Shopping mall self-service cashier intelligent management method and system

Abstract

The invention provides a shopping mall self-service cashier intelligent management method and system, and relates to the technical field of self-service cashier management. The method comprises establishing a database; generating a moving path of the customer in the shopping mall; querying commodity types and commodity prices; judging whether the customer passes through the region of the commodity; calculating actual commodity density; judging whether the commodity type is correct; and a plurality of payment modes are provided to complete the transaction and record. By comparing the area where the commodity is located with the moving path of the customer and comparing the actual density of the commodity with the standard density, whether the settlement information of the commodity has errors or not can be quickly judged, a complete verification chain is constructed, wrong settlement is avoided, the economic benefits of merchants are guaranteed, and the economic benefits of the merchants are improved. The fraudulent behavior of settlement by using wrong commodity codes is effectively hit, and a fair and just shopping environment is created for all customers.

Description

Technical Field

[0001] The present invention relates to the technical field of self-service cashier management, and in particular to a shopping mall self-service cashier intelligent management method and a shopping mall self-service cashier intelligent management system. Background Art

[0002] Self-service checkout, a key innovation in modern retail, is profoundly changing the consumer shopping experience. Leveraging advanced information technology and equipment, it enables an efficient and convenient checkout process. Self-service checkout areas are typically equipped with barcode scanners, electronic scales, and payment terminals. After selecting their items, customers proceed to the self-service checkout machine and place them one by one on the scanning table for scanning. The system quickly identifies the product information, including name, price, and quantity, and displays it on the screen in real time. The entire process is simple and straightforward. Customers follow the on-screen instructions. Once the product codes are scanned, the system automatically calculates the total price and offers a variety of payment options, including electronic payment and bank card payment. After confirming the payment information, the customer completes the transaction. With the continuous advancement of technology, self-service checkout systems are becoming increasingly intelligent and convenient, injecting new vitality into the retail industry.

[0003] In today's shopping malls, while self-service checkout systems have improved checkout efficiency, their vulnerabilities have also provided opportunities for some individuals to exploit. Some individuals exploit the autonomy of self-service checkout by holding high-priced items and then attaching the barcode of a lower-priced item when scanning the barcode, or simply placing the high-priced item inside the packaging of the lower-priced item. The system relies solely on barcode scanning to identify products, lacking in-depth verification of the actual product information. As long as the barcode is scannable, the total price will be calculated based on the incorrect lower price. This not only harms merchants, resulting in distorted sales data and reduced profits, but also undermines a fair trading environment. Summary of the Invention

[0004] The present invention provides a method and system for intelligent management of self-service cashiers in a shopping mall, which are used to solve the defects in the prior art.

[0005] In one aspect, the present invention provides a method for intelligent management of self-service checkout in a shopping mall, comprising: Draw a shopping route map and product distribution map for the mall, and establish a database containing multiple product information and associated locations.

[0006] Positioning base stations are deployed in various areas of the mall to locate the real-time location of customers and generate their movement paths within the mall.

[0007] A barcode scanner is installed in the self-service checkout area, which can scan the product barcode to query the corresponding product type and price in the database.

[0008] The obtained coordinates of the product's location are compared with the customer's movement path to determine whether the customer has passed through the product's area.

[0009] If a customer passes by the area where the product is located, the product weight and product image are obtained, the product volume is calculated based on the product image, and the actual density of the product is calculated based on the product weight.

[0010] Compare the actual density of the product with the standard density in the database and determine whether the product type is correct based on the preset error range.

[0011] If the product type is correct, the payment amount is calculated based on the product price and quantity, the product type and price are displayed on the checkout interface, and multiple payment methods are provided to complete the transaction and record it.

[0012] According to a method for intelligent management of self-service checkout in a shopping mall provided by the present invention, multiple commodity information includes commodity barcode, commodity type, commodity price, commodity standard density, commodity specification, commodity origin, commodity production date and shelf life.

[0013] According to a method for intelligent management of self-service checkout in a shopping mall provided by the present invention, the process of establishing a database containing multiple product information and associated locations includes: Collect multiple product information of all products in the mall.

[0014] Measure and determine the placement of each product in the mall, and use three-dimensional coordinates (x, y, z) to represent the location of the product, where x and y represent plane coordinates and z represents the vertical height coordinate.

