Warehousing order intelligent matching method and system for logistics goods receiving

Abstract

The invention relates to the technical field of intelligent logistics management, in particular to a warehousing order intelligent matching method and system for logistics goods receiving. A warehousing list intelligent matching method for logistics goods receiving comprises the following steps: S1, obtaining goods related data of a target goods, the goods related data including goods transportation stacking data, goods delivery coding data and cold chain interruption data, and obtaining goods related data of the target goods at the same time, the goods related data including goods transportation stacking data, goods delivery coding data and cold chain interruption data; obtaining the maximum mass variation value of the cargo sub-coded data by using a variation calculation formula; and S2, according to the delivery code data of the target goods and the maximum mass variation value of the goods sub-code data, carrying out intelligent matching on the goods. According to the method, the customized cargo proportion, the coding complexity and the real-time network quality are fused, the matching decision formula is used for dynamically selecting the center or edge equipment to execute the matching task, and intelligent matching of the warehousing list of logistics receiving is accurately and quickly completed.

Description

Technical Field

[0001] The present invention relates to the field of intelligent logistics management technology, and in particular to a method and system for intelligent matching of warehouse entry orders for logistics receipt. Background Art

[0002] The current logistics industry is in a stage of rapid development of informatization and intelligence. With the continuous expansion of e-commerce, supply chain management and logistics distribution, the demand for information collection, data processing and real-time monitoring in the logistics process is increasing, especially in the links of goods warehousing, receiving and acceptance. The traditional manual acceptance method and static data comparison can no longer meet the requirements of modern logistics for efficient, accurate and automated processing. The existing technology mainly has the following deficiencies: When collecting goods data, most traditional logistics management systems only focus on static information, such as goods coding, weight, volume, etc., and fail to fully obtain and utilize the dynamic changes in goods during transportation. Data; in traditional systems, central equipment and edge equipment often operate independently, lacking an effective task allocation and resource scheduling mechanism, and failing to dynamically adjust matching strategies based on customer historical data, resulting in unreasonable resource allocation and slow matching of incoming orders. Summary of the invention

[0003] In order to overcome the shortcoming of low efficiency in matching logistics receipt inbound orders, the present invention provides a method and system for intelligent matching of logistics receipt inbound orders.

[0004] The technical solution is as follows: A method for intelligent matching of incoming orders for logistics receipt, comprising the following steps: S1: Obtain cargo-related data of the target cargo, wherein the cargo-related data includes cargo transportation stacking data, cargo delivery coding data, and cold chain interruption data, and simultaneously obtain cargo-related data of the target cargo, and use a variation calculation formula to obtain a maximum mass variation value of the cargo sub-coding data; S2: Intelligently match the goods according to the maximum quality change value of the target goods’ shipping code data and the goods’ sub-code data; S3: Obtain the customer's historical cargo data, use the matching decision formula to obtain a matching decision value, and adjust the intelligent matching position of the cargo according to the matching decision value.

[0005] Preferably, the cargo-related data of the target cargo is obtained, the cargo-related data including the transportation stacking data of the cargo, the shipment coding data of the cargo and the cold chain interruption data, and the cargo-related data of the target cargo is obtained at the same time, and the maximum mass change value of the cargo sub-coding data is obtained using a change calculation formula, including: obtaining the cargo-related data of the target cargo, the cargo-related data including the transportation stacking data of the cargo, the shipment coding data of the cargo and the cold chain interruption data; inputting the cargo-related data into the change calculation formula to obtain the maximum mass change value of the cargo sub-coding data, wherein the shipment coding data of the cargo includes the fixed coding data of the cargo and the sub-coding data of the cargo, and the fixed coding data of the cargo is the immutable attribute data of the cargo; the sub-coding data of the cargo is the variable attribute data of the cargo; the transportation stacking data of the cargo includes the weight of the cargo stacked above the target cargo and the existence duration of the cargo stacked above the target cargo; the cold chain interruption data includes the duration of the cold chain interruption and the number of cold chain interruptions.

[0006] Preferably, the goods sub-coding data is variable attribute data of the goods, including: the goods sub-coding data includes initial goods quality, goods customized graphic data and goods customized structure data.

