A method and system for binding turnover boxes based on electronic tags

Abstract

The present invention discloses a method and system for binding turnover boxes based on electronic tags, which relate to the field of logistics and supply chain management. The method and system include: entering initial information of the turnover box, generating a first mapping table; when the turnover box enters the warehouse, verifying the RFID tag and QR code information, updating the turnover box status information, placing goods into the turnover box based on the turnover box status information, scanning the QR code of the goods, and binding with the RFID tag and QR code information of the turnover box to generate a second mapping table; when the turnover box is shipped out of the warehouse, confirming the turnover box information, updating the first mapping relationship table and the second mapping relationship table, establishing a turnover box status and maintenance demand prediction model, outputting the health status of the turnover box, and replacing and maintaining the turnover box according to the health status of the turnover box, which greatly facilitates the management and utilization of the turnover box, avoids the damage of the turnover box affecting the goods, and can also effectively reduce delays and losses caused by turnover box problems, thereby improving the reliability of the turnover box.

Description

Technical Field

[0001] The present invention relates to the field of logistics and supply chain management, and in particular to a method and system for binding turnover boxes based on electronic tags. Background Art

[0002] With the rapid development of modern logistics and supply chain management, turnover boxes, as important logistics carriers, play a vital role in warehousing, transportation, and distribution. To improve the management and utilization efficiency of turnover boxes, electronic tagging-based technologies are widely used. Traditional turnover box management systems typically rely on barcodes or manual record-keeping to track and manage turnover box information. However, these methods have many shortcomings, such as delayed information updates and a lack of automated management.

[0003] While existing turnover box management systems based on RFID and QR codes have improved management efficiency to a certain extent, some issues remain that need to be addressed. For example, the system's monitoring of environmental parameters is not comprehensive enough, making it difficult to dynamically adjust the operating mode based on the actual usage of the turnover boxes. In addition, most existing systems lack effective prediction and maintenance mechanisms for the health of the turnover boxes, resulting in inadequate guarantees for the service life and performance of the turnover boxes. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a method and system for binding turnover boxes based on electronic tags to solve the problems of untimely information update and lack of turnover box health status prediction and maintenance mechanism in existing turnover box management systems.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a method for binding a turnover box based on an electronic tag, which includes entering initial information of the turnover box and generating a first mapping table;

[0008] When the turnover box enters the warehouse, verify the RFID tag and QR code information and update the turnover box status information;

[0009] Based on the turnover box status information, the goods are placed into the turnover box, the QR code of the goods is scanned, and the QR code information is bound to the RFID tag and QR code information of the turnover box to generate a second mapping table;

[0010] When the turnover box is shipped out of the warehouse, the turnover box information is confirmed and the first mapping relationship table and the second mapping relationship table are updated;

[0011] Establish a turnover box status and maintenance demand prediction model to output the health status of the turnover box;

[0012] Replace and maintain the turnover box according to its health condition.

[0013] As a preferred solution of the method for binding turnover boxes based on electronic tags of the present invention, the initial information of the turnover box is input and a first mapping table is generated, including the following steps:

[0014] Set a QR code and an adaptive RFID tag on each turnover box;

[0015] Install RFID readers and cameras at warehouse entrances, exits, and key nodes;

[0016] The unique identification information, specification information, status information, location information and environmental information of the turnover box are input to generate a first mapping table.

[0017] As a preferred solution of the method for binding turnover boxes based on electronic tags according to the present invention, when a turnover box enters the warehouse, the RFID tag and QR code information are verified and the turnover box status information is updated, including the following steps:

[0018] When the turnover box enters the warehouse, the adaptive tag automatically adjusts the operating frequency and power according to the current environmental parameters;

[0019] The camera captures the QR code on the turnover box and extracts the information in the QR code through image processing algorithms;

[0020] Compare and verify the RFID tag and QR code information. Once the information is consistent, update the status information of the turnover box.

[0021] As a preferred solution of the method for binding turnover boxes based on electronic tags of the present invention, the method includes placing goods into the turnover box based on the turnover box status information, scanning the QR code of the goods, and binding with the RFID tag and QR code information of the turnover box to generate a second mapping table, including the following steps:

[0022] The staff uses a handheld device to scan the QR code on the goods, obtains the goods information, and uploads the scanned QR code information of the goods;

[0023] Use linear combination to combine the temperature and humidity requirements of goods and turnover boxes into the environmental requirements of goods and the environmental status of turnover boxes respectively;

[0024] Extract the environmental requirements, size characteristics, and volume characteristics of the goods to form a cargo feature vector. Extract the current environmental status, internal size characteristics, and available volume characteristics of the turnover box to form a turnover box feature vector.