[0015] Build a database table structure with the product barcode as the primary key, and store the product's multiple information and regional location coordinates in the corresponding fields of the database.

[0016] The database is maintained and updated according to the preset cycle. When the product information or placement changes, the corresponding content in the database is modified.

[0017] According to a method for intelligent management of self-service checkout in a shopping mall provided by the present invention, the process of generating a customer's movement path in the shopping mall includes: N positioning base stations are deployed in the shopping mall, and each positioning base station has a displacement identification number.

[0018] The positioning base station collects the signal strength value of the customer identification device in real time.

[0019] According to the signal strength value, the weighted centroid positioning method is used to calculate the customer's real-time location coordinates. The formula is expressed as: ; ; ; in, represents the weight of the i-th positioning base station, and the formula is expressed as: ; Where, Indicates the customer's real-time location coordinates, represents the location coordinates of the i-th positioning base station, n represents the total number of positioning base stations, Indicates the signal strength value sent by the i-th positioning base station.

[0020] Record the customer's real-time location coordinates in chronological order to form a coordinate sequence of s moments , get the customer’s movement path in the mall.

[0021] According to a method for intelligent management of self-service checkout in a shopping mall provided by the present invention, the process of determining whether a customer has passed through the area where the product is located includes: According to the type of product scanned, the three-dimensional coordinates of the center position of the product are queried in the database.

[0022] According to the product specifications and product distribution range, the error range in the x, y, and z directions is set to obtain the three-dimensional spatial range of the area where the product is located.

[0023] Traverse the customer's moving path coordinate sequence, and for each position coordinate, determine whether it meets the three-dimensional space range conditions.

[0024] If one or more real-time location coordinates of the customer are within the three-dimensional space, it is determined that the customer has passed through the area where the product is located.

[0025] According to a method for intelligent management of self-service checkout in a shopping mall provided by the present invention, the process of calculating the volume of a product based on a product image includes: Using stereo vision methods, multiple cameras are used to capture images of products from different angles to obtain multiple sets of image data.

[0026] The feature matching algorithm is used to find feature points with the same name in multiple sets of image data.

[0027] The three-dimensional coordinates of feature points with the same name are calculated using the triangulation principle.

[0028] Based on the 3D coordinates of the feature points with the same name, the Poisson surface reconstruction algorithm is used to reconstruct the 3D model of the product.

[0029] Discretize the three-dimensional model into N cubic units, calculate the spatial volume occupied by the three-dimensional model, and obtain the product volume.

[0030] According to a method for intelligent management of self-service checkout in a shopping mall provided by the present invention, the process of reconstructing a three-dimensional model of a product using a Poisson surface reconstruction algorithm includes: The three-dimensional coordinates of the feature points with the same name As input data, the normal vector of each feature point with the same name is calculated by calculating the normal direction of the local plane of the neighborhood around the feature point .

[0031] Defining indicator functions , indicator function The value is 1 inside the product and 0 outside the product.

[0032] The normal vector of the feature point with the same name is smoothed by the Gaussian kernel function to obtain the indicator function gradient field , the calculation formula is expressed as: ; In the formula, p represents any point in space, M represents the number of feature points with the same name, It represents the weight of the i-th feature point with the same name, which is determined by the distance from the feature point with the same name to point p. K represents the Gaussian kernel function. and Respectively represent the position and normal vector of the i-th feature point with the same name.

[0033] According to the exponential function gradient field , solve the Poisson equation ,in, represents the Laplace operator, and F represents a scalar field.

[0034] The marching cubes algorithm is used to extract the zero isosurface of the scalar field F on a discrete three-dimensional grid, that is, the point set where F(p)=0, to obtain the three-dimensional model of the product.

[0035] According to a method for intelligent management of self-service checkout in a shopping mall provided by the present invention, the process of calculating the spatial volume occupied by a three-dimensional model includes: Place the 3D model in a 3D space grid and divide the grid into N cubic units. The side length of each cubic unit is a. The volume of each cubic unit is .

[0036] For each cube unit, the ray method is used to determine whether it is completely inside the three-dimensional model.

[0037] Count the number Q of all cube units inside the three-dimensional model and calculate the volume of space occupied by the three-dimensional model. The formula is expressed as: ; In the formula, V represents the volume of the product, Q represents the number of cube units in the three-dimensional model, represents the volume of each cubic unit, and a represents the side length of the cubic unit.