[0007] Preferably, the inputting of the cargo-related data into the change calculation formula to obtain the maximum change value of the quality of the cargo sub-code data comprises: pre-processing the cargo-related data by cleaning, normalizing, noise filtering and filling missing values, and then inputting the data into the change calculation formula to obtain the maximum change value of the quality of the cargo sub-code data, wherein the change calculation formula is: ; In the formula, The maximum change value of the quality of the cargo sub-coding data; For the The duration of the stacked cargo on top of the secondary target cargo; For the The weight of the cargo stacked above the secondary target cargo; For the Duration of the cold chain interruption; , is the corresponding weight adjustment factor; The initial cargo mass in the cargo sub-coding data; is the maximum allowable mass change value.

[0008] Preferably, the intelligent matching of goods based on the maximum quality change value of the shipping coding data and the goods sub-coding data of the target goods includes: issuing an alarm reminder when there is an inconsistency between the target goods and the fixed coding data of the goods; when the target goods are consistent with the fixed coding data of the goods and there is an inconsistency between the target goods and the sub-coding data of the goods, obtaining the maximum quality change value of the target goods and making a judgment based on the actual quality of the target goods, when the absolute difference between the actual quality of the target goods and the initial quality of the goods in the sub-coding data of the goods is less than or equal to the maximum quality change value, the target goods are successfully matched; when the absolute difference between the actual quality of the target goods and the initial quality of the goods in the sub-coding data of the goods is greater than the maximum quality change value, issuing an alarm reminder.

[0009] Preferably, the method of obtaining the customer's historical cargo data, using a matching decision formula to obtain a matching decision value, and adjusting the intelligent matching position of the cargo according to the matching decision value includes: obtaining the customer's historical cargo data, the historical cargo data including the number of standardized cargoes of the target merchant within a preset time period, the number of customized cargoes of the target merchant within a preset time period, the number of fixed cargo codes, and the number of cargo sub-codes, wherein the number of fixed cargo codes is the number of coding entries of immutable attribute data; the number of cargo sub-codes is the number of coding entries of variable attribute data; inputting the historical cargo data into the matching decision formula to obtain a matching decision value, and adjusting the intelligent matching position of the cargo according to the matching decision value.

[0010] Preferably, the step of inputting the historical cargo data into a matching decision formula to obtain a matching decision value includes: wherein the matching decision formula is: ; In the formula, is the matching decision value; Subcode quantity for the goods; Fixed coding quantity for goods; The quantity of customized goods for the target merchant within a preset time period; It is the standardized quantity of goods of the target merchant within the preset time period; Real-time network quality scoring for edge devices; Score standard network quality for edge devices; , , is the weight adjustment factor.

[0011] Preferably, the historical cargo data is input into a matching decision formula to obtain a matching decision value, and the intelligent matching position of the cargo is adjusted according to the matching decision value, including: when the matching decision value is greater than or equal to a first preset threshold, using a central device to perform intelligent matching on the cargo; when the matching decision value is less than the first preset threshold, using an edge device to perform intelligent matching on the cargo.

[0012] Preferably, when the matching decision value is less than a first preset threshold, the edge device is used to intelligently match the goods, including: using the edge device to match the fixed coding data of the goods, and when the fixed coding data matches the goods successfully, matching the goods sub-coding data of the goods, and actually recording the changes in the goods sub-coding data during the transportation of the goods.

[0013] Preferably, an intelligent matching system for inbound orders for logistics receipt includes: A data collection module is used to obtain cargo-related data of target cargo and historical cargo data of customers; A change calculation module, used for inputting the cargo related data into a change calculation formula to obtain a maximum change value of the mass of the cargo sub-code data; An intelligent matching module, used for intelligently matching goods according to the fixed code data of the target goods, the sub-code data of the goods and the maximum change value of the quality of the sub-code data of the goods; A decision value acquisition module is used to obtain the customer's historical cargo data and obtain the matching decision value using the matching decision formula; A decision adjustment module, used to adjust the intelligent matching position of the goods according to the matching decision value; The alarm and exception handling module is used to trigger alarms in time for abnormal situations that occur during the matching process.

[0014] Beneficial Effects

[0015] 1. The present invention can timely reflect the changes in the status of goods through real-time collection and analysis of dynamically changing data during transportation, avoiding matching errors caused by insufficient static data, thereby greatly improving the matching speed and accuracy of the warehouse entry order. By using the dual verification mechanism of fixed coding data and goods sub-coding data, while ensuring the accuracy of the goods identity, the present invention can make reasonable tolerance judgments on the actual changes in the quality of the goods, further shorten the matching response time, and achieve efficient and intelligent matching; 2. This system designs the task allocation and resource scheduling mechanism between the central device and the edge device, integrates the customized cargo ratio, coding complexity and real-time network quality, uses the matching decision formula to dynamically select the central or edge device to perform the matching task, and accurately and quickly completes the intelligent matching of the logistics receipt inbound order; 3. The transport stacking data and cold chain interruption data are integrated with the shipment coding data of the goods, so that the system can automatically correct errors when dealing with various dynamic interferences during the transportation process to ensure efficient and accurate matching results. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of the intelligent matching method of the inbound order for logistics receipt of the present invention; Figure 2 This is a flow chart of the intelligent matching system for incoming orders for logistics receipts according to the present invention. DETAILED DESCRIPTION

