An unmanned digital warehouse intelligent supervision method, system and medium

Abstract

The application provides an unmanned digital warehouse intelligent supervision method, system and medium, and relates to the technical field of intelligent warehousing. The method comprises the following steps: determining identity information according to face information and IC card information; inputting the identity information into a database to obtain historical material taking records; obtaining a prediction result according to the historical material taking records; obtaining article label information, material position and material characteristics of the current material taken by the target user; judging whether to send a warning signal according to the prediction result and the article label information, and determining actual taking article information of the target user according to the article characteristics in the database; recording the actual taking article information in the database to update inventory information in the intelligent warehouse shelf. The purpose of automatic warehouse material counting is achieved while the material taking condition does not need to be manually registered. Moreover, the method supports multiple users to take materials and automatically register at the same time, and the problem of material taking registration error caused by multiple users taking materials at the same time is avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent warehousing, in particular to an unmanned digital warehouse intelligent supervision method, system and medium. BACKGROUND

[0002] Currently, there are two ways to realize unmanned warehouse:

[0003] The first one is a gravity cabinet with an identity authentication device, an electric control door lock and a gravity sensor layer. In the use of the gravity cabinet, the weight data of the materials need to be pre-entered, and different materials are arranged in different cabinets. The user is authenticated by the identity authentication device, and the electric control door lock is opened after the authentication is successful. The user's material taking operation is judged by the change of the sensor value of different areas, and the corresponding outbound single is generated. This way of unmanned warehouse is limited by the space in the cabinet, and the pre-determined area lacks flexibility in arrangement, which cannot adapt to the diversified warehouse sku spanning multiple sizes. And only one user can use it at a time. In addition, in a large warehouse, deploying multiple cabinets will involve multiple identity authentication and repeated unlocking, which is low in efficiency.

[0004] The second one is an RFID shelf with a radio frequency identification antenna, which is deployed in a closed environment with an identity authentication access control. It is used with materials with pre-pasted RFID labels. By scanning the trigger signal of the RFID label on the material, uninterrupted inventorying is realized. In cooperation with the access control record of the deployment environment, the user's material taking operation can be identified, and the corresponding outbound single can be generated. The application of this way of unmanned warehouse needs to continuously invest in high-value RFID labels and manual pasting costs, and the accuracy of this technology depends on whether the RFID is correctly pasted and whether the user complies with the cumbersome material arrangement and taking requirements (the improper pasting of RFID stickers on some surfaces or the unfavorable angle between the antenna recognition plane will affect the accuracy), at the same time, this technology only realizes the identification of materials, and cannot realize the simultaneous identification of multiple users, and cannot support multiple users to take materials at the same time.

[0005] Therefore, there is an urgent need for an unmanned digital warehouse intelligent supervision method and system to solve the problem that the prior art cannot support multiple users to take materials at the same time and is prone to material taking registration errors. SUMMARY

[0006] The purpose of the present application is to provide an unmanned digital warehouse intelligent supervision method, system and medium to solve the problem that the prior art cannot support multiple users to take materials at the same time and is prone to material taking registration errors.

[0007] The embodiments of the present application are implemented as follows:

[0008] In a first aspect, the embodiments of the present application provide an unmanned digital warehouse intelligent supervision method, which comprises the following steps:

[0009] Obtaining facial information and IC card information of a target user, performing identity authentication on the target user according to the facial information and the IC card information, and determining identity information;

[0010] Inputting the identity information into a database for matching to obtain corresponding historical material taking records;

[0011] According to the historical material taking records, predicting a current material taking behavior of the target user to obtain a prediction result;

[0012] Real-time monitoring all articles in an intelligent warehouse shelf, obtaining article label information, corresponding material positions and material characteristics of the material currently taken by the target user;

[0013] According to the prediction result and the article label information, determining whether to send a warning signal, and meanwhile, calling the article characteristics corresponding to the material positions from the database;

[0014] Matching the article characteristics with the material characteristics to determine actual taking article information of the target user;

[0015] According to the identity information, recording the actual taking article information into the database, and meanwhile, updating inventory information in the intelligent warehouse shelf.