[0038] According to the present invention, a method for intelligent management of self-service checkout in a shopping mall, the process of calculating the actual density of goods based on the weight of the goods includes: Use the electronic scale installed at the self-service checkout counter to measure the weight of the goods.

[0039] The actual density of the product is calculated based on its volume. The formula is: ; Where, Indicates the actual density of the product, m indicates the weight of the product, and V indicates the volume of the product.

[0040] On the other hand, the present invention also provides a shopping mall self-service checkout intelligent management system, comprising: The mall information management module is used to draw a shopping route map and a product distribution map for the mall, and to establish and manage a database containing multiple product information and associated locations.

[0041] The customer positioning and path tracking module is used to locate the customer's position in real time through positioning base stations deployed in various areas of the mall, and generate the customer's movement path in the mall.

[0042] The product information query module is used to scan the product barcode with a barcode scanner in the self-service checkout area and query the corresponding product type and price from the database.

[0043] The path and product area comparison module is used to compare the location coordinates of the product area with the customer's movement path to determine whether the customer has passed through the product area.

[0044] The product density calculation and verification module is used to obtain the product weight and product image, calculate the product volume, and then obtain the actual density of the product. It is then compared with the standard density in the database and the product type is determined to be correct based on the preset error range.

[0045] The cashier settlement and transaction record module is used to calculate the payment amount based on the price and quantity of the goods after confirming that the goods type is correct, display the goods type and price on the cashier interface, provide multiple payment methods for customers to complete the transaction, and record transaction information.

[0046] The present invention provides a method and system for intelligent management of self-service checkouts in shopping malls. By establishing a database containing multiple product information and associated locations, this system provides a solid data foundation for accurate product identification and verification. This allows for verification of products from multiple dimensions during checkout, rather than relying solely on the surface information provided by the barcode.

[0047] The entire solution builds a complete verification chain, from the customer's location and movement within the mall to the physical characteristics of the goods. In traditional self-service checkout systems, once a barcode is successfully scanned, the product is automatically identified as the scanned item, with few subsequent verification mechanisms. This solution, however, determines whether the customer has passed through the area where the product is located, obtains the product's weight and image, calculates the product's volume and actual density, and compares it with the standard density in the database. Through this series of steps, the product type is reconfirmed. If a customer replaces a high-priced product code with a low-priced product code, the system can quickly determine whether there are any errors in the product's settlement information by comparing the product's area with the customer's movement path, as well as the product's actual density with the standard density. This avoids incorrect settlements and protects the merchant's economic interests. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 This is a flow chart of a method for intelligent management of self-service checkout in a shopping mall provided by an embodiment of the present invention; Figure 2 This is a structural diagram of a shopping mall self-service checkout intelligent management system provided by an embodiment of the present invention; Figure 3 It is a structural diagram of an electronic device provided by an embodiment of the present invention.

[0050] Reference numerals: 610 , processor; 620 , communication interface; 630 , memory; 640 , communication bus. DETAILED DESCRIPTION

[0051] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0052] The following combination Figure 1-Figure 3 The present invention describes a method and system for intelligent management of self-service cashiers in a shopping mall.

[0053] Figure 1 The present invention provides a flowchart of a method for intelligent management of self-service checkout in a shopping mall.

[0054] like Figure 1 As shown, an embodiment of the present invention provides a method and system for intelligent management of self-service checkout in a shopping mall. The execution subject can be an intelligent management method for self-service checkout in a shopping mall, and the method includes: Draw a shopping route map and product distribution map for the mall, and establish a database containing multiple product information and associated locations.

[0055] Organize professionals to use measurement tools (such as laser rangefinders and total stations) to accurately measure each area of ​​the mall, recording data such as the mall's length, width, and height, the width and length of each aisle, and the distances between different areas. Obtain the mall's original architectural drawings from the mall's developer or property management department. These drawings contain detailed information such as the mall's structural layout, wall locations, and entrance and exit locations, providing a basic framework for drawing the route map.

[0056] Choose to use professional drawing software, such as AutoCAD, SketchUp, etc. According to the measured and obtained data, draw the general outline of the shopping mall in the software, and mark the main passages, entrances and exits, elevators, escalators and other locations.

[0057] Add various signs to the route map, such as the location of public facilities such as toilets, information desks, and rest areas.

