Logistics warehouse cargo identification and classification method and system
By verifying cargo lists, developing cargo classification models, and correcting classifications, the problem of inaccurate cargo classification in existing technologies has been solved, enabling efficient, accurate classification and quality assurance in logistics warehousing.
Patent Information
- Application Number
- CN202511701665.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-19
- Publication Date
- 2026-02-24
AI Technical Summary
Existing technologies cannot detect goods with quality abnormalities in a timely manner, nor can they conduct a comprehensive analysis of all goods, leading to incorrect classification of goods, posing storage quality risks, and preventing accurate classification.
By verifying the goods list, building a goods classification model, analyzing the classification results and assessing their accuracy, implementing classification corrections, and combining early warning prompts, we ensure the accuracy of the status verification and classification results of goods before they enter the warehouse.
It enables efficient identification and correct classification of goods, reduces the probability of backlog, ensures warehousing quality, reduces the impact of disputes, and ensures smooth warehousing and delivery of goods.
Smart Images
Figure CN121563402A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of logistics and warehousing technology, specifically to a method and system for identifying and classifying goods in logistics and warehousing. Background Technology
[0002] As e-commerce gradually becomes a new trend in the current development industry, the types and quantities of goods handled by its logistics warehousing are also increasing. Therefore, a method and system for identifying and classifying goods in logistics warehousing is proposed to achieve efficient identification and classification of goods, ensure the efficient operation of the goods logistics chain, and effectively avoid the backlog of goods, which could lead to damage or supply disputes.
[0003] Existing technology, such as the invention patent application CN118468089B, discloses a method and system for identifying and classifying goods in logistics warehousing. The method includes: collecting distance data of target goods and goods retrieval and placement data of target shelves; calculating the degree of location anomaly of the target goods and the degree of storage and retrieval disorder of the target shelves based on the distance data and the storage and retrieval data; calculating the necessity of inspecting the target goods based on the degree of storage and retrieval disorder of the target shelves, the degree of location anomaly of the target goods, and the number of days between the current day and the last inspection; determining the goods to be inspected based on the inspection necessity; and classifying the goods to be inspected based on the identification results of the storage location information of the goods to be inspected. This invention improves the overall operation of the warehouse.
[0004] The above solution has the following technical problems: Currently, the classification of goods mainly focuses on analyzing the chaotic storage and retrieval of target goods from target shelves. However, during logistics warehousing, it cannot be guaranteed that the goods entering the current logistics warehouse belong to the first time period's logistics warehouse. If the status verification of goods before warehousing classification is not performed, goods with quality abnormalities cannot be detected in a timely manner. Furthermore, the analysis of all goods is not comprehensive, resulting in a single-subject analysis of target goods, which cannot guarantee that all goods will be correctly classified. This leads to insufficient generalization of goods classification and potential warehousing quality risks. It also fails to perform timely classification corrections for incorrectly classified goods, and cannot fully and effectively guarantee the accurate classification of goods in logistics warehousing. Summary of the Invention
[0005] To address the aforementioned technical shortcomings, the present invention aims to provide a method and system for identifying and classifying goods in logistics warehousing.
[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The present invention provides a method for identifying and classifying logistics warehouse goods, including: Step 1, goods list verification: By verifying the goods arriving at the logistics warehouse, the basic status of the goods is confirmed.
[0007] Step 2, Goods Identification and Classification: When the basic status of the goods is qualified, a goods classification model for the goods stored in the logistics warehouse is constructed, and the classification results of the goods stored in the logistics warehouse are analyzed.
[0008] Step 3: Goods Identification and Classification Analysis: Obtain the actual data of the goods stored in the logistics warehouse after classification, and then evaluate the correctness of the classification results. If the classification results are incorrect, the classification of the goods stored in the logistics warehouse will be corrected, and the correction will be verified.
[0009] Step 4: Early Warning: An early warning will be issued when the basic status of the goods before they enter the warehouse is abnormal or when the classification of the goods stored in the logistics warehouse is incorrect.
[0010] In a second aspect, the present invention provides a logistics warehousing cargo identification and classification system, comprising: a cargo manifest verification module, used to verify the manifest of goods arriving at the logistics warehouse and confirm the basic state of the goods before they enter the warehouse.
[0011] The cargo identification and classification module is used to construct a cargo classification model for the corresponding stored cargo in the logistics warehouse when the basic status of the cargo before it enters the warehouse is qualified, and to analyze the classification results of the corresponding stored cargo in the logistics warehouse.
