Warehouse management system

Abstract

The invention discloses a warehouse management system, and relates to the technical field of warehouse management. The warehouse management system comprises an intelligent inventory monitoring module, a central management module, an Internet of Things platform, a mobile client terminal and an automatic warehouse-in and warehouse-out management module, the central management module realizes real-time decoding based on an RFID technology, and decoding information after real-time decoding is transmitted to the intelligent inventory monitoring module through the Internet of Things platform. The intelligent inventory monitoring module completes checking of transmitted decoding information based on a monitoring result, and the automatic warehouse-in and warehouse-out management module completes intelligent comparison of adjacent frames of images based on the image intelligent analysis unit. According to the invention, through the inventory unit and the central management module, the central management module realizes real-time update response when materials are put in and out of a warehouse, manual intervention is reduced through the image intelligent analysis unit, and manual auditing is used as a final mode of real-time decoding times and put-out-of-warehouse quantity, so that the accuracy of put-in and put-out-of-warehouse statistics and update is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and specifically to a warehouse management system. Background Art

[0002] Warehouse management is to manage warehouses and the materials stored in the warehouses, and store and preserve goods through the warehouses. "Warehouse" also known as a storehouse, is a building or site for storing items, which can be a building, a large container, a cave or a specific site, etc., and has the function of storing and protecting items; "Storage" means storing for future use, with the meaning of storing, preserving and delivering for use, and is also called storage when applicable to tangible items. "Warehousing" is the act of using a warehouse to store and keep items that are not used in time. In short, warehousing is the act of storing items in a specific place.

[0003] In most warehouse management, data is collected and statistically sorted in the way of first recording on paper, then transferring documents, and finally manually inputting into the computer. This not only has low efficiency, but also causes a large amount of waste of human resources. During the statistical process, only the registration management of the incoming and outgoing of goods and the statistics of the quantity of goods are carried out, and the location of the goods is not statistically in real time. After a long time, the location of the goods will be messy, which brings difficulties in finding the goods. A large amount of manpower needs to be invested in standardizing the placement of items, regularly sorting and inventorying, and registering the incoming and outgoing of goods, etc., which increases the labor intensity of workers. In addition, the data information obtained statistically is generally stored locally or in the server, which is not only easy to be lost, but also easy to be leaked. Therefore, it is very necessary to design a logistics warehouse management system and method.

[0004] As disclosed in a logistics warehousing management system and method with Chinese invention publication number CN114715592B, this technical solution is provided with a conveyor belt capable of connecting the inside and outside of the warehouse to transport external goods into the warehouse. The system is provided with an item detection module capable of identifying the text labels of the goods on the conveyor belt, obtaining the information of the goods, and setting RFID tags corresponding to the goods information on the goods. The system is provided with a space allocation module capable of allocating the goods storage area according to the goods information. The system is provided with a path planning module capable of planning a route for the forklift according to the allocation of the goods storage area. The forklift moves the goods to the stereoscopic shelf along the planned route. The stereoscopic shelf is provided with multiple placement racks for placing goods. The bottom of the placement rack is provided with a pressure sensor capable of judging whether there are goods placed on the placement rack according to the pressure value of the pressure sensor. The top of the placement rack is provided with an RFID reader, and the RFID reader is directly opposite the RFID tag on the goods. The control module can control the RFID reader to collect the content of the RFID tag through the controller, thereby obtaining the goods number placed on the current placement rack, and then obtaining the goods information, which is convenient for subsequent searching for goods out of the warehouse. The system is provided with an information encryption module capable of encrypting the goods information and storing it in the blockchain through a third-party institution, which will not be lost and can ensure information security, improving the security.

[0005] To sum up, this technical solution completes the reading of labels or barcodes based on RFID technology, which is completed by exciting the tag with a radio frequency signal. To a large extent, it can quickly shorten the inspection efficiency of material warehousing and out-of-warehouse, but the reading result is difficult to be fed back to the warehousing system in real time and unified quickly. Then, during the process from the content collection of the RFID tag to the search for goods out of the warehouse, the instant control module cannot be displayed in real time on the terminal, and the quantity and type of in-and-out materials can only be determined by the reading result of RFID. Then, once an error occurs in the generation of the RFID tag, it is easy to cause the quantity and type of in-and-out materials to not match the statistical data, so it is difficult for the warehousing system to collect and update the goods information in real time, the degree of manual intervention increases, and the accuracy and efficiency of warehousing operations are also greatly reduced. Summary of the Invention

[0006] Aiming at the deficiencies of the prior art, the present invention provides a warehousing management system, which solves the problems put forward in the above background technology.

