Electronic tag structure capable of preventing liquid from transferring

Abstract

The invention discloses an electronic tag structure capable of preventing liquid transfer, belongs to the field of electronic tags, and aims to solve the problem that liquid approaching and tag transfer conditions are difficult to monitor. Comprising a data sensing module, a data processing module and a communication transmission module. Monitoring information of an environment where the electronic tag is located, the pasting state of the electronic tag and dynamic changes of the electronic tag in real time, collecting state data of the electronic tag, and carrying out preliminary abnormal screening on the electronic tag based on the state data to obtain a potential abnormal electronic tag; integrity processing is carried out on the state data, an evaluation data set is constructed based on time interval division and data screening, the abnormal type and severity of the potential abnormal electronic tag are determined through comprehensive humidity, pressure and acceleration multi-dimensional deep analysis, and an execution instruction is generated; intelligent identification, authority verification, dynamic response and flow distribution scheduling are carried out on communication requests from different sources, and transmission data is transmitted to a target terminal through hierarchical encryption of the transmission data.

Description

Technical Field

[0001] The invention relates to the field of electronic labels, and more particularly to an electronic label structure that is liquid-proof and transfer-proof. Background Art

[0002] In the daily operation of the airport, a large number of passenger baggage from a wide range of sources must be handled every day. Considering environmental factors, airport baggage will inevitably be exposed to various external conditions during transportation, among which rain and other liquid forms of interference are particularly prominent. Whether it is the rain erosion while waiting for loading on the apron, or the various water stains and humid environments that may be encountered during the baggage handling process, they may have a serious impact on the electronic tags attached to the luggage. Once the electronic tag is penetrated or soaked by liquid, the electronic components inside it may be short-circuited and damaged, resulting in the loss of baggage information stored in the tag or the inability to read it normally, which in turn makes it difficult to track and identify the baggage, affecting the accuracy and efficiency of baggage check-in.

[0003] At the same time, the transfer problem during baggage check-in has always troubled airport operators. In the entire transfer chain from the check-in counter to the boarding gate, to the aircraft cargo hold and after arriving at the destination, the electronic tag needs to be firmly attached to the luggage at all times. However, in reality, due to factors such as frequent bumps of luggage on the conveyor belt, collisions and squeezing during loading and unloading, and manual handling, traditional electronic tags are easily displaced or even fall off. Moreover, in some extreme cases, there may be a risk of the tag being maliciously transferred to other luggage, which will cause the luggage information to be confused with the actual passenger, causing safety and service problems. An anti-liquid and anti-transfer electronic tag structure is of great importance and urgency for airports to improve the level of baggage check-in management, protect the rights and interests of passengers, and maintain normal operating order.

[0004] A Chinese patent application with publication number CN118627529A discloses an airport checked baggage electronic tag system and a recycling method. The surface of the electronic tag is provided with a one-dimensional code / two-dimensional code and a unique identification ID code. The electronic tag can be taken away and kept by the passenger or kept by the airport and recycled within the airport system. The system includes an electronic tag information filling client, a check-in counter electronic tag reader / writer, a self-service check-in device, an electronic tag reader, and a self-service exit gate.

[0005] Although the existing technology has improved the intelligence level of airports, reduced the probability of wrongly taking the same checked luggage, and solved the huge waste problem caused by the one-time use of existing electronic tags, it still fails to solve the accurate perception and multi-dimensional abnormal analysis of the physical state changes of the humidity, pressure, acceleration and other physical states of the electronic tags in the checked luggage, as well as the insufficiency in ensuring data transmission security and intelligent interaction, and cannot effectively prevent the baggage management risks and data transmission risks caused by abnormal situations such as liquid erosion and tag transfer. Therefore, in order to overcome these limitations, the present invention proposes an electronic tag structure that is anti-liquid and anti-transfer. Summary of the invention

[0006] In view of the shortcomings of the prior art, the purpose of the present invention is to provide an electronic tag structure that is resistant to liquids and transfer, which solves the technical problems that the prior art cannot effectively monitor and respond to abnormal conditions such as electronic tags being affected by liquids and transfer in scenarios such as airport checked baggage, and that data interaction lacks security and intelligence.

[0007] To achieve the above object, the present invention provides the following technical solutions: An anti-liquid and anti-transfer electronic tag structure, comprising a data sensing module, a data processing module and a communication transmission module; The data perception module is used to monitor the environment information of the electronic tag, the sticking status of the electronic tag, and the dynamic changes of the electronic tag in real time, collect the status data of the electronic tag, and perform preliminary abnormal screening of the electronic tag based on the status data to obtain potential abnormal electronic tags; The data processing module is used to process the integrity of the status data, build an evaluation data set based on time interval division and data screening, determine the abnormal type and severity of potential abnormal electronic tags through comprehensive humidity, pressure, and acceleration multi-dimensional analysis, and generate execution instructions; The communication transmission module is used to intelligently identify, verify permissions, dynamically respond to and schedule traffic allocation for communication requests from different sources, and to encrypt the transmitted data in layers so that the transmitted data can be delivered to the target terminal in a variety of wireless communication environments.

[0008] Specifically, the data perception module includes a data acquisition unit and a preprocessing unit; The data collection unit is configured with an adaptive collection strategy, which is used to perform dynamic data collection through sensors and dynamically adjust the collection time interval according to the sensor data change rate to collect the status data of the electronic tag; The preprocessing unit is configured with a data prediction strategy, which is used to extract key features based on the collected status data, calculate the abnormal probability of the electronic tag, perform preliminary abnormal screening, and obtain potential abnormal electronic tags.

[0009] Specifically, the steps of the adaptive acquisition strategy include: Set the initial collection time interval, start the sensor to collect data according to the initial collection time interval, and obtain the status data of the electronic tag; After each data collection, the change rate of the status data is calculated by comparing it with the status data collected last time; Configuring the Evaluation Interval ,When the number of data collections is greater than the evaluation interval, the comprehensive change rate of the state data within the evaluation interval is calculated by combining the change rate of the state data at each state data collection; Configure the change rate threshold, dynamically adjust the collection time interval according to the comprehensive change rate of the status data, and dynamically reduce the collection time interval. The formula for dynamically adjusting the collection time interval is as follows;

[0010] in, is the adjusted collection time interval, is the rate of change threshold, is the adjustment factor, The number of data collections is The comprehensive change rate of the state data at is the minimum value function, is the ceiling function, is the current collection time interval; After each evaluation interval, the collection time interval is dynamically adjusted to collect the status data of the electronic tags.