[0025] Normalize and calculate the difference between the feature vectors of goods and turnover boxes to obtain the difference between the feature vectors of goods and turnover boxes;

[0026] The optimization algorithm is used to generate the matching degree between the turnover box and the goods based on the difference between the feature vectors of the goods and the turnover box. The expression is:

[0027]

[0028] Among them, B represents the matching degree between goods and turnover boxes, D() represents the difference between the feature vectors of goods and turnover boxes, and E b Indicates the environmental status of the turnover box, S g The environmental demand of the goods, σ represents the parameter that controls the sensitivity of environmental matching;

[0029] The unique identification information of the goods is bound to the RFID tag and QR code information of the turnover box to generate a second mapping table that records the corresponding relationship between the goods and the turnover box.

[0030] As a preferred solution of the method for binding turnover boxes based on electronic tags of the present invention, when the turnover box is shipped out, the turnover box information is confirmed, and the first mapping relationship table and the second mapping relationship table are updated, including the following steps:

[0031] When the turnover box needs to be shipped out of the warehouse, the RFID reader reads the RFID tag to confirm the unique identification information of the turnover box;

[0032] The camera captures the QR code to further verify the unique identification information of the turnover box;

[0033] After confirming that the unique identification information of the turnover box is correct, an outbound document is generated and a delivery document is printed. The delivery personnel then perform outbound operations based on the document.

[0034] When the turnover box is successfully shipped out and delivered, the shipping information is recorded and the first mapping relationship table and the second mapping relationship table are updated.

[0035] As a preferred solution of the method for binding turnover boxes based on electronic tags of the present invention, a turnover box status prediction model is established to output the health status of the turnover box, including the following steps:

[0036] When the turnover box returns to the warehouse, the RFID reader reads the RFID tag and confirms the unique identification information of the turnover box.

[0037] The camera captures the QR code to further verify the unique identification information of the turnover box;

[0038] After confirming that the unique identification information of the turnover box is correct, update the turnover box status information and complete the turnover box return operation;

[0039] Set a time window, collect the temperature and humidity of the turnover box within the time window, form a temperature sequence and a humidity sequence, and calculate the average value of the temperature sequence and the humidity sequence respectively;

[0040] Calculate the standard deviation of temperature and humidity based on the average value, and use the obtained standard deviation of temperature and humidity as the fluctuation;

[0041] Extract the maintenance interval and average temperature and humidity features of the turnover box and normalize them. Combine the normalized feature values ​​with the temperature fluctuation and humidity fluctuation to form a feature vector.

[0042] Use feature selection algorithms to determine the importance of each feature, assign weight factors to each feature based on feature importance, and form these weight factors into a weight vector;

[0043] Introducing a dynamic weight adjustment mechanism to adjust the weight of features based on the gap between the maintenance interval and the ideal maintenance interval and the set appropriate interval;

[0044] For each feature, define the health scoring rules of the feature, obtain the feature score, and fuse the feature score with the feature vector to form a comprehensive feature vector;

[0045] The Sigmoid function is introduced to capture the nonlinear relationship between the comprehensive feature vector and the weight vector;

[0046] The optimization algorithm is used to generate the health status prediction value of the turnover box based on the comprehensive feature vector of the turnover box. The expression is:

[0047]

[0048] Among them, H represents the predicted health status of the turnover box, g() represents the Sigmoid function, W' represents the weight vector, X' represents the comprehensive feature vector, μ represents the mean, and σ represents the standard deviation.

[0049] As a preferred solution of the method for binding turnover boxes based on electronic tags of the present invention, the method includes the following steps: replacing and maintaining the turnover boxes according to their health conditions:

[0050] There are three levels of health thresholds established based on historical data;

[0051] The current status of the turnover box is determined based on the health level of the health prediction value being within the health threshold;

[0052] The health prediction value at level 3 indicates that the turnover box is damaged and the warehouse manager needs to be notified for replacement.

[0053] The health status prediction value at the second level indicates that the turnover box is in poor condition and the warehouse manager needs to be notified for maintenance;

[0054] The health status prediction value at level 1 indicates that the turnover box is in good condition and can continue to be used without replacement or maintenance.

[0055] In a second aspect, the present invention provides a system for binding turnover boxes based on electronic tags, comprising:

[0056] Initial information entry module, enters basic information of turnover box and generates the first mapping table;

[0057] Incoming verification module verifies and updates the information of turnover boxes when they enter the warehouse;

[0058] Goods and turnover box matching optimization module, matching the most suitable turnover box based on the goods information;

[0059] The cargo binding module binds the cargo to the turnover box and generates a second mapping table;

[0060] The outbound confirmation module confirms the outbound information of turnover boxes, updates the mapping table, and generates outbound documents;

[0061] The status monitoring module continuously monitors the environmental parameters of the turnover box and automatically adjusts the working mode;

[0062] The health status prediction module predicts the health status of the turnover box and outputs the health prediction value;

[0063] The maintenance management module performs replacement and maintenance operations based on the health status prediction results.