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions. A warehousing management system, the management system includes an intelligent inventory monitoring module, a central management module, an Internet of Things platform, a mobile client terminal, and an automated in-and-out warehouse management module; The central management module realizes real-time decoding based on RFID technology, and the decoded information after real-time decoding is transmitted by the Internet of Things platform to the intelligent inventory monitoring module. The intelligent inventory monitoring module completes the verification of the transmitted decoded information based on the monitoring results. The automated warehousing and outbound management module docks the decoded information to complete the outbound closed-loop; The automated warehousing and outbound management module completes the intelligent comparison of adjacent frame images based on the image intelligent analysis unit. Among them, the real-time monitoring screen of the image intelligent analysis unit is opened to the mobile client terminal through the Internet of Things platform. The characteristic parameters and inbound quantity of the inbound materials are obtained based on the intelligent comparison of adjacent frame images. The automated warehousing and outbound management module forms a product code containing time nodes based on the characteristic parameters of the inbound materials. The central management module obtains the product code of the inbound materials based on the Internet of Things platform, and the central management module forms a unique barcode based on the product code. The mobile client terminal obtains the unique barcode, product code and characteristic parameters of the inbound materials through the Internet of Things platform to complete the inbound closed-loop.

[0008] A further improvement of the technical solution of the present invention is that the image intelligent analysis unit includes a non-blind monitoring network formed by multiple groups of camera probes arranged in the inbound channel and the outbound channel. The monitoring network is transmission-connected to the Internet of Things platform, and the real-time monitoring screen is transmitted to the mobile client terminal based on the Internet of Things platform. The image intelligent analysis unit obtains the inbound quantity according to the number of contours of the focus difference in adjacent frame images; The Internet of Things platform includes an intelligent comparison database. The data source of the intelligent comparison database is the historical inbound image sample or the manually captured image sample. The image intelligent analysis unit completes the rotation amplification, random noise and gamma correction of the historical inbound image sample and the manually captured image sample, and extracts the characteristic parameters to form a characteristic parameter set.

[0009] Furthermore, the purpose of the image intelligent analysis unit to complete the rotation amplification based on the historical inbound image sample and the manually captured image sample is that during the inbound process of the inbound materials, there is handling and transmission, so there are significant differences in the placement positions. Then, during the rotation amplification of the historical inbound image sample and the manually captured image sample, they can be accurately matched with the inbound materials at different placement angles; Here, the rotation amplification step of the historical inbound image sample or the manually captured image sample in the intelligent comparison database based on the Faster-CNN algorithm of the present application is further disclosed: Based on the historical stored image samples or the file stream information of the manually captured image samples in the intelligent comparison database, according to the horizontal flipping function code of append_flipped_images in py-faster-rcnn / lib / datasets / imdb.py, the four coordinates in the boxes of each historical stored image sample or manually captured image sample are subjected to rotation transformation, and based on the _get_image_blob function in py-faster-rcnn / lib / datasets / imdb.py, a ±90° flip is performed on the image matrix.

[0010] The purpose of random noise is that during the image transmission process of the incoming materials monitored by the monitoring network, noise interference will inevitably occur. If the captured images are preprocessed, it will undoubtedly cause unnecessary computational burden. Based on this situation, random noise is implemented for the historical stored image samples and manually captured image samples to achieve the random noise effect of the monitoring network shooting. And this step can be completed before warehousing, avoiding unnecessary algorithmic burden on the automated warehousing and central management modules, and achieving real-time dynamic and rapid update of the inventory status; After eliminating the influence of noise and angle, there is also a certain influence of lighting during the shooting process. Therefore, gamma correction can detect the dark and light parts in the images in the database, increase the details of the dark parts of the images, and slightly improve the brightness details at the same time, enhancing the image contrast for easy matching with the captured images.

[0011] A further improvement of the technical solution of the present invention is that after the image intelligent analysis unit scales the adjacent frame images proportionally based on the Faster-CNN algorithm, candidate box extraction is performed, and corresponding feature parameters are extracted using CNN based on each group of candidate regions, and the obtained feature parameters are matched with the feature parameter set.