[0011] Specifically, the steps of the data prediction strategy include: Configuring the prediction interval When the number of data collections is greater than the predicted interval, the electronic tag status data is filtered out and the number of data collections is traced back to the current number of data collections. The state data in the acquisition process is used to construct a prediction data set; Extract the key features of each state data in the prediction data set, construct the key feature vector based on the key features, and calculate the deviation degree of the key feature vector; According to the degree of deviation of key feature vectors between electronic tags, an abnormal probability calculation model is constructed to calculate the abnormal probability of electronic tags. The abnormal probability calculation method is as follows:

[0012] in, It is The abnormal probability of an electronic tag, It is The first electronic tag The weight of the key features, It is The first electronic tag The degree of deviation of key features, is the number of key eigenvectors, is an exponential function with base e; Configure an abnormal probability threshold. When the abnormal probability of an electronic tag is greater than the abnormal probability threshold, it is marked as a potential abnormal electronic tag.

[0013] Specifically, the data processing module includes an analysis and decision-making unit and an execution and disposal unit; The analysis and decision-making unit is equipped with a comprehensive evaluation strategy, which is used to conduct multi-dimensional analysis on the status data of potential abnormal electronic tags. By dividing the benchmark time interval, calculating the comprehensive status data, and comparing and analyzing the abnormalities to determine the abnormal indicators, the abnormal type and severity of the electronic tags are judged.

[0014] Specifically, the steps of the comprehensive assessment strategy include: Check the integrity of the status data of the electronic tag and fill in the missing values ​​for the status data that does not meet the integrity requirements; Count the number of sampling points of the status data of each electronic tag, traverse all electronic tags, and select the electronic tag with the largest number of sampling points as the benchmark electronic tag; According to the minimum time interval for collecting the status data of the electronic tag, the reference time granularity is calculated in combination with the adjustment factor, and the reference time interval is divided; The earliest timestamp and the latest timestamp of the sampling point of the reference electronic tag are obtained as the reference time interval; based on the reference time interval and the reference time granularity, continuous time intervals are divided in sequence starting from the earliest timestamp to form a reference time interval sequence; For each electronic tag, traverse the timestamps corresponding to all its sampling points and calculate the reference time interval number to which each timestamp belongs; For each reference time interval number, the state data set of the electronic tags falling within the reference time interval number is screened, and the comprehensive state data corresponding to the reference time interval number is calculated, where the comprehensive state data includes comprehensive humidity data, comprehensive pressure data, and comprehensive acceleration data; Traverse the status data of each electronic tag, calculate the comprehensive status data corresponding to the reference time interval number, build an evaluation data set, and filter the comprehensive status data of potential abnormal electronic tags to build an abnormal evaluation data set; filter the comprehensive status data of non-potential abnormal electronic tags to build a normal evaluation data set.

[0015] Specifically, the steps of the comprehensive assessment strategy also include: Configure the abnormal evaluation threshold, combine the relationship between the current humidity value and the historical comprehensive humidity data and the discrete degree of the overall humidity data, and calculate the humidity anomaly index, namely:

[0016] in, It is the humidity abnormality indicator of the electronic tag. is the anomaly assessment threshold, is the number of base time intervals, It is The comprehensive humidity data in the abnormal evaluation data set corresponding to the benchmark time interval number, is the average value of the comprehensive humidity data in the normal evaluation data set, is the standard deviation of the comprehensive humidity data in the normal evaluation data set, It is The comprehensive humidity data in the abnormal evaluation data set corresponding to the benchmark time interval number, is a non-negative weight coefficient; Calculate the humidity anomaly index of each potential abnormal electronic tag in the anomaly assessment data set, configure the humidity threshold, including the upper humidity threshold and the lower humidity threshold. If the humidity anomaly index of the potential abnormal electronic tag is greater than the upper humidity threshold, it is marked as a first-level humidity anomaly. If the humidity anomaly index of the potential abnormal electronic tag is less than the lower humidity threshold, it is marked as a third-level humidity anomaly. Otherwise, it is marked as a second-level humidity anomaly.

[0017] Specifically, the steps of the comprehensive assessment strategy also include: The comprehensive pressure data of the abnormal evaluation data set and the normal evaluation data set are fitted respectively, and the curvature of the fitting curve is obtained to calculate the pressure anomaly index, that is:

[0018]

[0019] in, It is the abnormal pressure indicator of the electronic tag. is the anomaly assessment threshold, is the number of base time intervals, It is The curvature of the comprehensive pressure data in the abnormal assessment data set corresponding to the reference time interval number, is the maximum value of the curvature of the integrated pressure data in the normal evaluation data set; Combined with acceleration, the coupled eigenvalues ​​of pressure acceleration in the abnormal evaluation data set and the normal evaluation data set are calculated respectively, namely:

[0020] in, It is The pressure-acceleration coupling characteristic value corresponding to the reference time interval number, It is The change value of the comprehensive pressure data in the abnormal evaluation data set corresponding to the reference time interval number, It is The change value of the comprehensive acceleration data in the abnormal evaluation data set corresponding to the reference time interval number, It is The change value of the curvature of the comprehensive pressure data in the abnormal assessment data set corresponding to the reference time interval number; The coupling anomaly index is calculated by comprehensively considering the current value of the pressure-acceleration coupling feature and the influence of the historical pressure-acceleration coupling data; The pressure anomaly index and coupling anomaly index are combined to calculate the transfer anomaly index of the potential abnormal electronic tag; Configure the transition threshold, including the upper transition threshold and the lower transition threshold. If the transition anomaly index of the potential abnormal electronic label is greater than the upper transition threshold, the system is marked as a level 1 transition anomaly. If the transition anomaly index of the potential abnormal electronic label is less than the lower transition threshold, the system is marked as a level 3 transition anomaly. Otherwise, the system is marked as a level 2 transition anomaly.

[0021] Specifically, the communication transmission module includes a communication control unit and a data sending unit; The data transmission unit is configured with an encryption transmission strategy, which is used to perform layered encryption processing on the transmitted data and adjust the encryption parameters and key length for different data types; The communication control unit is equipped with an intelligent interaction strategy, which is used to intelligently identify and verify permissions based on communication requests from different sources, dynamically respond and control traffic based on the request type, and allocate and schedule communication traffic based on the urgency of the communication request.

