition equipment and sensors in the customs clearance area to capture the target facial features of passengers in real time and collect the location information of passengers;

[0045] The behavior assessment module is responsible for comparing the target's facial features with the identity information pre-stored in the backend database; analyzing the location information to obtain the passenger's movement trajectory and stay time, and continuously assessing whether there is any abnormal behavior;

[0046] The risk assessment module is responsible for not triggering the risk assessment procedure and automatically guiding the passenger to the customs clearance gate when both the identity information comparison result and the abnormal behavior are judged as qualified; when either the identity information comparison result or the abnormal behavior is judged as unqualified, the risk assessment procedure is triggered and an alarm is issued.

[0047] The present invention provides a passenger customs inspection device, comprising: a camera, a sensor, a background database, a controller, a power supply, and a display device;

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

[0049] The data collection and preprocessing of the present invention collects the data of passengers in real time in multiple dimensions, including facial images, biometric features (such as irises and fingerprints), moving speed, luggage weight and size, etc., by deploying multiple facial image capture devices and sensor devices; it can quickly extract the facial features of passengers and convert them into digital format for subsequent processing; it monitors the location information of passengers in the customs clearance area, including key entry and exit locations, and generates the movement trajectory and duration of passengers based on the data. Significance: Through multi-angle and multi-mode real-time data collection, the system's comprehensive understanding of the identity and behavior of passengers is improved, which helps to lay the foundation for subsequent identity verification and risk assessment; it makes the passenger clearance process more accurate and efficient, and helps to detect potential risk factors. Identity verification and abnormal behavior analysis compares the target facial features extracted in real time with the identity information pre-stored in the background database, and adopts a fast image matching algorithm to improve efficiency; analyzes the location information and movement trajectory of passengers to detect whether there is abnormal behavior, such as staying in a certain location for a long time or irregular movement patterns. Significance: Through identity verification, only legitimate passengers can pass through, preventing identity fraud and related crimes, thereby maintaining the security of the customs clearance area; behavioral analysis enables the system to proactively detect potential suspicious behaviors, and respond in a timely manner based on the passenger's movement history, thereby improving the overall security management capabilities. Risk assessment and guidance decision-making, when both identity information comparison and abnormal behavior detection are judged to be qualified, passengers will be automatically guided to the customs clearance gate to simplify the customs clearance process; once any of the conditions in identity information comparison and abnormal behavior are found to be unqualified, the system will trigger the risk assessment procedure and immediately alarm, notifying security personnel for follow-up processing. Significance: The automatic guidance mechanism greatly improves the efficiency of passenger customs clearance, reduces queuing and waiting time, and optimizes the travel experience of passengers; the risk assessment and alarm mechanism ensures the effectiveness of security management, and it is better to issue more alarms than to maintain safety awareness, providing security personnel with timely and reliable information, so as to facilitate timely adjustment and flexible response to potential risks.

[0050] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0051] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0053] Figure 1 This is a flow chart of the passenger clearance inspection method in Example 1 of the present invention;

[0054] Figure 2 The process of capturing the target facial features of passengers in real time in Embodiment 2 of the present invention;

[0055] Figure 3 This is the process of extracting the target facial features and obtaining the passenger's movement trajectory and stay time in Example 3 of the present invention;

[0056] Figure 4 This is the process of dynamically adjusting the lens angle, focal length and mode of the face device in Embodiment 4 of the present invention;

[0057] Figure 5 The process of continuously evaluating whether there is abnormal behavior in Embodiment 5 of the present invention;

[0058] Figure 6 The process of capturing the dynamic behavior of each passenger in the customs clearance area in Embodiment 6 of the present invention;

[0059] Figure 7 The process of identifying the duration of stay at security check, passport check and other key monitoring points in Example 7 of the present invention;

[0060] Figure 8 The process of determining a potential abnormal behavior in Embodiment 8 of the present invention;

[0061] Fig. 9 A process for obtaining the existing deviation in Embodiment 9 of the present invention;

[0062] Fig.10 is a process diagram of triggering a risk assessment procedure in Embodiment 10 of the present invention;

[0063] Fig.11 This is a block diagram of a passenger clearance inspection system in Embodiment 11 of the present invention;

[0064] Fig.12 This is a schematic diagram of the passenger clearance inspection device in Example 12 of the present invention. DETAILED DESCRIPTION

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

[0066] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms of "a", "said" and "the" used in the embodiments of the present application are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in this article refers to and includes any or all possible combinations of one or more associated listed items.

[0067] When the following description relates to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are only examples of devices and methods consistent with some aspects of the present application. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0068] Example 1: Figure 1 As shown, an embodiment of the present invention provides a passenger clearance inspection method, comprising the following steps:

[0069] S100: Facial recognition equipment and sensors are deployed in the customs clearance area to capture the target facial features of passengers in real time and collect the location information of passengers;

[0070] S200: Compare the target facial features with the identity information pre-stored in the background database; analyze the location information to obtain the passenger's movement trajectory and stay time, and continuously evaluate whether there is any abnormal behavior;

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

[0072] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, face recognition devices and sensors are first arranged in the customs clearance area to capture the target facial features of passengers in real time and collect the location information of passengers; secondly, the target facial features are compared with the identity information pre-stored in the background database; the location information is analyzed to obtain the movement trajectory and residence time of the passengers, and whether there is abnormal behavior is continuously evaluated; finally, 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 passengers will be automatically guided to the customs clearance; 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 issued. Step S100 of the above scheme collects data and preprocesses data in real time in multiple dimensions by arranging multiple facial image capture devices and sensor devices; the facial features of passengers can be quickly extracted and converted into digital format for subsequent processing; the location information of passengers in the customs clearance area is monitored, including the key positions of entry and exit, and the movement trajectory and residence time of passengers are generated based on the data. Significance: Through real-time data collection from multiple angles and in multiple ways, the system's comprehensive understanding of the identity and behavior of passengers is improved, which helps lay the foundation for subsequent identity verification and risk assessment; it 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 target facial features extracted in real time with the identity information pre-stored in the background database, and adopts a fast image matching algorithm to improve efficiency; analyzes the passenger's location information and movement trajectory to detect whether there is abnormal behavior, such as staying in a certain location for a long time or irregular movement patterns. Significance: Through identity verification, it ensures that only legitimate passengers can pass, prevents identity fraud and related crimes, and thus maintains the security of the clearance area; behavioral analysis enables the system to proactively detect potential suspicious behaviors, and respond in a timely manner in combination with the passenger's movement history, thereby improving the overall security management capabilities. Step S300: Risk assessment and guidance decision-making. When both identity information comparison and abnormal behavior detection are judged as qualified, passengers will be automatically guided to the customs clearance gate to simplify the customs clearance process. Once any of the identity information comparison and abnormal behavior conditions are found to be unqualified, the system will trigger the risk assessment procedure and immediately alarm, notifying security personnel for follow-up processing. Significance: The automatic guidance mechanism greatly improves the efficiency of passenger customs clearance, reduces queuing and waiting time, and optimizes the travel experience of passengers. The risk assessment and alarm mechanism ensures the effectiveness of security management. It is better to issue more alarms than to maintain safety awareness, and provide security personnel with timely and reliable information, so as to facilitate timely adjustment and flexible response to potential risks.