[0012] A further improvement of the technical solution of the present invention includes any one of the following two settings: The automated warehousing management module uses the successful matching of the feature parameters with the feature parameter set as the output signal to form a product code containing a time node and a unique identifier based on the feature parameters. After the internal warehousing handling system scans the product code, it is transported to the corresponding storage area according to the unique identifier; the product code containing the unique identifier indicates the major category of the incoming materials. In order to facilitate taking and easy counting, such materials are often placed in the same area; The automated warehousing management module uses the failure of feature parameter matching with the feature parameter set as the output signal, which is transmitted to the central management module through the Internet of Things platform. The central management module conducts manual review and intelligent comparison to align the data in the database. The lack of matching response between the feature parameters of the incoming materials and the existing feature parameter set indicates that the incoming materials are not among the historical materials in this warehouse. In terms of feature parameters, there are differences in length, width, height, shape features, surface texture features, weight, etc. compared with the historical feature parameters. Therefore, for the subsequent rapid warehousing of this type of materials and the real-time update of the central management module, after manual review, the feature parameters of this material should be recorded in the intelligent comparison database.

[0013] A further improvement of the technical solution of the present invention is that, furthermore, the central management module serves as the center of warehouse management. Therefore, the quantity and type of warehouse goods are stored in the central management module as inventory data and displayed on the mobile client terminal through the Internet of Things platform. Then, when the inventory data is too little or too much, the mobile client terminal should be enabled to quickly learn the warehouse quantity for the subsequent deployment of the enterprise. The central management module further includes an inventory unit. The inventory unit prepares an inventory table based on the unique barcode and product code of the incoming materials as the sorting serial number. As disclosed above, the product code is the major category, and the unique barcode is the sub-category under the major category. Since the unique barcode of each batch of incoming materials is different, corresponding alarm architectures should be set for the incoming materials with different product codes. Moreover, the list setting of product code - unique barcode enables the mobile client terminal to quickly and conveniently view the warehouse materials and the warehouse materials of each batch. The inventory table sets corresponding alarm thresholds based on the quantity of unique barcodes under different product codes, so that when the quantity of unique barcodes is less than the corresponding alarm threshold, it is displayed on the mobile client terminal through the Internet of Things platform.

[0014] A further improvement of the technical solution of the present invention is that the inventory unit uses the transmission times of the generated signal based on the product code and unique barcode as the increment of the quantity of the corresponding unique barcode in the inventory table. The inventory unit completes the operation of the deletion quantity of the corresponding unique barcode in the inventory table based on the real-time decoding times of the central management module.

[0015] A further improvement of the technical solution of the present invention is that for the data information contained in the product code disclosed in detail above, here, for the real-time decoding, the reading process of the unique barcode and the data information contained in the unique barcode and different from the product code during material outbound are disclosed. The real-time decoding is completed by the reader through the antenna to read the data and timing in the unique barcode. The data information different between the unique barcode and the product code is that the data includes feature parameters, unique identifiers of feature parameters, product codes, and freely defined codes, and the timing includes time nodes.

[0016] It can be seen that the free - defined code is randomly generated to classify the incoming materials of each batch under this commodity code category. During the outbound process, after the unique barcode of the incoming materials of each batch is read, the corresponding unique barcode in the inventory table is deleted according to its reading times and reading information, thus realizing the dynamic update of the inventory status, reducing manual intervention, significantly improving the accuracy and response speed of warehouse management, and reducing the operation cost. Furthermore, the automated inbound and outbound management module forms a commodity code containing time nodes based on the characteristic parameters of the incoming materials, and the real - time decoding to complete the reading of the time sequence in the unique barcode by the reader through the antenna all involves time. Then, in this process of time reading, it also means that the warehouse management system has completed the closed - loop of the material inbound and outbound time records, meeting the requirement of real - time update of the inventory table in the central management module.

[0017] A further improvement of the technical solution of the present invention is that the intelligent inventory monitoring completes the outbound monitoring operation based on the monitoring network, and obtains the outbound quantity based on the number of contours of the focus differences in adjacent outbound frame images. The output result of the outbound quantity is transmitted to the central management module through the Internet of Things platform.