[0017] The above scheme is further described below in conjunction with specific examples. It should be understood that these examples are used to illustrate the present application and are not limited to the scope of the present application. The implementation conditions adopted in the examples can be further adjusted according to the conditions of the specific manufacturer, and the implementation conditions not specified are usually the conditions in conventional experiments.

[0018] Example 1: A method for intelligently matching incoming orders for logistics receipt, such as Figure 1 As shown, the following steps are included: S1: Obtain cargo-related data of the target cargo, wherein the cargo-related data includes cargo transportation stacking data, cargo delivery coding data, and cold chain interruption data, and simultaneously obtain cargo-related data of the target cargo, and use a variation calculation formula to obtain a maximum mass variation value of the cargo sub-coding data; Obtain cargo-related data of the target cargo, wherein the cargo-related data includes cargo transportation stacking data, cargo delivery coding data and cold chain interruption data; input the cargo-related data into a change calculation formula to obtain a maximum mass change value of cargo sub-coding data, wherein the cargo delivery coding data includes cargo fixed coding data and cargo sub-coding data, wherein the cargo fixed coding data is the immutable attribute data of the cargo; the cargo sub-coding data is the variable attribute data of the cargo; the cargo transportation stacking data includes the weight of the cargo stacked above the target cargo and the existence duration of the cargo stacked above the target cargo; the cold chain interruption data includes the duration of the cold chain interruption and the number of cold chain interruptions.

[0019] It should be noted that the transportation stacking data of the goods, which records in detail the weight of the stacked goods located above the target goods during transportation and the length of time these stacked goods exist above the target goods. For example, during the logistics transportation process, the weight information of the stacked goods and the stacking duration are collected in real time through sensors installed in the cargo containers and transmitted to the data center; the shipping coding data of the goods: this part of the data is further divided into fixed coding data of the goods and sub-coding data of the goods; the fixed coding data of the goods represents the immutable attributes of the target goods, such as the factory code and product type; and the sub-coding data of the goods represents the mutable attributes of the target goods, which may be changed due to external factors during transportation or warehousing. The cold chain interruption data records the interruptions that occur during cold chain transportation, including the duration of the interruption and the number of cold chain interruptions. Through the monitoring of the temperature control environment by monitoring equipment, various parameters of the cold chain interruption are fed back in real time to ensure the accuracy and timeliness of the data. The transport stacking data, shipping code data and cold chain interruption data of the target goods are input into the pre-designed change calculation formula in sequence. In the calculation process here, the fixed code data in the shipping code data of the goods is used as the comparison benchmark to ensure that only when the fixed code data is consistent, the sub-code data of the goods with variable attributes is further judged for quality changes.

[0020] The sub-coding data of the goods includes the initial goods quality, the customized graphic data of the goods and the customized structural data of the goods.

[0021] It should be noted that the cargo sub-coding data includes the initial cargo quality, which represents the initial quality value of the cargo after standard testing before leaving the factory or loading. It is an important benchmark for subsequently judging the difference between the actual quality of the cargo and the initial quality, which is the actual content of the sub-code. At the same time, the cargo sub-coding data also includes customized cargo graphic data, which involves customized feature information of the cargo appearance and label, and is used to assist in confirming the identity of the cargo in visual recognition or automated inspection. The cargo customized structural data records the customized attributes of the cargo in the structural design, such as special protective structures and packaging forms. These data reflect the unique information of the target cargo during the manufacturing or subsequent packaging process.

[0022] After preprocessing the cargo-related data by cleaning, normalizing, filtering noise, and filling missing values, the data is input into the change calculation formula to obtain the maximum change value of the cargo sub-code data quality. The change calculation formula is: ; In the formula, The maximum change value of the quality of the cargo sub-code data; For the The duration of the stacked cargo on top of the secondary target cargo; For the The weight of the cargo stacked above the secondary target cargo; For the Duration of the cold chain interruption; , is the corresponding weight adjustment factor; The initial cargo mass in the cargo sub-coding data; is the maximum allowable mass change value.