[0064] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the method for binding turnover boxes based on electronic tags as described in the first aspect of the present invention.

[0065] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored, wherein: when the computer program is executed by a processor, it implements any step of the method for binding turnover boxes based on electronic tags as described in the first aspect of the present invention.

[0066] The present invention has the following beneficial effects: The simultaneous use of RFID tags and QR codes on turnover boxes improves the accuracy of binding the electronic tags to the boxes. The RFID tag and QR code information are verified and the current status of the turnover boxes is updated when the turnover boxes enter or leave the warehouse and when loading goods, greatly facilitating the management and utilization of the turnover boxes. By establishing a turnover box status and maintenance demand prediction model and outputting the health status of the turnover boxes, potential problems with the turnover boxes can be discovered in a timely manner and preventive maintenance can be performed. This not only prevents damage to the turnover boxes from affecting the goods, but also effectively reduces delays and losses caused by turnover box problems, thereby improving the reliability of the turnover boxes. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0068] Figure 1 This is a flow chart of the method and system for binding turnover boxes based on electronic tags in Example 1.

[0069] Figure 2 This is the decision diagram of the turnover box status and maintenance demand prediction model in Example 1. DETAILED DESCRIPTION

[0070] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0071] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0072] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0073] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, provides a method for binding turnover boxes based on electronic tags, comprising the following steps:

[0074] S1. Install a unique QR code and an adaptive RFID tag for each turnover box;

[0075] The QR code is used to store the basic information of the turnover box. The basic information of the turnover box contained in the QR code is the unique identification information, basic attribute information and status information of the turnover box;

[0076] The unique identification information of the turnover box contained in the QR code refers to the unique identifier of each turnover box, ensuring that each turnover box is unique globally;

[0077] The basic attribute information of the turnover box refers to the physical specifications such as size and capacity of the turnover box and the material type;

[0078] The status information refers to whether the turnover box is empty;

[0079] RFID tags with adaptive functions are a wireless identification technology that transmits data via radio waves;

[0080] RFID tags have built-in temperature and humidity sensors that can automatically adjust the operating frequency and power according to environmental conditions to ensure stable operation in different environments;

[0081] The RFID tag with adaptive function contains the unique identification information, basic attribute information, status information, location information and environmental information of the turnover box;

[0082] The unique identification information of the turnover box contained in the RFID tag refers to the unique identifier of each turnover box;

[0083] The basic attribute information refers to the physical specifications such as size and capacity of the turnover box and the material type;

[0084] The status information refers to whether the turnover box is empty;

[0085] The location information refers to the warehouse area where the turnover box is currently located;

[0086] The environmental information refers to the temperature and humidity of the environment in which the turnover box is currently located;

[0087] It is further explained that combining QR code information and RFID tag information can strengthen the management of turnover boxes.

[0088] S1.2. Install RFID readers and cameras at warehouse entrances, exits, and key locations to ensure they cover all areas requiring monitoring.

[0089] The RFID reader is used to automatically read the RFID tag information on the turnover box;

[0090] The camera is used to capture the QR code and perform image processing;

[0091] The key nodes refer to key locations, such as sorting areas, temporary storage areas, etc.

[0092] S1.3. Enter the unique identification information, basic attribute information, status information, location information and environmental information of the turnover box to generate a first mapping table, which records the unique identification information of the turnover box and its corresponding RFID tag information and QR code information.

[0093] Furthermore, detailed initial information entry and generation of the first mapping table can provide a better understanding of the usage and demand of turnover boxes. This helps optimize resource allocation, rationally arrange the use of turnover boxes, and reduce idleness and waste.

[0094] S2. When a turnover box enters the warehouse, the RFID tag automatically adjusts its operating frequency and transmission power based on current environmental parameters (such as temperature, humidity, and electromagnetic interference). This adaptive function ensures the stability and reliability of the RFID tag in different environments. For example, in high humidity, the tag may reduce power to reduce energy consumption; in strong electromagnetic interference, the tag may adjust to a more stable frequency.

[0095] S2.1. The camera installed at the warehouse entrance captures the QR code on the turnover box. The captured QR code image is preprocessed, including noise removal, contrast enhancement, and edge sharpening.