[0018] A further improvement of the technical solution of the present invention is that when the outbound quantity does not match or matches the real - time decoding times, the central management module and the inventory unit also include any one of the following settings: The outbound quantity matches the real - time decoding times, and the inventory unit deletes the corresponding unique barcode in the inventory table according to the decoding information of the real - time decoding; The outbound quantity does not match the real - time decoding times. The central management module receives the non - matching result transmitted through the Internet of Things platform, and the central management module conducts manual review.

[0019] A further improvement of the technical solution of the present invention is that the mobile client terminal is connected to the central management module through the Internet of Things platform, and the mobile client terminal displays the inventory unit and the inventory table through a data dashboard.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: The inventory unit uses the transmission times of the generated signal based on the commodity code and the unique barcode as the increase amount of the corresponding unique barcode quantity in the inventory table. The inventory unit completes the operation of the deletion amount of the corresponding unique barcode in the inventory table based on the real - time decoding times of the central management module, enabling the central management module to achieve real - time update response during material inbound and outbound. And the image intelligent analysis unit obtains the inbound and outbound quantity based on the number of contours of the focus differences in adjacent frame images, and checks with the real - time decoding times and the outbound quantity, further avoiding statistical errors caused by incorrect generation of unique barcodes. While reducing manual intervention, manual review is used as the final guarantee after the failure of the match between the real - time decoding times and the outbound quantity, ensuring the accuracy of inbound and outbound statistics and updates.

[0021] With the central management module as the center of warehouse management, the quantity and types of warehouse goods are stored as inventory data in the central management module and displayed on the mobile client terminal through the Internet of Things platform. When the inventory data is too low or too high, the mobile client terminal can quickly learn the warehouse quantity, facilitating the subsequent allocation of the enterprise. In addition, an alarm architecture should be set for the incoming materials corresponding to different product codes, and the list setting of the product code - unique barcode enables the mobile client terminal to quickly and conveniently view the warehouse materials and the warehouse materials of each batch. By randomly generating free - defined codes, each batch of incoming materials under this product code category is classified. After the unique barcode of each batch of incoming materials is read during the outbound process, the corresponding unique barcode in the inventory table is deleted according to the reading times and reading information, thus realizing the dynamic update of the inventory status, reducing manual intervention, significantly improving the accuracy and response speed of warehouse management, and reducing the operation cost. Brief Description of the Drawings

[0022] Figure 1 It is a schematic diagram of related modules in this warehouse management system; Figure 2 It is a schematic diagram of the real - time update of material incoming and inventory units in this warehouse management system; Figure 3 It is a schematic diagram of the real - time update of material outbound and inventory units in this warehouse management system; Figure 4 It is a flow chart of material incoming in this warehouse management system; Figure 5 It is a flow chart of material outbound in this warehouse management system. Detailed Embodiments

[0023] Hereinafter, various exemplary embodiments, features, and aspects of the present application will be described in detail with reference to the drawings. The same reference numerals in the drawings denote elements with the same or similar functions. Although various aspects of the embodiments are shown in the drawings, the drawings do not have to be drawn to scale unless otherwise specified.

[0024] The special term "exemplary" here means "serving as an example, embodiment, or illustrative". Any embodiment described as "exemplary" here does not have to be construed as superior to or better than other embodiments.

[0025] In addition, to better illustrate the present application, numerous specific details are given in the following detailed embodiments. Those skilled in the art should understand that the present application can also be implemented without some specific details. In some instances, methods, means, and elements well - known to those skilled in the art are not described in detail to highlight the gist of the present application.

[0026] Embodiment 1. To solve the problem of real-time updating of inventory status and material in and out in a warehousing system, the present invention provides a warehousing management system, which includes an intelligent inventory monitoring module, a central management module, an Internet of Things platform, a mobile customer terminal, and an automated in and out management module; The central management module realizes real-time decoding based on RFID technology, and the decoded information after real-time decoding is transmitted by the Internet of Things platform to the intelligent inventory monitoring module. The intelligent inventory monitoring module completes the verification of the transmitted decoded information based on the monitoring results, and the automated in and out management module docks the decoded information to complete the outbound closed loop; The automated in and out management module completes the intelligent comparison of adjacent frame images based on the image intelligent analysis unit. Among them, the real-time monitoring screen of the image intelligent analysis unit is opened to the mobile customer terminal through the Internet of Things platform. Based on the intelligent comparison of adjacent frame images, the characteristic parameters and inbound quantity of the inbound materials are obtained. The automated in and out management module forms a product code containing time nodes based on the characteristic parameters of the inbound materials. The central management module obtains the product code of the inbound materials based on the Internet of Things platform, and the central management module forms a unique barcode based on the product code. The mobile customer terminal obtains the unique barcode, product code and characteristic parameters of the inbound materials through the Internet of Things platform to complete the inbound closed loop.