[0022] Specifically, the steps of the intelligent interaction strategy include: When a communication request is received, the communication request data packet is parsed to identify the source of the communication request; Determine the type of communication request, including data query request, control instruction request and status report request; Divide the scope of authority according to the source and type of communication requests, and verify the authority of communication requests with identified sources and types; If the communication request passes the authority verification, an authorization token is generated. If the verification fails, the request is rejected and an error message indicating insufficient authority is fed back to the requester. Based on the urgency of the communication request, the amount of data involved and the network bandwidth, the communication request is assigned a traffic priority weight, and the communication traffic is allocated and scheduled.

[0023] Beneficial effects of the present invention: 1. Through adaptive collection strategies, the collection time interval is dynamically adjusted according to the rate of change of sensor data. The collection frequency can be flexibly changed according to the degree of change of the actual status data of the electronic tag, ensuring that key change information is not missed, making the collected data more in line with the real-time status changes of the electronic tag, and improving the accuracy and effectiveness of data collection. It also quantitatively analyzes the status data of the electronic tag from multiple angles, clearly and intuitively presents the possibility of the electronic tag being in an abnormal state in the form of probability values, and accurately screens out potential abnormal electronic tags, which helps to discover possible problems in advance and provide strong early warning support for baggage safety management and other tasks.

[0024] 2. In-depth analysis of the status data of potential abnormal electronic tags from multiple dimensions, comprehensive consideration of multiple factors such as humidity, pressure, acceleration, etc., by dividing the benchmark time interval, calculating the comprehensive status data, and comparing and analyzing the abnormalities to determine the abnormal indicators, and then accurately judge the abnormal type and severity of the electronic tag, so as to make the grasp of the abnormal situation more comprehensive and in-depth, generate execution instructions based on different abnormal types and severities, and take corresponding targeted measures such as dehumidification, attention, monitoring, and inspection for different humidity abnormal levels and different transfer abnormal levels, thereby achieving differentiated responses.

[0025] 3. Through intelligent identification, authority verification, dynamic response and traffic allocation scheduling of communication requests from different sources, on the one hand, communication traffic can be reasonably allocated according to factors such as the urgency of the request, the amount of data involved and the network bandwidth, ensuring stable and efficient service of the system in high-concurrency scenarios; on the other hand, accurate authority verification and targeted dynamic response mechanism can quickly process legitimate requests and reject illegal or insufficiently authorized requests, thereby improving the smoothness, security and timeliness of two-way communication, optimizing the communication efficiency and user experience of the entire system, and making the interaction of information related to baggage management more efficient and orderly. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a schematic structural diagram of an electronic tag structure that is liquid-proof and anti-transferable according to the present invention; Figure 2 A flowchart of the specific steps of the adaptive acquisition strategy of the present invention; Figure 3 A flowchart of the specific steps of the data pre-judgment strategy of the present invention; Figure 4 A flowchart of the specific steps of the comprehensive evaluation strategy of the present invention; Figure 5 The figure is a flowchart of the specific steps of the intelligent interaction strategy of the present invention. DETAILED DESCRIPTION

[0027] See also Figure 1 , This embodiment introduces an anti-liquid and anti-transfer electronic tag structure, including a data sensing module, a data processing module and a communication transmission module; The data perception module is used to monitor the environmental information of the electronic tag, the sticking status of the electronic tag and the dynamic changes of the electronic tag in real time, collect the status data of the electronic tag, and perform preliminary abnormal screening of the electronic tag based on the status data, providing comprehensive and accurate data support for the safety management and status monitoring of luggage.

[0028] Preferably, the data perception module includes a data acquisition unit and a preprocessing unit; The data collection unit is configured with an adaptive collection strategy, which is used to collect dynamic data through sensors and dynamically adjust the collection time interval according to the sensor data change rate to collect the status data of the electronic tag; The preprocessing unit is configured with a data prediction strategy, which is used to extract key features based on the collected status data, calculate the abnormal probability of the electronic tag, perform preliminary abnormal screening, and obtain potential abnormal electronic tags.

[0029] See also Figure 2 Preferably, the specific steps of the adaptive acquisition strategy include: Set the initial collection time interval, start the sensor to collect data according to the initial collection time interval, and obtain the status data of the electronic tag, which includes humidity, pressure and acceleration; by setting the initial collection time interval, the sensor can be started in an orderly manner according to the established rules and obtain the status data of the electronic tag.

[0030] After each data collection, the change rate of the state data is calculated by comparing it with the state data collected last time, including the humidity change rate, pressure change rate and acceleration change rate, that is:

[0031] in, It is The first collection The rate of change of state data, is a positive integer greater than 1, It is The first collection The value of the state data, It is The first collection The value of the state data, is the current collection time interval; the rate of change calculated for each collection moment focuses on the data change characteristics within the local time interval between two adjacent collections, making it possible to analyze the fluctuation details of the data within a short time scale in detail without being disturbed by the comprehensive data in other longer time periods. This helps to discover state changes that may indicate local abnormalities in electronic tags or temporary interference factors.

[0032] Configuring the Evaluation Interval , when the number of data collection is greater than the evaluation interval, the comprehensive change rate of the state data within the evaluation interval is calculated by combining the change rate of the state data at each state data collection, that is:

[0033] in, The number of data collections is The comprehensive change rate of the state data at It is The non-negative weight coefficient of the state data ranges from (0,1). The number of types of status data; combined with the change rate of each status data at each collection, the comprehensive change rate is calculated, realizing the transition from multiple single status data change rates to overall comprehensive evaluation. The changes in different types of status data are considered in a comprehensive manner, avoiding the problem of focusing on the change of a single data type while ignoring the impact of the coordinated changes of other data on the overall status of the electronic tag, and more comprehensively reflecting the comprehensive change trend of the overall status data of the electronic tag within a relatively long evaluation interval.