[0012] The cargo identification and classification analysis module is used to obtain the actual data of the cargo stored in the logistics warehouse after classification, and then to evaluate the correctness of the classification results. If the classification result of the cargo stored in the logistics warehouse is incorrect, the classification correction will be performed on the cargo stored in the logistics warehouse, and the classification correction will be checked.
[0013] The early warning terminal is used to issue early warnings when the basic status of goods before they are put into the warehouse is abnormal or when the classification of goods stored in the logistics warehouse is incorrect.
[0014] The beneficial effects of this invention are as follows: 1. This invention provides a method and system for identifying and classifying goods in logistics warehousing. By verifying the goods through a list, the status of the goods is confirmed. Then, the goods are classified according to the logistics warehousing, and the actual data of the classified goods in the logistics warehouse is obtained. The correctness of the classification results of the goods in the logistics warehouse is evaluated, and the classification of the goods in the logistics warehouse is corrected. This achieves effective identification and classification of goods in logistics warehousing, avoids the inefficient congestion effect caused by manual identification and classification, reduces the probability of goods backlog, effectively ensures the quality of goods storage, reduces the impact of disputes caused by goods quality problems, and realizes intelligent and efficient logistics warehousing classification of goods.
[0015] 2. By verifying the list of goods arriving at the logistics warehouse, the basic status of the goods is confirmed, and the overall quality of the goods is intelligently guaranteed, providing effective process assurance for the smooth entry of goods into the warehouse and delivery to users.
[0016] 3. Construct a goods classification model for the goods stored in the logistics warehouse, and analyze the classification results of the goods stored in the logistics warehouse to realize intelligent goods logistics warehousing identification and classification based on the model, so that the goods can be correctly classified.
[0017] 4. Obtain the actual data of the goods stored in the logistics warehouse after classification, then evaluate the correctness of the classification results, correct the classification of the goods stored in the logistics warehouse, and check the classification correction of the goods stored in the logistics warehouse. This enables timely correction of goods storage classification errors and effectively ensures the correctness of goods storage classification. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a schematic diagram of the implementation steps of the method of the present invention.
[0020] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation
[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0022] Please see Figure 1 As shown, a method for identifying and classifying goods in logistics warehousing includes: Step 1, goods list verification: By verifying the goods arriving at the logistics warehouse, the basic status of the goods is confirmed.
[0023] By verifying the list of goods arriving at the logistics warehouse, the basic status of the goods is confirmed, and the overall quality of the goods is intelligently guaranteed, providing effective process assurance for the smooth entry of goods into the warehouse and delivery to users.
[0024] In a specific instance, the confirmation process for obtaining the basic status of the goods is as follows: when the goods arrive at the logistics warehouse, the goods are tagged and basic data is obtained. At the same time, the performance data corresponding to the goods is obtained. The performance data corresponding to the goods is compared with the preset performance data thresholds. If all the data contained in the performance data corresponding to the goods are less than or equal to the preset performance data thresholds, the basic status of the goods is determined to be qualified.
[0025] If one or more data points in the performance data of the goods exceed the preset performance data threshold, the basic status of the goods is determined to be abnormal, and feedback on the abnormal status of the goods is communicated with the supplier to verify the basic status of the goods.
[0026] It should be noted that the performance data includes appearance data and cargo requirement condition data. Appearance data includes damaged and stained surfaces of cargo packaging. Based on machine vision automatic detection in the logistics warehouse, the actual appearance image of the cargo is obtained, and the actual appearance is compared with the standard appearance stored in the database to automatically detect the appearance data of the cargo. The comparison between the actual appearance and the standard appearance is performed automatically by machine vision detection after obtaining the actual appearance image of the cargo. Cargo requirement condition data includes temperature and the cushioning force of the cargo packaging. The temperature of the cargo is obtained using a temperature and humidity detector, and the thickness of the cargo packaging is monitored. The thickness of the cargo packaging reflects the cushioning force of the cargo. Professional logistics managers set reference performance data thresholds. The reference performance data thresholds are used to more intuitively verify the basic condition of the cargo, reduce the probability of incomplete cargo, and ensure the quality of cargo entering the warehouse.
[0027] It should be noted that labeling goods involves scanning and recording the corresponding barcode, QR code, or RFID tag on the goods. The goods already have complete labeling before entering the warehouse.
[0028] Step 2, Goods Identification and Classification: When the basic status of the goods is qualified, a goods classification model for the goods stored in the logistics warehouse is constructed, and the classification results of the goods stored in the logistics warehouse are analyzed.