[0023] It should be noted that in the data cleaning stage, duplicate data are deleted, records with incorrect formats are removed, and outliers are corrected; in the normalization process, minimum-maximum scaling or Z-score standardization is used to ensure that the relative contribution of each variable data is consistent with the actual situation; in the noise filtering stage, the sliding window mean filtering method is used to smooth the data to eliminate the interference caused by short-term abnormal fluctuations and improve data stability; in the missing value filling stage, the interpolation method based on historical data or the machine learning prediction algorithm is used to fill the missing values ​​to ensure the integrity of the data during the calculation process.

[0024] S2: Intelligently match the goods according to the maximum quality change value of the target goods’ shipping code data and the goods’ sub-code data; When there is an inconsistency between the target goods and the fixed coding data of the goods, an alarm is issued; when the target goods and the fixed coding data of the goods are consistent and there is an inconsistency between the target goods and the sub-coding data of the goods, the maximum change value of the mass of the target goods is obtained and judged according to the actual mass of the target goods. When the absolute difference between the actual mass of the target goods and the initial mass of the goods in the sub-coding data of the goods is less than or equal to the maximum change value of the mass, the target goods are matched successfully; when the absolute difference between the actual mass of the target goods and the initial mass of the goods in the sub-coding data of the goods is greater than the maximum change value of the mass, an alarm is issued.

[0025] It should be noted that the matching of the fixed coding data of the goods is carried out by comparing the fixed coding data of the target goods. If the fixed coding data of the target goods are inconsistent with the fixed coding data of the goods, it means that there is an error or abnormality in the identity of the goods. At this time, the system triggers an alarm to remind the operator to check. For example, if the fixed coding data of the goods is a cup, but the target goods is a bowl, the goods will be blocked from entering the warehouse and a warning will be issued to the management personnel. When the fixed coding data of the target goods are consistent, the goods sub-coding data will be further compared. Since the goods sub-coding data is a variable attribute data, it will not be directly judged whether it is completely consistent with the warehouse entry data, but through The difference between the actual mass of the goods and the initial mass of the goods in the goods sub-coding data is calculated, and matched with the previously calculated maximum mass change value; if the absolute difference between the actual mass of the target goods and the initial mass of the goods in the goods sub-coding data, that is, the absolute value of the difference between the two, is less than or equal to the maximum mass change value, the target goods are considered to be matched successfully, and the goods are automatically confirmed to be put into storage; if the absolute difference between the actual mass of the target goods and the initial mass of the goods in the goods sub-coding data is greater than the maximum mass change value, an alarm is triggered to prompt that there is an abnormality in the quality of the goods, such as damaged packaging, damaged goods or overweight, and manual verification is required to decide whether to allow entry into the warehouse.

[0026] S3: Obtain the customer's historical cargo data, use the matching decision formula to obtain a matching decision value, and adjust the intelligent matching position of the cargo according to the matching decision value.

[0027] The customer's historical cargo data is obtained, wherein the historical cargo data includes the quantity of standardized cargo of the target merchant within a preset time period, the quantity of customized cargo of the target merchant within a preset time period, the quantity of fixed codes of cargo, and the quantity of sub-codes of cargo, wherein the quantity of fixed codes of cargo is the quantity of coding entries of immutable attribute data; the quantity of sub-codes of cargo is the quantity of coding entries of variable attribute data; the historical cargo data is input into a matching decision formula to obtain a matching decision value, and the intelligent matching position of the cargo is adjusted according to the matching decision value.

[0028] It should be noted that the number of standardized goods of the target merchant within the preset time period, the standardized goods of the target merchant are the target merchant's commonly sold goods, and the number of commonly sold goods sold within the preset time period, such as in the past 30 days, is obtained; the number of customized goods of the target merchant within the preset time period, the customized goods of the target merchant are the sold goods that require specific temperature control, special packaging or special labels, and the number of customized goods sold within the preset time period, such as in the past 30 days, is obtained; the number of fixed codes for goods is the number of coding entries for immutable attribute data, such as the SKU code and batch number of the product, and the number of fixed codes for goods is two; the number of sub-codes for goods is the number of coding entries for variable attribute data, such as the weight, storage conditions and packaging size of the goods, and the number of sub-codes for goods is three.

[0029] The matching decision formula is: ; In the formula, is the matching decision value; Subcode quantity for the goods; Fixed coding quantity for goods; The quantity of customized goods for the target merchant within a preset time period; It is the standardized quantity of goods of the target merchant within the preset time period; Score the real-time network quality of edge devices; Score standard network quality for edge devices; , , is the weight adjustment factor.