[0034] Configure the change rate threshold, dynamically adjust the collection time interval according to the comprehensive change rate of the status data, dynamically reduce the collection time interval, obtain more data points to monitor the status data, and the formula for dynamically adjusting the collection time interval is as follows;

[0035] in, is the adjusted collection time interval, is the rate of change threshold, is the adjustment coefficient, the value range is (0,1), is the minimum value function, It is an upward rounding function; according to the configured change rate threshold and the calculation result of the comprehensive change rate, the collection time interval is dynamically adjusted, especially when the comprehensive change rate of the status data exceeds the threshold, the collection time interval is reduced to obtain more data points, so that the data collection process has adaptive capabilities. It can flexibly change the collection frequency according to the intensity of the change of the actual status data of the electronic tag. When the status is relatively stable and the change is small, a relatively loose collection interval is used to save system resources; and when a large change occurs that may indicate an abnormality, the collection frequency is quickly increased to obtain more intensive data in order to monitor the status data more finely, ensuring that key change information is not missed, so that data collection matches the real-time status changes of the electronic tag.

[0036] After each evaluation interval, the collection time interval is dynamically adjusted to obtain the status data of the electronic tag. This ensures that the entire data collection process can continuously track the dynamic changes in the status data of the electronic tag. Regardless of whether the status of the electronic tag is in a relatively stable state for a long time, or changes over time, environment and other factors, this periodic adjustment mechanism can respond in a timely manner, continuously optimize the frequency of data collection, and continuously provide data that meets actual needs for subsequent analysis, which helps to more comprehensively and accurately grasp the operating status and change trends of electronic tags at different stages.

[0037] See also Figure 3 Preferably, the specific steps of the data prediction strategy include: Configuring the prediction interval When the number of data collections is greater than the predicted interval, the electronic tag status data is filtered out and the number of data collections is traced back to the current number of data collections. The status data in the collection process is used to build a prediction data set; ensure that the constructed data set focuses on the collection data that is closer to the current one, so that the subsequent analysis is more in line with the actual operating status of the current electronic tag, avoid interference with the judgment of the current abnormal situation due to the inclusion of too much outdated data, and improve the timeliness and pertinence of the data.

[0038] Extract the key features of each state data in the prediction data set, including mean, variance, extreme value, average change rate and coefficient of variation, construct key feature vectors based on the key features, and calculate the degree of deviation of the key feature vectors. The calculation methods of the degree of deviation of the key feature vectors include: calculation method based on empirical percentile, calculation method based on statistical distribution and calculation method based on cluster center; extract multiple key features and quantitatively describe the state data from different angles. The mean reflects the average level of the data, the variance reflects its degree of dispersion, the extreme value can show the boundary conditions of data fluctuations, the average change rate can measure the speed of data changes, and the coefficient of variation comprehensively considers the relationship between dispersion and mean. These features can be combined to comprehensively and meticulously characterize the intrinsic characteristics of the electronic tag state data, providing a rich information basis for subsequent abnormal judgment.

[0039] Based on the key feature vectors of the electronic tags and the degree of deviation of the key feature vectors between the electronic tags, an abnormal probability calculation model is constructed to calculate the abnormal probability of the electronic tags. The abnormal probability calculation method is as follows:

[0040] in, It is The abnormal probability of an electronic tag, It is The first electronic tag The weight of a key feature is determined according to the importance of the feature to abnormal judgment, and the value range is (0,1). It is The first electronic tag The degree of deviation of key features, is the number of key eigenvectors, It is an exponential function with e as the base. It quantifies the possibility of the electronic tag being in an abnormal state in the form of a probability value, which is convenient for subsequent comparison with the set abnormal probability threshold. It clearly and intuitively presents the degree of abnormality of the current electronic tag, providing a clear and quantifiable basis for further decision-making.

[0041] Configure an abnormal probability threshold. When the abnormal probability of an electronic tag is greater than the abnormal probability threshold, it is marked as a potential abnormal electronic tag.

[0042] The data processing module is used to classify the causes and conduct risk assessment of potential abnormal electronic tags, and to respond differentially. Based on the abnormal type and severity of the potential abnormal electronic tags, execution instructions are generated to take effective measures to ensure the normal operation of the electronic tags and the security of the information they carry, thereby facilitating the orderly development of baggage safety management.

[0043] Preferably, the data processing module includes an analysis and decision-making unit and an execution and disposal unit; The analysis and decision-making unit is equipped with a comprehensive evaluation strategy, which is used to conduct a multi-dimensional in-depth analysis of the status data of potential abnormal electronic tags, comprehensively evaluate the abnormal situation and severity of the electronic tags by combining humidity, pressure, and acceleration, and determine the abnormal indicators by dividing the benchmark time interval, calculating the comprehensive status data, and comparing and analyzing the abnormalities to determine the abnormal type and severity of the electronic tags; A differentiated response strategy is configured in the execution and disposal unit. The differentiated response strategy is used to take corresponding dehumidification, attention, and monitoring measures for different humidity abnormality levels according to the type and severity of the abnormality, and to take measures such as stopping or intermittent inspection, recording, and continuous monitoring for different transfer abnormality levels to ensure the normal operation and information security of the electronic tag and monitor its status changes.

[0044] See also Figure 4 , preferably, the specific steps of the comprehensive evaluation strategy include: Check the integrity of the status data of the electronic tag and fill in the missing values ​​of the status data that does not meet the integrity requirements. The missing value filling methods include the average value filling method and the linear interpolation method. Count the number of sampling points of the status data of each electronic tag, traverse all abnormal electronic tags, and select the electronic tag with the largest number of sampling points as the benchmark electronic tag; The reference time granularity is calculated based on the minimum time interval for collecting the status data of the electronic tag and the adjustment factor to divide the reference time interval. The calculation formula for the reference time granularity is:

[0045]

[0046] in, is the base time granularity, is the minimum collection time interval, is the regulating factor, is the ceiling function, is the standard deviation of the time interval for collecting status data of all electronic tags, [ , ] is the standard deviation range of the benchmark collection time interval, which is determined according to the actual data fluctuation. , ] is the reference value range of the adjustment factor, which is determined according to the actual expected time granularity adaptability; The earliest and latest timestamps of the sampling points of the reference electronic tags are obtained as the reference time intervals. Based on the reference time intervals and the reference time granularity, continuous time intervals are divided in sequence starting from the earliest timestamp to form a reference time interval sequence, namely:

[0047] in, It is Base time interval, The value range is , is the number of base time intervals, It is the earliest timestamp of the sampling point of the reference electronic tag; For each electronic tag, traverse the timestamps corresponding to all its sampling points and calculate the reference time interval number to which each timestamp belongs, that is:

[0048] in, It is The electronic tag belongs to Base time interval number, It is The electronic tag belongs to The timestamp of each sampling point, is the floor function; For each reference time interval number, the state data set of the electronic tags falling within the reference time interval number is screened, and the comprehensive state data corresponding to the reference time interval number is calculated. The comprehensive state data includes comprehensive humidity data, comprehensive pressure data and comprehensive acceleration data, that is:

[0049] in, It is The electronic tag belongs to The comprehensive status data corresponding to the reference time interval number, It is The electronic tag belongs to The minimum value of the status data in the base time interval number, It is The electronic tag belongs to The maximum value of the status data in the base time interval number, It is The electronic tag belongs to The mean value of the state data in the base time interval number, , and is a non-negative weighting coefficient, ranging from [0,1]; Traverse the status data of each electronic tag, calculate the comprehensive status data corresponding to the reference time interval number, and construct an evaluation data set. Each row of the evaluation data set contains the electronic tag name, reference time interval number, comprehensive humidity data, comprehensive pressure data, and comprehensive acceleration data; filter the comprehensive status data of potential abnormal electronic tags to construct an abnormal evaluation data set; filter the comprehensive status data of non-potential abnormal electronic tags to construct a normal evaluation data set; Configure the abnormal evaluation threshold, combine the relationship between the current humidity value and the historical comprehensive humidity data and the discrete degree of the overall humidity data, and calculate the humidity anomaly index, namely:

[0050] in, It is the humidity abnormality indicator of the electronic tag. is the anomaly evaluation threshold, which is used to express the amount of historical comprehensive humidity data considered, is the number of base time intervals, It is The comprehensive humidity data in the abnormal evaluation data set corresponding to the benchmark time interval number, is the average value of the comprehensive humidity data in the normal evaluation data set, is the standard deviation of the comprehensive humidity data in the normal evaluation data set, It is The comprehensive humidity data in the abnormal evaluation data set corresponding to the benchmark time interval number, The value range is [1, ], It is a non-negative weight coefficient, which is used to measure the importance of data in different lag intervals to the current humidity value judgment; it distinguishes the humidity value deviation caused by accidental fluctuations and actual humidity anomalies, improves the accuracy of humidity value anomaly judgment, avoids misjudgment and missed judgment, and enhances the reliability of humidity anomaly detection.

[0051] Calculate the humidity anomaly index of each potential abnormal electronic tag in the anomaly assessment data set, configure the humidity threshold, including the upper humidity threshold and the lower humidity threshold. If the humidity anomaly index of the potential abnormal electronic tag is greater than the upper humidity threshold, it is marked as a first-level humidity anomaly. If the humidity anomaly index of the potential abnormal electronic tag is less than the lower humidity threshold, it is marked as a third-level humidity anomaly. Otherwise, it is marked as a second-level humidity anomaly. The comprehensive pressure data of the abnormal evaluation data set and the normal evaluation data set are fitted respectively, and the curvature of the fitting curve is obtained to calculate the pressure anomaly index, that is:

[0052]

[0053] in, It is the abnormal pressure indicator of the electronic tag. is the anomaly assessment threshold, is the number of base time intervals, It is The curvature of the comprehensive pressure data in the abnormal assessment data set corresponding to the reference time interval number, is the maximum value of the curvature of the integrated pressure data in the normal evaluation data set; Combined with acceleration, the coupled eigenvalues ​​of pressure acceleration in the abnormal evaluation data set and the normal evaluation data set are calculated respectively, namely:

[0054] in, It is The pressure-acceleration coupling characteristic value corresponding to the reference time interval number, It is The change value of the comprehensive pressure data in the abnormal evaluation data set corresponding to the reference time interval number, , It is The comprehensive pressure data in the abnormal assessment data set corresponding to the reference time interval number, It is The comprehensive pressure data in the abnormal assessment data set corresponding to the reference time interval number, It is The change value of the comprehensive acceleration data in the abnormal evaluation data set corresponding to the reference time interval number, , It is The comprehensive acceleration data in the abnormal evaluation data set corresponding to the benchmark time interval number, It is The comprehensive acceleration data in the abnormal evaluation data set corresponding to the benchmark time interval number, It is The change value of the curvature of the comprehensive pressure data in the abnormal evaluation data set corresponding to the reference time interval number, , It is The curvature of the comprehensive pressure data in the abnormal assessment data set corresponding to the reference time interval number, It is The curvature of the comprehensive pressure data in the abnormal assessment data set corresponding to the reference time interval number; Taking into account the current value of the pressure-acceleration coupling feature and the influence of the historical pressure-acceleration coupling data, the coupling anomaly index is calculated, namely:

[0055]

[0056] in, It is the coupling abnormality indicator of the electronic tag. It is The pressure-acceleration coupling eigenvalue in the abnormal assessment data set corresponding to the reference time interval number, It is The maximum value of the pressure-acceleration coupling characteristic in the normal evaluation data set corresponding to the reference time interval number, It is The minimum value of the pressure-acceleration coupling characteristic in the normal evaluation data set corresponding to the reference time interval number; The pressure anomaly index and coupling anomaly index are combined to calculate the transfer anomaly index of the potential abnormal electronic tag, namely:

[0057] in, It is the transfer abnormality indicator of potential abnormal electronic tags. and are the non-negative weight coefficients of the pressure anomaly index and coupling anomaly index of the electronic tag respectively; Configure the transition threshold, including the upper transition threshold and the lower transition threshold. If the transition anomaly index of the potential abnormal electronic label is greater than the upper transition threshold, the system is marked as a level 1 transition anomaly. If the transition anomaly index of the potential abnormal electronic label is less than the lower transition threshold, the system is marked as a level 3 transition anomaly. Otherwise, the system is marked as a level 2 transition anomaly.