[0029] A goods classification model is constructed for the goods stored in the logistics warehouse, and the classification results are analyzed to achieve intelligent goods logistics warehousing identification and classification based on the model, so that the goods can be correctly classified.
[0030] In a specific example, the construction process of the commodity classification model corresponding to the stored goods in the logistics warehouse is as follows: Based on the basic data corresponding to the goods, select historical goods that are the same as the current goods, extract historical sudden risk data from the database, and use the historical sudden risk data corresponding to the historical goods as the risk prevention data to be paid attention to for the current goods.
[0031] By standardizing the basic data and historical emergency risk data corresponding to the goods, standardized basic data and historical emergency risk data are obtained. The standardized basic data is used to build a model to obtain the initial level model corresponding to the goods. Then, the standardized historical emergency risk data is input into the initial level model to build a goods classification model for the goods stored in the logistics warehouse.
[0032] It should be noted that the basic data and historical emergency risk data corresponding to the goods are standardized to remove fuzzy and poorly labeled data. Then, the standardized data is substituted into a lightweight model, and redundant neurons and convolutional kernels are removed. Finally, the model is converted to a model supported by edge architecture devices. The construction process for the other models in this paper is the same, so it will not be elaborated further here. Removing redundant neurons and convolutional kernels reduces the computational cost of parameters. Using historical emergency risk data corresponding to historical goods as the focus of current risk prevention is to make the current model more complete, enabling proactive risk construction and prevention based on known risks, thus avoiding risk oversights.
[0033] In a specific example, the mapping between basic data and risk prevention data for analyzed goods is analyzed as follows: Basic data includes goods category data, goods placement requirement data, and goods special requirement data. The goods placement requirement data and goods special requirement data are decomposed into indicator data to obtain the corresponding placement focus indicators and special focus indicators for the goods. According to the current goods category, the specific performance of the same category of goods in the past when sudden risk situations occurred is obtained. By tracing the causes of the sudden risks of the corresponding goods in the past, if it is found that the cause of the sudden risks of the corresponding goods in the past was that the placement focus indicators or special focus indicators did not meet the standards in logistics warehousing or the indicator fluctuations exceeded the safety threshold of the goods, it indicates that the sudden risks of the goods are related to the placement requirements and special requirements of the goods, thus obtaining the mapping relationship between the two.
[0034] It should be noted that by analyzing the relationship between sudden risks to goods and their own conditions, we can gain a clearer understanding of the reasons for changes in goods, thereby enabling more targeted risk prevention. Based on the extraction of key and special requirements for goods placement, and by tracing the causes of sudden risks, we can obtain the specific reasons leading to the risks. This reveals the mapping relationship between the data of the two types of goods. For example, if the required temperature for goods in logistics warehousing is 0 to 4 degrees Celsius, with temperature fluctuations less than or equal to 1 degree Celsius, and the sudden risk of similar goods in logistics warehousing in the past was food spoilage, we can retrieve historical data on the current conditions of the goods. If the required temperature for the goods at that time was 5 degrees Celsius, with temperature fluctuations greater than 1 degree Celsius, and all other conditions were normal, then the cause of the sudden risk was determined to be the failure to meet the key or special requirements for placement. The placement requirements and special requirements of the goods affect the occurrence of sudden risks, thus obtaining the corresponding relationship mapping. Based on understanding the relationship mapping between goods data, we can construct a data-complete model to perform corresponding goods classification.
[0035] It should be noted that the goods category data refers to the specific types of goods, such as electronics, household goods, and fresh produce; the goods placement requirements data refers to the basic placement methods required for the goods during storage, transportation, and placement, such as frozen fresh produce requiring freezing, while fresh food requires refrigeration; and the goods special requirements data refers to the precautions that need to be taken for the goods, such as porcelain requiring attention to force and fresh produce requiring attention to temperature and humidity.
[0036] In a specific example, the analysis yields the classification results of the goods stored in the logistics warehouse. The specific classification process is as follows: the goods are divided into categories according to the goods category data, and different types of goods are named according to the category name to obtain the category sets corresponding to the goods. Secondly, based on the goods placement requirement data corresponding to the goods, a secondary subdivision is performed under each category set to extract the demand characteristics under the goods placement requirement data. When two goods have the same demand characteristics, they are classified into the same category. This subdivision is used to obtain the demand classification under each category set corresponding to the goods. Finally, the basic characteristics of the special requirements data of the goods are extracted, and the emphasis direction under the goods classification is executed. This analysis yields the classification results of the goods stored in the logistics warehouse.