[0058] According to the layout of the mall and customers' walking habits, plan a reasonable shopping route, use different colors or lines to indicate the main and secondary channels, and mark the directions.

[0059] According to the business categories and product characteristics of the mall, formulate reasonable product classification standards, such as clothing, food, home appliances, cosmetics, etc.

[0060] Each major category can be further divided into categories. For example, clothing can be divided into men's clothing, women's clothing, and children's clothing; food can be divided into fresh food, snacks, alcoholic beverages, etc.

[0061] Collect detailed information of all goods in the mall, including product name, brand, specifications, price, etc., and record the storage location of the goods, such as shelf number, floor, area, etc.

[0062] Measure the shelves in the mall, record the size, quantity, arrangement and other information of the shelves, and accurately draw the distribution of goods on the shelves.

[0063] Use professional drawing or graphics software to create a product distribution map based on the shopping path map, based on product classification and storage location. Use different colors or icons to represent different categories of goods, and mark the types of goods sold in each area.

[0064] The product information includes product barcode, product type, product price, product standard density, product specifications, product origin, product production date and shelf life.

[0065] The process of building a database containing multiple product information and associated locations includes: Collect multiple product information of all products in the mall.

[0066] Measure and determine the placement of each product in the mall, and use three-dimensional coordinates (x, y, z) to represent the location of the product, where x and y represent plane coordinates and z represents the vertical height coordinate.

[0067] Build a database table structure with the product barcode as the primary key, and store the product's multiple information and regional location coordinates in the corresponding fields of the database.

[0068] The database is maintained and updated according to the preset cycle. When the product information or placement changes, the corresponding content in the database is modified.

[0069] Positioning base stations are deployed in various areas of the mall to locate the real-time location of customers and generate their movement paths within the mall.

[0070] According to the layout and positioning requirements of the shopping mall, plan the coverage range of the base station to ensure that all areas in the shopping mall are effectively covered.

[0071] Choose a suitable installation location, such as a ceiling or wall, to avoid signal obstruction. Also, consider the base station's power supply and network connectivity. Install the appropriate brackets according to the base station's installation requirements to ensure the base station is securely installed.

[0072] Connect the base station to a stable power source and network to ensure normal operation. For base stations that use wireless transmission, ensure they are well connected to the mall's Wi-Fi network or other wireless communication network.

[0073] After the installation is complete, debug the base station and check parameters such as signal strength, coverage, and communication quality to ensure normal operation of the base station.

[0074] Select a server with stable performance and strong processing power, and determine the server configuration parameters such as CPU, memory, hard disk capacity, etc. according to the scale and positioning requirements of the shopping mall.

[0075] Install the positioning server software, which receives, processes, and analyzes positioning data from the base station. Also, configure the server's network parameters to ensure proper communication with the base station and other related systems (such as the mall management system and data analysis system).

[0076] Develop an app or distribute wristbands: If using a mobile app as a location tag, you'll need to develop a dedicated mall location app and instruct customers to download and install it. If using a location-tracking wristband, you'll need to initialize and configure it, such as setting a unique identification number and binding customer information.

[0077] Test the positioning tag to ensure that it can communicate with the base station normally and send positioning information accurately.

[0078] The process of generating a customer's movement path within a mall includes: N positioning base stations are deployed in the shopping mall, and each positioning base station has a displacement identification number.

[0079] The positioning base station collects the signal strength value of the customer identification device in real time.

[0080] According to the signal strength value, the weighted centroid positioning method is used to calculate the customer's real-time location coordinates. The formula is expressed as: ; ; ; in, represents the weight of the i-th positioning base station, and the formula is expressed as: ; Where, Indicates the customer's real-time location coordinates, represents the location coordinates of the i-th positioning base station, n represents the total number of positioning base stations, Indicates the signal strength value sent by the i-th positioning base station.

[0081] Record the customer's real-time location coordinates in chronological order to form a coordinate sequence of s moments , get the customer’s movement path in the mall.

[0082] A barcode scanner is installed in the self-service checkout area, which can scan the product barcode to query the corresponding product type and price in the database.

[0083] Install the barcode scanner at the self-service checkout counter, ensuring the scanning window is easily accessible to customers and clearly reads product barcodes. Depending on the scanner type and installation location, choose an appropriate mounting method, such as screws or adhesive, to ensure the scanner is securely mounted and prevents movement or displacement during use.