[0096] Extract edge and corner features from the preprocessed image information and obtain the feature value at the position (u, y);

[0097] Use the Canny edge detection algorithm to detect edges in the image;

[0098] Use Harris corner detection algorithm to detect corners in the image;

[0099] Integrate the results of edge and corner inspection into a feature map and determine the position and size of the QR code in the feature map to make it a standard square QR code image;

[0100] The stored information is extracted from the QR code image. The expression is:

[0101]

[0102] Among them, D represents the information of the QR code, Z represents the normalization factor, P represents the size in the u direction, Q represents the size of the feature in the v direction, F(u k ,v l ) means at position u k and v lThe eigenvalue at , min(F) represents the minimum value of the feature map F, max(F) represents the maximum value of the feature map F, u k Indicates the kth position coordinate of the feature map in the u direction, v l Represents the lth position coordinate of the feature map in the v direction, Represents the central coordinate of the feature map in the u direction, Represents the central coordinate of the feature map in the v direction, and γ represents the standard deviation of the Gaussian distribution, which is used to control the range of the decoding area.

[0103] S2.2: Compare and verify the information read from the RFID tag with the information extracted from the QR code. If the information matches, the identity of the turnover box is confirmed and the status information of the turnover box is updated.

[0104] Furthermore, dual verification of the RFID tag and QR code ensures the accuracy and consistency of the turnover box information. Even if one tag or QR code is damaged or fails to read, the other can serve as a backup, reducing the risk of information errors and omissions. Adaptive RFID tags automatically adjust their operating frequency and power according to environmental conditions, improving the reliability and stability of RFID reading. Combined with a camera and image processing algorithm, automatic reading and verification of information is achieved, reducing the need for manual intervention and improving work efficiency.

[0105] S3. When the goods enter the warehouse, the staff uses a handheld device (such as a barcode scanner, mobile terminal, etc.) to scan the QR code on the goods. The QR code contains basic information about the goods, such as the unique identification code, type of goods, and size of the goods, and uploads it;

[0106] S3.1. To achieve intelligent matching between turnover boxes and goods, extract the size, volume, temperature, and humidity requirements of the goods.

[0107] The temperature and humidity requirements of the cargo are combined into the environmental requirements of the cargo through linear combination, and the expression is:

[0108] S g =α·S temp +β·S hum ;

[0109] Among them, S g represents the cargo environment requirement, represents the temperature weight, S temp represents the temperature requirement of the goods, β represents the humidity weight, S hum Indicates the humidity requirement of the cargo.

[0110] S3.1.1. Dimensional characteristics are the length, width, and height of the goods, which determine whether they can be properly placed in the turnover box;

[0111] The volume feature is the total volume of the goods, ensuring that it matches the available volume of the turnover box;

[0112] Temperature demand characteristics are that some goods (such as perishable products) have strict temperature requirements;

[0113] Humidity requirement characteristics mean that, for example, electronic products or paper products require specific humidity conditions to prevent damage.

[0114] S3.2, extract the internal size characteristics, available volume characteristics, current temperature and humidity characteristics of the turnover box,

[0115] The current temperature and humidity of the turnover box are combined into the environmental state of the turnover box through linear combination, and its expression is:

[0116] E b =α·E temp +β·E hum ;

[0117] Among them, E b Indicates the environmental status of the turnover box, E temp Indicates the actual temperature of the turnover box, E hum Indicates the actual humidity of the turnover box.

[0118] S3.2.1. Internal dimensions refer to the length, width, and height of a turnover box, which determine the size of the goods it can accommodate.

[0119] The available volume feature refers to the current available space of the turnover box, ensuring that the goods can be loaded;

[0120] The current temperature characteristic of the turnover box refers to the temperature inside the turnover box, which is used to match the temperature requirements of the goods;

[0121] The current humidity characteristic of the turnover box refers to the humidity inside the turnover box, which is used to match the humidity requirements of the goods.

[0122] S3.3. To ensure the rationality of calculations between different feature dimensions, first normalize the feature vectors of goods and turnover boxes, and calculate the difference between the normalized feature vectors of goods and turnover boxes.

[0123] On the basis of calculating the difference of eigenvectors, we further consider the matching between the environmental conditions of the turnover box (such as temperature and humidity) and the demand for goods. The expression is:

[0124]

[0125] Among them, B represents the matching degree between goods and turnover boxes, D() represents the difference between the feature vectors of goods and turnover boxes, and E bIndicates the environmental status of the turnover box, S g represents the environmental demand of the goods, and σ represents the parameter that controls the sensitivity of environmental matching.

[0126] A matching threshold T is set. If the result of the matching degree B is greater than the matching threshold T, the goods and the turnover box are considered to be matched, and the matching relationship is recorded. If the result of the matching degree B is less than the matching threshold T, it is considered not to be matched.

