Self-service vending machine system based on artificial intelligence recognition and operation method thereof

Abstract

The invention discloses a self-service vending machine system based on artificial intelligence recognition and an operation method thereof, and the system comprises a vending machine main body, a high-definition camera, a depth sensor, an infrared sensor, an artificial intelligence processing unit, a display screen, a payment module and a commodity storage and distribution system. The artificial intelligence processing unit is connected with and controls each component to complete a self-service vending process; the intelligent level and the user experience of the self-service vending machine can be remarkably improved by integrating the high-precision recognition technology, personalized recommendation, interactive interface optimization and diversified payment modes, the vending efficiency is improved, the user experience is enhanced, the operation cost is reduced, and the market application prospect is wide.

Description

Technical Field

[0001] The present invention relates to the technical field of vending machines, and particularly to a vending machine system based on artificial intelligence recognition and an operation method thereof. Background Art

[0002] Traditional vending machines mainly allow users to make purchases by selecting product buttons on the user selection interface or scanning product barcodes. This method is not convenient enough when there are a large variety of products or when users need to quickly select products.

[0003] In recent years, although some vending machines have attempted to introduce image recognition technology to simplify the shopping process, these systems are often limited by problems such as recognition accuracy, processing speed, and user interaction friendliness, and cannot fully meet market demands. Summary of the Invention

[0004] The purpose of the present invention is to provide a vending machine system based on artificial intelligence recognition and an operation method thereof for the above problems in the prior art, thereby solving all or one of the above problems existing in the prior art.

[0005] To solve the above technical problems, the specific technical solutions of the present invention are as follows: On the one hand, the present invention provides a vending machine system based on artificial intelligence recognition, including: A vending machine main body, a high-definition camera, a depth sensor, an infrared sensor, an artificial intelligence processing unit, a display screen, a payment module, and a product storage and distribution system. The artificial intelligence processing unit is connected to and controls each component to complete the vending process; The high-definition camera and the depth sensor are arranged inside the vending machine and are used to capture user gestures and three-dimensional product information; The display screen supports touch operations and voice command inputs, and supports users to browse product information, adjust the purchase quantity, or select a payment method.

[0006] Further, the artificial intelligence recognition module integrates a deep learning algorithm and is used to analyze the video stream captured by the camera and the depth sensor data in real time.

[0007] Further, the vending machine system based on artificial intelligence recognition further includes: A personalized recommendation module, which is used to generate a product recommendation list according to the user's historical purchase data.

[0008] Further, the payment module supports multiple payment methods, including: mobile payment, bank card payment, and face recognition payment.

[0009] Further, the infrared sensor is located near the entrance of the vending machine and is used to detect the approach of the user. When the user is detected, it enters the recognition preparation state and activates the camera and depth sensor.

[0010] On the other hand, the present invention also provides an operation method for a vending machine system based on artificial intelligence recognition, including the following steps: S100. The user triggers recognition by gestures or placing goods. S200. The artificial intelligence processing unit recognizes the goods and calculates the price. S300. The display screen shows the goods information and the total price. S400. The user selects a payment method and completes the transaction. S500. The goods storage and distribution system distributes the goods according to the instruction.

[0011] Further, before the step S100, it further includes: Detecting the approach of the user through the infrared sensor and starting the recognition preparation state.

[0012] Further, after the step S300, it further includes: The personalized recommendation module pushes product recommendations according to the user's preferences.

[0013] Further, the payment process in the step S400 supports voice confirmation of payment instructions.

[0014] Further, the operation method further includes: Performing fault self-check and remote maintenance, and automatically notifying the management personnel when an abnormality is detected.

[0015] The beneficial effects of the technical solution of the present invention are: 1. The vending machine system based on artificial intelligence recognition according to the present invention can significantly improve the intelligent level and user experience of the vending machine by integrating high-precision recognition technology, personalized recommendation, optimizing the interaction interface and diversified payment methods, improve the vending efficiency, enhance the user experience and reduce the operation cost, and has a broad market application prospect.

[0016] 2. The operation method of the vending machine system based on artificial intelligence recognition according to the present invention can orderly call the system modules, and then realize the system logic of the vending machine system based on artificial intelligence recognition according to the present invention. Description of the Drawings

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0018] Figure 1 is a schematic diagram of the architecture of the vending machine system based on artificial intelligence recognition described in Embodiment 1 of the present invention; Figure 2 is a schematic flowchart of the operation method of the vending machine system based on artificial intelligence recognition described in Embodiment 2 of the present invention. Specific Embodiments

[0019] The following will elaborate on the preferred embodiments of the present invention in conjunction with the drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention.