[0016] In some embodiments of the present application, the label of any article in the above-mentioned intelligent warehouse shelf is configured with an LED lamp;

[0017] After the step of predicting the current material taking behavior of the target user according to the historical material taking records to obtain a prediction result, the method further comprises:

[0018] According to the prediction result, determining all predicted taking articles, and sending a lighting instruction to the LED lamp corresponding to each predicted taking article.

[0019] In some embodiments of the present application, the step of real-time monitoring all articles in an intelligent warehouse shelf to obtain article label information, corresponding material positions and material characteristics of the material currently taken by the target user comprises:

[0020] Real-time collecting scene image information and all article image information of the intelligent warehouse shelf through a camera, wherein any article image information comprises corresponding material characteristics;

[0021] Real-time detecting whether the corresponding article is taken through a gravity sensor arranged on the intelligent warehouse shelf, simultaneously combining the scene image information to determine the material position of the material currently taken by the target user, and inputting the material position into the database to determine the corresponding article label information.

[0022] In some embodiments of the present application, the above-mentioned unmanned digital warehouse intelligent supervision method further comprises:

[0023] According to the latest inventory information of the intelligent warehouse shelf, the information of the to-be-supplemented goods is determined;

[0024] According to the to-be-supplemented goods information, after supplementing the goods in the intelligent warehouse shelf, the inventory information in the intelligent warehouse shelf is updated.

[0025] In some embodiments of the present application, after the step of updating the inventory information in the intelligent warehouse shelf, the method further comprises:

[0026] When responding to the inventory report generation request, an inventory report is generated according to the latest inventory information of the intelligent warehouse shelf.

[0027] In a second aspect, the embodiments of the present application provide an unmanned digital warehouse intelligent supervision system, which comprises:

[0028] An identity information determination module is configured to obtain face information and IC card information of a target user, perform identity authentication on the target user according to the face information and the IC card information, and determine identity information;

[0029] A matching module is configured to input the identity information into a database for matching, and obtain corresponding historical material taking records;

[0030] A prediction module is configured to predict a current material taking behavior of the target user according to the historical material taking records, and obtain a prediction result;

[0031] A monitoring module is configured to monitor all goods in an intelligent warehouse shelf in real time, and obtain goods tag information, corresponding material positions and material characteristics of the material taken by the target user currently;

[0032] A warning module is configured to determine whether to send a warning signal according to the prediction result and the goods tag information, and simultaneously call the goods characteristics corresponding to the material positions from the database;

[0033] An actual taken goods information determination module is configured to match the goods characteristics with the material characteristics, so as to determine actual taken goods information of the target user;

[0034] An inventory information updating module is configured to record the actual taken goods information into the database according to the identity information, and simultaneously update the inventory information in the intelligent warehouse shelf.

[0035] In a third aspect, the embodiments of the present application provide an electronic device, which comprises a memory for storing one or more programs, and a processor. When the one or more programs are executed by the processor, the method of any one of the above-mentioned first aspect is implemented.

[0036] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the method of any one of the above first aspect.

[0037] Compared with the prior art, the embodiments of the present application have at least the following advantages or beneficial effects:

[0038] The present application provides an unmanned digital warehouse intelligent supervision method, system and medium, which comprises the following steps: obtaining face information and IC card information of a target user, performing identity verification on the target user according to the face information and the IC card information, and determining identity information. The identity information is input into a database for matching to obtain corresponding historical material taking records. According to the historical material taking records, the current material taking behavior of the target user is predicted to obtain a prediction result. All items in the intelligent warehouse shelf are monitored in real time to obtain the item tag information, corresponding material position and material characteristics of the material currently taken by the target user. According to the prediction result and the item tag information, it is judged whether to send a warning signal, and the corresponding item characteristics of the material position are called from the database. The item characteristics and the material characteristics are matched to determine the actual taken item information of the target user. According to the identity information, the actual taken item information is recorded in the database, and the inventory information in the intelligent warehouse shelf is updated. The purpose of automatic warehouse material counting is achieved without the need for manual material taking registration. Not only the time-consuming and laborious and easy-to-make mistakes caused by manual registration are avoided, but also the time and energy occupied by material counting are avoided. The effect of warehouse material taking immediately, without identification and without manual form is achieved. Moreover, the method and system can monitor the material taking of each user entering the warehouse, so that multiple users can take materials at the same time and be automatically registered, avoiding the problem of material taking registration error when multiple users take materials at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0040] Figure 1 A flowchart of an unmanned digital warehouse intelligent supervision method provided by the embodiments of the present application;