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

[0074] Example 2: Figure 2 As shown, based on Example 1, the process of capturing the target facial features of passengers in real time provided by the embodiment of the present invention includes the following steps:

[0075] S101: Install high-definition facial equipment and facial recognition equipment at multiple key locations in the customs clearance area to capture passengers' facial images in real time and extract facial features, such as facial features and facial textures. Arrange a variety of sensors in the customs clearance area to monitor passengers' moving speed, luggage weight and size, and collect passengers' location information in real time.

[0076] S102: The facial image captured by the face recognition device is analyzed in real time through an image processing algorithm to extract the target facial features; the location information collected by the sensor is processed through location analysis to obtain the passenger's movement trajectory and stay time;

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

[0078] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, high-definition face devices and face recognition devices are first installed at multiple key locations in the customs clearance area to capture the facial images of passengers in real time and extract facial features, such as facial features and facial texture; multiple sensors are arranged in the customs clearance area to monitor the passenger's moving speed, the weight and size of the luggage, and collect the passenger's location information in real time; secondly, the facial image captured by the face recognition device is analyzed in real time by the image processing algorithm to extract the target facial features; the location information collected by the sensor is processed by location analysis to obtain the passenger's movement trajectory and stay time; finally, the extracted facial features and location information are transmitted to the background database in real time via the wireless network; the background database stores and manages the data. In the step S101 of the above solution, equipment installation and data collection, by installing high-definition face devices and face recognition devices at multiple key locations in the customs clearance area, the system can capture the passenger's facial images in all directions and from multiple angles to ensure the comprehensiveness and accuracy of the data. At the same time, the arrangement of multiple sensors enables the system to monitor the passenger's moving speed, the weight and size of the luggage, and the passenger's location information in real time, providing a rich data basis for subsequent analysis. Significance achieved: It ensures the comprehensive collection of data and lays the foundation for accurate identification and analysis. Through real-time capture and monitoring, the system can detect abnormal situations in time and improve the efficiency and safety of customs clearance. Step S102 Image processing and position analysis: The facial image captured by the face recognition device is analyzed in real time through advanced image processing algorithms, which can accurately extract the target facial features, such as facial features and facial texture; at the same time, the location information collected by the sensor is processed through location analysis, which can accurately depict the passenger's movement trajectory and stay time. Significance achieved: Through efficient image processing and location analysis, accurate identification and behavior analysis of passengers are achieved; it not only helps to improve customs clearance efficiency, but also effectively prevents potential security risks and ensures 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 to the background database in real time through the wireless network to ensure the timeliness and integrity of the data; the background database stores and manages the data, providing reliable support for subsequent data analysis and application. Significance achieved: It ensures real-time transmission and secure storage of data, providing guarantee 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, this embodiment achieves comprehensive and accurate identification and behavior analysis of passengers through multi-level and multi-dimensional technical means, which not only improves the customs clearance efficiency, but also enhances the security and reliability of the customs clearance process.

[0080] Example 3: Figure 3As shown, based on Example 2, the process of extracting target facial features and obtaining the passenger's movement trajectory and stay time provided in the embodiment of the present invention includes the following steps:

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

[0082] S1012: Use Haar feature classifier to locate the facial region in the image, determine the position and size of the face in the image; locate the positions of key points of facial features (eyes, nose, mouth) in the detected facial region, and determine the coordinates of the key points; extract the facial contour and the contours of the facial features through edge detection, perform texture analysis on the facial region through gray level co-occurrence matrix, and extract facial texture features;

[0083] S1013: Process the passenger's movement speed, luggage weight and size, and location information collected by various sensors (such as infrared sensors, pressure sensors, facial devices, etc.) in real time, track the passenger's movement path in the customs clearance area in real time, and generate a movement trajectory; calculate the passenger's stay time in a specific area based on the movement trajectory.

[0084] The working principle and beneficial effects of the above technical solution are as follows: in this embodiment, the captured facial image is first denoised and image enhancement is performed through histogram equalization; secondly, the Haar feature classifier is used to locate the facial area in the image and determine the position and size of the face in the image; within the detected facial area, 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, and the texture analysis of the facial area is performed through the gray-level co-occurrence matrix to extract the facial texture features; finally, the passenger movement speed, luggage weight and size and location information collected by a variety of sensors (such as infrared sensors, pressure sensors, face devices, etc.) are processed in real time, and the passenger's movement path in the customs clearance area is tracked in real time to generate a movement trajectory; according to the movement trajectory, the passenger's stay time in a specific area is calculated. In step S1011 of the above scheme, the image quality is significantly improved through denoising and histogram equalization; denoising eliminates random noise in the image, while histogram equalization enhances the contrast of the image, making the facial features more clearly visible; high-quality image preprocessing lays a solid foundation for subsequent facial feature extraction, ensuring the accuracy and reliability of facial recognition. In step S1012, facial feature extraction uses the Haar feature classifier to accurately locate the facial area, and obtains high-precision facial features through the location and contour extraction of the key points of the facial features; texture analysis further enriches the dimensions of facial features and provides more recognition basis. Significance: The sophisticated facial feature extraction technology not only improves the accuracy of recognition, but also enhances the robustness of the system, and can cope with various complex environments and lighting conditions. In step S1013, passenger movement trajectory analysis, through the data fusion and real-time processing of multiple sensors, the system can accurately track the passenger's movement path and calculate his / her stay time in a specific area; this real-time and accuracy is difficult to match with traditional methods. Significance: Real-time tracking and dwell time analysis provide valuable data support for security monitoring and traffic management, helping to optimize customs clearance processes and improve overall efficiency.

[0085] In summary, this embodiment not only technically realizes efficient and accurate facial feature extraction and passenger movement trajectory analysis, but also demonstrates great value in practical applications, providing strong support for modern security management and intelligent services.