[0058] Preferably, the specific steps of the differentiated response strategy include: Receive information related to potential abnormal electronic tags that have completed comprehensive evaluation, including the abnormality type of each potential abnormal electronic tag, the abnormality type including primary humidity abnormality, secondary humidity abnormality, tertiary humidity abnormality, primary transfer abnormality, secondary transfer abnormality, and tertiary transfer abnormality; For level 1 humidity anomalies, immediately start powerful dehumidification equipment to dehumidify the environment where the electronic tags are located, notify relevant staff to conduct emergency inspection and reinforcement of the moisture-proof packaging of the electronic tags, and report to the management system for continuous tracking, etc., so as to quickly alleviate the damage that the humidity anomaly may cause to the electronic tags and ensure their normal operation and the security of the information they carry; for level 2 humidity anomalies, remind staff to pay close attention to the humidity change trend and appropriately adjust the environmental humidity control parameters, including adjusting the operating modes of air conditioners and ventilation equipment, and conduct moisture-proof maintenance inspections on the electronic tags; for level 3 humidity anomalies, continue to monitor humidity data; For the first-level transfer abnormality, stop the circulation and transportation of the luggage marked as the first-level transfer abnormality, notify the personnel to check and reinforce the sticking and fixing devices of the electronic tags and luggage, and calibrate the pressure and acceleration sensors to ensure that the status changes of the electronic tags can continue to be monitored in the future to prevent data loss or label failure due to transfer problems; for the second-level transfer abnormality, notify the personnel to conduct routine inspections on the electronic tags of the luggage marked as the second-level transfer abnormality during the intervals of luggage circulation to check whether there are signs of looseness, whether there are abnormal fluctuations in the data, etc., and keep records. For the third-level transfer abnormality, continue to monitor the pressure and acceleration data.

[0059] The communication transmission module is used to ensure that the transmitted data is safely and quickly delivered to the target terminal in a variety of wireless communication environments through layered encryption of the transmitted data, and to perform intelligent identification, permission verification, dynamic response and traffic allocation scheduling for communication requests from different sources, so as to achieve stable and efficient services in high-concurrency scenarios, ensure smooth, secure and timely two-way communication, and improve overall communication efficiency and user experience.

[0060] Preferably, the communication transmission module includes a communication control unit and a data sending unit; The communication control unit is equipped with an intelligent interaction strategy, which is used to intelligently identify and verify permissions based on communication requests from different sources, dynamically respond and control traffic based on the request type, and allocate and schedule communication traffic based on the urgency of the request, so as to achieve stable operation and efficient service of the system in high-concurrency communication scenarios, ensure the smoothness, security and timeliness of two-way communication, and improve the overall communication efficiency and user experience of the baggage management system; The data sending unit is configured with an encrypted transmission strategy, which is used to perform layered encryption processing on the transmitted data according to its importance and sensitivity, dynamically adjust encryption parameters and key lengths for different data types, and achieve secure and fast data transmission in a variety of wireless communication environments, so as to effectively resist network attacks and data leakage risks, ensure that baggage data is accurately delivered to the target terminal device, and ensure the security and reliability of information interaction.

[0061] Preferably, the specific steps of the encrypted transmission strategy include: Classify the data into different categories, including core key data, important data and general data, according to the degree of correlation between the data and key information such as baggage safety and electronic tag status, as well as the sensitivity of the data; core key data includes abnormal diagnosis results and high-risk warning information of electronic tags; important data includes humidity, pressure and acceleration data; general data includes the timestamp of data collection and the device number; For core critical data, the AES encryption algorithm is used with a 256-bit key length to provide strong encryption protection; for important data, a 128-bit key length is used to ensure security while taking into account the efficiency of encryption and decryption; for general data, an encryption algorithm based on a hash function or a lightweight symmetric encryption algorithm is used to reduce the consumption of computing resources.

[0062] For different categories of data, corresponding key pairs are generated respectively. The public key is used for data encryption, and the private key is used for data decryption. During the key generation process, a random number generator is used in combination with a cryptographically secure hash function to ensure the randomness and uniqueness of the key and to update the key regularly.

[0063] The data is encrypted according to the data type, and the encrypted data is encapsulated into a data packet format suitable for wireless communication transmission. Header information is added, including the data type identifier, source address, and destination address. According to the current wireless communication environment, including signal strength, interference conditions, and network bandwidth, the communication protocol and transmission parameters are selected for data transmission. The communication protocols include Wi-Fi, Bluetooth, and 4G / 5G, and the transmission parameters include transmission power, frequency band, and data rate.

[0064] See also Figure 5 , preferably, the specific steps of the intelligent interaction strategy include: When a communication request is received, the communication request data packet is parsed to identify the source of the communication request, including the baggage management system server, other related equipment, and mobile terminals, and to confirm the identity of the initiator of the communication request; Determine the type of communication request, including data query request, control command request and status report request. Data query request includes: querying detailed historical data and real-time status data of a specific electronic tag; control command request includes: sending instructions to adjust the data collection frequency of the electronic tag, start or stop related auxiliary equipment; status report request includes: the electronic tag actively reports its current working status and whether there is any abnormality to the server or other management terminal; The authority scope is divided according to the source and type of communication request, and the authority verification is performed on the communication request with the identified source and type, including: the core server of the baggage management system has the advanced authority to conduct all-round data query on all electronic tags and issue key control instructions; mobile terminal devices are allowed to view some data or send simple operation instructions; If the communication request passes the authority verification, an authorization token is generated. If the verification fails, the request is rejected and a clear error message indicating insufficient authority is fed back to the requesting party. Considering the urgency of the communication request, the amount of data involved and the network bandwidth, the communication request is assigned a traffic priority weight, and the communication traffic is allocated and scheduled, namely:

[0065]

[0066] in, It is The traffic priority weight of each communication request, It is The urgency of each communication request type, It is The amount of data for a communication request, is the current network bandwidth, is the maximum amount of data that can be processed for a communication request, is the maximum network bandwidth, It is The traffic allocated to each communication request is is the total flow, It is The traffic priority weight of each communication request, The value range is [1, ], is the number of communication requests received simultaneously, , and They are all non-negative weighting coefficients, and their value range is (0,1).

[0067] According to the type of communication request and the scope of authority, and based on the priority weight and communication traffic, dynamic response is performed. For data query requests, the required data is extracted, sorted and packaged according to the communication request requirements, and then transmitted back to the requester; for control instruction requests, the legality, validity and security of the control instruction are verified. If the control instruction verification passes, the control instruction is executed, and the process of the control instruction is recorded in real time, and the execution result is sent to the request initiator; for status report requests, the report data is received and parsed, and the early warning mechanism is automatically triggered for abnormal information in the report, and the staff is notified to handle and investigate.

