Airport security checkpoint scheduling methods, equipment, procedures, and storage media

Abstract

A method, equipment, program product, and storage medium for scheduling airport security checkpoints are disclosed, relating to the technical field of airport management. The method includes: acquiring passenger flow density data in real time; calculating passenger flow rate based on the passenger flow density data; calculating the overall potential time benefit of all inspection areas based on each passenger flow rate; determining the operating scenario based on the current time and a preset time-scenario mapping relationship; calculating the time benefit threshold and duration threshold under the operating scenario based on the operating scenario and each passenger flow rate; determining whether the target resource scheduling scheme meets preset conditions based on the potential time benefit, time benefit threshold, and duration threshold; if the target resource scheduling scheme meets the preset conditions, executing the scheduling according to the target resource scheduling scheme; if the target resource scheduling scheme does not meet the preset conditions, maintaining the current resource scheduling scheme unchanged. Implementing the technical solution provided in this application can improve the operational efficiency of the security checkpoint system.

Description

Technical Field

[0001] This application relates to the technical field of airport management, specifically to an airport security checkpoint scheduling method, equipment, program product, and storage medium. Background Technology

[0002] With the rapid development of the civil aviation industry and the continuous growth of passenger traffic, airport security systems, as the first line of defense for air transport security, directly impact passenger travel experience and the overall operational efficiency of the airport. Modern large airports typically have multiple security checkpoints and inspection areas. How to rationally allocate these resources based on real-time passenger flow has become a crucial technical issue in airport operation and management.

[0003] Currently, airport security checkpoint scheduling primarily employs a dynamic scheduling method based on real-time monitoring. This method deploys passenger flow monitoring equipment in each inspection area to acquire real-time passenger flow density data. When the detected passenger flow density exceeds a preset threshold, resource scheduling operations are triggered, such as opening additional security checkpoints or redeploying inspection personnel. Compared to traditional static scheduling, this dynamic scheduling method offers better real-time response capabilities and can alleviate congestion during peak passenger flow periods to some extent.

[0004] However, existing dynamic scheduling methods suffer from insufficient accuracy in determining the timing of scheduling decisions. Because airport passenger flow exhibits distinct time-varying characteristics and random fluctuations, simple threshold-triggered mechanisms often fail to accurately distinguish between genuine passenger flow increases requiring scheduling and temporary fluctuations. This results in scheduling decisions that are either too frequent, leading to resource waste, or delayed responses that miss the optimal scheduling opportunity, severely impacting the operational efficiency of the security check system. Summary of the Invention

[0005] This application provides a method, equipment, program product, and storage medium for scheduling airport security checkpoints, which can improve the operating efficiency of the security checkpoint system.

[0006] The first aspect of this application provides an airport security checkpoint scheduling method, specifically including: Real-time acquisition of passenger flow density data in various inspection areas of the airport; Calculate the passenger flow rate of each inspection area within a preset time window based on the passenger flow density data; The potential time benefit of all inspection areas after the simulated execution of the target resource scheduling scheme is calculated based on the passenger flow rate of each of the above. The target resource scheduling scheme is the theoretically optimal scheme determined based on the passenger flow density data of each of the above. The operational scenario is determined based on the current time and the preset time-scenario mapping relationship. The time revenue threshold and duration threshold under the operational scenario are calculated based on the operational scenario and each of the passenger flow rates. Based on the potential time benefit, the time benefit threshold, and the duration threshold, it is determined whether the target resource scheduling scheme meets the preset conditions; If the target resource scheduling scheme meets the preset conditions, then the scheduling is performed according to the target resource scheduling scheme; If the target resource scheduling scheme does not meet the preset conditions, the current resource scheduling scheme will remain unchanged.

[0007] By adopting the above technical solution, the system first acquires passenger flow density data in real time and calculates passenger flow rate. Based on this, it calculates the potential time benefit of the target resource scheduling plan, thereby quantitatively evaluating the effectiveness of the scheduling plan. Simultaneously, the solution introduces the concept of operational scenarios. Based on the current time and a preset time-scenario mapping relationship, the operational scenario is determined, and time benefit thresholds and duration thresholds are dynamically calculated based on this scenario. This allows scheduling decisions to better adapt to the operational characteristics of different time periods. Specifically, by comparing potential time benefits with time benefit thresholds and continuously verifying them within the minimum economic scheduling cycle determined by the duration threshold, it is possible to effectively distinguish between real passenger flow growth requiring resource scheduling and short-term passenger flow fluctuations that do not require scheduling. This avoids resource waste caused by frequent scheduling and ensures the economy and stability of scheduling decisions. This scheduling mechanism based on multi-dimensional threshold judgment ensures sensitive response to passenger flow changes and improves the reliability of scheduling decisions through continuous verification, thereby enhancing the operational efficiency of the airport security system.

[0008] Optionally, the potential time benefit for all inspection areas after simulating the execution of the target resource scheduling scheme is calculated based on each of the aforementioned passenger flow rates, including: Calculate the first estimated waiting time for all inspection areas under the current resource scheduling scheme based on the passenger flow rates described above. Simulate the execution of the target resource scheduling scheme, and calculate the second estimated waiting time for all inspection areas as a whole based on the target resource scheduling scheme; The difference between the first estimated waiting time and the second estimated waiting time is calculated to obtain the overall potential time gain for the inspection area.

[0009] By adopting the above technical solution, the first estimated waiting time under the current resource scheduling scheme is calculated based on the real-time acquired passenger flow rate. Then, the second estimated waiting time is calculated by simulating the execution of the target resource scheduling scheme. The difference between the two reflects the time gain that may be brought by implementing the new scheduling scheme. This method of calculating benefits based on waiting time differences not only intuitively reflects the actual improvement of passenger throughput efficiency by the scheduling scheme, but also ensures that scheduling decisions can be optimized based on the overall performance of the security system by considering the waiting times of multiple inspection areas in a unified manner, avoiding the problem of focusing only on local improvements while ignoring the overall effect.

[0010] Optionally, calculating the time revenue threshold and duration threshold under the operational scenario based on the operational scenario and each of the passenger flow rates includes: Obtain the preset passenger flow rate threshold corresponding to the operational scenario, and calculate the overall comprehensive passenger flow rate of the inspection area based on each passenger flow rate; When the overall passenger flow rate is greater than the preset passenger flow rate threshold, obtain the benchmark time revenue threshold and benchmark duration threshold corresponding to the operation scenario. The time revenue threshold of the operation scenario is calculated based on the benchmark time revenue threshold and the first passenger flow density data. The first passenger flow density data includes the overall average passenger flow density of all inspection areas, the standard passenger flow density corresponding to the operation scenario, and the change in passenger flow density within a preset time window. The duration threshold of the operational scenario is calculated based on the baseline duration threshold and the second passenger flow density data. The second passenger flow density data includes the coefficient of variation of the overall passenger flow density of all inspection areas within a preset time window, the average passenger flow density of all inspection areas, and the passenger flow density of the same historical period.