[0020] In the description of the present invention, it should be noted that the embodiments described in the present invention are some embodiments of the present invention, rather than all embodiments; based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.

[0021] The terms "first", "second", etc. in the specification, claims and drawings of this article are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances, so that the embodiments described in this article can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or equipment comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or equipment. Embodiment 1

[0022] This embodiment provides a vending machine system based on artificial intelligence recognition, as Figure 1 shown, including: a vending machine main body, a high-definition camera, a depth sensor, an infrared sensor, an artificial intelligence processing unit, a display screen, a payment module, and a commodity storage and distribution system. The artificial intelligence processing unit is connected to and controls each component to complete the self-service vending process.

[0023] In one embodiment, the high-definition camera and the depth sensor are configured inside the vending machine to capture user gestures and three-dimensional information of the goods.

[0024] In one embodiment, the display screen is used to support touch operations and voice command inputs.

[0025] In one embodiment, the payment module supports multiple payment methods, including: mobile payment, bank card payment, and face recognition payment.

[0026] In one embodiment, the self-service vending machine system based on artificial intelligence recognition further includes: A personalized recommendation module for generating a product recommendation list based on the user's historical purchase data.

[0027] In one embodiment, the artificial intelligence recognition module integrates a deep learning algorithm to analyze the video stream captured by the camera and the depth sensor data in real time, achieving high-precision product recognition and gesture recognition.

[0028] In one embodiment, the personalized recommendation module generates a personalized product recommendation list through AI algorithms based on the user's historical purchase records and behavior analysis.

[0029] In one embodiment, the interaction interface is optimized to design an intuitive and easy-to-use touch screen interface that supports voice command inputs, enhancing the barrier-free usage experience.

[0030] In one embodiment, the composition and working principle of the system include: (1) The system main body is designed as an open structure for easy direct interaction with users.

[0031] (2) The high-definition camera and the depth sensor are installed at the top inside the vending machine to capture the user's gesture actions and the three-dimensional form of the placed goods.

[0032] (3) The infrared sensor is located near the entrance of the vending machine to detect the approach of users. Once a user is detected, the system immediately enters the recognition preparation state and activates the camera and the depth sensor.

[0033] (4) The artificial intelligence processing unit uses a deep learning model accelerated by a high-performance GPU, which can analyze the camera and depth sensor data in real time, accurately identify user gestures (such as pointing and grasping actions) and product types, calculate the total price of the products, and display it to the user through the display screen.

[0034] (5) The display screen supports touch operations and voice command inputs, allowing users to easily browse product information, adjust the purchase quantity, or select a payment method.

[0035] In one embodiment, the personalized recommendation and interaction optimization function of the system specifically includes: (1) Using big data analysis technology, according to information such as the user's historical purchase records and browsing habits, generate a personalized product recommendation list through AI algorithms and display it in a prominent position on the shopping interface to guide users to discover potentially interesting products and enhance the shopping experience and satisfaction.

[0036] (2) The interaction interface is designed to be simple and intuitive, supporting multi-language selection to ensure that users with different backgrounds can easily operate.

[0037] (3) It has a voice interaction function. Users can complete operations such as product selection and payment through voice commands, which is especially suitable for people with visual impairments and reflects the principle of barrier-free design.

[0038] In one embodiment, the payment and delivery function of the system specifically includes: (1) The payment module integrates multiple payment methods, including but not limited to: QR code scanning payment, bank card payment, and face recognition payment, to meet the payment preferences of different users.

[0039] (2) After successful payment, the product storage and delivery system automatically removes the selected product from the shelf and sends it to the pick-up port according to the instructions of the artificial intelligence processing unit, and the whole process is fast and smooth.

[0040] In one embodiment, the fault self-check and remote maintenance function of the system specifically includes: (1) The system has a built-in fault self-check mechanism that can monitor the operating status of each component in real time. Once an abnormality is found, it immediately notifies the management personnel through the wireless network and attempts to perform preliminary self-repair measures.

[0041] (2) The management personnel can access the system remotely to obtain the details of the fault, conduct remote diagnosis or send instructions to restart the system, effectively reducing the maintenance cost and downtime.