[0041] Figure 2 A flowchart of monitoring a target user provided by the embodiments of the present application;

[0042] Figure 3 FIG. 1 shows a flowchart of an embodiment of the present application.

[0043] Figure 4 FIG. 2 shows a structural block diagram of an embodiment of the present application.

[0044] Figure 5 FIG. 3 shows a schematic structural block diagram of an electronic device according to an embodiment of the present application.

[0045] Icon: 110 - identity information determination module; 120 - matching module; 130 - prediction module; 140 - monitoring module; 150 - warning module; 160 - actual item pickup information determination module; 170 - inventory information updating module; 101 - memory; 102 - processor; 103 - communication interface. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0047] Therefore, the detailed description of the embodiments of the present application provided below in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative labor are within the scope of protection of the present application.

[0048] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. In the case of no conflict, each of the following embodiments and each feature in the embodiments can be combined with each other.

[0049] EMBODIMENT

[0050] Please refer to Figure 1 , Figure 1 FIG. 1 shows a flowchart of an embodiment of the present application. The present application provides an intelligent monitoring method for unmanned digital warehouse, which comprises the following steps:

[0051] S110: obtaining face information and IC card information of a target user, performing identity authentication on the target user according to the face information and the IC card information, and determining identity information;

[0052] Specifically, when the target user enters the warehouse, the face information of the target user can be acquired through the camera, and the IC card held by the target user is scanned and read to acquire the IC card information. Then, the identity of the target user is verified by using the face information and the IC card information, so as to determine the identity information of the target user, thereby ensuring the security of the warehouse materials.

[0053] S120: inputting the identity information into the database for matching to obtain corresponding historical material taking records;

[0054] Specifically, the historical material taking records of each user are saved in the database. Then, according to the identity information of the target user, the historical material taking records of the target user can be acquired from the database.

[0055] S130: predicting the current material taking behavior of the target user according to the historical material taking records to obtain a prediction result;

[0056] S140: real-time monitoring all the goods in the intelligent warehouse goods shelf to acquire the goods tag information, corresponding material position and material characteristics of the material currently taken by the target user;

[0057] The material characteristics can include, but are not limited to, the shape, size and pattern of the goods.

[0058] S150: judging whether to send a warning signal according to the prediction result and the goods tag information, and calling the goods characteristics corresponding to the material position from the database;

[0059] In some embodiments of the embodiment, the database pre-stores the material position, material characteristics and goods tag information of each good in all the intelligent warehouse goods shelves in the warehouse.

[0060] Specifically, when the target user enters the warehouse, the current material taking behavior of the target user is predicted according to the historical material taking records of the target user to obtain a prediction result. The prediction result is the material that the target user is likely to take this time. When the user self-takes the material from the intelligent warehouse goods shelf, the material position, material characteristics and goods tag information of the material currently taken by the target user can be determined through the gravity sensor and the camera, and the material characteristics are the characteristics of the material currently in the material position. If the prediction result and the goods tag information are inconsistent, a warning signal is sent to remind the user whether the material is taken incorrectly. Meanwhile, according to the material position of the material currently taken by the target user, the goods characteristics of the material corresponding to the material position are acquired from the database, and the goods characteristics are the characteristics of the goods corresponding to the material position which are previously saved in the database.

[0061] S160: matching the goods characteristics with the material characteristics to determine the actual taken goods information of the target user;

[0062] Specifically, the article features are matched with the material features, if the article features are consistent with the material features, the actual taking article information of the target user can be directly determined according to the article features or the material features. On the contrary, if the article features are inconsistent with the material features, the actual taking article information of the target user is determined according to the material features.