[0011] By adopting the above technical solution, the current operational pressure is first determined by comparing the overall passenger flow rate with a preset passenger flow rate threshold. Threshold adjustments are only made when the threshold is exceeded, avoiding unnecessary calculations when passenger flow is low. Based on this, the solution calculates the time benefit threshold and duration threshold using two sets of passenger flow density data from different dimensions. The calculation of the time benefit threshold fully considers the overall level of current passenger flow, its deviation from the standard level, and short-term trends, allowing the threshold to be adjusted accordingly with changes in passenger flow intensity and volatility. The calculation of the duration threshold incorporates the coefficient of variation of passenger flow density and compares the current average level with historical data from the same period, ensuring that the minimum economic scheduling cycle adapts to the stability and periodicity of passenger flow.

[0012] Optionally, calculating the time revenue threshold for the operational scenario based on the baseline time revenue threshold and the first passenger flow density data includes: Substitute the benchmark time revenue threshold and the first passenger flow density data into the first formula to calculate the time revenue threshold of the operational scenario. The first formula is: ; in, The time benefit threshold, The benchmark time return threshold, The average passenger flow density of the entire inspection area. The standard passenger flow density corresponding to the aforementioned operating scenario. This represents the change in passenger flow density within a preset time window. The current resource utilization rate is... The weighting coefficient for passenger flow deviation Weighting coefficients for the intensity of passenger flow changes This is the weighting coefficient for passenger flow saturation.

[0013] By adopting the above technical solution and using a designed mathematical formula, the benchmark time revenue threshold is weighted and combined with multiple influencing factors, achieving precise adjustment of the threshold. Specifically, the formula introduces three core adjustment terms: the first term is based on passenger flow deviation. The first term reflects the degree of deviation between the current passenger flow and the standard level, and its influence is controlled by a weighting coefficient α; the second term reflects the intensity of passenger flow changes. The third term represents the dynamic changes in passenger flow, with its contribution adjusted by a weighting coefficient β; the fourth term incorporates the current utilization rate of scheduling resources. The impact of resource utilization efficiency is balanced by a weighting coefficient γ. This multi-factor weighted calculation method not only accurately reflects the combined impact of static passenger flow, dynamic changes, and resource utilization on the threshold, but also provides a flexible parameter optimization space through adjustable weighting coefficients. This allows the threshold calculation to be finely adjusted according to actual operational needs, thus providing a more accurate basis for subsequent scheduling decisions.

[0014] Optionally, calculating the duration threshold of the operational scenario based on the baseline duration threshold and the second passenger flow density data includes: Substituting the baseline duration threshold and the second passenger flow density data into the second formula, the duration threshold of the operational scenario is calculated. The second formula is: ; in, For duration threshold, The baseline duration threshold, This is the coefficient of variation of the overall passenger flow density in all inspection areas within a preset time window. The average passenger flow density across all inspection areas. This represents the average passenger flow density for the same historical period. The coefficient of variation of passenger flow density for the same historical period. This represents the number of valid sampling points within a preset time window.

[0015] By adopting the above technical solution, the combination of natural logarithm and exponential function makes the threshold adjustment exhibit non-linear characteristics, which can better adapt to the complexity of passenger flow changes. This study assesses the deviation between current passenger flow and historical levels, and standardizes the data using the coefficient of variation, effectively eliminating the impact of data fluctuations. It also introduces... The ratio is used to measure the change in current passenger flow volatility relative to historical levels, ensuring the threshold's sensitivity to passenger flow stability. Furthermore, using... The term is used to adjust the impact of the current passenger flow intensity on the threshold. It approaches 1 when the passenger flow is high and approaches 0 when it is low, achieving a smooth transition. The formula also considers the number of sampling points. The impact of data reliability is ensured, thus constraining the threshold calculation. This calculation method based on multidimensional statistical indicators guarantees the threshold's sensitivity to passenger flow characteristics while maintaining the stability of the calculation results, providing a reliable time constraint reference for scheduling decisions. Simultaneously, the formula design fully considers the influence of various complex factors in actual operational scenarios, improving the practicality and adaptability of the duration threshold.

[0016] Optionally, determining whether the target resource scheduling scheme meets the preset conditions based on the potential time benefit, the time benefit threshold, and the duration threshold includes: Determine whether the potential time gain is greater than the time gain threshold; if not, determine that the target resource scheduling scheme does not meet the preset conditions. If so, the observation period timing is started, and the duration threshold is used as the length of the observation period. During the observation period, the potential time benefits are repeatedly calculated according to the preset verification interval to obtain multiple target potential time benefits. If any target potential time gain is less than or equal to the time gain threshold during the observation period, it is determined that the target resource scheduling scheme does not meet the preset conditions. When the potential time gain of all targets within the observation period is greater than the time gain threshold, the target resource scheduling scheme is determined to meet the preset conditions.

[0017] By adopting the above technical solution and employing a two-stage judgment mechanism, the risk of misjudgment that may arise from a single evaluation is effectively avoided. First, preliminary screening quickly eliminates scheduling schemes that clearly do not meet the conditions, improving overall evaluation efficiency. For schemes that pass the preliminary screening, the system initiates an observation period mechanism based on a duration threshold. During the observation period, changes in potential time benefits are continuously monitored at preset verification intervals. This continuous verification mechanism fully considers the impact of dynamic changes in passenger flow on scheduling effectiveness, ensuring that the scheduling scheme can continuously generate the expected benefits during actual execution. Simultaneously, by performing multiple verifications during the observation period, the system can promptly detect fluctuations in potential time benefits. If any verification result fails to meet the requirements, the execution of the scheme is immediately terminated, effectively preventing resource waste.

[0018] Optionally, after performing scheduling according to the target resource scheduling scheme, the method further includes: Within a preset monitoring time window, continuously acquire passenger flow density data for each inspection area and calculate the actual waiting time after the target resource scheduling plan is executed; The actual waiting time is compared with the second estimated waiting time to calculate the scheduling effect deviation. When the deviation of the scheduling effect exceeds the preset deviation threshold, the current passenger flow density data is re-acquired and the resource scheduling scheme is re-determined. When the scheduling effect deviation does not exceed a preset deviation threshold, the execution parameters of the target resource scheduling scheme and the corresponding actual effect data are recorded. Based on the execution parameters and the actual effect data, update the baseline time benefit threshold and baseline duration threshold of the corresponding operational scenario in the time-scenario mapping relationship.