[0037] It should be noted that if the goods are electronic products, they are categorized as digital products; if the goods are food, they are categorized as fresh produce. This yields a set of categories. When the demand characteristics of a certain ice cream product and a certain meat product are both found to be frozen, these two products are labeled as frozen products. Since the basic characteristic of the special requirements for frozen products is short-term storage, the focus is on not being able to store them immediately. Therefore, they are classified as priority delivery or urgent delivery. This analysis yields the classification results of the goods stored in the logistics warehouse.
[0038] Step 3: Goods Identification and Classification Analysis: Obtain the actual data of the goods stored in the logistics warehouse after classification, and then evaluate the correctness of the classification results. If the classification results are incorrect, the classification of the goods stored in the logistics warehouse will be corrected, and the correction will be verified.
[0039] The system obtains actual data on the categorized goods stored in the logistics warehouse, assesses the accuracy of the categorization results, corrects the categorization of the goods, and verifies the corrections. This ensures timely correction of warehousing and classification errors and effectively guarantees the accuracy of warehousing and classification.
[0040] In a specific example, the accuracy assessment of the classification results of goods stored in the logistics warehouse is carried out as follows: The actual data of the classification of goods stored in the logistics warehouse is compared with the preset reference actual data threshold range for the goods. If any data in the actual data of the classification of goods stored in the logistics warehouse is not included in the reference actual data threshold range for the goods, the classification result of the goods stored in the logistics warehouse is determined to be incorrect. If all the actual data of the classification of goods stored in the logistics warehouse are included in the reference actual data threshold range for the goods, the classification result of the goods stored in the logistics warehouse is determined to be correct.
[0041] It should be noted that the actual data includes basic attribute data, management attribute data, and special constraint data. Basic attribute data is obtained from the goods list provided by the supplier, including physical morphology data and specifications. Management attribute data includes gravity and storage duration. The gravity of the goods is obtained using a digital pressure gauge, and the storage duration is calculated by obtaining the time difference between the goods' entry and classification time and the current time from the database. Special constraint data includes flammability and corrosiveness values. The environment in which the goods are placed in the logistics warehouse is monitored, including temperature and humidity. If the temperature and humidity of the environment exceed the acceptable temperature and humidity for the goods, the special constraint data for the goods is indirectly obtained based on the threshold exceeded by the environment.
[0042] It should be noted that the reference actual data threshold range for goods, preset by professional logistics managers, is used as a reference for more accurately judging whether the classification of goods stored in the logistics warehouse is correct.
[0043] In a specific example, the analysis yields the classification correction of the goods stored in the logistics warehouse. The specific analysis process is as follows: extract reference data when the classification result of the goods stored in the logistics warehouse is incorrect, use the reference data as the adjustment reference data item for the incorrect classification of goods, and correct the classification of all the incorrectly classified goods in the logistics warehouse according to the corresponding reference item.
[0044] It should be noted that, for example, if the data for goods entered is for solids, but when classifying foggy weather as liquid, the classification will be re-corrected and reclassified according to the data of the corresponding entry reference specifications.
[0045] In a specific example, the verification process for the classification correction of goods stored in the logistics warehouse is as follows: Based on the classification display after the classification correction of goods stored in the logistics warehouse, the classification set items of the goods stored in the logistics warehouse after classification correction are compared with the preset standard classification set items corresponding to the goods. When the classification set items of the goods stored in the logistics warehouse after classification correction are consistent with the preset standard classification set items corresponding to the goods, it indicates that the classification correction of goods stored in the logistics warehouse has been correctly completed. The classification correction of goods stored in the logistics warehouse is verified in this way.
[0046] It should be noted that standard classification and attribution sets are set by professional logistics managers. These standard classification and attribution sets are used as reference items to determine whether the classification correction performed on the corresponding stored goods in the current logistics warehouse has been completed correctly, thus ensuring that the goods are correctly classified.
[0047] Step 4: Early Warning: An early warning will be issued when the basic status of the goods before they enter the warehouse is abnormal or when the classification of the goods stored in the logistics warehouse is incorrect.
[0048] Please see Figure 2 As shown, a logistics warehousing cargo identification and classification system includes a cargo list verification module, a cargo identification and classification module, a cargo identification and classification analysis module, an early warning terminal, and a database.