[0127] The setting of the matching threshold T can be customized according to the usage scenario and scope.

[0128] S3.1. After matching goods with turnover boxes, the system binds the goods' unique identification information to the box's RFID tag and QR code. Through this binding, the system generates a second mapping table that records the corresponding relationship between goods and turnover boxes. This mapping table not only records the matching relationship between goods and turnover boxes but also can be used for subsequent tracking, querying, and scheduling of turnover boxes in the warehouse.

[0129] Real-time updating of the information in the second mapping table can accurately reflect the status changes of all items in the warehouse, which is of great significance for maintaining good supply chain operations.

[0130] It is further explained that the automated data collection process reduces the workload of manual data entry while improving speed and accuracy. By establishing a second mapping table, the flow trajectory of any product in the entire supply chain can be easily tracked.

[0131] S4. When a turnover box needs to be shipped out of the warehouse, the RFID reader automatically reads the RFID tag on the turnover box, obtains the unique identification information of the turnover box, and confirms the identity information and current status of the turnover box based on the unique identification information of the turnover box;

[0132] The camera captures the QR code on the turnover box, extracts the information in the QR code, and compares the information extracted from the QR code with the information read by the RFID reader to ensure that the two are consistent;

[0133] S4.1. After confirming that the unique identification information of the turnover box is correct, the system automatically generates an outbound document. The outbound document contains the unique identification information of the turnover box and detailed information about the goods. The outbound document is printed for the reference of the delivery personnel.

[0134] The delivery personnel carry out outbound operations according to the outbound documents and delivery documents, and move the turnover boxes to the designated transport vehicles or delivery areas.

[0135] When the turnover box is successfully shipped out and delivered, the system records the shipping information, including shipping time, operator, destination, etc.

[0136] S4.2. Update the first mapping relationship table, mark the turnover box as "outbound" status, and record the outbound time.

[0137] Update the second mapping relationship table to reflect the status that the goods have been shipped out.

[0138] Furthermore, detailed records are kept for each operation, making it easy to track the movement of turnover boxes and goods, facilitating subsequent audits and troubleshooting. Real-time updates to the first and second mapping tables ensure the accuracy and real-time nature of inventory information, helping to better manage and schedule inventory resources.

[0139] S5. When the turnover box returns to the warehouse, the RFID reader automatically reads the RFID tag on the turnover box to obtain the unique identification information of the turnover box;

[0140] The camera captures the QR code on the turnover box and extracts the information in the QR code.

[0141] Compare the information extracted from the QR code with the unique identification information of the turnover box read by the RFID reader to ensure that the two are consistent; after confirming that the unique identification information of the turnover box is correct, update the status information of the turnover box.

[0142] S5.1. Update the first mapping relationship table to record the latest status and storage time of the turnover box.

[0143] Update the second mapping relationship table. If there are still goods in the turnover box, update the relevant entries; if it is empty, clear the relevant entries.

[0144] S5.2. Select a time window for calculating volatility. This time window can be set according to actual needs, such as the past week, month, etc.

[0145] For each turnover box within the selected time window, all temperature and humidity measurement values ​​of the turnover box within the selected time window are extracted and divided into a temperature series and a humidity series.

[0146] Calculate the average value of the temperature series and humidity series respectively, and calculate the standard deviation of temperature and humidity based on the average value of the temperature series and humidity series. The expression is:

[0147]

[0148] Where TSD represents the standard deviation of temperature, T i represents the temperature measurement value at the i-th time point, μ T represents the average temperature, and n represents the number of temperature measurements.

[0149] Use the same method to calculate the standard deviation of humidity, and use the standard deviation of temperature and humidity as the fluctuation of temperature and humidity;

[0150] It is further explained that the introduction of fluctuation can better reflect the impact of environmental changes on the performance of turnover box materials.

[0151] Extract the maintenance interval, average temperature, and humidity eigenvalues ​​of the turnover box. Normalize these eigenvalues ​​and the temperature and humidity fluctuation values ​​to keep them within the same numerical range for ease of subsequent processing. The normalized eigenvalues ​​and temperature and humidity fluctuation values ​​form a eigenvector.

[0152] S5.2. Use an information gain-based method to calculate the importance of each feature, assign weight factors based on the importance of the feature, and form a weight vector with all weight factors to represent the relative importance of each feature to the health status.

[0153] A dynamic weight adjustment mechanism is introduced to adjust the weight of the maintenance interval based on the gap between the actual maintenance interval and the ideal maintenance interval. The larger the gap between the actual maintenance interval and the ideal maintenance interval, the smaller the weight of the maintenance interval will be.

