Control method of automatic vending cabinet

Abstract

The invention provides a control method of an automatic vending cabinet. The control method mainly comprises the steps that a user submits a goods returning request and places goods in a goods returning window; an identification module verifies whether the commodity belongs to a returned commodity category; if the verification is passed, transferring the commodity and updating inventory information; recommending alternative commodities to the user; executing price difference processing operation according to the price difference between the alternative commodity and the original commodity; therefore, the goods return request can be automatically processed, the goods can be intelligently recommended, and price difference processing can be quickly executed, so that the automatic vending cabinet can efficiently process the goods return request of the user, and the user satisfaction and the shopping experience are improved.

Description

Technical Field

[0001] This application relates to the technical field of vending, and more specifically, to a control method for a vending cabinet. Background Art

[0002] Currently, with the rapid development of the unmanned retail industry, vending cabinets are widely welcomed due to their convenience and flexibility. However, existing vending cabinets often have problems of cumbersome processes and low efficiency when dealing with user returns. Users need to return goods through manual customer service or specific return channels, which not only increases operating costs but also reduces the user experience. In addition, vending cabinets also have deficiencies in product recommendation and price difference processing, and it is difficult to meet the diverse shopping needs of users.

[0003] In view of the above problems, it is necessary to develop a control method for a vending cabinet that can automatically process return requests, intelligently recommend products, and quickly execute price difference processing. Summary of the Invention

[0004] This application aims to at least partially solve the above technical problems and provides a control method for a vending cabinet.

[0005] An embodiment of this application provides a control method for a vending cabinet, and the control method includes:

[0006] A user submits a return request and places the product at the return window;

[0007] An identification module verifies whether the product belongs to a returnable category;

[0008] If the verification passes, transfer the product and update the inventory information;

[0009] Recommend alternative products to the user;

[0010] Execute a price difference processing operation according to the price difference between the alternative product and the original product.

[0011] Further, the identification module includes at least one of the following units: an RFID tag reading unit, a QR code scanning unit, and an image recognition unit. The verification includes matching the product identification information with a preset returnable category database and detecting the integrity of the product. Through the RFID tag reading unit, the QR code scanning unit, or the image recognition unit, product information can be quickly read and matched with the preset returnable category database to verify whether the product belongs to a returnable category. At the same time, by detecting the integrity of the product, it is ensured that the returned product meets the return conditions.

[0012] Furthermore, the transfer of goods is performed by a robotic arm, which is configured with a flexible clamping device and a pressure feedback module. The jaws of the flexible clamping device are covered with a silica gel layer, and the pressure feedback module monitors the clamping force in real time to adapt to goods of different shapes. The robotic arm clamps the goods through the flexible clamping device, and the silica gel layer can protect the goods from damage. At the same time, the pressure feedback module monitors the clamping force in real time to ensure stable clamping and prevent damage to the goods. This design enables the robotic arm to adapt to goods of different shapes and sizes, improving the flexibility and accuracy of return processing.

[0013] Furthermore, the replacement goods include: generating a recommendation list through a machine learning model based on the user's purchase history data, the attributes of the returned goods, and the current inventory status, and dynamically displaying it in the interactive interface according to the priority. By analyzing the user's purchase history data, the attributes of the returned goods, and the current inventory status through a machine learning model, a recommendation list of replacement goods that meets the user's needs can be generated. At the same time, the recommended goods are dynamically displayed in the interactive interface according to the priority, enabling the user to quickly find satisfactory replacement goods.

[0014] Furthermore, the price difference processing operation includes: if the price of the replacement goods is higher than the price of the original goods, the difference is collected through the payment interface; if the price of the replacement goods is lower than the price of the original goods, the difference is refunded through the cloud server according to the original payment path, and the refund operation is completed within 30 seconds after submission. If the price of the replacement goods selected by the user is higher than the price of the original goods, the system collects the difference from the user through the payment interface; if the price of the replacement goods is lower than the price of the original goods, the system refunds the difference to the user's account through the cloud server according to the original payment path. The refund operation is completed within 30 seconds after submission to ensure that the user can receive the refund in a timely manner.

