Turnover box binding method and system based on electronic tag

Abstract

The invention discloses a turnover box binding method and system based on an electronic tag, and relates to the field of logistics and supply chain management, and the method comprises the steps: inputting the initial information of a turnover box, generating a first mapping table, verifying the information of an RFID tag and a two-dimensional code when the turnover box enters a warehouse, and updating the state information of the turnover box, and putting the goods into the turnover box based on the turnover box state information, scanning the two-dimensional code of the goods, binding the two-dimensional code with the RFID tag and the two-dimensional code information of the turnover box to generate a second mapping table, and when the turnover box is delivered out of a warehouse, confirming the information of the turnover box, updating the first mapping relation table and the second mapping relation table, and establishing a turnover box state and maintenance demand prediction model. The health condition of the turnover box is output, replacement and maintenance are carried out according to the health condition of the turnover box, management and utilization of the turnover box are greatly facilitated, the situation that goods are affected due to damage of the turnover box is avoided, delay and loss caused by the problem of the turnover box can be effectively reduced, and the reliability of the turnover box is improved.

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. In order to improve the management and use efficiency of turnover boxes, technology based on electronic tags is widely used. Traditional turnover box management systems usually rely on barcodes or manual records to track and manage the information of turnover boxes. However, these methods have many shortcomings, such as untimely information updates and inability to achieve automated management.

[0003] Although the existing turnover box management system based on RFID and QR code has improved management efficiency to a certain extent, there are still some problems that need to be solved. For example, the system's monitoring of environmental parameters is not comprehensive enough, and it is difficult to dynamically adjust the working mode according to the actual use of the turnover box; in addition, most of the existing systems lack an effective prediction and maintenance mechanism for the health status of the turnover box, resulting in the turnover box's service life and performance cannot be fully guaranteed. 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 the existing turnover box management system.

[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] Put the goods into the turnover box based on the turnover box status information, scan the QR code of the goods, and bind it with 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 to generate a first mapping table, including the following steps:

[0014] Set a QR code and an RFID tag with adaptive function 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 of the present invention, when the 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 working 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. When the information is consistent, update the status information of the turnover box.

[0021] As a preferred solution of the method for binding a turnover box based on an electronic tag of the present invention, the goods are placed in the turnover box based on the turnover box status information, the QR code of the goods is scanned, and the goods are bound to 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 controlling 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 out of the warehouse, 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, generate the outbound document and print the delivery document. The delivery personnel will perform the outbound operation according to the document.

[0034] When the turnover box is successfully shipped out of the warehouse 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 operation of returning the turnover box to the warehouse;

[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 values ​​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] The maintenance interval, average temperature and humidity characteristics of the turnover box are extracted and normalized, and the normalized characteristic values ​​are combined with the temperature fluctuation and humidity fluctuation to form a characteristic 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 merge 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 value of the 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 turnover boxes are replaced and maintained according to their health conditions, including the following steps:

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

[0051] The current state of the turnover box is determined according to the health level of the health prediction value being within the health threshold;

[0052] The health prediction value at the third level 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 the first level indicates that the turnover box is in good condition and can continue to be used without replacement and maintenance.

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

[0056] An initial information input module is used to input the basic information of the turnover box and generate a first mapping table;

[0057] Incoming verification module verifies and updates the information of the turnover box when it enters the warehouse;

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

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

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

[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, any step of the method for binding turnover boxes based on electronic tags as described in the first aspect of the present invention is implemented.

[0065] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, 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 beneficial effects of the present invention are as follows: RFID tags and QR codes are used on turnover boxes at the same time, which improves the accuracy of binding electronic tags with turnover boxes. When the turnover boxes enter and leave the warehouse and load goods, the RFID tags and QR code information will be verified and the status information of the current turnover boxes will be updated, which greatly facilitates 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 of the turnover boxes can be discovered in time and preventive maintenance can be performed. This not only avoids the damage of the turnover boxes affecting the goods, but also effectively reduces the delays and losses caused by turnover box problems and improves 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 accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying 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 implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0071] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and 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" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

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

[0074] S1. Install a unique QR code and an RFID tag with adaptive function 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, which 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 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 the warehouse entrance, exit and key nodes to ensure that the RFID readers and cameras can cover all areas that need to be monitored;

[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] Further explanation: detailed initial information entry and generation of the first mapping table can better understand the usage and demand of turnover boxes, which helps to optimize resource allocation, reasonably arrange the use of turnover boxes, and reduce idleness and waste.

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

[0095] S2.1. The camera installed at the warehouse entrance will capture the QR code on the turnover box. The captured QR code image is preprocessed, including removing noise, enhancing contrast and sharpening edges;

[0096] Extract edge and corner features from the preprocessed image information to 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 point 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] Extract the stored information from the QR code image, and its 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, and 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 represents 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, It 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 is consistent, the identity of the turnover box is confirmed and the status information of the turnover box is updated.