[0154] It is further explained that the ideal maintenance interval is set based on historical maintenance records, but can also be set through the turnover box manufacturer's maintenance manual and industry standards, depending on actual usage and scenarios.

[0155] Set optimal ranges for temperature and humidity and assign weights based on these ranges. For example, in a low-temperature, low-humidity environment, humidity may have a greater impact than temperature; whereas in a high-temperature, high-humidity environment, temperature has a more significant impact.

[0156] The suitable range of temperature and humidity can be customized according to the specific usage environment and region.

[0157] For temperature fluctuation and humidity fluctuation, an exponential decay function is used to calculate the weight. The greater the fluctuation, the smaller the weight.

[0158] It is further shown that being able to adjust the importance of features according to different environmental conditions makes the model more flexible.

[0159] S5.3. Set up segmented health scores.

[0160] When the actual maintenance interval is equal to or less than the ideal maintenance period, the maintenance interval score is full marks;

[0161] The full score is usually 1 point, and the specific value can be adjusted according to actual conditions.

[0162] The temperature and humidity are divided into the optimum temperature zone and the optimum humidity zone. When the temperature and humidity are higher or lower than the optimum temperature zone and the optimum humidity zone, the score is 0 points. If they are in the optimum temperature zone and the optimum humidity zone, the score is full marks.

[0163] The full score is usually 1 point, and the specific value can be adjusted according to actual conditions.

[0164] The obtained score is added to the feature vector to obtain a comprehensive feature vector.

[0165] Taking into account the nonlinear relationship between different features, the Sigmoid function is introduced to capture the nonlinear relationship between the comprehensive feature vector and the weight vector.

[0166] Finally, the optimization algorithm is used to generate the health status prediction value of the turnover box based on the comprehensive feature vector and weight vector, and its expression is:

[0167]

[0168] Among them, H represents the predicted health status of the turnover box, g() represents the Sigmoid function, W' represents the weight vector, X' represents the comprehensive feature vector, μ represents the mean, and σ represents the standard deviation.

[0169] It is further explained that the maintenance interval is an important indicator of the service life and working cycle of the turnover box;

[0170] If the turnover box is not maintained for a long time, it may cause fatigue wear, deformation, cracks and other problems due to long-term use, which will reduce the health of the turnover box.

[0171] Temperature is an important parameter of the environment in which the turnover box is located, and has a significant impact on the material properties and life of the turnover box;

[0172] The average temperature reflects the environmental stability and adaptability of the turnover box over a period of time. A more stable temperature (such as a suitable room temperature) helps maintain the ideal state of the turnover box, while extreme temperatures often have a negative impact on health.

[0173] For example, when turnover boxes are exposed to high temperatures for extended periods, thermal expansion and contraction may cause the material to develop minor cracks, deformation, and other problems. In low-temperature environments, certain materials become brittle, reducing their impact resistance and increasing the likelihood of breakage.

[0174] If the turnover box frequently experiences large temperature fluctuations (such as alternating between hot and cold), the stress in the material will accumulate, thereby accelerating aging and damage.

[0175] Humidity is another key environmental characteristic. Frequent fluctuations in humidity can cause repeated moisture absorption and dehumidification processes in materials, thereby inducing fatigue and damage within the materials.

[0176] For example, if a container is exposed to high humidity for an extended period, it may cause corrosion (for metal parts) or mold growth (for wood or organic materials). Especially when humidity remains at a high level, the container's structure and appearance may be damaged. It may also accelerate the aging process of certain materials (such as plastics and coatings), reducing their strength and durability. Extremely low humidity may cause certain materials (such as wood) to crack and deform, weakening the container's load-bearing capacity.

[0177] Temperature and humidity fluctuations reflect the degree of temperature and humidity variability. Even if the average temperature and humidity are within a suitable range, frequent temperature and humidity changes can still cause material fatigue and damage. The fluctuation value more accurately reflects the impact of these short-term fluctuations.

[0178] For example, there are two turnover boxes with the same average temperature and humidity, one of which has large fluctuations in temperature and humidity every day, while the other has very stable temperature and humidity. Therefore, the turnover box with large fluctuations in temperature and humidity every day will be more easily damaged.

[0179] Therefore, through the above characteristics, we can comprehensively consider the impact of time on the natural aging and wear of turnover boxes, and the impact of environmental conditions on the material properties of turnover boxes.

[0180] S6. Three levels of health thresholds are established based on historical data, with the health threshold range being [0.5, 1];

[0181] The predicted health status value is greater than or equal to 0.9, which is the first level; the predicted health status value is greater than or equal to 0.7 and less than 0.9, which is the second level; the predicted health status value is less than or equal to 0.7, which is the third level;

[0182] The current status of the turnover box is determined based on the health level of the health prediction value being within the health threshold;

[0183] The health prediction value at level 3 indicates that the turnover box is damaged and the warehouse manager needs to be notified for replacement.