[0049] The cargo list verification module is connected to the cargo identification and classification module, the database, and the early warning terminal, respectively. The cargo identification and classification module is connected to the cargo identification and classification analysis module and the database, respectively. The cargo identification and classification analysis module is connected to the early warning terminal and the database, respectively.
[0050] The Goods List Verification Module is used to verify the goods arriving at the logistics warehouse and confirm the basic status of the goods before they enter the warehouse.
[0051] The cargo identification and classification module is used to construct a cargo classification model for the corresponding stored cargo in the logistics warehouse when the basic status of the cargo before it enters the warehouse is qualified, and to analyze the classification results of the corresponding stored cargo in the logistics warehouse.
[0052] The cargo identification and classification analysis module is used to obtain the actual data of the cargo stored in the logistics warehouse after classification, and then to evaluate the correctness of the classification results. If the classification result of the cargo stored in the logistics warehouse is incorrect, the classification correction will be performed on the cargo stored in the logistics warehouse, and the classification correction will be checked.
[0053] The early warning terminal is used to issue early warnings when the basic status of goods before they are put into the warehouse is abnormal or when the classification of goods stored in the logistics warehouse is incorrect.
[0054] The database is used to store basic data, performance data, historical data on sudden risks corresponding to historical goods, and actual data.
[0055] The examples described in this invention are not limited to the specific embodiments listed above. The examples are merely illustrative to facilitate understanding of the invention and do not constitute a limitation on the scope of protection of this invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of this invention should be included within the scope of protection.
[0056] This invention, through a list verification process, confirms the status of the goods. Next, the goods are categorized according to their corresponding logistics and warehousing needs. The actual data of the categorized goods in the logistics warehouse is obtained, and the accuracy of the categorization results is evaluated and corrected. This achieves effective identification and categorization of goods in logistics and warehousing, avoiding the inefficiency and congestion caused by manual identification and classification, reducing the probability of goods backlog, effectively ensuring the quality of goods storage, reducing disputes caused by goods quality issues, and realizing intelligent and efficient logistics and warehousing classification.
[0057] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.
Claims
1. A method for identifying and classifying goods in logistics warehousing, characterized in that, Includes the following steps: Step 1: Goods list verification: Verify the goods list upon arrival at the logistics warehouse to confirm the basic status of the goods. Step 2, Goods Identification and Classification: When the basic status of the goods is qualified, a goods classification model for the goods stored in the logistics warehouse is constructed, and the classification results of the goods stored in the logistics warehouse are analyzed. Step 3: Goods identification and classification analysis: Obtain the actual data of the goods stored in the logistics warehouse after classification, and then evaluate the correctness of the classification results of the goods stored in the logistics warehouse. If the classification results of the goods stored in the logistics warehouse are incorrect, the classification of the goods stored in the logistics warehouse will be corrected, and the classification correction of the goods stored in the logistics warehouse will be checked. Step 4: Early Warning: An early warning will be issued when the basic status of the goods before they enter the warehouse is abnormal or when the classification of the goods stored in the logistics warehouse is incorrect.
2. The method for identifying and classifying goods in logistics warehousing according to claim 1, characterized in that, The confirmation process obtains the basic status of the goods, and the specific confirmation process is as follows: When goods arrive at the logistics warehouse, they are tagged and their basic data is obtained. At the same time, the corresponding performance data of the goods is obtained. The corresponding performance data of the goods is compared with the preset performance data thresholds. If all the data contained in the corresponding performance data of the goods are less than or equal to the preset performance data thresholds, the basic status of the goods is determined to be qualified. If one or more data points in the performance data of the goods exceed the preset performance data threshold, the basic status of the goods is determined to be abnormal, and feedback on the abnormal status of the goods is communicated with the supplier to verify the basic status of the goods.
3. The method for identifying and classifying logistics and warehousing goods according to claim 2, characterized in that, The specific construction process for the product classification model corresponding to the stored goods in the logistics warehouse is as follows: Based on the basic data corresponding to the goods, select historical goods that are the same as the current goods, extract historical sudden risk data from the database, and use the historical sudden risk data corresponding to the historical goods as the risk prevention data to be paid attention to for the current goods. By standardizing the basic data and historical emergency risk data corresponding to the goods, standardized basic data and historical emergency risk data are obtained. The standardized basic data is used to build a model to obtain the initial level model corresponding to the goods. Then, the standardized historical emergency risk data is input into the initial level model to build a goods classification model for the goods stored in the logistics warehouse.