[0086] Example 4: Figure 4 As shown, based on Example 3, the process of dynamically adjusting the lens angle, focal length and mode of the face device provided in the embodiment of the present invention includes the following steps:

[0087] S10131: When collecting light data through mobile devices, combine the timestamp of each data point to generate a comprehensive time series, reflecting the trend of light changes in different time periods; through the mobility heat map, show the gathering situation and movement path of passengers in different areas;

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

[0089] The expressions for automatically adjusting the lens angle, focal length and shooting mode are as follows:

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

[0091] In the formula, C actire Indicates the activation status of the currently enabled face recognition device, 0 indicates inactive, 1 indicates activated, L indicates light intensity, the unit is 1x (lux), indicating the lighting environment of the environment, T indicates time period characteristics, indicating the impact of time period on monitoring needs, which can be expressed by discrete values ​​(for example, 0, 1, 2, indicating the morning peak, evening peak and off-peak, respectively), P indicates passenger mobility characteristics, indicating the flow rate of passengers in a specific time period (in persons / second), reflecting the density and flow of people in the area, V indicates the important area coefficient, the value is between 0 and 1, indicating the importance of the current monitoring area, the closer to 1, the more important the area;

[0092] Focus adjustment equation:

[0093]

[0094] Angle adjustment equation:

[0095]

[0096] Shooting mode selection equation:

[0097] M

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

[0099] Where F is the focal length in mm, which is the lens focal length setting of the face device. A is the lens angle in degrees, which is the shooting angle setting of the face device. f, k a , k b Indicates the coefficient, which is used to adjust the sensitivity of focal length and angle. The value needs to be adjusted according to the system characteristics. L threshola Indicates the threshold of light intensity, which is set according to the actual monitoring needs. threshold The threshold of passenger flow rate is determined according to the monitoring focus. max , L min Indicates the maximum and minimum values ​​of ambient light to ensure the rationality of adjustment, P peak Indicates the peak value of passenger flow, so as to determine whether the flow exceeds the standard;

[0100] S10133: The PTZ control will change the direction of the facial recognition device upon receiving an adjustment command. It will also adjust the distance of the lens in combination with electric zoom technology to cover key monitoring areas. When insufficient coverage of certain areas is detected or important blind spots exist, an alarm will be automatically sounded and readjustments will be made to optimize the monitoring layout of the facial recognition device to ensure that no important areas are missed from monitoring.

[0101] The working principle and beneficial effects of the above technical solution are as follows: first, when collecting illumination data through a mobile device, this embodiment combines the timestamp of each data point to generate a comprehensive time series, reflecting the illumination change trend in different time periods; through the mobility heat map, the gathering situation and movement path of passengers in different areas are displayed; secondly, according to the processed illumination data and motion trajectory information, the adjustment command of the facial device is implemented through the control interface; the currently enabled facial device will automatically adjust the angle, focal length and shooting mode of the lens according to the illumination intensity and passenger flow characteristics; finally, the pan-tilt control will change the direction of the facial 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 detected that the coverage of certain areas is insufficient or there are important blind spots, an alarm will be automatically issued, and readjustment will be made to optimize the monitoring layout of the facial device to ensure that no important areas are missed. In the above scheme, step S1031 of light data collection and passenger flow analysis is performed by combining the light data collected by the mobile device with the timestamp to generate a detailed time series; the time series accurately reflects the changing trend of light in different time periods, which is convenient for identifying peak hours and abnormal situations; the generated mobility heat map shows the gathering and movement paths of passengers in specific areas, providing visual data support for understanding the dynamic behavior of passengers. The significance achieved: the time series extracted from the light data provides a basis for subsequent decision-making, enabling the face device to initiate remedial measures in time when the light is insufficient; the mobility heat map helps system operators to grasp the dynamics of passengers in real time, identify busy areas, optimize the allocation of monitoring resources, and improve monitoring efficiency. Step S1032 of the control interface adjusts the face device command, and by processing the light data and the dynamic characteristics of passengers, it can automatically generate adjustment commands for the face device; the automation process reduces manual intervention and improves the speed and accuracy of response; the face device dynamically and automatically adjusts the angle, focal length and shooting mode of the lens based on the real-time monitored light intensity and passenger flow to ensure that the captured image meets the current needs. Significance achieved: The adaptive adjustment capability enhances the adaptability of the monitoring system to the ever-changing environment, and can effectively improve the attention to important events or areas; the automated adjustment mechanism can quickly remedy the situation when the lighting conditions or the density of people flow change, avoiding blind spots in monitoring or blurred images, and ensuring the clear capture of important information. Step S1033 PTZ control and monitoring layout optimization, after receiving the adjustment command, the PTZ control can quickly change the direction of the face device, so as to flexibly respond to the needs of different environments; at the same time, the electric zoom technology is used to adjust the distance of the lens to ensure that the image covers the key monitoring area; real-time monitoring of the coverage range and blind spots, when it is identified that the monitoring coverage is insufficient, an alarm is automatically issued and corresponding readjustment is made to ensure the integrity of the monitoring area.Significance achieved: It has greatly improved the effectiveness of monitoring, ensured that all important areas are not missed, and improved the ability to respond to potential safety hazards in a timely manner; the automatic alarm and readjustment mechanism has enhanced the intelligence level of the system, enabling it to better adapt to dynamic environmental changes and ensure the continuity and effectiveness of security monitoring work.

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

[0103] Example 5: Figure 5 As shown, based on Example 1, the process of continuously evaluating whether there is abnormal behavior provided by the embodiment of the present invention includes the following steps:

[0104] S201: Analyze the passenger's movement trajectory, extract the location information of each time node, draw the passenger's movement path through continuous coordinate points, and capture the dynamic behavior of each passenger in the customs clearance area;

[0105] S202: Calculate the dwell time at each key location using dwell time analysis, and identify the dwell time at security check, passport check and other key monitoring points through mathematical comparison of timestamp data; if the dwell time at a location exceeds the threshold determined by historical data analysis, it will be marked as abnormal; calculate the average moving speed of passengers in parallel, combine acceleration data and location information, and monitor the flow status of passengers in the customs clearance area in real time;

[0106] S203: Compare the passenger's current speed with historical data. In the captured movement data, if the speed is significantly higher than the normal driving speed, or the movement speed fluctuates drastically in a short period of time, it is determined as potential abnormal behavior.