[0104] Further explanation: Through the dual verification of RFID tags and QR codes, the accuracy and consistency of the turnover box information is ensured. Even if one of the tags or QR codes is damaged or fails to read, the other can be used as a backup, thus reducing the risk of information errors and omissions; adaptive RFID tags can automatically adjust the operating frequency and power according to environmental conditions, improving the reliability and stability of RFID reading. Combined with cameras and image processing algorithms, 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 the basic information of the goods, such as the unique identification code of the goods, the type of goods, and the size of the goods, and uploads it;

[0106] S3.1. In order to achieve intelligent matching between turnover boxes and goods, the size characteristics, volume characteristics, temperature and humidity requirement characteristics of the goods are extracted;

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

[0108] S g =α·S temp +β·S hum ;

[0109] Among them, S g represents the environmental requirements of the goods, 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. The size characteristics are the length, width and height of the goods, which determine whether they can be placed reasonably in the turnover box;

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

[0112] The temperature demand feature is 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 by linear combination, and the 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 the turnover box, which determine the size of the goods it can accommodate;

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

[0120] The current temperature feature 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. In order to ensure the rationality of calculation between different feature dimensions, the feature vectors of goods and turnover boxes are first normalized, and the difference between the normalized feature vectors of goods and turnover boxes is calculated;

[0123] On the basis of calculating the difference of characteristic vectors, we further consider the matching between the environmental conditions (such as temperature and humidity) of the turnover box 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 match, and the matching relationship is recorded. If the result of the matching degree B is less than the matching threshold T, it is considered to be unmatched.

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

[0128] S3.1. After completing the matching of goods and turnover boxes, the system will bind the unique identification information of the goods with the RFID tag and QR code information of the turnover box. Through this binding, the system generates a second mapping table that records the corresponding relationship between the goods and the turnover box. This mapping table not only records the matching relationship between the goods and the turnover box, but can also be used for subsequent tracking, query, 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 the 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 according to 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, which contains the unique identification information of the turnover box and detailed information of the goods. The outbound document is printed for the reference of the delivery personnel;

[0134] The distribution 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 of the warehouse.

[0138] Further explanation: every operation step has a detailed record, which can easily track the flow of turnover boxes and goods, and facilitate subsequent audits and troubleshooting. The first mapping relationship table and the second mapping relationship table are updated in real time to ensure the accuracy and timeliness of inventory information, which helps 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 in the selected time window, all temperature and humidity measurement values ​​of the turnover box in the selected time window are extracted and divided into a temperature sequence and a humidity sequence.

[0146] Calculate the average values ​​of the temperature series and humidity series respectively, and calculate the standard deviation of temperature and humidity based on the average values ​​of the temperature series and humidity series. The expressions are as follows:

[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 characteristic values ​​of the turnover box, normalize these characteristic values ​​and temperature and humidity fluctuation values ​​to make them in the same numerical range for subsequent processing, and the normalized characteristic values ​​and temperature and humidity fluctuation values ​​form a characteristic vector;

[0152] S5.2. Use the information gain-based method to calculate the importance of each feature, assign weight factors based on the importance of the feature, and combine all weight factors into a weight vector; this is used to represent the relative importance of each feature to the health status.

[0153] Introduce a dynamic weight adjustment mechanism to adjust the weight of the maintenance interval according to 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] To further explain, 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 appropriate ranges for temperature and humidity and assign weights based on them. For example, in a low-temperature and low-humidity environment, humidity may have a greater impact than temperature; whereas in a high-temperature and 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 weights. 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 suitable temperature and humidity zones. When the temperature and humidity are higher or lower than the suitable temperature and humidity zones, the score is 0 points. If they are in the suitable temperature and humidity zones, 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 scores are 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 value of the 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 representation of the use time 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 container over a period of time. A more stable temperature (such as a suitable room temperature) helps maintain the ideal state of the container, while extreme temperatures usually have a negative impact on health.

[0173] For example, when the turnover box is in a high temperature environment for a long time, it may cause the material to expand and contract due to heat and cold, resulting in problems such as tiny cracks and deformation. In a low temperature environment, some materials will become brittle, and their impact resistance will decrease, increasing the possibility of fracture.

[0174] If the turnover box frequently experiences large temperature fluctuations (such as alternating between hot and cold), 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 of the material, thereby inducing fatigue and damage within the material.