[0019] By adopting the above technical solution, a continuous monitoring mechanism is established after the scheduling plan is executed, enabling real-time tracking of scheduling effects and timely detection of deviations between actual and expected results. When the system detects that the scheduling effect deviation exceeds a preset threshold, it immediately triggers a rescheduling process to ensure that resource allocation remains in an optimal state, effectively preventing the deterioration of scheduling effects due to environmental changes. Simultaneously, for scheduling plans with good results, the system records detailed execution parameters and actual effect data, providing valuable experience data for subsequent decision-making. More importantly, the system can dynamically update the benchmark parameters in the time-context mapping relationship based on this real execution data, including the benchmark time benefit threshold and benchmark duration threshold, allowing the system's judgment criteria to continuously improve with the accumulation of actual operational experience. This parameter update mechanism based on actual feedback not only improves the system's adaptability to complex operating environments but also enhances the accuracy and reliability of scheduling decisions.

[0020] In a second aspect, this application provides an airport security checkpoint scheduling device, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, which includes computer instructions, and the one or more processors call the computer instructions to cause the airport security checkpoint scheduling device to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, this application provides a computer program product containing instructions that, when run on an airport security checkpoint scheduling device, cause the airport security checkpoint scheduling device to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, this application provides a computer-readable storage medium including instructions that, when executed on an airport security checkpoint scheduling device, cause the airport security checkpoint scheduling device to perform the method described in the first aspect and any possible implementation thereof. Attached Figure Description

[0023] Figure 1 This is a system architecture diagram of an airport security checkpoint scheduling system provided in an embodiment of this application; Figure 2 This is a flowchart illustrating an airport security checkpoint scheduling method provided in an embodiment of this application; Figure 3 This is a flowchart of a database update based on a target scheduling scheme provided in an embodiment of this application; Figure 4 This is a schematic diagram of an exemplary hardware structure of an airport security checkpoint scheduling device provided in an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0025] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0026] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0027] Figure 1 An airport security checkpoint scheduling system architecture is illustrated. For example... Figure 1 As shown, the system architecture may include monitoring device 011, network 012, and electronic device 013. Network 012 is used to provide a data transmission link between monitoring device 011 and electronic device 013. Network 012 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0028] Monitoring device 011 can send real-time passenger flow data and channel status information to electronic device 013 via network 012. Monitoring device 011 is mainly responsible for acquiring key information such as passenger flow density data, channel occupancy, passenger queue length, and equipment operating status in each inspection area, and sending scheduling data to electronic device 013 according to the preset data transmission protocol.

[0029] Monitoring equipment 011 refers to hardware, which can be monitoring equipment with data acquisition and information transmission functions, including but not limited to video surveillance cameras and other devices with monitoring functions.

[0030] Electronic device 013 is responsible for receiving and comprehensively analyzing scheduling data, including core functions such as passenger flow density calculation, estimated waiting time assessment, potential time benefit analysis, scheduling scheme generation, and resource allocation optimization. Electronic device 013 can adaptively generate scheduling schemes based on passenger flow trends and channel load status, calculate the optimal resource allocation strategy, and combine it with preset scheduling rules and time benefit thresholds to ultimately achieve dynamic scheduling of security checkpoint resources. These analysis and processing results can be used to improve passenger throughput and reduce waiting time.

[0031] It should be noted that electronic devices can be either hardware or software. When an electronic device is hardware, it can be implemented as a distributed cluster of multiple electronic devices or as a single electronic device. When an electronic device is software, it can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed processing) or as a single software program or software module. No specific limitations are set here.

[0032] It should be understood that Figure 1 The number of monitoring devices 011, networks 012, and electronic devices 013 shown is merely illustrative. Depending on implementation needs, there can be any number of monitoring devices 011, networks 012, and electronic devices 013. In particular, if scheduling data does not need to be transmitted remotely, the above system architecture may exclude network 012 and include only monitoring devices 011 or electronic devices 013.

[0033] This application provides a method for scheduling airport security checkpoints, referencing... Figure 2 , Figure 2 This is a flowchart illustrating an airport security checkpoint scheduling method provided in an embodiment of this application, including steps S101 to S106, as follows: S101: Real-time acquisition of passenger flow density data in various inspection areas of the airport.

[0034] In this embodiment of the application, passenger flow density data refers to a quantitative indicator of the number of passengers in a unit area obtained through statistics and calculation within a specific time period. It is used to represent the degree of personnel gathering and flow within the inspection area, such as the number of passengers per square meter of area, the number of passengers passing through a certain checkpoint per unit time, and other numerical information.

[0035] Specifically, monitoring equipment deployed in various inspection areas of the airport continuously monitors and collects passenger flow information. This includes capturing image data of people within the inspection area using the monitoring equipment, and identifying the dynamics of passengers entering and leaving the inspection area by detecting changes in the number of people within the area. After preliminary processing of the collected raw data, the monitoring equipment transmits it in real time via the network to electronic devices for further data analysis and calculation, ultimately generating passenger flow density data containing key information such as timestamps, area identifiers, number of people, and density values.

[0036] S102: Calculate the passenger flow rate of each inspection area within the preset time window based on passenger flow density data.

[0037] In this embodiment of the application, passenger flow rate refers to the rate of change of passenger flow through the inspection area within a specific time period. It is used to represent the number and frequency of passengers passing through the inspection area per unit time, such as dynamic indicators such as the number of passengers passing through the security checkpoint per minute and the passenger flow entering the waiting area per hour.

[0038] Specifically, a fixed-length preset time window is set as the calculation period, and the time window is divided into several consecutive time segments according to fixed time intervals. For each inspection area, the passenger flow density of the inspection area at two adjacent time points is extracted, and the difference in passenger flow density between the two time points is calculated, that is, the passenger flow density at the later time point minus the passenger flow density at the previous time point, to obtain the passenger flow density change. The passenger flow density change is divided by the corresponding time interval length to obtain the passenger flow density change rate within that time period. The above calculation process is repeated for all time segments within the preset time window to obtain multiple passenger flow rates for the inspection area throughout the entire time window. The above calculation process is repeated for all inspection areas to obtain the passenger flow rate for each inspection area.

[0039] S103: Calculate the potential time benefit of all inspection areas after simulating the execution of the target resource scheduling scheme based on each passenger flow rate. The target resource scheduling scheme is the theoretically optimal scheme determined based on each passenger flow density data.

[0040] In this embodiment of the application, the target resource scheduling scheme refers to the theoretical resource allocation strategy determined by the optimization algorithm based on passenger flow density data and passenger flow rate analysis results. It is used to represent the optimal combination of personnel allocation, equipment scheduling and channel management that can theoretically maximize inspection efficiency or minimize waiting time under given constraints. For example, specific resource reallocation measures such as transferring security personnel from areas with less passenger flow to areas with more passenger flow, dynamically opening or closing inspection channels, and adjusting equipment operating parameters.