[0015] Furthermore, the return window is connected to a temperature-controlled storage area, which includes a thermoelectric refrigeration module and a humidity regulation module. The thermoelectric refrigeration module is used to maintain the storage temperature of refrigerated goods at 2°C to 8°C; the humidity regulation module is used to control the storage humidity of dry goods at 30% to 60%. Connecting the return window to the temperature-controlled storage area can ensure that the returned goods maintain suitable storage conditions during the return process. The thermoelectric refrigeration module and the humidity regulation module are respectively used to adjust the storage environment of refrigerated goods and dry goods to ensure that the quality of the goods is not affected.

[0016] Further, the updated inventory information includes: marking the status of the returned goods as "pending quality inspection", "resalable", or "dispute locked", and synchronizing the marking information to the blockchain network to generate an immutable product traceability record. After the returned goods are initially inspected, they are marked as "pending quality inspection", "resalable", or "dispute locked" according to the status of the goods. At the same time, the marking information is synchronized to the blockchain network to generate an immutable product traceability record. This design can ensure the traceability of the flow of returned goods and improve the transparency and security of product management.

[0017] Further, the submission of the return request is triggered by at least one of the following methods: touch screen interaction interface, mobile application, voice command input. Among them, voice command input requires voiceprint recognition to verify the user's identity. Users can submit return requests through methods such as touch screen interaction interfaces, mobile applications, or voice command input. In particular, for the voice command input method, the user's identity needs to be verified through voiceprint recognition to ensure the authenticity of the return request. This design enables users to submit return requests conveniently and improves the efficiency of return processing.

[0018] Further, data is transmitted between the cloud server and the payment platform through an encrypted communication protocol. The payment request is attached with a dynamically generated unique token, and the refund difference requires dual biometric authentication by fingerprint or facial recognition. The cloud server and the payment platform use an encrypted communication protocol to transmit data to ensure the security of data transmission. The payment request is attached with a dynamically generated unique token, which further enhances the security of payment. At the same time, the refund difference requires dual biometric authentication by fingerprint or facial recognition to ensure the authenticity and security of the refund operation.

[0019] Further, the vending cabinet is interconnected with an external server group through blockchain nodes. The external server group includes an inventory management server, a user behavior analysis server, and a payment gateway server. The inventory management server records the full life cycle data of the products and generates a distributed ledger; the user behavior analysis server constructs a user preference map to optimize the recommendation strategy; the payment gateway server uses zero-knowledge proof technology to verify the transaction privacy data. The vending cabinet is interconnected with the external server group through blockchain nodes to achieve data sharing and collaborative processing. The inventory management server records the full life cycle data of the products and generates a distributed ledger, improving the transparency and traceability of product management. The user behavior analysis server constructs a user preference map for optimizing the product recommendation strategy. The payment gateway server uses zero-knowledge proof technology to verify the transaction privacy data to ensure the security and privacy protection of the transaction process.

[0020] The present application provides a control method for a vending cabinet, which can automate the processing of return requests, intelligently recommend products, and quickly execute price difference processing. The main method is to verify the return product information through an identification module, automatically transfer the return product by a robotic arm, the recommendation module intelligently generates a recommended list of alternative products, the price difference processing module quickly executes the price difference processing operation, and the temperature control storage module maintains suitable storage conditions for the return product. These designs enable the vending cabinet to efficiently process user return requests and improve user satisfaction and shopping experience. Detailed implementation

[0021] An embodiment of the present application provides a control method for a vending cabinet.