[0176] For example, if the container is in a high humidity environment for a long time, it may cause corrosion (for metal parts) or mold growth (for wood or organic materials). Especially when the humidity is maintained at a high level, the structure and appearance of the container may be damaged. It also accelerates the aging process of certain materials (such as plastics, coatings, etc.), reducing strength and durability. Extremely low humidity may cause cracking and deformation of certain materials (such as wood), weakening the carrying capacity of the container.

[0177] The fluctuation of temperature and humidity reflects the degree of change in temperature and humidity. Even if the average temperature and humidity are within the appropriate range, frequent temperature and humidity changes may still cause material fatigue and damage. The fluctuation value can more accurately reflect 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 performance of turnover boxes.

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

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

[0182] The current state of the turnover box is determined according to the health level of the health prediction value being within the health threshold;

[0183] The health prediction value at the third level 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 the first level indicates that the turnover box is in good condition and can continue to be used without replacement and maintenance.

[0186] Further explanation: The health status of the turnover box is calculated through scientific methods and formulas, which reduces the error of human judgment. The automated health status assessment and notification mechanism reduces the workload of manual inspection, improves the efficiency of maintenance and replacement, and promptly detects and handles damaged or poorly condition turnover boxes, avoiding production interruptions caused by turnover box failures and optimizing the utilization of inventory resources.

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

[0188] An initial information input module is used to input the basic information of the turnover box and generate a first mapping table;

[0189] Incoming verification module verifies and updates the information of the turnover box when it enters the warehouse;

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

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

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

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

[0194] The health status prediction module predicts the health status of the turnover box and outputs the health prediction value;

[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 applicable to 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 as proposed in the above embodiment.

[0197] The computer device may be a terminal, and the computer device includes 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 includes 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 can 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 screen 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 key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0198] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for realizing turnover box binding based on electronic tags as proposed in the above embodiment is implemented; 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 (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0199] In summary, the present invention improves the accuracy of binding the electronic tag with the turnover box by: applying the RFID tag and the QR code to the turnover box at the same time; the turnover box will verify the RFID tag and QR code information and update the current status information of the turnover box when entering and leaving the warehouse and loading goods, which greatly facilitates the management and utilization of the turnover box; by establishing a turnover box status and maintenance demand prediction model and outputting the health status of the turnover box, potential problems of the turnover box can be discovered in time and preventive maintenance can be performed. This not only avoids the damage of the turnover box affecting the goods, but also effectively reduces the delays and losses caused by turnover box problems and improves 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 rather than to limit it. 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 in that: 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; Put the goods into the turnover box based on the turnover box status information, scan the QR code of the goods, and bind it 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, 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 as claimed in 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 RFID tag with adaptive function 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 as claimed in claim 2, characterized in that: When the 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 working 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. When the information is consistent, update the status information of the turnover box.

4. The method for binding turnover boxes based on electronic tags as claimed in claim 3 is characterized in that: Based on the turnover box status information, the goods are placed in the turnover box, the QR code of the goods is scanned, and the goods are 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 The environmental demand of the goods, σ represents the parameter controlling the sensitivity of environmental matching; 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.

5. The method for binding turnover boxes based on electronic tags as claimed in claim 4, characterized in that: 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, 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, generate the outbound document and print the delivery document. The delivery personnel will perform the outbound operation according to the document. When the turnover box is successfully shipped out of the warehouse and delivered, the shipping information is recorded and the first mapping relationship table and the second mapping relationship table are updated.

6. The method for binding turnover boxes based on electronic tags as claimed in claim 5, 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 operation of returning the turnover box to the warehouse; 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 values ​​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; The maintenance interval and average temperature and humidity characteristics of the turnover box are extracted and normalized, and the normalized characteristic values ​​are combined 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 merge 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 value of the 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.

7. The method for binding turnover boxes based on electronic tags as claimed in claim 6, 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 state of the turnover box is determined according to the health level of the health prediction value being within the health threshold; The health prediction value at the third level 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 the first level indicates that the turnover box is in good condition and can continue to be used without replacement and maintenance.

8. 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 7, characterized in that: include, An initial information input module is used to input the basic information of the turnover box and generate a first mapping table; Incoming verification module verifies and updates the information of the turnover box when it enters the warehouse; Goods and turnover box matching optimization module, matching the most suitable turnover box according to the goods information; The cargo binding module binds the cargo with the turnover box and generates a second mapping table; The outbound confirmation module confirms the outbound information of the turnover box, updates the mapping table, and generates the outbound document; The status monitoring module continuously monitors the environmental parameters of the turnover box and automatically adjusts the working mode; The health status prediction module predicts the health status of the turnover box and outputs the health prediction value; The maintenance management module performs replacement and maintenance operations based on the health status prediction results.

9. 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 7 are implemented.

10. 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 as described in any one of claims 1 to 7 are implemented.

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