[0068] Working principle and its effect: An electronic tag structure that is resistant to liquid and transfer. The sensor of the data acquisition unit collects data through an adaptive acquisition strategy. After each acquisition, the change rate of the state data is carefully compared and calculated. When the number of acquisitions reaches the evaluation interval, the comprehensive change rate is calculated by combining the change rates of each time, and then the acquisition time interval is dynamically adjusted according to the change rate threshold to ensure that the data acquisition frequency accurately matches the actual state change of the electronic tag. It saves resources when the state is stable, and once there is an abnormal situation, such as the impact of liquid or the label being moved, it can be monitored in detail, which not only improves the collection efficiency and accuracy, but also provides a reliable data basis for subsequent judgments on whether the electronic tag has encountered liquid invasion or transfer and other abnormalities. The data prediction strategy of the preprocessing unit constructs a prediction data set under the condition of satisfying the prediction interval, extracts key features to construct feature vectors and calculates the degree of deviation, and then constructs an abnormal probability calculation model through the degree of deviation of the feature vectors between electronic tags, accurately screens out potential abnormal electronic tags, and warns of possible liquid and transfer problems in advance.

[0069] After receiving the data of potential abnormal electronic tags, the data processing module selects the benchmark electronic tags by counting the number of sampling points, calculates the benchmark time granularity to divide the time interval, determines the interval number for each electronic tag and calculates the corresponding comprehensive status data, and distinguishes the abnormal evaluation data set from the normal evaluation data set after constructing the evaluation data set. For the potential abnormal electronic tags in the abnormal evaluation data set, the humidity, pressure, and acceleration are integrated to calculate the humidity abnormality index, pressure abnormality index, and pressure-acceleration coupling characteristics to obtain the coupling abnormality index, and the transfer abnormality index is obtained comprehensively. The type and severity of the abnormality are accurately judged based on the humidity threshold and the transfer threshold, and the execution instruction is finally generated. From the multi-dimensional in-depth analysis, the misjudgment of a single factor is avoided, so that the subsequent differentiated response measures such as dehumidification, reinforcement and pasting, and inspection for different abnormal levels are more targeted, which effectively guarantees the normal functioning of the electronic tag's anti-liquid and anti-transfer functions, maintains the stable operation order of the entire baggage management system, and minimizes the losses and risks caused by liquid or transfer problems.

[0070] The communication transmission module also plays an important role. The encryption transmission strategy of the data sending unit is layered according to the importance and sensitivity of the data, matching the appropriate encryption algorithm and key length for different types of data, generating a key pair to encrypt the data and then encapsulate and transmit it. In a variety of wireless communication environments, it effectively prevents the data from being stolen or tampered with during transmission, ensuring the reliability of information interaction. When receiving a communication request, the intelligent interaction strategy of the communication control unit parses the data packet to determine the source, judges the request type, and verifies the authority according to the authority range divided by the source and type. If it passes, it generates an authorization token. If it fails, it is rejected and an error is fed back. At the same time, it assigns traffic priority weights and allocates scheduling traffic according to the urgency of the request, the amount of data, and the network bandwidth. Optimize the allocation of communication resources, ensure stable and efficient service of the system in high-concurrency scenarios, improve the smoothness, security and timeliness of two-way communication, make the information interaction of each link of the baggage management system around the anti-liquid and anti-transfer functions of the electronic tag more efficient and orderly, and help the smooth development of baggage management work in all aspects.

[0071] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. An electronic tag structure that prevents liquid transfer, characterized in that: It includes a data sensing module, a data processing module and a communication transmission module; The data sensing module is used to monitor the environment information of the electronic tag, the sticking status of the electronic tag and the dynamic changes of the electronic tag in real time, collect the status data of the electronic tag, and perform preliminary abnormal screening of the electronic tag based on the status data to obtain potential abnormal electronic tags; The data processing module is used to process the integrity of the status data, construct an evaluation data set based on time interval division and data screening, determine the abnormal type and severity of the potential abnormal electronic tag through comprehensive humidity, pressure, and acceleration multi-dimensional analysis, and generate execution instructions; The communication transmission module is used to intelligently identify, verify permissions, dynamically respond to and schedule traffic allocation for communication requests from different sources, and to encrypt the transmission data in layers so that the transmission data can be delivered to the target terminal in a variety of wireless communication environments; The data perception module includes a data acquisition unit and a preprocessing unit; The data collection unit is configured with an adaptive collection strategy, which is used to perform dynamic data collection through sensors and dynamically adjust the collection time interval according to the sensor data change rate to collect the status data of the electronic tag; The preprocessing unit is configured with a data prejudgment strategy, which is used to extract key features based on the collected status data, calculate the abnormal probability of the electronic tag, perform preliminary abnormality screening, and obtain potential abnormal electronic tags.

2. The liquid-proof and anti-transfer electronic tag structure according to claim 1, characterized in that: The steps of the adaptive acquisition strategy include: Set the initial collection time interval, start the sensor to collect data according to the initial collection time interval, and obtain the status data of the electronic tag; After each data collection, the change rate of the status data is calculated by comparing it with the status data collected last time; Configuring the Evaluation Interval ,When the number of data collections is greater than the evaluation interval, the comprehensive change rate of the state data within the evaluation interval is calculated by combining the change rate of the state data at each state data collection; Configure the change rate threshold, dynamically adjust the collection time interval according to the comprehensive change rate of the status data, and dynamically reduce the collection time interval. The formula for dynamically adjusting the collection time interval is as follows; ； in, is the adjusted collection time interval, is the rate of change threshold, is the adjustment factor, The number of data collections is The comprehensive change rate of the state data at is the minimum value function, is the ceiling function, is the current collection time interval; After each evaluation interval, the collection time interval is dynamically adjusted to collect the status data of the electronic tags.

3. The liquid-proof and anti-transfer electronic tag structure according to claim 1, characterized in that: The steps of the data prediction strategy include: Configuring the prediction interval When the number of data collections is greater than the predicted interval, the electronic tag status data is filtered out and the number of data collections is traced back to the current number of data collections. The state data in the acquisition process is used to construct a prediction data set; Extract the key features of each state data in the prediction data set, construct the key feature vector based on the key features, and calculate the deviation degree of the key feature vector; According to the degree of deviation of key feature vectors between electronic tags, an abnormal probability calculation model is constructed to calculate the abnormal probability of electronic tags. The abnormal probability calculation method is as follows: ； in, It is The abnormal probability of an electronic tag, It is The first electronic tag The weight of the key features, It is The first electronic tag The degree of deviation of key features, is the number of key eigenvectors, is an exponential function with base e; Configure an abnormal probability threshold. When the abnormal probability of an electronic tag is greater than the abnormal probability threshold, it is marked as a potential abnormal electronic tag.