[0084] Connect the scanner to the cash register using a data cable or wireless module, depending on the scanner's connection method. Install the scanner driver and related application software on the cash register and configure the necessary parameters, such as scanning mode and decoding type, to ensure the scanner works properly.

[0085] Extract the regional location coordinates of the product in the database based on the product type, compare them with the customer's movement path, and determine whether the customer has passed through the area where the product is located. The process includes: According to the type of product scanned, query the database for the three-dimensional coordinates of the center position of the product .

[0086] According to the product specifications and product distribution range, the error ranges in the x, y, and z directions are set as follows: 、 、 , then the three-dimensional spatial range of the region is expressed as .

[0087] Traverse the customer's moving path coordinate sequence , for each position coordinate , to determine whether it meets the conditions of three-dimensional space range.

[0088] If one or more real-time location coordinates of the customer are within the three-dimensional space, it is determined that the customer has passed through the area where the product is located.

[0089] If a customer passes by the area where the product is located, the product weight and product image are obtained, the product volume is calculated based on the product image, and the actual density of the product is calculated based on the product weight.

[0090] In this embodiment, the image features of each product can also be associated with the database. When determining whether the product is correct, the product image features are extracted and compared with the feature database, and the similarity is calculated through an algorithm. If the similarity is within a preset reasonable range, the product is determined to be correct; if it is below a threshold, the product may be incorrect and further manual verification is required to ensure the accuracy of product identification.

[0091] The process of calculating product volume based on product images includes: Using stereo vision methods, multiple cameras are used to capture images of products from different angles to obtain multiple sets of image data.

[0092] Use feature matching algorithms (such as SIFT or SURF) to find feature points with the same name in image data at different angles, and calculate the three-dimensional coordinates of these feature points with the same name based on the triangulation principle. Assume that the positions of the two cameras are and , whose coordinates are and The coordinates of the feature points with the same name matched in the two image data in the first image are , the coordinates of the image point in the second image are . Calculate the three-dimensional coordinates of the feature point P according to the triangulation formula : Assume that the focal lengths of the two cameras are and , then: ; ; By solving the above equations together, the three-dimensional coordinates of the feature point P with the same name are obtained.

[0093] Based on the 3D coordinates of the feature points with the same name, the Poisson surface reconstruction algorithm is used to reconstruct the 3D model of the product. The process includes: The three-dimensional coordinates of the feature points with the same name As input data, the normal vector of each feature point with the same name is calculated by calculating the normal direction of the local plane of the neighborhood around the feature point .

[0094] Defining indicator functions , indicator function The value is 1 inside the product and 0 outside the product.

[0095] The normal vector of the feature point with the same name is smoothed by the Gaussian kernel function to obtain the indicator function gradient field , the calculation formula is expressed as: ; In the formula, p represents any point in space, M represents the number of feature points with the same name, It represents the weight of the i-th feature point with the same name, which is determined by the distance from the feature point with the same name to point p. K represents the Gaussian kernel function. and Respectively represent the position and normal vector of the i-th feature point with the same name.

[0096] According to the exponential function gradient field , solve the Poisson equation ,in, represents the Laplace operator, and F represents a scalar field.

[0097] The marching cubes algorithm is used to extract the zero isosurface of the scalar field F on a discrete three-dimensional grid, that is, the point set where F(p)=0, to obtain the three-dimensional model of the product.

[0098] Discretize the 3D model into N cubic units, calculate the volume of the space occupied by the 3D model, and obtain the product volume. The process includes: Place the 3D model in a 3D space grid and divide the grid into N cubic units. The side length of each cubic unit is a. The volume of each cubic unit is .

[0099] For each cube unit, the ray method is used to determine whether it is completely inside the three-dimensional model.

[0100] Count the number Q of all cubic units inside the 3D model, calculate the volume of the space occupied by the 3D model, and get the product volume. The formula is: ; In the formula, V represents the volume of the product, Q represents the number of cube units in the three-dimensional model, represents the volume of each cubic unit, and a represents the side length of the cubic unit.

[0101] The process of calculating the actual density of a product based on its weight includes: Use the electronic scale installed at the self-service checkout counter to measure the weight of the goods.

[0102] The actual density of the product is calculated based on its volume. The formula is: ; Where, Indicates the actual density of the product, m indicates the weight of the product, and V indicates the volume of the product.