[0184] The health status prediction value at the second level indicates that the turnover box is in poor condition and the warehouse manager needs to be notified for maintenance;

[0185] The health status prediction value at level 1 indicates that the turnover box is in good condition and can continue to be used without replacement or maintenance.

[0186] Furthermore, the use of scientific methods and formulas to calculate the health status of turnover boxes reduces errors caused by human judgment. Automated health assessment and notification mechanisms reduce the workload of manual inspections, improve the efficiency of maintenance and replacement, and promptly detect and address damaged or poorly functioning turnover boxes, avoiding production interruptions caused by turnover box failures and optimizing the use of inventory resources.

[0187] This embodiment also provides a system for binding turnover boxes based on electronic tags, including:

[0188] Initial information entry module, enters basic information of turnover box and generates the first mapping table;

[0189] Incoming verification module verifies and updates the information of turnover boxes when they enter the warehouse;

[0190] Goods and turnover box matching optimization module, matching the most suitable turnover box based on the goods information;

[0191] The cargo binding module binds the cargo to the turnover box and generates a second mapping table;

[0192] The outbound confirmation module confirms the outbound information of turnover boxes, updates the mapping table, and generates outbound documents;

[0193] The status monitoring module continuously monitors the environmental parameters of the turnover box and automatically adjusts the working mode;

[0194] Health status prediction module predicts the health status of turnover boxes and outputs health prediction values;

[0195] The maintenance management module performs replacement and maintenance operations based on the health status prediction results.

[0196] This embodiment also provides a computer device, which is suitable for the method of turnover box binding based on electronic tags, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the method of turnover box binding based on electronic tags proposed in the above embodiment.

[0197] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0198] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for implementing turnover box binding based on electronic tags as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0199] In summary, the present invention improves the accuracy of binding electronic tags to turnover boxes by simultaneously applying RFID tags and QR codes to turnover boxes. The RFID tag and QR code information are verified and the current status of the turnover box is updated when the turnover box enters or leaves the warehouse and when loading goods, greatly facilitating the management and utilization of the turnover box. Furthermore, by establishing a turnover box status and maintenance needs prediction model and outputting the health status of the turnover box, potential problems with the turnover box can be promptly identified and preventive maintenance can be performed. This not only prevents damage to the turnover box from affecting the goods, but also effectively reduces delays and losses caused by turnover box problems, thereby improving the reliability of the turnover box.

[0200] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for binding turnover boxes based on electronic tags, characterized by: include, Enter the initial information of the turnover box and generate the first mapping table; When the turnover box enters the warehouse, verify the RFID tag and QR code information and update the turnover box status information; Based on the turnover box status information, the goods are placed into the turnover box, the QR code of the goods is scanned, and the QR code information is bound to the RFID tag and QR code information of the turnover box to generate a second mapping table, including the following steps: The staff uses a handheld device to scan the QR code on the goods, obtains the goods information, and uploads the scanned QR code information of the goods; Use linear combination to combine the temperature and humidity requirements of goods and turnover boxes into the environmental requirements of goods and the environmental status of turnover boxes respectively; Extract the environmental requirements, size characteristics, and volume characteristics of the goods to form a cargo feature vector. Extract the current environmental status, internal size characteristics, and available volume characteristics of the turnover box to form a turnover box feature vector. Normalize and calculate the difference between the feature vectors of goods and turnover boxes to obtain the difference between the feature vectors of goods and turnover boxes; The optimization algorithm is used to generate the matching degree between the turnover box and the goods based on the difference between the feature vectors of the goods and the turnover box. The expression is: ； Among them, B represents the matching degree between goods and turnover boxes, D() represents the difference between the feature vectors of goods and turnover boxes, and E b Indicates the environmental status of the turnover box, S g represents the environmental demand of the goods, and θ represents the parameter that controls the sensitivity of environmental matching; Bind the unique identification information of the goods with the RFID tag and QR code information of the turnover box to generate a second mapping table that records the correspondence between the goods and the turnover box; When the turnover box is shipped out of the warehouse, the turnover box information is confirmed and the first mapping relationship table and the second mapping relationship table are updated; Establish a turnover box status and maintenance demand prediction model to output the health status of the turnover box; Replace and maintain the turnover box according to its health condition.

2. The method for binding turnover boxes based on electronic tags according to claim 1, characterized in that: Enter the initial information of the turnover box and generate the first mapping table, including the following steps: Set a QR code and an adaptive RFID tag on each turnover box; Install RFID readers and cameras at warehouse entrances, exits, and key nodes; The unique identification information, specification information, status information, location information and environmental information of the turnover box are input to generate a first mapping table.