[0027] Embodiment 2. Based on the above disclosure, this application completes the real-time monitoring of material in and out based on the intelligent inventory monitoring module, and provides an extended solution related to the in and out quantity and inbound material identification for the central management module. The image intelligent analysis unit includes a non-blind monitoring network formed by multiple groups of camera probes arranged in the inbound channel and the outbound channel. The monitoring network is transmission-connected to the Internet of Things platform, and the real-time monitoring screen is transmitted to the mobile customer terminal based on the Internet of Things platform. The image intelligent analysis unit obtains the inbound quantity according to the number of contours of the focus difference in adjacent frame images; The Internet of Things platform includes an intelligent comparison database. The data source of the intelligent comparison database is historical inbound image samples or manually taken image samples. The image intelligent analysis unit completes the rotation amplification, random noise and gamma correction of the historical inbound image samples and manually taken image samples, and performs feature parameter extraction to form a feature parameter set.

[0028] Furthermore, the purpose of the image intelligent analysis unit to complete the rotation amplification based on the historical inbound image samples and manually taken image samples is that during the inbound process of the inbound materials, there is handling and transmission, so there are large differences in the placement positions. Then, during the rotation amplification of the historical inbound image samples and manually taken image samples, they can be accurately matched with the inbound materials at different placement angles; Here, it is further disclosed that this application rotates and amplifies the historical inbound image samples or manually taken image samples in the intelligent comparison database based on the Faster-CNN algorithm: Based on the historical warehoused image samples or the file stream information of the manually captured image samples in the intelligent comparison database, according to the horizontal flipping function code of append_flipped_images in py-faster-rcnn / lib / datasets / imdb.py, the four coordinates in the boxes of each historical warehoused image sample or manually captured image sample are rotated, and ±90° flipping is performed on the image matrix based on the _get_image_blob function in py-faster-rcnn / lib / datasets / imdb.py.

[0029] The purpose of random noise is that when monitoring the warehoused materials captured by the network, noise will inevitably be generated during the image transmission process. If the captured images are preprocessed, it will undoubtedly cause unnecessary computational burden. Based on this situation, random noise is implemented for the historical warehoused image samples and manually captured image samples to achieve the random noise effect of the monitoring network capture, and this step can be completed before warehousing, avoiding unnecessary algorithmic burden on the automated warehousing and outbound management module and the central management module, and achieving real-time dynamic and rapid update of the inventory status; After eliminating the influence of noise and angle, there is also a certain influence of light during the shooting process. Therefore, gamma correction can detect the dark and light parts in the images in the database, increase the details of the dark parts of the images, and slightly improve the brightness details at the same time, improving the image contrast for easy matching with the captured images.

[0030] After the image intelligent analysis unit completes the equal-proportion scaling of adjacent frame images based on the Faster-CNN algorithm, candidate box extraction is performed, and corresponding feature parameters are extracted using CNN based on each group of candidate regions, and the obtained feature parameters are matched with the feature parameter set.

[0031] A further aspect of the present invention is that it further includes any one of the following two settings: The automated warehousing and outbound management module uses the successful matching of the feature parameters with the feature parameter set as the output signal to form a product code containing the time node and a unique identifier based on the feature parameters. After the internal warehousing handling system scans the product code, it is transported to the corresponding storage area according to the unique identifier; the product code containing the unique identifier means the major category of the warehoused materials, and such materials are often placed in the same area for convenient retrieval and easy counting; The automated inbound and outbound management module uses the failure of feature parameter matching with the feature parameter set as the output signal, which is transmitted to the central management module through the Internet of Things platform. The central management module performs manual review and intelligent comparison to align the data in the database. The feature parameters of the incoming material do not match the existing feature parameter set, indicating that the incoming material is not available in the warehouse's historical materials. In terms of feature parameters, there are differences in length, width, height, shape features, surface texture features, weight, etc. compared with the historical feature parameters. Therefore, for the subsequent rapid inbound of this type of material and the real-time update of the central management module, after manual review, the feature parameters of this material should be recorded in the intelligent comparison database.