[0042] It should be noted that the above examples are only for explaining the present invention and should not limit the protection scope of the present invention. Embodiment 2

[0043] This embodiment is based on the same inventive concept as the vending machine system based on artificial intelligence recognition described in Embodiment 1, and provides an operation method of a vending machine based on artificial intelligence recognition, as Figure 2 shown, including the following steps: S100. The user triggers recognition by gesture or placing a product; S200. The artificial intelligence processing unit identifies the product and calculates the price; S300. The display screen shows the product information and the total price; S400. The user selects a payment method and completes the transaction; S500. The commodity storage and distribution system distributes the commodity according to the instruction.

[0044] Furthermore, before the step S100, the following is also included: Detect the approach of the user through an infrared sensor and start the recognition preparation state.

[0045] Furthermore, after the step S300, the following is also included: The personalized recommendation module pushes commodity recommendations according to the user's preferences.

[0046] Furthermore, the payment process in the step S400 supports voice confirmation of payment instructions.

[0047] Furthermore, the described operation method also includes: Perform fault self-check and remote maintenance, and automatically notify the management personnel when an abnormality is detected.

[0048] It should be understood that in various embodiments of this article, the magnitudes of the serial numbers of the above processes do not mean the sequence of execution. The execution sequence of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of this article.

[0049] It should also be understood that in the embodiments of this article, the term "and / or" is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the front and rear associated objects.

[0050] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described according to their functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this article.

[0051] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific logical process of the method described above can refer to the corresponding working processes of the system, device, and unit in the foregoing method embodiments, and will not be elaborated herein.

[0052] In several embodiments provided in this document, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Additionally, the displayed or discussed couplings or direct couplings or communication connections between each other can be indirect couplings or communication connections through some interfaces, devices, or units, and can also be in electrical, mechanical, or other forms of connection.

[0053] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the objectives of the embodiments of this document.

[0054] In addition, in each embodiment of this document, the functional units can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0055] If the above-mentioned integrated units are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the essence of the technical solution in this document, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable 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 each embodiment of this document. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0056] The above are only the embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structural or equivalent process transformations made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, are similarly included in the patent protection scope of the present invention.

Claims

1. A vending machine system based on artificial intelligence recognition, characterized in that, Including: A vending machine main body, a high-definition camera, a depth sensor, an infrared sensor, an artificial intelligence processing unit, a display screen, a payment module, and a commodity storage and distribution system. The artificial intelligence processing unit is connected to and controls each component to complete the self-service vending process. The high-definition camera and the depth sensor are configured inside the vending machine to capture user gestures and three-dimensional information of commodities. The display screen supports touch operations and voice command inputs, and supports users to browse commodity information, adjust the purchase quantity, or select a payment method.

2. The self-service vending machine system based on artificial intelligence recognition according to claim 1, wherein: The artificial intelligence recognition module integrates a deep learning algorithm for real-time analysis of the video stream captured by the camera and the data of the depth sensor.

3. The self-service vending machine system based on artificial intelligence recognition according to claim 1, wherein: The self-service vending machine system based on artificial intelligence recognition further includes: A personalized recommendation module for generating a commodity recommendation list according to the user's historical purchase data.

4. The self-service vending machine system based on artificial intelligence recognition according to claim 1, wherein: The payment module supports multiple payment methods, including: mobile payment, bank card payment, and face recognition payment.

5. The self-service vending machine system based on artificial intelligence recognition according to claim 1, wherein: The infrared sensor is located near the entrance of the vending machine for detecting the approach of a user. When a user is detected, it enters the recognition preparation state and activates the camera and the depth sensor.

6. An operating method of a vending machine system based on artificial intelligence recognition, characterized in that, Including the following steps: S100. The user triggers recognition through gestures or placing a commodity. S200. The artificial intelligence processing unit identifies the commodity and calculates the price. S300. The display screen displays the commodity information and the total price. S400. The user selects a payment method and completes the transaction. S500. The commodity storage and distribution system distributes the commodity according to the instruction.

7. The operation method according to claim 6, wherein: Before the step S100, it further includes: Detecting the approach of a user through the infrared sensor and activating the recognition preparation state.

8. The operation method according to claim 6, wherein: After the step S300, it further includes: The personalized recommendation module pushes commodity recommendations according to the user's preferences.

9. The operation method according to claim 6, wherein: The payment process in the step S400 supports voice confirmation of payment instructions.

10. The operation method according to claim 6, wherein: The operation method further includes: Performing fault self-check and remote maintenance, and automatically notifying the management personnel when an abnormality is detected.

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