[0103] Compare the actual density of the product with the standard density in the database and determine whether the product type is correct based on the preset error range; The actual density of the product is compared with the standard density in the database, and the product type is determined to be correct based on the preset error range. This process involves multiple steps to ensure the consistency of the product type and settlement information. The following is a detailed judgment process: When establishing a database, collect standard density data for each item in the mall. This data can be obtained from product specifications, supplier technical documentation, or specialized databases. Accurately enter the standard density data into the database and associate it with other key product information (such as barcode, name, price, etc.).

[0104] The setting of the error range requires comprehensive consideration of multiple factors, including the accuracy of the measuring equipment, the density fluctuation range of the product itself, and the impact of environmental factors on density measurement.

[0105] Different tolerance ranges can be set for different types of goods based on their characteristics. For example, for goods with relatively stable density and a single ingredient, the tolerance range can be set smaller; while for goods with complex ingredients and large density fluctuations, the tolerance range needs to be appropriately relaxed.

[0106] Using the product barcode as an index, query the database for the product's corresponding standard density data. Ensure that the retrieved standard density data accurately matches the currently measured product information.

[0107] Compare the calculated actual density of the product with the standard density found in the database. Calculate the difference between the two and compare that difference with a preset error range.

[0108] If the difference between the actual density and the standard density is within the preset error range, the product type is determined to be correct. The system can continue with the subsequent settlement process, such as calculating the payment amount and displaying product information.

[0109] If the difference between the actual density and the standard density exceeds the preset error range, the product type may be incorrect. The system should issue an alarm or prompt, prompting staff to conduct further inspection and confirmation. Staff can manually verify the product information to confirm whether the product type is indeed incorrect.

[0110] When the system determines that the product type may be incorrect, staff need to carefully check the product. They can check the product's appearance, packaging, label and other information and compare them with the product information in the database to confirm whether the product type is correct.

[0111] If the product type is correct, the payment amount is calculated based on the product price and quantity, the product type and price are displayed on the checkout interface, and multiple payment methods are provided to complete the transaction and record it.

[0112] The system extracts the unit price of confirmed items from the database and obtains the quantity of each item from scanning or customer input. For each item, the system calculates its total price using the formula "Total price per item = unit price x quantity." The total price of all items is then added together to determine the total amount collected for the transaction.

[0113] The checkout interface features a clear and intuitive layout. The product information display area is presented in a list format, with each row displaying the product name, specifications, unit price, quantity, and total price. The total price display area highlights the total amount of the transaction, using a larger font and eye-catching color for easy viewing. The payment method selection area lists the available payment methods and their icons and descriptions.

[0114] Integrate multiple common payment methods, including but not limited to cash payment, bank card payment, mobile payment (such as WeChat Pay, Alipay), etc. Each payment method has corresponding hardware equipment or software interface support.

[0115] Each payment method has clear instructions and steps on the checkout screen. Once a customer selects a payment method, they'll be prompted accordingly. For example, if they choose WeChat Pay, the system will display a QR code and prompt them to scan it using WeChat to complete the payment. The system will also monitor the payment status in real time, awaiting feedback on the payment result.

[0116] When the payment is successful, the transaction status is immediately updated to "paid", a payment success message is displayed on the cashier interface, and a transaction receipt is printed. The receipt will list the product information, total price, payment method, transaction time, and transaction number in detail.

[0117] If the payment fails, the customer will be informed of the reason for the failure, such as insufficient balance, network abnormality, etc., and the customer will be allowed to reselect the payment method and try again.

[0118] Transaction details, including product information, total payment amount, payment method, transaction time, and transaction number, are stored in the database. A series of data security measures, such as data encryption and access control, are implemented. Transaction records are also regularly backed up and stored on multiple storage media or in different locations to prevent data loss or corruption.

[0119] In summary, this embodiment provides a method for intelligently managing self-service checkouts in shopping malls. By establishing a database containing multiple product information and associated locations, it provides a solid data foundation for accurate product identification and verification. This allows for verification of products from multiple dimensions during checkout, rather than relying solely on the surface information provided by the barcode.