[0107] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first analyzes the movement trajectory of passengers, extracts the location information of each time node, draws the movement path of passengers through continuous coordinate points, and captures the dynamic behavior of each passenger in the customs clearance area; secondly, the residence time analysis is used to calculate the residence time of each key location, and the residence time at security check, passport check and other key monitoring points is identified through mathematical comparison of timestamp data; if the residence time at a certain location exceeds the threshold determined by historical data analysis, it will be marked as abnormal; the average moving speed of passengers is calculated in parallel, and the flow status of passengers in the customs clearance area is monitored in real time by combining acceleration data and location information; finally, the current speed of the passenger is compared with the historical data. In the captured mobile data, if the speed is significantly higher than the normal driving speed, or the moving speed fluctuates violently in a short period of time, it is judged as potential abnormal behavior. Step S201 of the above scheme is the analysis of the movement trajectory. It analyzes the movement trajectory of passengers in detail, generates continuous coordinate points by extracting the location information of each time node, and accurately draws the movement path of passengers in the customs clearance area. It uses spatial data analysis technology to effectively capture the dynamic behavior of passengers, including the behavior patterns of entering and leaving each key location. Significance: By clearly presenting the movement trajectory of passengers, we can intuitively understand the activities of passengers in the customs clearance area; it not only helps to supplement the background data of identity information query, but also lays the foundation for the subsequent abnormal behavior identification; accurate trajectory analysis can reveal potential suspicious activities and provide empirical support for security personnel, thereby enhancing the security and effective monitoring of the customs clearance area. Step S202 is the analysis of the residence time. The residence time analysis method is used to calculate the residence time of key locations. By mathematically comparing the timestamp data, the length of time that passengers stay at important monitoring points such as security check and passport inspection can be identified; once the residence time exceeds the set reasonable threshold, the behavior will be marked as abnormal; at the same time, the average movement speed of passengers is calculated in parallel, and the flow status of passengers in the customs clearance area is monitored in real time in combination with acceleration data and location information. Significance: Through a comprehensive analysis of the dwell time and average speed, possible abnormal behaviors of passengers can be identified; for example, during the security check, if a passenger stays at a certain monitoring point for too long, or the moving speed deviates significantly from the normal range, this may indicate a safety hazard or suspicious activity; this analysis result can trigger an alarm in time, improve the ability to respond quickly to potential risks, and thus ensure the smoothness and safety of the customs clearance process. Step S203 speed comparison analysis, compare the passenger's current moving speed with historical data, use the existing behavior pattern as a benchmark, and quickly identify situations that are significantly higher than the normal speed, or behaviors that have drastic speed fluctuations in a short period of time; use statistical analysis methods to ensure that anomalies can be accurately captured.Significance: The importance of speed comparison analysis lies in its ability to reliably monitor the whereabouts of passengers. For individuals with normal movements, there is a certain range of moving speeds. Once a significant speed anomaly is detected, a risk alarm is triggered, allowing precise interception. Through this measure, the customs clearance area can find a balance between dynamism and security, ensure rapid and effective monitoring, and reduce the probability of safety hazards.

[0108] In summary, the process of continuously evaluating whether there is abnormal behavior in this embodiment forms a highly integrated dynamic monitoring system through movement trajectory analysis, dwell time analysis and speed comparison analysis, which effectively improves the security and efficiency of passenger clearance. It ensures that potential security threats can be responded to in real time, providing passengers with a faster and safer customs clearance experience.

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

[0110] S2011: Synchronize the data of each sensor through the timestamp, extract the passenger location information captured by the sensor at each time node, and generate continuous coordinate points, which represent the movement trajectory of the passenger in the customs clearance area;

[0111] S2012: Draw the passenger's movement path by connecting continuous coordinate points; analyze the passenger's behavior pattern based on the drawn movement path, such as whether there is frequent turning back, stopping or fast movement, and identify potential abnormal behavior;

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

[0113] The working principle and beneficial effects of the above technical solution are as follows: the present embodiment first synchronizes the data of each sensor through the timestamp, extracts the passenger location information captured by the sensor for each time node, and generates continuous coordinate points, which represent the passenger's moving trajectory in the customs clearance area; secondly, the passenger's moving path is drawn by connecting the continuous coordinate points; based on the drawn moving path, the passenger's behavior pattern is analyzed, such as whether there are frequent turns, stops or fast movements, etc., to identify potential abnormal behaviors; finally, the drawn moving path is compared with the real-time data to dynamically capture the passenger's behavior changes; through real-time monitoring, the abnormal changes in passenger behavior are discovered. Step S2011 of the above solution ensures the time consistency of the data of each sensor and avoids errors caused by time deviation; by extracting the passenger's location information captured by the sensor, continuous coordinate points are generated, which accurately record the passenger's moving trajectory in the customs clearance area. The significance achieved: the timestamp synchronization and coordinate point generation ensure the accuracy and integrity of the data, providing a reliable basis for behavior analysis; through real-time data collection, the dynamic behavior of passengers 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 continuous coordinate points, draw the passenger's moving path, intuitively display the passenger's behavior in the customs clearance area; based on the drawn moving path, analyze the passenger's behavior pattern, such as frequent return, stay or fast movement, etc., to identify potential abnormal behavior. Significance achieved: Through path drawing, the dynamic behavior of passengers is visualized, which is convenient for intuitive understanding and analysis; through behavior pattern recognition, potential abnormal behavior can be discovered in time, providing a basis for abnormal behavior evaluation. Step S2013: Dynamic behavior capture and real-time monitoring, compare the drawn moving path with real-time data, dynamically capture the behavior changes of passengers, and ensure the real-time and effectiveness of monitoring; through real-time monitoring, abnormal changes in passenger behavior, such as sudden acceleration, frequent return, etc., can be discovered in time, providing real-time feedback for abnormal behavior detection. Significance achieved: Through real-time comparison and monitoring, abnormal behavior of passengers can be discovered and responded to in time, improving the safety and management efficiency of the customs clearance area; through dynamic behavior capture, an early warning mechanism can be established to remind management personnel to pay attention to potential abnormal behavior in time to ensure the safety of the customs clearance area.

[0114] In summary, this embodiment can comprehensively and accurately capture the dynamic behavior of each passenger in the customs clearance area, ensuring the accuracy and real-time nature of the data. It not only provides a reliable basis for abnormal behavior assessment, but also timely discovers and responds to potential abnormal behaviors through behavior pattern recognition and real-time monitoring, thereby improving the security and management efficiency of the customs clearance area.

[0115] Example 7: Figure 7As shown, based on Example 5, the process of identifying the length of stay at security check, passport check and other key monitoring points provided by the embodiment of the present invention includes the following steps:

[0116] S2021: Continuously collect the location information and corresponding timestamps of passengers in real time through sensors and facial recognition devices placed at key locations; record the coordinates and time information of the location whenever the passenger passes a monitoring point; pair the consecutive timestamp data, and obtain the time difference between each entry and exit of the key location through subtraction operations, thereby determining the passenger's stay time at the location;

[0117] S2022: Preset a stay time threshold for each key location. If the stay time exceeds the set stay time, the behavior will be automatically marked as abnormal by comparing the stay time with the preset threshold;

[0118] S2023: The collected location information is combined with the acceleration data and the location coordinates to perform statistical operations on the location information corresponding to the timestamp to calculate the passenger's movement speed between the key locations.