3. The method for binding turnover boxes based on electronic tags according to claim 2, characterized in that: When a turnover box enters the warehouse, verify the RFID tag and QR code information and update the turnover box status information, including the following steps: When the turnover box enters the warehouse, the adaptive tag automatically adjusts the operating frequency and power according to the current environmental parameters; The camera captures the QR code on the turnover box and extracts the information in the QR code through image processing algorithms; Compare and verify the RFID tag and QR code information. Once the information is consistent, update the status information of the turnover box.

4. The method for binding turnover boxes based on electronic tags according to claim 3, characterized in that: When the turnover box is shipped out, the turnover box information is confirmed and the first mapping relationship table and the second mapping relationship table are updated, including the following steps: When the turnover box needs to be shipped out of the warehouse, the RFID reader reads the RFID tag to confirm the unique identification information of the turnover box; The camera captures the QR code to further verify the unique identification information of the turnover box; After confirming that the unique identification information of the turnover box is correct, an outbound document is generated and a delivery document is printed. The delivery personnel then perform outbound operations based on the document. When the turnover box is successfully shipped out and delivered, the shipping information is recorded and the first mapping relationship table and the second mapping relationship table are updated.

5. The method for binding turnover boxes based on electronic tags according to claim 4, characterized in that: Establish a turnover box status prediction model to output the health status of the turnover box, including the following steps: When the turnover box returns to the warehouse, the RFID reader reads the RFID tag and confirms the unique identification information of the turnover box. The camera captures the QR code to further verify the unique identification information of the turnover box; After confirming that the unique identification information of the turnover box is correct, update the turnover box status information and complete the turnover box return operation; Set a time window, collect the temperature and humidity of the turnover box within the time window, form a temperature sequence and a humidity sequence, and calculate the average value of the temperature sequence and the humidity sequence respectively; Calculate the standard deviation of temperature and humidity based on the average value, and use the obtained standard deviation of temperature and humidity as the fluctuation; Extract the maintenance interval, average temperature and humidity characteristics of the turnover box and normalize them. Combine the normalized characteristic values ​​with the temperature fluctuation and humidity fluctuation. Composition feature vector; Use feature selection algorithms to determine the importance of each feature, assign weight factors to each feature based on feature importance, and form these weight factors into a weight vector; Introducing a dynamic weight adjustment mechanism to adjust the weight of features based on the gap between the maintenance interval and the ideal maintenance interval and the set appropriate interval; For each feature, define the health scoring rules of the feature, obtain the feature score, and fuse the feature score with the feature vector to form a comprehensive feature vector; The Sigmoid function is introduced to capture the nonlinear relationship between the comprehensive feature vector and the weight vector; The optimization algorithm is used to generate the health status prediction value of the turnover box based on the comprehensive feature vector of the turnover box. The expression is: ； Among them, H represents the predicted health status of the turnover box, g() represents the Sigmoid function, W' represents the weight vector, X' represents the comprehensive feature vector, μ represents the mean, and σ represents the standard deviation.

6. The method for binding turnover boxes based on electronic tags according to claim 5, characterized in that: Replace and maintain the turnover box according to its health condition, including the following steps: There are three levels of health thresholds established based on historical data; The current status of the turnover box is determined based on the health level of the health prediction value being within the health threshold; The health prediction value at level 3 indicates that the turnover box is damaged and the warehouse manager needs to be notified for replacement. The health status prediction value at the second level indicates that the turnover box is in poor condition and the warehouse manager needs to be notified for maintenance; The health status prediction value at level 1 indicates that the turnover box is in good condition and can continue to be used without replacement or maintenance.

7. A system for binding turnover boxes based on electronic tags, based on the method for binding turnover boxes based on electronic tags according to any one of claims 1 to 6, characterized in that: include, Initial information entry module, enters basic information of turnover box and generates the first mapping table; Incoming verification module verifies and updates the information of turnover boxes when they enter the warehouse; Goods and turnover box matching optimization module, matching the most suitable turnover box based on the goods information; The cargo binding module binds the cargo to the turnover box and generates a second mapping table; The outbound confirmation module confirms the outbound information of turnover boxes, updates the mapping table, and generates outbound documents; The status monitoring module continuously monitors the environmental parameters of the turnover box and automatically adjusts the working mode; Health status prediction module predicts the health status of turnover boxes and outputs health prediction values; The maintenance management module performs replacement and maintenance operations based on the health status prediction results.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for binding turnover boxes based on electronic tags according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for binding turnover boxes based on electronic tags according to any one of claims 1 to 6 are implemented.

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