[0041] First, the resource configuration status of each inspection area at the current moment is obtained, including resource distribution information such as the number of staff, the number of inspection devices, and the number of open channels in each area. For each inspection area, the ratio of passenger flow rate to the current number of staff is calculated as the personnel load index, and the ratio of passenger flow rate to the current number of devices is calculated as the device load index. Personnel load thresholds and device load thresholds are set as judgment criteria. When the personnel load index of an inspection area exceeds the personnel load threshold, the area is marked as a personnel resource shortage area; when the personnel load index is lower than a first preset percentage of the personnel load threshold (e.g., 70%), the area is marked as a personnel resource abundance area. The same logic is used to judge the device load index. When the device load index exceeds the device load threshold, it is marked as a device resource shortage area; when it is lower than a second preset percentage of the device load threshold (e.g., 70%), it is marked as a device resource abundance area. Standard processing capacity parameters for each staff member and standard inspection speed parameters for each piece of equipment are set as calculation benchmarks. For each inspection area, the passenger flow rate is divided by the standard processing capacity of each staff member, and the result is rounded up to obtain the ideal staffing demand for that area. Similarly, the passenger flow rate is divided by the standard inspection speed of each piece of equipment, and the result is rounded up to obtain the ideal equipment demand. The ideal resource demand for each inspection area is compared with the current actual configuration. When the ideal demand is greater than the current configuration, the resource gap is calculated; when the ideal demand is less than the current configuration, the resource redundancy is calculated. Following the principles of proximity and minimum allocation cost, surplus personnel and equipment from resource-sufficient areas are allocated to resource-sufficient areas to form a new resource allocation scheme as the target resource scheduling scheme. Based on the current resource configuration status, the service speed of each inspection area is calculated according to the passenger flow rate and the processing capacity of each staff member, and then the queuing time is calculated. The waiting time of each area is weighted and averaged according to passenger flow to obtain the first estimated waiting time for all inspection areas as a whole. By applying the new resource configuration of the target resource scheduling scheme, the service speed and waiting time of each inspection area under the new configuration are recalculated. The second estimated waiting time for all inspection areas is obtained by using the same weighted averaging method. The difference between the first and second estimated waiting times is calculated to obtain the potential time gain for the entire inspection area.

[0042] Based on the above embodiments, as an optional embodiment, S103: the step of calculating the potential time benefit of all inspection areas as a whole after simulating the execution of the target resource scheduling scheme according to each passenger flow rate may specifically include the following steps: S201: Calculate the first estimated waiting time for all inspection areas under the current resource scheduling plan based on the passenger flow rate.

[0043] In this embodiment of the application, the first estimated waiting time refers to the overall expected queuing waiting time of all inspection areas calculated based on the passenger flow rate data of each inspection area under the current resource scheduling scheme configuration. It is used to represent the average time interval between a passenger entering the inspection queue and starting to receive inspection services under the current personnel allocation, equipment deployment and channel opening status. For example, under the current configuration, the overall estimated waiting time of a certain airport security inspection area is 8 minutes, which means that passengers need to wait an average of 8 minutes to start receiving security inspection services.

[0044] Specifically, the resource configuration status of each inspection area at the current moment is obtained, including the number of staff, inspection equipment, and open channels in each area. Based on the passenger flow rate data for each inspection area, the service capacity of each inspection area is calculated. The service capacity equals the number of staff multiplied by the standard processing rate per staff member, then multiplied by the equipment efficiency coefficient and channel utilization coefficient. For each inspection area, when the passenger flow rate is less than the service capacity, the waiting time is calculated as the passenger flow rate divided by the difference between the service capacity and the passenger flow rate, then multiplied by the average service time. The actual passenger flow data for each inspection area in the current time period is obtained, and the waiting time for each area is multiplied by the proportion of passenger flow in that area as a weighting coefficient. The weighted waiting times of all inspection areas are summed to obtain the overall first estimated waiting time for all inspection areas.

[0045] S202: Simulate the execution of the target resource scheduling scheme and calculate the second estimated waiting time for all inspection areas as a whole based on the target resource scheduling scheme.

[0046] In this embodiment of the application, the second estimated waiting time refers to the overall expected queuing time of all inspection areas calculated by simulating the execution of a new resource allocation strategy under the target resource scheduling scheme configuration. It is used to represent the average time interval between a passenger entering the inspection queue and starting to receive inspection services under the optimized personnel redistribution, equipment redeployment, and channel adjustment state. For example, if the overall estimated waiting time of a certain airport security inspection area is 5 minutes after the implementation of the target resource scheduling scheme, it means that after resource optimization configuration, passengers only need to wait an average of 5 minutes to start receiving security inspection services.

[0047] Specifically, based on the target resource scheduling scheme, the adjusted resource configuration status of each inspection area is obtained, including the number of staff in each area after reallocation, the number of inspection equipment after reallocation, and the number of newly opened channels, among other updated configuration information. The target resource scheduling scheme is simulated and executed in a virtual environment, redeploying surplus personnel from resource-sufficient areas to resource-scarce areas, redeploying idle equipment to high-load areas, and dynamically opening or closing inspection channels based on the new passenger flow distribution. Combining passenger flow rate data for each inspection area, the service capacity of each inspection area under the new configuration is recalculated. The service capacity equals the adjusted number of staff multiplied by the standard processing rate per staff member, then multiplied by the equipment efficiency coefficient and the channel utilization coefficient. For each inspection area, when the passenger flow rate is less than the new service capacity, the waiting time for that area is calculated as the passenger flow rate divided by the difference between the new service capacity and the passenger flow rate, then multiplied by the average service time. When the passenger flow rate is greater than or equal to the new service capacity, the steady-state waiting time is calculated based on queuing theory principles. The actual passenger flow data for each inspection area is obtained, and the waiting time for each area under the new configuration is multiplied by the proportion of passenger flow in that area as a weighting coefficient. The weighted waiting times of all inspection areas are summed to obtain the second estimated waiting time for all inspection areas as a whole.

[0048] S203: Calculate the difference between the first estimated waiting time and the second estimated waiting time to obtain the overall potential time gain of the inspection area.

[0049] In this embodiment of the application, potential time gain refers to the amount of time efficiency improvement that can be obtained by implementing the target resource scheduling scheme compared with the current resource scheduling scheme, and is used to represent the degree of improvement in overall inspection efficiency reflected by the difference between the first expected waiting time and the second expected waiting time.

[0050] Specifically, the first estimated waiting time for all inspection areas, calculated based on the current resource scheduling scheme, is obtained. The second estimated waiting time for all inspection areas, calculated by simulating the execution of the target resource scheduling scheme, is also obtained. The first estimated waiting time is subtracted from the second estimated waiting time, and the time difference between the two is calculated. A positive result indicates that the target resource scheduling scheme can reduce the overall waiting time, and this positive value represents the potential time gain. A negative result indicates that the target resource scheduling scheme will increase the overall waiting time, and the potential time gain is set to zero.