[0022] In this embodiment, the process of the user submitting a return request and product verification mainly includes:

[0023] 1. User interface design: The user clicks the "Return" button on the touch screen main interface of the vending cabinet, and the system pops up a return application form. The form needs to fill in the following information:

[0024] Name or number of the return product (support for barcode scanning input);

[0025] Options for the return reason (such as "product damaged", "not delivered as required", "personal reasons", etc.);

[0026] Payment method verification (identity verification needs to be completed through the original payment account or the bound electronic social security card).

[0027] After the form is submitted, the system verifies the user's identity through the voiceprint recognition module (integrated in the microphone array on the top of the cabinet) to prevent malicious returns.

[0028] 2. Operation of the product placement and identification module

[0029] After the user places the return product on the tray of the return window, the system triggers the following verification process:

[0030] RFID tag reading: If the product packaging contains an RFID tag, the system obtains the product code through a UHF band reader / writer (model: Impinj R2000) and compares it with the cloud database of returnable products.

[0031] Image recognition assisted verification: For products without tags, the system activates an 8-megapixel high-definition camera to capture the appearance of the product, identifies the product category through a convolutional neural network (CNN) model (based on the ResNet-50 architecture), and compares it with the inventory record.

[0032] Integrity detection: The 3D structured light sensor scans the surface of the product to detect whether the packaging is damaged or opened. If signs of opening are detected, the system will mark it as "dispute locked" and notify the backend for manual review.

[0033] 3. Verification result feedback

[0034] If the verification is successful, the touch screen displays a "Return Successful" prompt and activates the robotic arm to perform the product transfer operation.

[0035] If the verification fails, the system prompts the user to re-place the product or contact customer service, and uploads the error log to the blockchain node (based on the Hyperledger Fabric framework) for subsequent tracing.

[0036] In this embodiment, the robot arm commodity transfer and temperature-controlled storage mainly include the following contents:

[0037] 1. Robotic arm control logic

[0038] Path planning: The robot arm (model: UR10e) uses lidar to build a three-dimensional map from the return window to the temperature-controlled storage area in real time, and uses the A* algorithm to plan the optimal path to avoid collision with other products in the cabinet.

[0039] Dynamic adjustment of clamping force: The flexible clamping device has a built-in pressure sensor (range: 0-50N) to monitor the clamping force in real time. When the clamping force exceeds the preset threshold (such as 10N for fragile items), the robot arm automatically reduces the motor torque to prevent damage to the product.

[0040] Exception handling: If the robot arm's operation is interrupted due to path obstruction or clamping failure, the system triggers a buzzer alarm and sends a fault code to the operation and maintenance personnel through the LoRa module.

[0041] 2. Temperature controlled storage area design

[0042] Zoning management: The storage area is divided into a cold storage area (2-8°C) and a dry area (humidity 30-60%). The environmental parameters are regulated by semiconductor cooling sheets (TEC1-12706) and ultrasonic humidifiers (model: HSU-01).

[0043] Dynamic monitoring: The temperature and humidity sensor (model: DHT22) collects data every 30 seconds. If it detects that the temperature deviates from the set value by ±2°C or the humidity deviates by ±10%, the system automatically starts the backup cooling / dehumidification module and generates an alarm log.

[0044] Product classification storage: The robotic arm places the returned products in the corresponding partition according to the product type (such as beverages, snacks, and fresh food), and records the storage location and timestamp in the blockchain ledger.

[0045] In this embodiment, the substitute product recommendation and price difference processing mechanism mainly includes the following:

[0046] 1. Recommendation algorithm implementation

[0047] Data input: The recommendation module integrates the following data sources:

[0048] User's historical purchase records (retrieved from the cloud database by user ID);

[0049] Attributes of returned products (such as category, price, shelf life);

[0050] Current inventory status (synchronized in real time from the edge computing node).

[0051] Model training: A hybrid model combining collaborative filtering and content filtering is adopted, and the training data covers 100,000 user behavior logs. After the model outputs the recommendation list, it is sorted by "matching degree score" and the top 5 items are dynamically displayed through the interactive interface.