[0119] The working principle and beneficial effects of the above technical solution are as follows: First, the present embodiment continuously collects the location information and corresponding timestamps of passengers in real time through sensors and face devices arranged at key positions; whenever a passenger passes a certain monitoring point, the coordinates and time information of the location are recorded; the continuous timestamp data are paired, and the time difference between each entry and exit of the key position is obtained by subtraction operation, so as to determine the passenger's stay time at the position; secondly, the stay time threshold of each key position is pre-set, and if the stay time exceeds the set stay time, the behavior will be automatically marked as abnormal by comparing the stay time with the preset threshold; finally, through the collected location information, combined with the acceleration data and the location coordinates, the location information corresponding to the timestamp is statistically calculated to calculate the passenger's moving speed between each key position. Step S2021 of the above scheme collects real-time location information and timestamps, and the sensors and face devices arranged at key monitoring points can continuously collect the location information and timestamps of passengers in real time; when a passenger passes a specific monitoring point, the system records the coordinates and precise time of the location; then, the continuous timestamp data is paired by subtraction operation to calculate the passenger's stay time at the location. Significance: It ensures the accurate recording of all passenger behaviors and forms a monitoring system based on real-time data; it provides basic data for subsequent behavior analysis to ensure the accuracy and reliability of the analysis results; through clear timestamps and corresponding location information, it can capture the actual flow of each passenger at key points, laying a solid foundation for the identification of abnormal behaviors. Step S2022 sets the dwell time threshold and abnormal mark, and pre-sets the reasonable dwell time threshold for each key location, which is usually derived based on historical data analysis and traffic patterns; when comparing the dwell time, once the passenger's dwell time exceeds the set threshold, the behavior is automatically marked as abnormal through comparison operations. Significance: The process of defining and applying the dwell time threshold is the key to ensuring the efficient operation of the monitoring system, quickly identifying possible safety hazards and abnormal behaviors; behaviors marked as abnormal will be reported to the monitoring personnel in a timely manner, so that potential security threats can be responded to quickly and in real time; it not only improves the security of customs clearance, but also effectively reduces the possibility of false alarms. Step S2023: Calculate the moving speed. Through the location information collected in the early stage, combined with the acceleration data and timestamp, the coordinate information between each key position is statistically calculated to calculate the moving speed of the passenger. The calculation depends on the change of continuous location information and the accurate measurement of time difference. Significance: The process of calculating the moving speed provides an important dimension for the analysis of the dwell time. By monitoring the average moving speed of passengers, abnormal movement patterns can be identified, such as rapid movement or abnormal stagnation in a short period of time. It is crucial to determine whether there is a potential threat and can further improve the ability to identify suspicious behavior. Through the comprehensive analysis of speed and dwell time, it is possible to make more effective security decisions in a dynamic environment to ensure the efficiency and safety of the customs clearance process.

[0120] In summary, through the synergy of the above steps, the monitoring system of this embodiment forms a multi-level monitoring mechanism when analyzing the length of stay and behavior of passengers; it not only enhances the real-time identification of potential abnormal behaviors, but also improves the security of the overall customs clearance area, providing strong data support for subsequent security measures. Each step plays an indispensable role in dynamic monitoring, abnormal identification and emergency response.

[0121] Example 8: Figure 8 As shown, based on Example 5, the process of determining potential abnormal behavior provided by the embodiment of the present invention includes the following steps:

[0122] S2031: When the passenger moves at the monitoring point, obtain the passenger's speed in real time and record it;

[0123] S2032: Compare the current passenger speed 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 status will be marked as abnormal; if the speed fluctuation of the passenger is monitored and exceeds the normal fluctuation range, it will also be determined as potential abnormal behavior.

[0125] The working principle and beneficial effects of the above technical solution are as follows: First, when the passenger moves at the monitoring point, the speed of the passenger is obtained in real time and recorded; secondly, the speed of the current passenger is compared with the historical average speed established previously to obtain the existing deviation; finally, 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 is monitored and exceeds the normal fluctuation range, it is also determined as a potential abnormal behavior. Step S2031 of the above solution is real-time speed acquisition, which acquires the moving speed data of the passenger in real time by deploying sensors and face devices at the monitoring point; the sensor has the ability of high-frequency acquisition and can quickly and accurately record the speed information of the passenger when passing the monitoring point. The significance achieved: timely acquisition of speed data enables rapid understanding of the dynamic behavior of passengers and provides first-hand information for subsequent analysis; high-precision speed measurement can eliminate human intervention and delay, and ensure the reliability of basic data for analysis; through real-time monitoring, the flow status of passengers in the customs clearance area can be understood at any time, and abnormal situations can be quickly intervened. Step S2032 speed comparison analysis compares the current passenger's real-time speed with the historical average speed established in the historical database, calculates the degree of deviation between the two, and helps identify abnormal characteristics of passenger behavior. Significance achieved: By comparing historical data, the standard of normal behavior can be set, which provides an objective basis for subsequent judgments; quickly identify speed deviation phenomena, and facilitate early detection of potential problems, such as rapid escape, unreasonable arrival time and other abnormal behaviors; comparative analysis not only focuses on static speed, but also combines multiple speed data of passengers at different monitoring points, thereby improving the accuracy of abnormal behavior identification. Step S2033 abnormal state determination, through comparative analysis, if the current speed is significantly higher than the normal range, or the passenger's speed fluctuates violently, the state will be immediately marked as abnormal; it may also involve setting various thresholds to improve the accuracy of judgment. Significance achieved: By marking abnormal status, alarms can be quickly generated and fed back to security personnel, prompting them to take timely action to prevent possible security incidents; by quickly identifying potential abnormal behaviors, the security prevention capabilities of the customs clearance area are enhanced, thereby reducing risks and potential threats; by continuously accumulating data on abnormal cases, the system can optimize abnormal patterns and judgment rules to improve the effectiveness and accuracy of future monitoring. Step S2031 Real-time speed acquisition: When passengers pass through monitoring points, sensors installed at these key locations are used to measure the passenger's movement speed in real time. This process includes several important links: First, the system continuously collects the location information and time data of passengers passing through specific monitoring points through sensors; second, by analyzing these position changes, the system accurately calculates the passenger's movement speed per unit time and records this real-time speed data in the database; the data is not just an instantaneous speed measurement, but forms a dynamically updated speed history record, providing a basis for subsequent analysis.Step S2032 speed comparison analysis, a detailed comparison analysis of the current passenger's speed with the pre-established historical average speed will be conducted, and the average speed value stored in the historical database will be used as a benchmark. These average speed values ​​are calculated based on the behavioral data of passengers in multiple customs clearance cycles in the past, ensuring that the flow trend under normal circumstances is accurately reflected. 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 focused on; not only static comparison is involved, but also multiple speed data within 100 meters will be considered, and the sensitivity to changes will be enhanced by evaluating the speed of passengers passing through repeated monitoring points. Step S2033 abnormal state determination, after speed comparison analysis, it will be 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 mark is based on the previously set speed threshold, which is obtained through statistical analysis and aims to capture dynamic changes beyond normal behavior. In addition, the system will also monitor the speed fluctuations of passengers. If the speed of passengers is found to change dramatically in a short period of time during the monitoring process, such fluctuations will also be judged as potential anomalies. The amplitude and frequency of these speed changes will be recorded to ensure timely feedback to security personnel for further investigation.