[0051] S104: Determine the operating scenario based on the current time and the preset time-scenario mapping relationship, and calculate the time revenue threshold and duration threshold under the operating scenario based on the operating scenario and each passenger flow rate.

[0052] In this embodiment, the operational scenario refers to a specific operational state category corresponding to the current time point in a preset time-scenario mapping relationship. This category represents the comprehensive operational environment of the airport inspection area at different time periods, encompassing passenger flow characteristics, resource demands, and service standards. For example, the morning peak operational scenario corresponds to the period from 7:00 AM to 9:00 AM, characterized by high passenger volume, high waiting time sensitivity, and peak resource demand. Conversely, the late-night operational scenario corresponds to the period from 11:00 PM to 5:00 AM, characterized by low passenger volume, high waiting time tolerance, and minimal resource demand. The time-scenario relationship refers to the correspondence between the current time and the operational scenario, including the operational scenario corresponding to each time period.

[0053] Specifically, the system matches the current system time against a pre-defined time-context mapping table to determine the operational context category corresponding to the current time point, including different operational states such as morning peak, evening peak, off-peak, and late night. A pre-defined passenger flow rate threshold corresponding to the determined operational context is obtained as a judgment benchmark. Based on passenger flow rate data from each inspection area, a weighted average method is used to calculate the overall comprehensive passenger flow rate of the inspection area, where the weight coefficient represents the processing capacity proportion of each area. When the comprehensive passenger flow rate exceeds the pre-defined passenger flow rate threshold, a baseline time benefit threshold and a baseline duration threshold corresponding to the operational context are obtained as the starting point for calculation. First passenger flow density data is collected, including the overall average passenger flow density of all inspection areas, the standard passenger flow density corresponding to the operational context, and the change in passenger flow density within a pre-defined time window. Based on the baseline time benefit threshold, combined with the ratio of average passenger flow density to standard passenger flow density and the influence coefficient of passenger flow density change, the time benefit threshold under the operational context is calculated. Second passenger flow density data is collected, including the coefficient of variation of the overall passenger flow density of all inspection areas within the pre-defined time window, the overall average passenger flow density of all inspection areas, and the passenger flow density of the same historical period. Based on the baseline duration threshold, and combined with the passenger flow density variation coefficient, the average passenger flow density and the historical passenger flow density for the same period are compared to calculate the duration threshold under the operational scenario.

[0054] Based on the above embodiments, as an optional embodiment, S104: the step of calculating the time revenue threshold and duration threshold under the operating scenario according to the operating scenario and each passenger flow rate may specifically include the following steps: S301: Obtain the preset passenger flow rate threshold corresponding to the operational scenario, and calculate the overall comprehensive passenger flow rate of the inspection area based on each passenger flow rate.

[0055] In this embodiment of the application, the comprehensive passenger flow rate refers to the overall passenger flow processing speed index of the inspection area obtained by integrating and calculating the passenger flow rate data of each inspection area. It is used to represent the overall passenger flow throughput capacity and processing efficiency of the entire inspection area under the current operating situation. For example, when the passenger flow rate of inspection channel A is 5 people per minute, the passenger flow rate of inspection channel B is 4 people per minute, and the passenger flow rate of inspection channel C is 6 people per minute, the overall comprehensive passenger flow rate of the inspection area can be obtained by weighted calculation as 5.2 people per minute, which reflects the average passenger flow processing level of the entire inspection area.

[0056] Specifically, based on the determined operational scenario category, the corresponding preset passenger flow rate threshold is queried from the preset scenario-threshold mapping table. Current passenger flow rate data for each inspection area is obtained, including the real-time passenger flow rate at each security checkpoint and inspection point. The processing capacity weighting coefficients for each inspection area are collected; these coefficients reflect the proportion and importance of different areas in the overall inspection capacity. A weighted average calculation is performed, multiplying the passenger flow rate value of each inspection area by its corresponding weighting coefficient, and then summing all weighted results to obtain a weighted total value. The weighted total value is divided by the sum of all weighting coefficients to calculate the overall comprehensive passenger flow rate of the inspection area.

[0057] S302: When the overall passenger flow rate is greater than the preset passenger flow rate threshold, obtain the benchmark time revenue threshold and benchmark duration threshold corresponding to the operation scenario.

[0058] In this embodiment, the benchmark time benefit threshold refers to the minimum time benefit standard value required to initiate resource scheduling optimization under a specific operating scenario. It is used to represent the time benefit baseline for judging whether the target resource scheduling scheme has implementation value. For example, in the morning peak operating scenario, the benchmark time benefit threshold is set to 3 minutes, indicating that it is worthwhile to perform resource scheduling operation only when the target scheduling scheme can bring at least 3 minutes of time benefit. In the late night operating scenario, the benchmark time benefit threshold may be set to 1 minute, reflecting the differentiated standards of time benefit requirements for different operating scenarios.

[0059] Specifically, the overall passenger flow rate is compared with a preset passenger flow rate threshold. When the overall passenger flow rate is greater than the preset passenger flow rate threshold, the corresponding baseline time revenue threshold is queried in the preset scenario-threshold configuration table according to the determined operation scenario category, and the baseline duration threshold corresponding to that operation scenario is also queried in the same configuration table.

[0060] S303: Calculate the time benefit threshold for the operating scenario based on the baseline time benefit threshold and the first passenger flow density data. The first passenger flow density data includes the overall average passenger flow density of all inspection areas, the standard passenger flow density corresponding to the operating scenario, and the change in passenger flow density within the preset time window.

[0061] Specifically, the baseline time revenue threshold and the first passenger flow density are obtained. These are then substituted into the first formula to calculate the time revenue threshold for the operational scenario. The first formula is: ;in, The time benefit threshold, This is the baseline time revenue threshold, which is directly derived from the basic threshold obtained from the configuration table based on the operational scenario in the preceding steps. To determine the average passenger flow density of the entire inspection area, the standard passenger flow density corresponding to the current operating scenario is retrieved from the preset standard configuration library for operating scenarios. It is determined based on statistical analysis of historical operating data and expert experience. The change in passenger flow density within a preset time window is obtained by calculating the difference in passenger flow density between the end and beginning times of the time window. The current scheduling resource utilization rate is calculated by dividing the number of used resources by the total number of resources. α is the weighting coefficient of passenger flow deviation, β is the weighting coefficient of passenger flow change intensity, and γ is the weighting coefficient of passenger flow saturation, which are read from the system parameter configuration file.