[0030] It should be noted that the signal strength, link quality index, transmission rate, packet loss rate and retransmission rate in the edge computing device are obtained, and the weighted sum is calculated after scoring respectively to obtain the real-time network quality score of the edge device; Much greater than When , it means that the target merchant's goods attributes have great variability and require a more accurate matching algorithm; when Much greater than This indicates that the target merchant mainly deals with customized goods during the preset time period. Customized goods have stronger inaccuracy and require a more precise matching algorithm.

[0031] When the matching decision value is greater than or equal to the first preset threshold, the central device is used to intelligently match the goods; when the matching decision value is less than the first preset threshold, the edge device is used to intelligently match the goods.

[0032] It should be noted that when the matching decision value is greater than or equal to the first preset threshold, the central device is used to intelligently match the goods. The central device usually has stronger computing power and is suitable for complex matching scenarios, such as goods matching tasks that require accurate comparison of multiple data sources, and matching processing tasks for more refined customized goods; when the matching decision value is less than the first preset threshold, the edge device is used to intelligently match the goods. Since a low matching decision value means that the goods matching process is simple, or is subject to the network environment, it is suitable to use the nearest edge device to complete the matching task to reduce computing delays and consumption of central device resources.

[0033] Use edge devices to match the fixed coding data of the goods. When the fixed coding data matches the goods successfully, match the goods sub-coding data of the goods, and actually record the changes in the goods sub-coding data during the transportation of the goods.

[0034] Example 2: Based on Example 1, an intelligent matching system for receiving goods in logistics, such as Figure 2 As shown, including: A data collection module is used to obtain cargo-related data of target cargo and historical cargo data of customers; A change calculation module, used for inputting the cargo related data into a change calculation formula to obtain a maximum change value of the mass of the cargo sub-code data; An intelligent matching module, used for intelligently matching goods according to the fixed code data of the target goods, the sub-code data of the goods and the maximum change value of the quality of the sub-code data of the goods; A decision value acquisition module is used to obtain the customer's historical cargo data and obtain the matching decision value using the matching decision formula; A decision adjustment module, used to adjust the intelligent matching position of the goods according to the matching decision value; The alarm and exception handling module is used to trigger alarms in time for abnormal situations that occur during the matching process.

[0035] While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions.

Claims

1. A method for intelligently matching incoming orders for logistics receipt, characterized in that: The following steps are involved: S1: Obtain cargo-related data of the target cargo, wherein the cargo-related data includes cargo transportation stacking data, cargo delivery coding data, and cold chain interruption data, and simultaneously obtain cargo-related data of the target cargo, and use a variation calculation formula to obtain a maximum mass variation value of the cargo sub-coding data; S2: Intelligently match the goods according to the maximum quality change value of the target goods’ shipping code data and the goods’ sub-code data; S3: Obtain the customer's historical cargo data, use the matching decision formula to obtain a matching decision value, and adjust the intelligent matching position of the cargo according to the matching decision value.

2. According to the method for intelligent matching of inbound orders for logistics receipt according to claim 1, it is characterized in that: The method of obtaining cargo-related data of the target cargo, wherein the cargo-related data includes cargo transportation stacking data, cargo shipment coding data and cold chain interruption data, and simultaneously obtaining the cargo-related data of the target cargo, and using a change calculation formula to obtain the maximum mass change value of the cargo sub-coding data, includes: inputting the cargo-related data into the change calculation formula to obtain the maximum mass change value of the cargo sub-coding data, wherein the cargo shipment coding data includes cargo fixed coding data and cargo sub-coding data, and the cargo fixed coding data is the immutable attribute data of the cargo; the cargo sub-coding data is the variable attribute data of the cargo; the cargo transportation stacking data includes the weight of the cargo stacked above the target cargo and the existence duration of the cargo stacked above the target cargo; and the cold chain interruption data includes the duration of the cold chain interruption and the number of cold chain interruptions.

3. According to the method for intelligent matching of inbound orders for logistics receipt as claimed in claim 2, it is characterized in that: The cargo sub-coding data is the variable attribute data of the cargo, including: the cargo sub-coding data includes the initial cargo mass, cargo customized graphic data and cargo customized structure data.