[0126] In summary, this embodiment conducts in-depth analysis of passenger movement behavior through three steps, from real-time data collection to comparative analysis, and then to the determination of abnormal status, forming a complete behavior recognition system. It not only enhances the monitoring efficiency of the customs clearance area, but also improves the response capability to deal with emergencies, which helps to maintain passenger safety and ensure the smoothness of the customs clearance process.

[0127] Example 9: Fig. 9 As shown, based on Example 8, the process of obtaining the existing deviation provided by the embodiment of the present invention includes the following steps:

[0128] S20321: At the monitoring point, real-time passenger speed data is collected, including the passenger's instantaneous speed and moving direction; passenger speed information is extracted from historical monitoring data to build 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;

[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, that is, the speed deviation value; obtain the speed deviation value 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 mode;

[0130] S20323: Analyze the speed deviation value to determine whether it exceeds 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, analyze the speed fluctuation. If the fluctuation exceeds 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 as follows: First, in this embodiment, the speed data of passengers, including the instantaneous speed and moving direction of passengers, are collected in real time at the monitoring point; the speed information of passengers is extracted from the historical monitoring data, and a historical speed database is constructed, 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, that is, 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 mode; finally, the speed deviation value is analyzed to determine whether it exceeds 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 as a 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 a potential abnormal behavior. Step S20321 of the above scheme is real-time collection of speed data and construction of historical data. By collecting passengers' speed data in real time, the system can capture immediate dynamic changes. At the same time, by building a historical speed database, the system can accumulate a large amount of data, providing a solid foundation for subsequent analysis. Significance achieved: It provides data support for speed deviation analysis, which not only helps the system understand the current passenger behavior, but also provides a reference framework for normal behavior through historical data, so that the system can identify anomalies more accurately. Step S20322 is the calculation of speed deviation value*. By comparing the current passenger's speed with the historical average speed, the speed deviation value can be calculated, and the value intuitively reflects the difference between the current speed and the normal mode. Significance achieved: The calculation of speed deviation value is the core step in identifying abnormal behavior, which enables the system to quantify the degree of abnormality and provide a clear basis for judgment. Quantitative analysis improves the accuracy and reliability of recognition. Step S20323 is the analysis of speed deviation value and abnormal judgment. By statistically analyzing the speed deviation value, the system can determine whether it exceeds the set normal range, and analyze the statistical characteristics based on historical data, such as standard deviation and confidence interval, to ensure the scientificity and reliability of the judgment. Significance achieved: Ensures that the system can detect and mark potential abnormal behaviors in a timely manner; not only improves the efficiency of monitoring, but also enhances the system's early warning capabilities, allowing managers to take quick measures to deal with possible security threats.

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

[0133] Example 10: Fig.10 As shown, based on Example 1, the process of triggering the risk assessment program provided by the embodiment of the present invention includes the following steps:

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

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

[0136] S303: Automatically initiate emergency measures according to the set emergency response protocol, such as locking a specific channel, enabling video surveillance to strengthen close monitoring of a certain area, or mobilizing security personnel to deal with the passenger's situation.

[0137] The working principle and beneficial effects of the above technical solution are as follows: the present embodiment first automatically generates detailed risk alarm information, including the identity information, real-time location, retrieved abnormal behavior description and assessed risk level of the relevant passengers; secondly, the alarm information is pushed to the terminal device of the monitoring personnel, who receive the alarm; finally, according to the set emergency response protocol, emergency measures are automatically initiated, such as locking a specific channel, enabling video surveillance to strengthen close monitoring of a certain area, or mobilizing security personnel to deal with the passenger situation. Step S301 of the above scheme automatically generates detailed risk alarm information, and automatically creates a detailed risk alarm information based on the data obtained from the identity information comparison and abnormal behavior detection; the information includes the passenger's identity information, such as name, ID number and biometrics; real-time location, which refers to the specific location of the passenger in the monitoring area; description of retrieved abnormal behavior, such as unusual stay time or abnormal movement trajectory; and assessed risk level (such as low, medium, high). Significance achieved: Ensure the integration of all relevant information, help monitoring personnel quickly understand the situation and improve processing efficiency; provide necessary data support so that monitoring personnel can decide corresponding processing measures according to specific circumstances; ensure the real-time nature of information, be able to reflect potential threats in a timely manner, and 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 may include a display, mobile phone or other types of information terminals, to ensure that the on-site staff can receive the alarm information immediately. Significance achieved: By pushing information in real time, monitoring personnel can understand potential security risks at the first time and respond quickly; timely acquisition of alarm information reduces information flow time, makes the response process more efficient, and enhances the ability to handle security incidents on site; ensures smooth information between the monitoring center and on-site security personnel, and facilitates coordination and linkage tasks. Step S303 automatically starts emergency measures according to the set emergency response protocol. According to the pre-set emergency response protocol, various emergency measures are automatically started; it may include locking specific channels and prohibiting passengers from passing; enabling video surveillance to strengthen close observation of a specific area; and mobilizing security personnel to rush to the scene to deal with potential risk passengers. Significance achieved: Through the immediate implementation of emergency measures, the occurrence of potential threats can be effectively reduced, and necessary monitoring and control of suspicious passengers can be carried out; the complex emergency response process can be standardized and systematized to improve the consistency and comprehensiveness of security work; necessary support can be provided to security personnel to ensure that they can respond specifically to potential threats at the first time and enhance overall security prevention capabilities.

[0138] In summary, the triggering of the risk assessment program in this 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 clearance environment, thereby ensuring passenger safety and smooth customs clearance. In addition, the information-based and automated operation process also reduces the need for manual intervention and reduces the probability of errors.