[0062] The first formula consists of a base threshold multiplied by three dynamic adjustment factors. The base threshold directly uses the baseline time benefit threshold. The first adjustment factor reflects the impact of passenger flow deviation on the threshold by multiplying the deviation of the current passenger flow density from the standard passenger flow density by the corresponding weight coefficient. The second adjustment factor reflects the impact of passenger flow fluctuation on the threshold by multiplying the relative intensity of passenger flow density changes by the corresponding weight coefficient. The third adjustment factor reflects the impact of resource scarcity on the threshold by multiplying resource utilization rate by the corresponding weight coefficient. The physical meaning of the formula is that when passenger flow deviates more from the standard state, passenger flow changes are more drastic, and resource utilization is more strained, a higher time benefit is required to justify initiating resource scheduling, ensuring the economy and effectiveness of scheduling decisions. This multi-dimensional parameter fusion calculation method enables the time benefit threshold to accurately adapt to the real-time operating environment, improving the targeting and success rate of resource scheduling. Multiplication and addition operations are performed to calculate the dynamically adjusted time benefit threshold for the operating scenario.

[0063] S304: Calculate the duration threshold of the operation scenario based on the baseline duration threshold and the second passenger flow density data. The second passenger flow density data includes the coefficient of variation of the overall passenger flow density of all inspection areas within the preset time window, the average passenger flow density of all inspection areas, and the passenger flow density of the same period in history.

[0064] Specifically, the baseline duration threshold and the second passenger flow density data are obtained. These are then substituted into the second formula to obtain the duration threshold for the operational scenario. The second formula is:

[0065] ;in, For duration threshold, As the baseline duration threshold, The coefficient of variation of passenger flow density within a preset time window is obtained by calculating the standard deviation and mean of passenger flow density in each inspection area, and then dividing the standard deviation by the mean. To check the overall average passenger flow density of the inspection area, the number of passengers and area information of each inspection area are obtained in real time. After calculating the passenger flow density of each area, a weighted average is performed to obtain the overall average passenger flow density of the inspection area. To obtain the historical average passenger flow density for the same period, query passenger flow density records for the same time period, perform statistical analysis on the historical passenger flow density data for the same period, and calculate the average value to obtain the historical average passenger flow density for the same period. The coefficient of variation for passenger flow density during the same historical period is calculated by dividing the standard deviation by the mean of the passenger flow density data for the same historical period. To determine the number of valid sampling points within a preset time window, count the total number of time points within the preset time window where valid passenger flow data was successfully collected, thus obtaining the number of valid sampling points within the preset time window.

[0066] The second formula consists of a base threshold and three consecutively multiplied adjustment factors. The base threshold directly uses the baseline duration threshold, and the first adjustment factor... The second adjustment factor is calculated using a logarithmic function to represent the combined impact of current passenger flow relative to historical levels and fluctuations. This is achieved by dividing the difference between current and historical passenger flow densities by the current coefficient of variation, then multiplying this by the ratio of historical passenger flow density to the current coefficient of variation, and finally dividing by the historical coefficient of variation. The saturation effect of the current passenger flow density relative to historical levels is represented by a negative exponential function. This is achieved by subtracting the natural exponential function value (which is the current passenger flow density divided by the historical passenger flow density) from the third adjustment factor. The formula uses the sum of the effective sampling points and their reciprocals to represent the impact of data sampling sufficiency on threshold reliability. The physical meaning of the formula is that when passenger flow volatility increases, current passenger flow levels significantly deviate from historical levels, or data sampling is insufficient, the duration of resource scheduling needs to be extended to ensure the stability and reliability of the scheduling effect.

[0067] S105: Determine whether the target resource scheduling scheme meets the preset conditions based on the potential time benefit, time benefit threshold, and duration threshold.

[0068] In this application embodiment, the preset conditions refer to the comprehensive evaluation criteria that the target resource scheduling scheme needs to meet before actual execution. They are used to represent the feasibility judgment rules of the resource scheduling scheme based on the verification of the potential time benefit and the comparison of the time benefit threshold. For example, when the potential time benefit of a resource scheduling scheme in a certain inspection area is 5 minutes and greater than the time benefit threshold of 3.8 minutes, and all the potential time benefit values ​​repeatedly calculated within the 12-minute observation period remain above 3.8 minutes, then the scheduling scheme is determined to meet the preset conditions and can be executed, ensuring the stability and effectiveness of resource scheduling decisions.

[0069] Specifically, the process involves obtaining the potential time benefit value, time benefit threshold value, and duration threshold value corresponding to the target resource scheduling scheme. The first round of judgment compares the potential time benefit with the time benefit threshold. If the potential time benefit is less than or equal to the time benefit threshold, the target resource scheduling scheme is directly determined not to meet the preset conditions, and the judgment process ends. If the potential time benefit is greater than the time benefit threshold, an observation period verification mechanism is initiated, setting an observation period timer and using the duration threshold as the observation period length. During the observation period, the potential time benefit calculation process is repeatedly executed at preset verification intervals. Each calculation uses real-time passenger flow data and resource status data at the current moment, and the result of each calculation is recorded as the target potential time benefit and stored in the verification data sequence. The comparison results of each target potential time benefit with the time benefit threshold are continuously monitored during the observation period. If any target potential time benefit is found to be less than or equal to the time benefit threshold, the observation period is immediately interrupted, and the target resource scheduling scheme is determined not to meet the preset conditions. When the observation period ends normally and all target potential time benefits during the period are greater than the time benefit threshold, all verification checks are performed, and the target resource scheduling scheme is determined to meet the preset conditions.

[0070] Based on the above embodiments, as an optional embodiment, S105: the step of determining whether the target resource scheduling scheme meets the preset conditions based on the potential time benefit, the time benefit threshold, and the duration threshold may specifically include the following steps: S601: Determine whether the potential time benefit is greater than the time benefit threshold. If not, determine that the target resource scheduling scheme does not meet the preset conditions.

[0071] Specifically, the potential time benefit and the time benefit threshold are compared. When the potential time benefit is less than or equal to the time benefit threshold, the judgment result is marked as not meeting the preset conditions. When the potential time benefit is greater than the time benefit threshold, the judgment result is marked as pending further verification, thus retaining the qualification for the target resource scheduling scheme to continue to enter the observation period verification stage.

[0072] S602: If so, start the observation period timing, use the duration threshold as the length of the observation period, and repeatedly calculate the potential time benefits according to the preset verification interval within the observation period to obtain multiple target potential time benefits.

[0073] In this embodiment of the application, the observation period refers to a continuous monitoring period set to verify the stability of the target resource scheduling scheme. It is used to represent the fixed time length from the start of verification to the completion of all stability checks. During this period, the performance of the scheduling scheme needs to be evaluated repeatedly at a specified frequency.