[0032] Embodiment 3. Further, in the present application, the central management module serves as the center of warehouse management. Therefore, the quantity and type of warehouse goods are stored in the central management module as inventory data and displayed on the mobile client terminal through the Internet of Things platform. Then, when the inventory data is too little or too much, the mobile client terminal should be able to quickly learn about the warehouse quantity to facilitate the subsequent allocation of the enterprise. The central management module also includes an inventory unit. The inventory unit prepares an inventory table based on the unique barcode and product code of the incoming material as the serial number. As disclosed above, the product code is the major category, and the unique barcode is the subcategory under the major category. The unique barcode of each batch of incoming materials is different. Therefore, an alarm structure should be set for the incoming materials with different product codes. Moreover, the list setting of product code - unique barcode enables the mobile client terminal to quickly and conveniently view the warehouse materials and the warehouse materials of each batch. The inventory table sets corresponding alarm thresholds based on the quantity of unique barcodes under different product codes, so that when the quantity of unique barcodes is less than the corresponding alarm threshold, it is displayed on the mobile client terminal through the Internet of Things platform.

[0033] The inventory unit uses the transmission times of the generated signal based on the product code and unique barcode as the increase amount of the corresponding unique barcode quantity in the inventory table. The inventory unit completes the calculation of the deletion amount of the corresponding unique barcode in the inventory table based on the real-time decoding times of the central management module.

[0034] Regarding the data information contained in the product code disclosed in detail above, here, for the real-time decoding during the outbound of materials, the reading process of the unique barcode and the data information contained in the unique barcode and different from the product code are disclosed. The real-time decoding is completed by the reader through the antenna to read the data and timing in the unique barcode. The data information different between the unique barcode and the product code is that the data includes feature parameters, unique identifiers of feature parameters, product codes, and freely defined codes, and the timing includes time nodes.

[0035] It can be seen that the free definition code is randomly generated to classify the incoming materials of each batch under this commodity code category. After the unique barcode of the incoming materials of each batch is read during the outbound process, the corresponding unique barcode in the inventory table is deleted according to the reading times and reading information, thus realizing the dynamic update of the inventory status, reducing manual intervention, significantly improving the accuracy and response speed of warehouse management, and reducing the operating cost. Furthermore, the automated inbound and outbound management module forms a commodity code containing time nodes based on the characteristic parameters of the incoming materials, and the real-time decoding to complete the reading of the time sequence in the unique barcode by the reader through the antenna all involves time. Then, in this process of time reading, it also means that the warehouse management system has completed the closed-loop of the material inbound and outbound time records, meeting the requirement of real-time update of the inventory table in the central management module.

[0036] Example 4: The intelligent inventory monitoring completes the outbound monitoring operation based on the monitoring network, and obtains the outbound quantity based on the number of contours of the focus differences in adjacent outbound frame images. The output result of the outbound quantity is transmitted to the central management module through the Internet of Things platform.

[0037] When the outbound quantity does not match or matches the real-time decoding times, the central management module and the inventory unit also include any of the following settings: The outbound quantity matches the real-time decoding times, and the inventory unit deletes the corresponding unique barcode in the inventory table according to the decoding information of the real-time decoding; The outbound quantity does not match the real-time decoding times, the central management module receives the mismatch result transmitted through the Internet of Things platform, and the central management module conducts manual review.

[0038] The mobile client terminal is connected to the central management module through the Internet of Things platform, and the mobile client terminal displays the inventory unit and the inventory table through the data dashboard.