[0052] Priority rules:

[0053] Products with a high shelf life are recommended first (remaining shelf life > 7 days);

[0054] The weighted score of products of the same brand or the same category is increased by 20%;

[0055] Promotional products are automatically displayed at the top.

[0056] 2. Technical details of price difference processing

[0057] Payment interface integration: The system accesses the Alipay, WeChat Pay, and UnionPay QuickPass APIs. After the user selects a substitute product, the following process is called:

[0058] Make up the difference: If the price of the substitute product is higher than the original product, a dynamic payment QR code (valid for 60 seconds) is generated, and after the user scans the code, the deduction is completed through the AES-256 encryption channel.

[0059] Refund the difference: If the price is lower than the original product, the system initiates a refund request through the original payment path and uses zero-knowledge proof technology (ZKP) to verify the user's identity to ensure that the refund arrives within 30 seconds.

[0060] Enhanced biometric authentication: For difference refunds exceeding 500 yuan, secondary verification is required through the fingerprint recognition module (model: Synaptics VFS7552) integrated in the cabinet or 3D structured light facial recognition.

[0061] In this embodiment, the inventory management and blockchain traceability system mainly includes the following:

[0062] 1. Inventory status marking rules

[0063] To be quality-inspected: Applicable to opened or damaged-packaged goods, manual intervention is required for inspection.

[0064] Resalable: Unopened goods that pass the automatic verification are directly added back to the salable inventory.

[0065] Dispute locked: When the system cannot make an automatic determination, the goods are temporarily stored in an independent isolation area and await customer service processing.

[0066] 2. Blockchain data synchronization

[0067] Node deployment: The vending machine acts as a light node to access the consortium blockchain and jointly maintains the distributed ledger with the inventory management server and the payment gateway server.

[0068] Data on-chain: Each return operation generates the following key fields and packages them onto the chain:

[0069] Unique product code (SHA-256 hash value);

[0070] Operation time (UTC timestamp);

[0071] Processor ID (system or manual auditor);

[0072] Temperature and humidity storage records.

[0073] Traceability query: Consumers can view the full life cycle records, including production, distribution, return, and resale information, by scanning the product QR code.

[0074] In this embodiment, the system coordination and fault tolerance mechanism mainly includes the following:

[0075] 1. Edge-cloud collaborative architecture

[0076] Edge computing: The in-cabinet embedded industrial computer (model: Advantech ARK-2120) is responsible for real-time data processing (such as robotic arm control and image recognition), reducing the cloud load.

[0077] Cloud backup: At 0:00 every day, the operation logs and inventory data are backed up to the Alibaba Cloud OSS bucket via the HTTPS protocol, and the retention period is 180 days.

[0078] 2. Fault emergency plan

[0079] Network interruption: If a network disconnection is detected, the system switches to the local cache mode, continues to process the return request, and synchronizes the data in batches after the network is restored.

[0080] Hardware failure: Redundant components are equipped for key modules (such as robotic arms and cooling fins). When the main module fails, it automatically switches to the standby module, and the user is prompted to wait via the LED indicator.

[0081] Specific case introduction:

[0082] Case 1: Return scenario of beverage products

[0083] User A puts in an unopened bottle of mineral water. The system reads the code through RFID and verifies whether it is a returnable product. The code is "BEV-20250228-001", and after verification, it is a returnable product.

[0084] The robotic arm transfers it to the refrigerated area (set temperature 5°C), the inventory status is marked as "resalable", and it is synchronized to the blockchain ledger.

[0085] Based on the historical data of User A (frequently purchased carbonated beverages), the recommendation module shows "soda water (same brand)" as the preferred alternative product.

[0086] After User A selects the alternative product, the system refunds the price difference of 0.5 yuan through the original payment path, and the whole process takes 22 seconds.

[0087] Case 2: Dispute handling of fresh products

[0088] User B puts in a box of opened strawberries. Image recognition detects the opening trace and marks it as "dispute locked".