[0074] Specifically, when the potential time gain exceeds the time gain threshold, the observation period timer is activated, the timer is initialized, and the current system time is set as the start time of the observation period. The duration threshold is directly assigned to the length of the observation period, and the end time of the observation period is determined as the start time plus the duration threshold. Starting from the start time of the observation period, the potential time gain calculation process is repeatedly triggered according to the time step set by the verification interval. At each verification time point, the real-time passenger flow data, resource status data, and queue length information are reacquired, and the potential time gain calculation is re-executed using the same algorithm and formula as the initial calculation, ensuring that each calculation is based on the latest system status data. The potential time gain result obtained from each calculation is marked as the target potential time gain and stored sequentially in the verification data array according to the calculation time order. When the accumulated time reaches the observation period length set by the duration threshold, the repeated calculation process is stopped, the timer is turned off, and multiple target potential time gains are output.

[0075] S603: If the potential time gain of any target is less than or equal to the time gain threshold during the observation period, the target resource scheduling scheme is determined to not meet the preset conditions.

[0076] Specifically, the potential time benefits of each target are checked sequentially according to their time order within the observation period. Each potential time benefit is compared to a time benefit threshold. If any potential time benefit is found to be less than or equal to the time benefit threshold, a judgment result is immediately set as not meeting the preset condition, and subsequent potential time benefits are no longer checked.

[0077] S604: When the potential time benefits of all targets within the observation period are greater than the time benefit threshold, the target resource scheduling scheme is determined to meet the preset conditions.

[0078] Specifically, the process determines whether the potential time gain within the observation period exceeds a time gain threshold. It counts the number of potential time gains that pass the threshold check and records the total number of potential time gains. It then determines whether the number of potential time gains that pass the threshold check equals the total number of potential time gains within the observation period. If the number of potential time gains equals the total number of potential time gains within the observation period, it confirms that all potential time gains within the observation period meet the condition of exceeding the time gain threshold. The determination result is then marked as meeting a preset condition.

[0079] S106: If the target resource scheduling scheme meets the preset conditions, then the scheduling shall be executed according to the target resource scheduling scheme; if the target resource scheduling scheme does not meet the preset conditions, then the current resource scheduling scheme shall remain unchanged.

[0080] Specifically, when the target resource scheduling scheme meets the preset conditions, the configuration of the target resource scheduling scheme is obtained and applied to the system, enabling the system to execute resource scheduling according to the target scheme. When the determination result is that the target resource scheduling scheme does not meet the preset conditions, the current resource scheduling configuration of the system remains unchanged, and the existing resource allocation strategy and scheduling rules continue to be used.

[0081] Based on the above embodiments, as an optional embodiment, S106: After executing the scheduling according to the target resource scheduling scheme, a step of tracking the scheduling effect is further included, which may specifically include the following steps: S701: Continuously acquire passenger flow density data for each inspection area within a preset monitoring time window, and calculate the actual waiting time after the target resource scheduling plan is executed.

[0082] In this embodiment of the application, the actual waiting time refers to the actual waiting time calculated from real-time monitoring data after the target resource scheduling scheme is executed, which is used to represent the specific performance of the target resource scheduling scheme in the actual operating environment.

[0083] Specifically, within a preset monitoring time window, passenger flow density data, including key indicators such as the number of people entering, the number of people queuing, and processing speed, is periodically obtained from the monitoring equipment in each inspection area. The average processing time and queuing time for each inspection area are calculated. Using mathematical statistical methods, the actual waiting time is calculated as: actual waiting time = queuing time + processing time, where queuing time = (current number of people in the queue × average processing time per person), and processing time is obtained through the start and end timestamps of the monitoring inspection process.

[0084] S702: Compare the actual waiting time with the second estimated waiting time to calculate the scheduling effect deviation.

[0085] Specifically, the actual waiting time and the second estimated waiting time are mathematically calculated. The scheduling effect deviation is calculated as: Actual waiting time - Second estimated waiting time. A positive result indicates that the actual waiting time is higher than expected, and a negative result indicates that the actual waiting time is lower than expected.

[0086] S703: When the scheduling effect deviation exceeds the preset deviation threshold, reacquire the current passenger flow density data and redetermine the resource scheduling plan.

[0087] Specifically, when the scheduling deviation exceeds a preset deviation threshold, real-time passenger flow density data is obtained from the monitoring equipment in each inspection area. This data includes the latest personnel distribution, queuing status, and processing speed. Based on the newly acquired passenger flow density data, the resource allocation requirements for each inspection area are recalculated, generating a new resource scheduling plan that includes adjustments to personnel configuration, equipment allocation, and channel opening strategies. The newly determined resource scheduling plan replaces the currently executed plan.

[0088] S704: When the scheduling effect deviation does not exceed the preset deviation threshold, record the execution parameters of the target resource scheduling scheme and the corresponding actual effect data.

[0089] Specifically, when the absolute value of the scheduling effect deviation is less than or equal to a preset deviation threshold, the complete execution parameters of the target resource scheduling plan are extracted, including configuration information such as the number of personnel in each inspection area, equipment allocation plan, channel opening strategy, and resource allocation ratio. Corresponding actual effect data is collected, including key performance indicators such as actual waiting time, passenger flow processing efficiency, resource utilization rate, and system response time. A data record structure is established to associate and map the execution parameters with the actual effect data, generating a complete scheduling plan execution archive. The recorded data is stored in a historical database, with timestamps and plan identifiers established for easy subsequent querying and analysis.

[0090] S705: Baseline time benefit threshold and baseline duration threshold based on the execution parameters and actual effect data update time-scenario mapping relationship corresponding to the operational scenario.

[0091] Specifically, the system identifies the operational scenario type corresponding to the current scheduling plan. It queries the existing baseline time benefit threshold and baseline duration threshold for this operational scenario from the time-scenario mapping database. It calculates the actual time benefit in the actual effect data as (expected time - actual time) / expected time. When the actual time benefit exceeds the current baseline time benefit threshold, it updates the baseline time benefit threshold according to a preset adjustment ratio; the new threshold lies between the current threshold and the actual time benefit. It extracts the duration information from the actual effect data and calculates the actual duration of the scheduling plan's effect. When the actual duration exceeds the current baseline duration threshold, it updates the baseline duration threshold using a weighted average method. Finally, it writes the updated baseline time benefit threshold and baseline duration threshold back to the time-scenario mapping database, completing the dynamic optimization update of the corresponding operational scenario parameters.

[0092] like Figure 3 The above, Figure 3 This is a flowchart of a database update based on a target scheduling scheme provided in an embodiment of this application, combined with... Figure 3 The user confirms that the scheduling system will execute the target resource scheduling plan, and calculates the deviation in scheduling effect between the actual execution of the target resource scheduling plan and the simulated execution of the target resource scheduling plan. Subsequently, the system performs a crucial conditional judgment: if the calculated deviation exceeds a preset threshold, the system will directly send an alarm message to the user; otherwise, if the deviation is within an acceptable range, the system will record the execution parameters of the simulated execution of the target resource scheduling plan and the actual effect data of the actual execution of the target resource scheduling plan into the historical database. Based on these newly recorded actual effect data, the system will recalculate and update the corresponding baseline time benefit threshold and baseline duration threshold in the time context mapping relationship database, thereby completing the dynamic adjustment and self-optimization of the system model.