4. The liquid-proof and anti-transfer electronic tag structure according to claim 1, characterized in that: The data processing module includes an analysis and decision-making unit and an execution and disposal unit; The analysis and decision-making unit is configured with a comprehensive evaluation strategy, which is used to perform multi-dimensional analysis on the status data of potential abnormal electronic tags, and determine the abnormal type and severity of the electronic tags by dividing the benchmark time interval, calculating the comprehensive status data, and comparing and analyzing the abnormalities to determine the abnormal indicators.

5. The liquid-proof and anti-transfer electronic tag structure as claimed in claim 4, characterized in that: The steps of the comprehensive assessment strategy include: Check the integrity of the status data of the electronic tag and fill in the missing values ​​for the status data that does not meet the integrity requirements; Count the number of sampling points of the status data of each electronic tag, traverse all electronic tags, and select the electronic tag with the largest number of sampling points as the benchmark electronic tag; According to the minimum time interval for collecting the status data of the electronic tag, the reference time granularity is calculated in combination with the adjustment factor, and the reference time interval is divided; The earliest timestamp and the latest timestamp of the sampling point of the reference electronic tag are obtained as the reference time interval; based on the reference time interval and the reference time granularity, continuous time intervals are divided in sequence starting from the earliest timestamp to form a reference time interval sequence; For each electronic tag, traverse the timestamps corresponding to all its sampling points and calculate the reference time interval number to which each timestamp belongs; For each reference time interval number, the state data set of the electronic tags falling within the reference time interval number is screened, and the comprehensive state data corresponding to the reference time interval number is calculated, where the comprehensive state data includes comprehensive humidity data, comprehensive pressure data, and comprehensive acceleration data; Traverse the status data of each electronic tag, calculate the comprehensive status data corresponding to the reference time interval number, build an evaluation data set, and filter the comprehensive status data of potential abnormal electronic tags to build an abnormal evaluation data set; filter the comprehensive status data of non-potential abnormal electronic tags to build a normal evaluation data set.

6. The liquid-proof and anti-transfer electronic tag structure according to claim 5, characterized in that: The steps of the comprehensive assessment strategy also include: Configure the abnormal evaluation threshold, combine the relationship between the current humidity value and the historical comprehensive humidity data and the discrete degree of the overall humidity data, and calculate the humidity anomaly index, namely: ； in, It is the humidity abnormality indicator of the electronic tag. is the anomaly assessment threshold, is the number of base time intervals, It is The comprehensive humidity data in the abnormal evaluation data set corresponding to the benchmark time interval number, is the average value of the comprehensive humidity data in the normal evaluation data set, is the standard deviation of the comprehensive humidity data in the normal evaluation data set, It is The comprehensive humidity data in the abnormal evaluation data set corresponding to the benchmark time interval number, is a non-negative weight coefficient; Calculate the humidity anomaly index of each potential abnormal electronic tag in the anomaly assessment data set, configure the humidity threshold, including the upper humidity threshold and the lower humidity threshold. If the humidity anomaly index of the potential abnormal electronic tag is greater than the upper humidity threshold, it is marked as a first-level humidity anomaly. If the humidity anomaly index of the potential abnormal electronic tag is less than the lower humidity threshold, it is marked as a third-level humidity anomaly. Otherwise, it is marked as a second-level humidity anomaly.

7. The liquid-proof and anti-transfer electronic tag structure according to claim 6, characterized in that: The steps of the comprehensive assessment strategy also include: The comprehensive pressure data of the abnormal evaluation data set and the normal evaluation data set are fitted respectively, and the curvature of the fitting curve is obtained to calculate the pressure anomaly index, that is: ； ； in, It is the abnormal pressure indicator of the electronic tag. is the anomaly assessment threshold, is the number of base time intervals, It is The curvature of the comprehensive pressure data in the abnormal assessment data set corresponding to the reference time interval number, is the maximum value of the curvature of the integrated pressure data in the normal evaluation data set; Combined with acceleration, the coupled eigenvalues ​​of pressure acceleration in the abnormal evaluation data set and the normal evaluation data set are calculated respectively, namely: ； in, It is The pressure-acceleration coupling characteristic value corresponding to the reference time interval number, It is The change value of the comprehensive pressure data in the abnormal evaluation data set corresponding to the reference time interval number, It is The change value of the comprehensive acceleration data in the abnormal evaluation data set corresponding to the reference time interval number, It is The change value of the curvature of the comprehensive pressure data in the abnormal assessment data set corresponding to the reference time interval number; The coupling anomaly index is calculated by comprehensively considering the current value of the pressure-acceleration coupling feature and the influence of the historical pressure-acceleration coupling data; The pressure anomaly index and coupling anomaly index are combined to calculate the transfer anomaly index of the potential abnormal electronic tag; Configure the transition threshold, including the upper transition threshold and the lower transition threshold. If the transition anomaly index of the potential abnormal electronic label is greater than the upper transition threshold, the system is marked as a level 1 transition anomaly. If the transition anomaly index of the potential abnormal electronic label is less than the lower transition threshold, the system is marked as a level 3 transition anomaly. Otherwise, the system is marked as a level 2 transition anomaly.

8. The liquid-proof and anti-transfer electronic tag structure according to claim 1, characterized in that: The communication transmission module includes a communication control unit and a data sending unit; The communication control unit is configured with an intelligent interaction strategy, which is used to perform intelligent identification and authority verification according to communication requests from different sources, and to dynamically respond and control traffic according to the request type, and to allocate and schedule communication traffic according to the urgency of the communication request; The data sending unit is configured with an encryption transmission strategy, which is used to perform layered encryption processing on the transmission data and adjust encryption parameters and key lengths according to different data types.

9. The liquid-proof and anti-transfer electronic tag structure according to claim 8, characterized in that: The steps of the intelligent interaction strategy include: When a communication request is received, the communication request data packet is parsed to identify the source of the communication request; Determine the type of communication request, including data query request, control instruction request and status report request; Divide the scope of authority according to the source and type of communication requests, and verify the authority of communication requests with identified sources and types; If the communication request passes the authority verification, an authorization token is generated. If the verification fails, the request is rejected and an error message indicating insufficient authority is fed back to the requester. Based on the urgency of the communication request, the amount of data involved and the network bandwidth, the communication request is assigned a traffic priority weight, and the communication traffic is allocated and scheduled.

Images