[0089] The temperature-controlled storage area starts an independent air duct to isolate the product and prevent contamination of other goods.

[0090] The back-end customer service retrieves the product circulation information through the blockchain record and manually processes the refund after confirming the liability.

[0091] In addition, this vending cabinet also includes a control system, which mainly includes a user interaction module, an identification module, a robotic arm control module, a recommendation module, a price difference processing module, and a temperature-controlled storage module. The user interaction module is used to receive the return request submitted by the user; the identification module is used to verify whether the returned product belongs to the returnable category; the robotic arm control module is used to control the robotic arm to transfer the returned product; the recommendation module is used to generate a recommended list of alternative products; the price difference processing module is used to perform the price difference processing operation; the temperature-controlled storage module is used to store the returned product and maintain suitable storage conditions.

[0092] It should be noted that in this text, 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. It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0093] Each embodiment in this specification is described in a related manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is based on a method embodiment and is similar, the description is relatively simple. For the relevant parts, reference can be made to the description of the method embodiment.

[0094] The above are only the embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A control method for an automatic vending machine, characterized in that: The control method comprises: The user submits a return request and places the product in the return window; The identification module verifies whether the product belongs to a returnable category; If the verification is successful, the product is transferred and the inventory information is updated; Recommend alternative products to users; A price difference processing operation is performed according to the price difference between the replacement product and the original product.

2. The control method according to claim 1, characterized in that: The identification module includes at least one of the following units: an RFID tag reading unit, a QR code scanning unit, and an image recognition unit; the verification includes matching the commodity identification information with a preset returnable category database and detecting the integrity of the commodity.

3. The control method according to claim 1, characterized in that: The transfer of goods is performed by a robotic arm, which is equipped with a flexible clamping device and a pressure feedback module. The surface of the clamping claw of the flexible clamping device is covered with a silicone layer, and the pressure feedback module monitors the clamping force in real time to adapt to goods of different shapes.

4. The control method according to claim 1, characterized in that: The alternative products include: based on the user's purchase history data, returned product attributes and current inventory status, a recommendation list is generated through a machine learning model, and dynamically displayed in an interactive interface according to priority.

5. The control method according to claim 1, characterized in that: The price difference processing operation includes: if the price of the substituted product is higher than the price of the original product, the difference will be collected through the payment interface; if the price of the substituted product is lower than the price of the original product, the difference will be refunded through the cloud server according to the original payment path, and the refund operation will be completed within 30 seconds after submission.

6. The control method according to claim 1, characterized in that: The return window is connected to a temperature-controlled storage area, and the temperature-controlled storage area includes: Semiconductor refrigeration module, used to maintain the storage temperature of refrigerated goods at 2°C to 8°C; The humidity adjustment module is used to control the storage humidity of dry goods at 30% to 60%.

7. The control method according to claim 1, characterized in that: The updating of inventory information includes: marking the status of returned goods as "pending quality inspection", "resalable" and "dispute locked", and synchronizing the marking information to the blockchain network to generate an unalterable product traceability record.

8. The control method according to claim 1, characterized in that: The submission of the return request is triggered by at least one of the following methods: Touch screen interactive interface, mobile application, voice command input; The voice command input needs to verify the user's identity through voiceprint recognition.

9. The control method according to claim 5, characterized in that: Data is transmitted between the cloud server and the payment platform via an encrypted communication protocol, a dynamically generated unique token is attached to the payment request, and the refund of the difference requires dual biometric authentication via fingerprint or facial recognition.

10. The control method according to claim 1, characterized in that: The vending machine is interconnected with an external server group via a blockchain node, and the external server group includes: Inventory management server, which records the data of the entire life cycle of goods and generates a distributed ledger; User behavior analysis server, building user preference graphs to optimize recommendation strategies; The payment gateway server uses zero-knowledge proof technology to verify transaction privacy data.