[0063] S170: According to the identity information, the actual taking article information is recorded in the database, and the inventory information in the intelligent storage shelf is updated.

[0064] Specifically, according to the identity information of the target user, the actual taking article information of the target user this time is saved to the database, and the inventory information in the intelligent storage shelf is updated in real time according to the taking material of the target user. Further, the purpose of automatic inventory of warehouse materials is achieved while realizing the need for manual registration of material taking. Not only the time-consuming and laborious and easy-to-error situation caused by manual registration is avoided, but also the time and energy occupied by material inventory is avoided. The effect of warehouse materials is achieved, that is, no identification and no manual form. Moreover, the method can monitor the material taking of each user entering the warehouse, so that multiple users can take materials and register automatically at the same time, avoiding the problem of material taking registration error when multiple users take materials at the same time.

[0065] In some embodiments of the present embodiment, the label of any article in the above-mentioned intelligent storage shelf is configured with an LED lamp;

[0066] After the above-mentioned step of predicting the current material taking behavior of the target user according to the historical material taking record to obtain a prediction result, the method further comprises:

[0067] According to the prediction result, all predicted taking articles are determined, and a lighting instruction is sent to the LED lamp corresponding to each predicted taking article.

[0068] Specifically, according to the prediction result, a lighting instruction is sent to the LED lamp corresponding to each predicted taking article, so as to light up the LED lamp corresponding to each predicted taking article, so that the label corresponding to each predicted taking article flashes, so as to facilitate the target user to see the label and position of each predicted taking article.

[0069] Please refer to Figure 2 , Figure 2 The flowchart for monitoring the target user provided by the present embodiment is shown. In some embodiments of the present embodiment, the above-mentioned step of real-time monitoring all articles in the intelligent storage shelf, obtaining the article label information of the material taken by the target user, the corresponding material position and the material features comprises:

[0070] The scene image information and all the article image information of the intelligent storage shelf are collected in real time by the camera, wherein any article image information comprises corresponding material characteristics;

[0071] The corresponding article is detected in real time by the gravity sensor arranged on the intelligent storage shelf whether it is taken, and the material position of the target user currently taking the material is determined in combination with the scene image information, and the material position is input into the database to determine the corresponding article label information.

[0072] Specifically, the scene image information and all the article image information of the intelligent storage shelf are collected in real time by the camera, and the corresponding article is detected in real time by the gravity sensor whether it is taken. When the user takes the material, the material position and the article label information of the target user currently taking the material are determined according to the scene image information collected by the camera and the detection result of the gravity sensor. The material characteristics of the target user currently taking the material are determined according to the article image information corresponding to the material position collected by the camera. Thus, the purpose of determining the material position, the material characteristics and the article label information of the target user currently taking the material by the gravity sensor and the camera when the user self-takes the material from the intelligent storage shelf is achieved.

[0073] Please refer to Figure 3 , Figure 3 The flow chart of another intelligent monitoring method of unmanned digital warehouse provided by the embodiment of the application is shown in the figure. In some embodiments of the embodiment, the above-mentioned intelligent monitoring method of unmanned digital warehouse further comprises:

[0074] According to the latest inventory information of the intelligent storage shelf, the to-be-supplemented article information is determined;

[0075] After the articles in the intelligent storage shelf are supplemented according to the to-be-supplemented article information, the inventory information in the intelligent storage shelf is updated. Thus, the purpose of real-time inventory of warehouse materials is further achieved without manual recording of the supplemented material information of the intelligent storage shelf after supplementing materials.

[0076] In some embodiments of the embodiment, after the step of updating the inventory information in the intelligent storage shelf, the method further comprises:

[0077] When responding to the inventory report generation request, the inventory report is generated according to the latest inventory information of the intelligent storage shelf. Thus, the inventory information of the intelligent storage shelf is directly reflected to the user through the inventory report.