[0039] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0040] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A warehouse management system, characterized in that: The management system includes an intelligent inventory monitoring module, a central management module, an Internet of Things platform, a mobile client terminal, and an automated in-and-out warehouse management module; The central management module implements real-time decoding based on RFID technology, and the decoded information after real-time decoding is transmitted to the intelligent inventory monitoring module by the Internet of Things platform. The intelligent inventory monitoring module completes the verification of the transmitted decoded information based on the monitoring results, and the automatic inbound and outbound management module connects with the decoded information to complete the outbound closed loop; The automated in-and-out warehouse management module completes the intelligent comparison of adjacent frame images based on the image intelligent analysis unit, wherein the real-time monitoring screen of the image intelligent analysis unit is opened to the mobile client terminal via the Internet of Things platform, and the characteristic parameters and the quantity of incoming materials are obtained based on the intelligent comparison of adjacent frame images. The automated in-and-out warehouse management module forms a commodity code containing a time node based on the characteristic parameters of the incoming materials, and the central management module obtains the commodity code of the incoming materials based on the Internet of Things platform, and the central management module forms a unique barcode based on the commodity code, and the mobile client terminal obtains the unique barcode, commodity code and characteristic parameters of the incoming materials through the Internet of Things platform to complete the warehousing closed loop.

2. A warehouse management system according to claim 1, characterized in that: The image intelligent analysis unit includes a monitoring network without blind spots formed by multiple groups of camera probes arranged in the storage channel and the storage channel. The monitoring network is connected to the Internet of Things platform, and the real-time monitoring screen is transmitted to the mobile client terminal based on the Internet of Things platform. The image intelligent analysis unit obtains the storage quantity according to the number of contours with focus differences in adjacent frame images; The Internet of Things platform includes an intelligent comparison database, the data source of which is historical stored image samples or manually shot image samples. The image intelligent analysis unit completes the rotation amplification, random noise and gamma correction of the historical stored image samples and the manually shot image samples, and extracts feature parameters to form a feature parameter set.

3. A warehouse management system according to claim 2, characterized in that: After the image intelligent analysis unit completes the proportional scaling of adjacent frame images based on the Faster-CNN algorithm, it extracts candidate frames, and uses CNN to extract corresponding feature parameters based on each group of candidate areas, and matches the acquired feature parameters with the feature parameter set.

4. A warehouse management system according to claim 3, characterized in that: Also includes either of the following two settings: The automated inbound and outbound management module uses the successful matching of the characteristic parameters with the characteristic parameter set as an output signal to form a commodity code containing a time node and a unique identifier based on the characteristic parameters. After the internal warehouse handling system scans the commodity code, it is transported to the corresponding storage area according to the unique identifier; The automated in-and-out warehouse management module uses the failure of matching the characteristic parameters with the characteristic parameter set as an output signal, which is transmitted to the central management module through the Internet of Things platform. The central management module performs manual review and intelligent comparison of database data alignment.

5. A warehouse management system according to claim 1, characterized in that: The central management module also includes an inventory unit, which prepares an inventory table based on the unique barcode and product code of the incoming material as an arrangement sequence number. The inventory table sets corresponding alarm thresholds based on the number of unique barcodes in each group under different product codes, so that when the number of unique barcodes is less than the corresponding alarm threshold, it is displayed on the mobile client terminal through the Internet of Things platform.

6. A warehouse management system according to claim 5, characterized in that: The inventory unit uses the number of transmissions of the signal generated based on the product code and the unique barcode as the increase in the number of corresponding unique barcodes in the inventory table, and the inventory unit completes the calculation of the corresponding unique barcode deletion in the inventory table based on the real-time decoding number of the central management module.

7. A warehouse management system according to claim 6, characterized in that: The real-time decoding is completed by the reader / writer through the antenna to read the data and time sequence in the unique barcode, wherein the data includes characteristic parameters, characteristic parameter uniqueness identification, product code and free definition code, and the time sequence includes time nodes.

8. A warehouse management system according to claim 6, characterized in that: The intelligent inventory monitoring completes the outbound monitoring operation based on the monitoring network, and obtains the outbound quantity based on the number of contours with focus differences in adjacent frame images of the outbound shipment. The outbound quantity output result is transmitted to the central management module through the Internet of Things platform.

9. A warehouse management system according to claim 7, characterized in that: Also includes either of the following two settings: The outbound quantity matches the real-time decoding times, and the inventory unit completes the deletion of the corresponding unique barcode in the inventory table according to the decoding information of the real-time decoding; The outbound quantity does not match the real-time decoding times, the central management module receives the mismatch result transmitted through the Internet of Things platform, and the central management module performs manual review.

10. A warehouse management system according to claim 9, characterized in that: The mobile client terminal is connected to the central management module via the Internet of Things platform, and the mobile client terminal displays the inventory unit and the inventory table via a data dashboard.

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