[0139] Example 11: Fig.11 As shown, an embodiment of the present invention provides a passenger clearance inspection system, comprising:

[0140] The feature extraction module is responsible for arranging facial recognition equipment and sensors in the customs clearance area to capture the target facial features of passengers in real time and collect the location information of passengers;

[0141] The behavior assessment module is responsible for comparing the target's facial features with the identity information pre-stored in the backend database; analyzing the location information to obtain the passenger's movement trajectory and stay time, and continuously assessing whether there is any abnormal behavior;

[0142] The risk assessment module is responsible for not triggering the risk assessment procedure and automatically guiding the passenger to the customs clearance gate when both the identity information comparison result and the abnormal behavior are judged as qualified; when either the identity information comparison result or the abnormal behavior is judged as unqualified, the risk assessment procedure is triggered and an alarm is issued.

[0143] The working principle and beneficial effects of the above technical solution are as follows: the feature extraction module of this embodiment arranges face recognition devices and sensors in the customs clearance area to capture the target facial features of passengers in real time and collect the location information of passengers; the behavior evaluation module compares the target facial features with the identity information pre-stored in the background database; analyzes the location information to obtain the movement trajectory and residence time of the passengers, and continuously evaluates whether there is abnormal behavior; when the risk assessment module judges that both the identity information comparison result and the abnormal behavior are qualified, the risk assessment program is not triggered, and the passengers will be automatically guided to the customs clearance; 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 issued. The feature extraction module of the above scheme can extract the biological features (such as facial features, irises, fingerprints) of passengers in real time by arranging multiple high-performance face image capture devices and sensor devices in the customs clearance area; the equipment can also collect the location information of passengers in the customs clearance area, including movement speed, activity path, key locations of entry and exit, and length of stay. The technical means for feature extraction of this module usually include high-resolution image acquisition, sensor data analysis and real-time update. Significance achieved: Through high-precision equipment and algorithms, it ensures the capture of passengers' biometrics and behavioral data, providing an accurate information basis; it can monitor the dynamic changes of passengers in real time, so that the system can quickly respond to potential risks; the collected location information and activity paths 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 target facial features extracted in real time with the identity information stored in the background database; analyzes the location information of passengers to obtain their movement trajectory and stay time, and evaluates whether there is abnormal behavior; usually includes efficient data matching algorithms and anomaly detection algorithms. Significance achieved: By comparing biometrics, the authenticity of passenger identities is ensured, and identity fraud is effectively prevented; it can promptly detect passengers' abnormal behavior patterns, helping security personnel to conduct further investigations and judgments; dynamically analyze passengers' movement behaviors, and can conduct real-time evaluations of potential risks, so as to respond to abnormal situations more quickly. The risk assessment module integrates the results of identity information comparison and abnormal behavior assessment; when both are judged as qualified, the system will not trigger the risk assessment procedure, and the passenger will be automatically guided to the customs clearance; on the contrary, if any one is judged as unqualified, the risk assessment procedure will be quickly triggered and an alarm signal will be issued. The significance achieved: reduce customs clearance delays for normal passengers, improve customs clearance efficiency, and ensure efficient use of resources; judge risks through clear standards, deal with potential threats in a timely manner, and improve the security of the customs clearance area; provide an emergency response framework that can quickly notify security personnel when risks are discovered, ensuring that the handling measures are accurate and timely.

[0144] In summary, this embodiment achieves efficient and safe customs clearance management. The feature extraction module ensures the real-time and accuracy of the data; the behavior assessment module strengthens the monitoring of passenger identity and behavior and detects abnormalities in a timely manner; the risk assessment module formulates standardized emergency response measures to quickly and effectively respond to potential risks. The security management level of the customs clearance area has been significantly improved, ensuring the safety and smoothness of passenger flow.

[0145] Example 12: Fig.12 As shown, based on Embodiment 1 to Embodiment 10, the passenger clearance inspection device provided by the embodiment of the present invention includes: a camera, a sensor, a background database, a controller, a power supply, and a display device;

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

[0147] The camera is used to capture the passenger's facial image, the sensor is used to monitor the passenger's movement speed and obtain the weight and size data of the luggage, etc.; the background database pre-stores identity information; the controller is used to control the coordinated control of the camera, sensor, background database and display device, analyze the location information, obtain the passenger's movement trajectory and stay time, and continuously evaluate whether there is any abnormal behavior; when any of the identity information comparison results and abnormal behavior is judged to be unqualified, the risk assessment program is triggered and an alarm is issued; the power supply is used to provide energy for the camera, sensor, background database, controller and display device; the display device is used to display the controller processing results.

[0148] The working principle and beneficial effects of the above technical solution are as follows: The working principle of this embodiment is that the camera captures the facial image of the passenger through the camera installed in the customs clearance area, which will be used for subsequent identity comparison; the sensor working in parallel with the camera is responsible for monitoring the passenger's moving speed, position change, and obtaining the weight and size data of the luggage, etc., to evaluate the passenger's behavior; all the collected images and sensor data are sent to the background database through the connected controller, and the background database pre-stores the passenger's identity information and corresponding biometrics, such as fingerprint and iris information; the controller receives the data transmitted by the sensor and the camera, first compares the identity information, and determines whether the captured facial features are consistent with the information in the background database; at the same time, the controller also analyzes the passenger's location information, generates the passenger's movement trajectory and stay time, and determines whether these behaviors are abnormal; according to the identity comparison results and behavior evaluation, if any item is judged to be unqualified, the controller will trigger the risk assessment program and send an alarm signal; the alarm information will be recorded and can be presented to the security personnel through the display device to notify them of further processing measures. The power supply provides a stable energy supply for the entire device, ensuring the normal operation of the camera, sensor, background database, controller and display device and realizing real-time data processing.

[0149] This embodiment, through the combination of cameras and sensors, can collect passengers' facial and behavioral data in real time, ensuring the timeliness of information processing, so as to quickly identify potential risks and abnormal behaviors; using the pre-stored identity information in the background database, through accurate comparison algorithms, the authenticity of the passenger's identity is ensured, the risk of identity fraud is reduced, and a reliable basis is provided for security checks; the sensor not only monitors the passenger's movement speed and luggage information, but also analyzes the passenger's behavior pattern, identifies abnormal activity tracks, and enhances the security response capability; when a risk is identified, the system can automatically trigger an alarm and present the processing results to relevant personnel through a display device, thereby improving the response speed and processing efficiency of on-site security; combined with cameras, sensors, databases, controllers and display devices, it can operate efficiently and stably without human intervention, saving human resources and operating costs, while reducing the possibility of human errors; it can be configured according to different customs clearance environments and requirements, has strong scalability, and adapts to application scenarios with different security requirements.

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

[0151] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention belong to the scope of equivalent technologies of the present invention, the present invention is also intended to include these modifications and variations.