[0078] Please refer to Figure 4 , Figure 4 The structural block diagram of an intelligent monitoring system of unmanned digital warehouse provided by the embodiment of the application is shown in the figure. The embodiment of the application provides an intelligent monitoring system of unmanned digital warehouse, which comprises:

[0079] The identity information determination module 110 is configured to acquire face information and IC card information of a target user, perform identity verification on the target user according to the face information and the IC card information, and determine identity information;

[0080] The matching module 120 is configured to input the identity information into a database for matching, and obtain corresponding historical material taking records;

[0081] The prediction module 130 is configured to perform prediction on a current material taking behavior of the target user according to the historical material taking records, and obtain a prediction result;

[0082] The monitoring module 140 is configured to monitor all articles in the intelligent warehouse shelf in real time, acquire article label information of a material taken by the target user currently, corresponding material positions and material features;

[0083] The warning module 150 is configured to determine whether to send a warning signal according to the prediction result and the article label information, and simultaneously call the article features corresponding to the material positions from the database;

[0084] The actual taken article information determination module 160 is configured to match the article features with the material features, so as to determine actual taken article information of the target user;

[0085] The inventory information updating module 170 is configured to record the actual taken article information into the database according to the identity information, and simultaneously update inventory information in the intelligent warehouse shelf.

[0086] In the above implementation process, the system not only realizes the purpose of automatic warehouse material counting without manual material taking registration, but also avoids the time-consuming and laborious and error-prone situation caused by manual registration, and avoids the time and energy occupied by material counting. The effect of warehouse material taking without identification and manual form is achieved. Moreover, the system can monitor material taking for each user entering the warehouse, so that multiple users can take materials and register automatically at the same time, and the problem of material taking registration error caused by multiple users taking materials at the same time is avoided.

[0087] Please refer to Figure 5 , Figure 5A schematic structural block diagram of an electronic device is provided in the embodiments of the present application. The electronic device includes a memory 101, a processor 102 and a communication interface 103, which are electrically connected to each other directly or indirectly to realize the transmission or interaction of data. For example, these elements can be electrically connected to each other through one or more communication buses or signal lines. The memory 101 can be used to store software programs and modules, such as the program instructions / modules corresponding to the unmanned digital warehouse intelligent supervision system provided by the embodiments of the present application. The processor 102 performs various functional applications and data processing by executing the software programs and modules stored in the memory 101. The communication interface 103 can be used for signaling or data communication with other node devices.

[0088] The memory 101 can be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read only memory (PROM), an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM), etc.

[0089] The processor 102 can be an integrated circuit chip with signal processing capability. The processor 102 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; or can be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0090] It can be understood that Figure 5 The structure shown is only schematic, and the electronic device can further include more or fewer components than those shown in the figures, or have a different configuration from that shown in the figures. Figure 5 The components shown in the figures can be realized in hardware, software or a combination thereof. Figure 5 The components shown in the figures can be realized in hardware, software or a combination thereof. Figure 5 The components shown in the figures can be realized in hardware, software or a combination thereof.

[0091] In the embodiments of the present disclosure, it should be understood that the disclosed apparatus and method can also be implemented in other manners. The embodiments described above are merely exemplary. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architectures, functions and operation of the apparatus, method and computer program product according to the embodiments of the present disclosure. In this regard, each block in the flowcharts and block diagrams can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logic function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in a different order from that noted in the accompanying drawings. For example, two consecutive blocks can actually be executed in a substantially parallel manner, or they can be executed in a reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and the combination of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or by a combination of dedicated hardware and computer instructions.

[0092] In addition, each functional module in the various embodiments of the present disclosure can be integrated together to form a separate part, or each module can exist independently, or two or more modules can be integrated to form a separate part.

[0093] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present disclosure can be embodied in the form of a software product, and the computer software product is stored in a storage medium, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present disclosure. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0094] The above only describes the preferred embodiments of the present disclosure and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

[0095] It will be apparent to those skilled in the art that the application is not limited to the details of the above-exemplified embodiments and that the present application can be implemented in other particular forms without departing from the spirit or essential characteristics thereof. The embodiments should be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the above description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. No reference herein to any prior art is to be taken as an admission that the application is not entitled to antedate such prior art by virtue of prior application. Any reference to the use of a term in the singular herein shall also be taken to refer to the plural, and vice versa, unless otherwise indicated by context. Any reference to the use of a term in the present application shall be taken to refer to the use of the term in the context of the present application, and not to the use of the term in any other context. Any reference to the use of a term in the present application shall be taken to refer to the use of the term in the context of the present application, and not to the use of the term in any other context.