4. According to the method for intelligent matching of inbound orders for logistics receipt as claimed in claim 2, it is characterized in that: The inputting of the cargo related data into the change calculation formula to obtain the maximum change value of the quality of the cargo sub-code data includes: pre-processing the cargo related data by cleaning, normalizing, noise filtering and filling missing values, and then inputting the data into the change calculation formula to obtain the maximum change value of the quality of the cargo sub-code data, wherein the change calculation formula is: ； In the formula, The maximum change value of the quality of the cargo sub-code data; For the The duration of the stacked cargo on top of the secondary target cargo; For the The weight of the cargo stacked above the secondary target cargo; For the Duration of the cold chain interruption; , is the corresponding weight adjustment factor; The initial cargo mass in the cargo sub-coding data; is the maximum allowable mass change value.

5. According to the method for intelligent matching of inbound orders for logistics receipt as claimed in claim 1, it is characterized in that: The intelligent matching of goods according to the maximum quality change value of the shipping coding data and the goods sub-coding data of the target goods includes: when there is an inconsistency between the target goods and the fixed coding data of the goods, an alarm is issued; when the target goods and the fixed coding data of the goods are consistent and there is an inconsistency between the target goods and the sub-coding data of the goods, the maximum quality change value of the target goods is obtained and a judgment is made according to the actual quality of the target goods, when the absolute difference between the actual quality of the target goods and the initial quality of the goods in the goods sub-coding data is less than or equal to the maximum quality change value, the target goods are successfully matched; when the absolute difference between the actual quality of the target goods and the initial quality of the goods in the goods sub-coding data is greater than the maximum quality change value, an alarm is issued.

6. According to the method of intelligent matching of inbound orders for logistics receipt according to claim 1, it is characterized in that: The method of obtaining the historical cargo data of the customer, using the matching decision formula to obtain the matching decision value, and adjusting the intelligent matching position of the cargo according to the matching decision value includes: obtaining the historical cargo data of the customer, the historical cargo data including the number of standardized cargoes of the target merchant within a preset time period, the number of customized cargoes of the target merchant within a preset time period, the number of fixed codes of cargoes, and the number of sub-codes of cargoes, wherein the number of fixed codes of cargoes is the number of coding entries of immutable attribute data; the number of sub-codes of cargoes is the number of coding entries of variable attribute data; inputting the historical cargo data into the matching decision formula to obtain the matching decision value, and adjusting the intelligent matching position of the cargo according to the matching decision value.

7. According to the method for intelligent matching of inbound orders for logistics receipt according to claim 6, it is characterized in that: The step of inputting the historical cargo data into a matching decision formula to obtain a matching decision value includes: wherein the matching decision formula is: ； In the formula, is the matching decision value; Subcode quantity for the goods; Fixed coding quantity for goods; The quantity of customized goods for the target merchant within a preset time period; It is the standardized quantity of goods of the target merchant within the preset time period; Real-time network quality scoring for edge devices; Score standard network quality for edge devices; , , is the weight adjustment factor.

8. According to the method for intelligent matching of inbound orders for logistics receipt according to claim 7, it is characterized in that: The historical cargo data is input into a matching decision formula to obtain a matching decision value, and the intelligent matching position of the cargo is adjusted according to the matching decision value, including: when the matching decision value is greater than or equal to a first preset threshold, the central device is used to perform intelligent matching on the cargo; when the matching decision value is less than the first preset threshold, the edge device is used to perform intelligent matching on the cargo.

9. According to the method of intelligent matching of inbound orders for logistics receipt as claimed in claim 8, it is characterized in that: When the matching decision value is less than a first preset threshold, the edge device is used to intelligently match the goods, including: using the edge device to match the fixed coding data of the goods, and when the fixed coding data matches the goods successfully, matching the goods sub-coding data of the goods, and actually recording the changes in the goods sub-coding data during the transportation of the goods.

10. An intelligent matching system for inbound orders for logistics receipt, according to an intelligent matching method for inbound orders for logistics receipt as claimed in any one of claims 1 to 9, characterized in that: include: A data collection module is used to obtain cargo-related data of target cargo and historical cargo data of customers; A change calculation module, used for inputting the cargo related data into a change calculation formula to obtain a maximum change value of the mass of the cargo sub-code data; An intelligent matching module, used for intelligently matching goods according to the fixed code data of the target goods, the sub-code data of the goods and the maximum change value of the quality of the sub-code data of the goods; A decision value acquisition module is used to obtain the customer's historical cargo data and obtain the matching decision value using the matching decision formula; A decision adjustment module, used to adjust the intelligent matching position of the goods according to the matching decision value; The alarm and exception handling module is used to trigger alarms in time for abnormal situations that occur during the matching process.

Images