Claims

1. A passenger customs inspection method, characterized in that: The following steps are involved: Facial recognition equipment and sensors are deployed in the customs clearance area to capture the target facial features of passengers in real time and collect the location information of passengers; Compare the target facial features with the identity information pre-stored in the backend database; Analyze location information to obtain passengers’ movement trajectories and duration of stay, and continuously assess whether there are any abnormal behaviors; If both the identity information comparison results and the abnormal behavior are judged to be qualified, the risk assessment procedure will not be triggered and the passenger will be automatically guided to the customs clearance gate; When any of the identity information comparison results and abnormal behaviors are judged to be unqualified, the risk assessment program is triggered and an alarm is issued.

2. The passenger clearance inspection method according to claim 1, characterized in that: in, The expressions for automatically adjusting the lens angle, focal length and shooting mode are: C active =f(L,T,P,V) In the formula, C active Indicates the activation status of the currently enabled face recognition device, 0 indicates inactive, 1 indicates activated, L indicates light intensity, the unit is lx, indicating the lighting environment of the environment, T indicates the time period characteristics, indicating the impact of the time period on the monitoring demand, expressed in discrete values, P indicates the passenger mobility characteristics, indicating the flow rate of passengers in a specific time period, reflecting the density and flow of people in the area, V indicates the important area coefficient, the value is between 0 and 1, indicating the importance of the current monitoring area, the closer to 1, the more important the area; Focus adjustment equation: Angle adjustment equation: Shooting mode selection equation: M={"LowLight"ifL <L threshold and P>P threshold "Standard"if L≥L threshold and P≤P threshold "HighDetail"if V≥0.8, where F is the focal length in mm, which is the lens focal length setting of the face device, A is the lens angle in degrees, which is the shooting angle setting of the face device, and k f , k a , k b Indicates the coefficient, which is used to adjust the sensitivity of focal length and angle. The value needs to be adjusted according to the system characteristics. L threshold Indicates the threshold of light intensity, which is set according to the actual monitoring needs. threshold The threshold of passenger flow rate is determined according to the monitoring focus. max , L min Indicates the maximum and minimum values ​​of ambient light to ensure the rationality of adjustment, P peak Indicates the peak value of passenger flow in order to determine whether the flow exceeds the standard.

3. The passenger clearance inspection method according to claim 1, characterized in that: The process of continuously evaluating for unusual behavior includes the following steps: Analyze the passenger's movement trajectory, extract the location information of each time node, draw the passenger's movement path through continuous coordinate points, and capture the dynamic behavior of each passenger in the customs clearance area; Use dwell time analysis to calculate dwell time at each key location and identify dwell time at security checkpoints, passport control points and key monitoring points through mathematical comparison of time stamp data; If the dwell time at a certain location exceeds the threshold determined by historical data analysis, it will be marked as abnormal; the average moving speed of passengers is calculated in parallel, and the flow status of passengers in the customs clearance area is monitored in real time by combining acceleration data and location information; The passenger's current speed is compared with historical data. If the speed in the captured mobile data is significantly higher than the normal driving speed, or the moving speed fluctuates dramatically in a short period of time, it is judged as potential abnormal behavior.

4. The passenger clearance inspection method according to claim 3, characterized in that: The process of capturing the dynamic behavior of each passenger in the customs clearance area includes the following steps: The data of each sensor is synchronized through timestamps. For each time node, the passenger location information captured by the sensor is extracted to generate continuous coordinate points, which represent the movement trajectory of the passenger in the customs clearance area. By connecting consecutive coordinate points, the passenger's movement path is mapped out; Analyze passengers’ behavior patterns based on the mapped movement paths and identify potential abnormal behaviors; Compare the drawn movement path with real-time data to dynamically capture changes in passenger behavior; through real-time monitoring, detect abnormal changes in passenger behavior.

5. The passenger clearance inspection method according to claim 3, characterized in that: The process of identifying the length of time spent at security, passport control, and other key monitoring points includes the following steps: Through sensors and facial recognition devices placed at key locations, the location information and corresponding timestamps of passengers are continuously collected in real time; whenever a passenger passes a monitoring point, the location coordinates and time information are recorded; the continuous timestamp data are paired, and the time difference between each entry and exit of the key location is obtained through subtraction operations, thereby determining the passenger's stay time at the location; Preset the dwell time threshold for each key location. If the dwell time exceeds the set dwell time, the behavior will be automatically marked as abnormal by comparing the dwell time with the preset threshold. By combining the collected location information with the acceleration data and location coordinates, the location information corresponding to the timestamp is statistically calculated to calculate the passenger's movement speed between key locations.

6. The passenger clearance inspection method according to claim 3, characterized in that: The process of determining potential abnormal behavior includes the following steps: When passengers move at the monitoring point, their speed is obtained in real time and recorded; Compare the current passenger speed 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 status is marked as abnormal; If the speed fluctuations of passengers are monitored and exceed the normal fluctuation range, they will also be judged as potential abnormal behavior.

7. The passenger clearance inspection method according to claim 6, characterized in that: The process of obtaining existing deviations includes the following steps: At the monitoring point, the speed data of passengers is collected in real time, including the instantaneous speed and moving direction of passengers; the speed information of passengers is extracted from the historical monitoring data to build 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; Compare the real-time speed of the current passenger with the historical average speed of the corresponding passenger group, and calculate the difference between the current speed and the historical average speed, that is, the speed deviation value; obtain the speed deviation value 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 mode; The speed deviation value is analyzed to determine whether it exceeds the set normal range. The normal range is determined by statistical analysis of historical data.

8. The passenger clearance inspection method according to claim 7, characterized in that: If the speed deviation value is significantly higher than the set normal range, it is judged as a potential abnormal behavior; at the same time, the speed fluctuation is analyzed, and if the fluctuation exceeds the normal fluctuation range, it is also judged as a potential abnormal behavior.

9. A passenger clearance inspection system, characterized in that: Include: The feature extraction module is responsible for arranging facial recognition equipment and sensors in the customs clearance area to capture the target facial features of passengers in real time and collect the location information of passengers; The behavior assessment module is responsible for comparing the target’s facial features with the identity information pre-stored in the backend database; Analyze location information to obtain passengers’ movement trajectories and duration of stay, and continuously assess whether there are any abnormal behaviors; The risk assessment module is responsible for determining that both the identity information comparison results and the abnormal behavior are qualified. If the risk assessment procedure is not triggered, the passenger will be automatically guided to the customs clearance gate; When any of the identity information comparison results and abnormal behaviors are judged to be unqualified, the risk assessment program is triggered and an alarm is issued.

10. A passenger clearance inspection device, characterized in that: Includes: camera, sensor, background database, controller, power supply, display device; The camera, sensor, background database and display device are connected to the controller, and the power supply is connected to the camera, sensor, background database, controller and display device.

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