Claims

1. An unmanned digital warehouse intelligent supervision method, characterized in that, It comprises the following steps: Obtain the facial information and IC card information of the target user, authenticate the target user according to the facial information and the IC card information, and determine the identity information; Input the identity information into the database for matching to obtain the corresponding historical material taking record; According to the historical material taking record, the current material taking behavior of the target user is predicted to obtain a prediction result; Real-time monitoring of all items in the intelligent warehouse shelf, obtaining the target user's current material taking item label information, corresponding material location and material characteristics; According to the prediction result and the item label information, it is judged whether to send a warning signal, and the corresponding material characteristics of the material location are called from the database; The material characteristics and the material characteristics are matched to determine the actual taking item information of the target user; According to the identity information, the actual taking item information is recorded in the database, and the inventory information in the intelligent warehouse shelf is updated; Wherein: The step of real-time monitoring of all items in the intelligent warehouse shelf, obtaining the target user's current material taking item label information, corresponding material location and material characteristics comprises: Real-time collection of scene image information and all item image information of the intelligent warehouse shelf through a camera, wherein any item image information comprises corresponding material characteristics; Through the gravity sensor arranged on the intelligent warehouse shelf, it is determined whether the corresponding item is taken, and the material location of the target user's current material taking is determined by combining the scene image information, and the material location is input into the database to determine the corresponding item label information. 2.The unmanned digital warehouse intelligent supervision method according to claim 1, characterized in that, The label of any item in the intelligent warehouse shelf is configured with an LED lamp; After the step of predicting the current material taking behavior of the target user according to the historical material taking record to obtain a prediction result, it further comprises: According to the prediction result, all predicted taking items are determined, and a lighting instruction is sent to the LED lamp corresponding to each predicted taking item. 3.The unmanned digital warehouse intelligent supervision method of claim 1, wherein, It further comprises: According to the latest inventory information of the intelligent warehouse shelf, determine the to-be-supplemented item information; After supplementing the items in the intelligent warehouse shelf according to the to-be-supplemented item information, update the inventory information in the intelligent warehouse shelf. 4.The unmanned digital warehouse intelligent supervision method of claim 1, wherein, After the step of updating the inventory information in the intelligent warehouse shelf, it further comprises: When responding to the inventory report generation request, generate an inventory report according to the latest inventory information of the intelligent warehouse shelf.

5. An unmanned digital warehouse intelligent supervision system, characterized in that, It comprises: An identity information determination module for obtaining the facial information and IC card information of the target user, authenticating the target user according to the facial information and the IC card information, and determining the identity information; A matching module for inputting the identity information into the database for matching to obtain the corresponding historical material taking record; A prediction module for predicting the current material taking behavior of the target user according to the historical material taking record to obtain a prediction result; A monitoring module for real-time monitoring of all items in the intelligent warehouse shelf, obtaining the target user's current material taking item label information, corresponding material location and material characteristics; Specifically comprising: collecting scene image information and all object image information of the intelligent warehouse shelf in real time through a camera, wherein any object image information comprises corresponding material characteristics; detecting whether the corresponding object is taken in real time through a gravity sensor arranged on the intelligent warehouse shelf, and determining a material position of the target user currently taking the material in combination with the scene image information, and inputting the material position into a database to determine corresponding object label information; a warning module configured to determine whether to issue a warning signal according to the prediction result and the object label information, and to retrieve the object characteristics corresponding to the material position from the database; an actual taking object information determination module configured to match the object characteristics with the material characteristics to determine actual taking object information of the target user; an inventory information updating module configured to record the actual taking object information into the database according to the identity information, and to update inventory information in the intelligent warehouse shelf.

6. An electronic device, comprising: comprise: a memory configured to store one or more programs; a processor; when the one or more programs are executed by the processor, the method of any one of claims 1-4 is implemented.

7. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the method of any one of claims 1-4.

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