[0093] The following describes an exemplary airport security checkpoint scheduling device provided in the embodiments of this application. Figure 4 This is a schematic diagram of an exemplary hardware structure of the airport security checkpoint scheduling equipment provided in this application embodiment.

[0094] In some embodiments, the airport security checkpoint scheduling equipment is a computer device or includes a computer device. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device stores data. The network interface of the computer device is used to communicate with other external terminals or servers via a network connection. In some embodiments, the network interface can be a wired network interface; in some embodiments, the network interface can also be a wireless network interface. When the computer program is executed by the processor, it implements the methods in the embodiments of this application.

[0095] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0096] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0097] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0098] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0099] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. An airport security checkpoint lane dispatching method, characterized by, The method includes: Real-time acquisition of passenger flow density data in various inspection areas of the airport; Calculate the passenger flow rate of each inspection area within a preset time window based on the passenger flow density data; The potential time benefit of all inspection areas after the simulated execution of the target resource scheduling scheme is calculated based on the passenger flow rate. The target resource scheduling scheme is a theoretical resource allocation strategy determined by an optimization algorithm based on the passenger flow density data and passenger flow rate analysis results. It is used to represent the optimal combination of personnel allocation, equipment scheduling and channel management that can theoretically maximize inspection efficiency or minimize waiting time under given constraints. The operational scenario is determined based on the current time and the preset time-scenario mapping relationship. The time revenue threshold and duration threshold under the operational scenario are calculated based on the operational scenario and each of the passenger flow rates. Based on the potential time benefit, the time benefit threshold, and the duration threshold, it is determined whether the target resource scheduling scheme meets the preset conditions; If the target resource scheduling scheme meets the preset conditions, then the scheduling is performed according to the target resource scheduling scheme; If the target resource scheduling scheme does not meet the preset conditions, the current resource scheduling scheme remains unchanged. Calculate the overall potential time benefit of all inspection areas after simulating the execution of the target resource scheduling scheme based on the aforementioned passenger flow rates, including: Calculate the first estimated waiting time for all inspection areas under the current resource scheduling scheme based on the passenger flow rates described above. Simulate the execution of the target resource scheduling scheme, and calculate the second estimated waiting time for all inspection areas as a whole based on the target resource scheduling scheme; Calculate the difference between the first estimated waiting time and the second estimated waiting time to obtain the overall potential time gain for the inspection area; The step of calculating the time revenue threshold and duration threshold under the operational scenario based on the operational scenario and each of the passenger flow rates includes: Obtain the preset passenger flow rate threshold corresponding to the operational scenario, and calculate the overall comprehensive passenger flow rate of the inspection area based on each passenger flow rate; When the overall passenger flow rate is greater than the preset passenger flow rate threshold, obtain the benchmark time revenue threshold and benchmark duration threshold corresponding to the operation scenario. The time revenue threshold of the operation scenario is calculated based on the benchmark time revenue threshold and the first passenger flow density data. The first passenger flow density data includes the overall average passenger flow density of all inspection areas, the standard passenger flow density corresponding to the operation scenario, and the change in passenger flow density within a preset time window. The duration threshold of the operation scenario is calculated based on the baseline duration threshold and the second passenger flow density data. The second passenger flow density data includes the coefficient of variation of the overall passenger flow density of all inspection areas within the preset time window, the average passenger flow density of all inspection areas, and the passenger flow density of the same historical period. The calculation of the time revenue threshold for the operational scenario based on the baseline time revenue threshold and the first passenger flow density data includes: Substitute the benchmark time revenue threshold and the first passenger flow density data into the first formula to calculate the time revenue threshold of the operational scenario. The first formula is: ； in, The time benefit threshold, The benchmark time return threshold, The average passenger flow density of the entire inspection area. The standard passenger flow density corresponding to the aforementioned operating scenario. This represents the change in passenger flow density within a preset time window. The current resource utilization rate is calculated by dividing the amount of resources used by the total amount of resources. The weighting coefficient for passenger flow deviation Weighting coefficients for the intensity of passenger flow changes This is a weighting coefficient for passenger flow saturation. The calculation of the duration threshold of the operational scenario based on the baseline duration threshold and the second passenger flow density data includes: Substituting the baseline duration threshold and the second passenger flow density data into the second formula, the duration threshold of the operational scenario is calculated. The second formula is: ； in, For duration threshold, The baseline duration threshold, This is the coefficient of variation of the overall passenger flow density in all inspection areas within a preset time window. The average passenger flow density across all inspection areas. This represents the average passenger flow density for the same historical period. The coefficient of variation of passenger flow density for the same historical period. The number of valid sampling points within the preset time window; After executing the scheduling according to the target resource scheduling scheme, the process further includes: Within a preset monitoring time window, continuously acquire passenger flow density data for each inspection area and calculate the actual waiting time after the target resource scheduling plan is executed; The actual waiting time is compared with the second estimated waiting time to calculate the scheduling effect deviation. When the deviation of the scheduling effect exceeds the preset deviation threshold, the current passenger flow density data is reacquired and the target resource scheduling scheme is re-determined. When the scheduling effect deviation does not exceed a preset deviation threshold, the execution parameters of the target resource scheduling scheme and the corresponding actual effect data are recorded. Based on the execution parameters and the actual effect data, update the baseline time benefit threshold and baseline duration threshold of the corresponding operational scenario in the time-scenario mapping relationship.

2. The airport security checkpoint scheduling method according to claim 1, characterized in that, The step of determining whether the target resource scheduling scheme meets the preset conditions based on the potential time benefit, the time benefit threshold, and the duration threshold includes: Determine whether the potential time gain is greater than the time gain threshold; if not, determine that the target resource scheduling scheme does not meet the preset conditions. If so, the observation period timing is started, and the duration threshold is used as the length of the observation period. During the observation period, the potential time benefits are repeatedly calculated according to the preset verification interval to obtain multiple target potential time benefits. If any target potential time gain is less than or equal to the time gain threshold during the observation period, it is determined that the target resource scheduling scheme does not meet the preset conditions. When the potential time gain of all targets within the observation period is greater than the time gain threshold, the target resource scheduling scheme is determined to meet the preset conditions.

3. An airport security checkpoint scheduling device, characterized in that, The airport security checkpoint scheduling device includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors invoke the computer instructions to cause the airport security checkpoint scheduling device to perform the method as described in any one of claims 1-2.

4. A computer program product containing instructions, characterized in that, When the computer program product is run on the airport security checkpoint scheduling equipment, the airport security checkpoint scheduling equipment performs the method as described in any one of claims 1-2.

5. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the airport security checkpoint scheduling equipment, the airport security checkpoint scheduling equipment performs the method as described in any one of claims 1-2.

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