4. The method for identifying and classifying goods in logistics warehousing according to claim 3, characterized in that, The analysis process involves the mapping between basic data and risk prevention data for the analyzed goods, and is as follows: The basic data includes cargo category data, cargo placement requirement data, and cargo special requirement data. The cargo placement requirement data and cargo special requirement data are decomposed into index data to obtain the corresponding placement focus index and special focus index for each cargo. Based on the current cargo category, the specific performance of the same cargo category in the past when sudden risks occurred is obtained. By tracing the causes of the sudden risks of the corresponding cargo in the past, if it is found that the cause of the sudden risks of the corresponding cargo in the past was that the placement focus index or special focus index did not meet the standards in the logistics warehousing or the index fluctuation exceeded the cargo safety threshold, it indicates that the sudden risks of the cargo are related to the cargo placement requirements and special requirements, thus obtaining the relationship mapping between the two.
5. The method for identifying and classifying goods in logistics warehousing according to claim 4, characterized in that, The analysis yielded the classification results of the goods stored in the logistics warehouse. The specific classification process is as follows: The goods are categorized according to their product type data, and different types of goods are named according to their category names to obtain the corresponding category sets. Next, based on the corresponding goods placement requirements data, a secondary subdivision is performed under each category set to extract the demand characteristics of the goods under the corresponding goods placement requirements data. When two goods have the same demand characteristics, they are classified into the same category. This subdivision is used to obtain the demand classification of each category set of goods. Finally, the basic characteristics of the special requirements data of goods are extracted, and the focus direction of the corresponding goods classification is applied. This analysis yields the classification results of the goods stored in the logistics warehouse.
6. The method for identifying and classifying goods in logistics warehousing according to claim 5, characterized in that, The accuracy of the classification results of the goods stored in the logistics warehouse is evaluated, and the specific evaluation process is as follows: The actual data for classifying the goods stored in the logistics warehouse is compared with the preset reference actual data threshold range for the goods. If any data in the actual data for classifying the goods stored in the logistics warehouse is not included in the reference actual data threshold range for the goods, the classification result of the goods stored in the logistics warehouse is determined to be incorrect. If all the actual data for classifying the goods stored in the logistics warehouse are included in the reference actual data threshold range for the goods, the classification result of the goods stored in the logistics warehouse is determined to be correct.
7. The method for identifying and classifying goods in logistics warehousing according to claim 6, characterized in that, The specific analysis process for classifying and correcting the stored goods corresponding to the logistics warehouse is as follows: The reference data for incorrectly categorized goods in the logistics warehouse is extracted and used as an adjustment reference data item for incorrectly categorized goods. All incorrectly categorized goods in the logistics warehouse are then corrected according to the corresponding reference item.
8. The method for identifying and classifying goods in logistics warehousing according to claim 7, characterized in that, The inspection process for classifying and correcting the goods stored in the logistics warehouse is as follows: Based on the classification display after the goods stored in the logistics warehouse are corrected, the classification set of items corresponding to the goods stored in the logistics warehouse after the classification correction is compared with the preset standard classification set of items corresponding to the goods. When the classification set of items corresponding to the goods stored in the logistics warehouse after the classification correction is consistent with the preset standard classification set of items corresponding to the goods, it indicates that the classification correction of the goods stored in the logistics warehouse has been completed correctly. The classification correction of the goods stored in the logistics warehouse is verified in this way.
9. A logistics warehousing cargo identification and classification system utilizing the logistics warehousing cargo identification and classification method according to any one of claims 1-8, characterized in that, include: The Goods List Verification Module is used to verify the goods arriving at the logistics warehouse and confirm the basic status of the goods before they entered the warehouse. The cargo identification and classification module is used to construct a cargo classification model for the corresponding stored cargo in the logistics warehouse when the basic status of the cargo before entering the warehouse is qualified, and to analyze the classification results of the corresponding stored cargo in the logistics warehouse. The cargo identification and classification analysis module is used to obtain the actual data of the cargo stored in the logistics warehouse after classification, and then to evaluate the correctness of the classification results of the cargo stored in the logistics warehouse. If the classification results of the cargo stored in the logistics warehouse are incorrect, the classification correction of the cargo stored in the logistics warehouse will be performed and the classification correction of the cargo stored in the logistics warehouse will be checked. The early warning terminal is used to issue early warnings when the basic status of goods before they are put into the warehouse is abnormal or when the classification of goods stored in the logistics warehouse is incorrect.
10. A logistics warehousing cargo identification and classification system according to claim 9, characterized in that, It also includes a database, which stores basic data, performance data, historical data on sudden risks corresponding to historical goods, and actual data.