[0120] The entire solution builds a complete verification chain, from the customer's location and movement within the mall to the physical characteristics of the goods. In traditional self-service checkout systems, once a barcode is successfully scanned, the product is automatically identified as the scanned item, with few subsequent verification mechanisms. This solution, however, determines whether the customer has passed through the area where the product is located, obtains the product's weight and image, calculates the product's volume and actual density, and compares it with the standard density in the database. Through this series of steps, the product type is reconfirmed. If a customer replaces a high-priced product code with a low-priced product code, the system can quickly determine whether there are any errors in the product's settlement information by comparing the product's area with the customer's movement path, as well as the product's actual density with the standard density. This avoids incorrect settlements and protects the merchant's economic interests.

[0121] This solution effectively combats fraudulent transactions involving incorrect product codes and creates a fair shopping environment for all customers. Customers no longer need to worry about other customers' fraudulent activities affecting product prices or availability, allowing them to shop with greater peace of mind, increasing their satisfaction and trust in their purchases.

[0122] Based on the same general inventive concept, the present invention also protects a shopping mall self-service checkout intelligent management system. The shopping mall self-service checkout intelligent management system provided by the present invention is described below. The shopping mall self-service checkout intelligent management system described below and the shopping mall self-service checkout intelligent management method described above can be referenced to each other.

[0123] Figure 2 The present invention provides a schematic diagram of the structure of a shopping mall self-service checkout intelligent management system.

[0124] like Figure 2 As shown, a shopping mall self-service checkout intelligent management system includes a shopping mall information management module, a customer positioning and path tracking module, a product information query module, a path and product area comparison module, a product density calculation and verification module, and a cashier settlement and transaction record module.

[0125] The mall information management module is used to draw a shopping route map and a product distribution map for the mall, and to establish and manage a database containing multiple product information and associated locations.

[0126] The customer positioning and path tracking module is used to locate the customer's position in real time through the positioning base stations deployed in various areas of the mall, and generate the customer's movement path in the mall.

[0127] The product information query module is used to scan the product barcode with a barcode scanner in the self-service checkout area and query the corresponding product type and price from the database.

[0128] The path and product area comparison module is used to compare the location coordinates of the product area with the customer's movement path to determine whether the customer has passed through the product area.

[0129] The product density calculation and verification module is used to obtain the product weight and product image, calculate the product volume, and then obtain the actual density of the product. It is then compared with the standard density in the database and the product type is determined to be correct based on the preset error range.

[0130] The cashier settlement and transaction record module is used to calculate the amount of payment based on the price and quantity of the goods after confirming that the goods type is correct, display the goods type and price on the cashier interface, provide multiple payment methods for customers to complete the transaction, and record transaction information.

[0131] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0132] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for intelligent management of self-service cashiers in shopping malls, characterized in that: include: Draw a shopping route map and product distribution map for the mall, and establish a database containing multiple product information and associated locations; Deploy positioning base stations in various areas of the mall to locate customers' real-time locations and generate their movement paths within the mall; Equipped with barcode scanners in the self-service checkout area, by scanning the product barcode to query the corresponding product type and price in the database; Extract the regional location coordinates of the product in the database according to the product type, compare them with the customer's movement path, and determine whether the customer has passed through the area where the product is located; If a customer passes by the area where the product is located, obtain the product weight and product image, build a 3D model based on the product image to obtain the product volume, and calculate the actual density of the product based on the product weight; Compare the actual density of the product with the standard density in the database and determine whether the product type is correct based on the preset error range; If the product type is correct, the payment amount is calculated based on the product price and quantity, the product type and price are displayed on the checkout interface, and multiple payment methods are provided to complete the transaction and record it.

2. A method for intelligent management of self-service cashiers in a shopping mall according to claim 1, characterized in that: The product information includes product barcode, product type, product price, product standard density, product specifications, product origin, product production date and shelf life.

3. A method for intelligent management of self-service cashiers in a shopping mall according to claim 1, characterized in that: The process of building a database containing multiple product information and associated locations includes: Collect multiple product information of all products in the mall; Measure and determine the placement of each product in the mall, using three-dimensional coordinates (x, y, z) to represent the location of the product, where x and y represent the plane coordinates and z represents the vertical height coordinate; Construct a database table structure, using the product barcode as the primary key, and store the product's multiple information and regional location coordinates in the corresponding fields of the database; The database is maintained and updated according to the preset cycle. When the product information or placement changes, the corresponding content in the database is modified.

4. A method for intelligent management of self-service cashiers in a shopping mall according to claim 1, characterized in that: The process of generating a customer's movement path within a mall includes: Deploy n positioning base stations in the shopping mall, each of which has a displacement identification number; The positioning base station collects the signal strength value of the customer identification device in real time; According to the signal strength value, the weighted centroid positioning method is used to calculate the real-time location coordinates of the customer, and the formula is expressed as: ； ； ； in, represents the weight of the i-th positioning base station, and the formula is expressed as: ； Where, Indicates the customer's real-time location coordinates, represents the location coordinates of the i-th positioning base station, n represents the total number of positioning base stations, represents the signal strength value sent by the i-th positioning base station; Record the customer's real-time location coordinates in chronological order to form a coordinate sequence of s moments , get the customer’s movement path in the mall.

5. The method for intelligent management of self-service cashiers in a shopping mall according to claim 1, characterized in that: The process of determining whether a customer has passed through the area where the product is located includes: According to the type of scanned goods, the three-dimensional coordinates of the center position of the goods are searched in the database; According to the product specifications and product distribution range, set the error range in the x, y, and z directions to obtain the three-dimensional spatial range of the area where the product is located; Traversing the customer's movement path coordinate sequence, for each position coordinate, determining whether it meets the conditions of the three-dimensional space range; If one or more real-time location coordinates of the customer are within the three-dimensional space, it is determined that the customer has passed through the area where the product is located.

6. A method for intelligent management of self-service cashiers in a shopping mall according to claim 1, characterized in that: The process of constructing a three-dimensional model based on the product image to obtain the product volume includes: Using stereo vision methods, multiple cameras are used to capture images of products from different angles to obtain multiple sets of image data; Finding feature points with the same name in multiple sets of image data using a feature matching algorithm; Calculating the three-dimensional coordinates of the feature points with the same name using the triangulation principle; Reconstructing a three-dimensional model of the product using a Poisson surface reconstruction algorithm based on the three-dimensional coordinates of the feature points with the same name; The three-dimensional model is discretized into N cubic units, and the spatial volume occupied by the three-dimensional model is calculated to obtain the volume of the product.

7. A method for intelligent management of self-service cashiers in a shopping mall according to claim 6, characterized in that: The process of reconstructing a 3D model of a product using the Poisson surface reconstruction algorithm includes: The three-dimensional coordinates of the feature points with the same name As input data, the normal vector of each feature point with the same name is calculated by calculating the normal direction of the local plane of the neighborhood around the feature point ; Defining indicator functions , the indicator function The value is 1 inside the product and 0 outside the product; The normal vector of the feature point with the same name is smoothed by the Gaussian kernel function to obtain the indicator function gradient field , the calculation formula is expressed as: ； In the formula, p represents any point in space, M represents the number of feature points with the same name, It represents the weight of the i-th feature point with the same name, which is determined by the distance from the feature point with the same name to point p. K represents the Gaussian kernel function. and Respectively represent the position and normal vector of the i-th feature point with the same name; According to the exponential function gradient field , solve the Poisson equation ,in, represents the Laplace operator, and F represents the scalar field; The marching cubes algorithm is used to extract the zero isosurface of the scalar field F on a discrete three-dimensional grid, that is, the point set where F(p)=0, to obtain the three-dimensional model of the product.

8. A method for intelligent management of self-service cashiers in a shopping mall according to claim 7, characterized in that: The process of calculating the volume of space occupied by the three-dimensional model includes: Place the three-dimensional model in a three-dimensional space grid, divide the grid into N cubic units, and the side length of each cubic unit is a. Then the volume of each cubic unit is ; For each cube unit, the ray method is used to determine whether it is completely inside the three-dimensional model; Count the number Q of all cube units inside the three-dimensional model and calculate the volume of space occupied by the three-dimensional model. The formula is expressed as: ； In the formula, V represents the volume of the product, Q represents the number of cube units in the three-dimensional model, represents the volume of each cubic unit, and a represents the side length of the cubic unit.

9. The method for intelligent management of self-service cashiers in a shopping mall according to claim 1, characterized in that: The process of calculating the actual density of a product based on the weight of the product includes: Use the electronic scale installed at the self-service checkout counter to measure the weight of the goods; The actual density of the product is calculated based on its volume. The formula is: ； Where, Indicates the actual density of the product, m indicates the weight of the product, and V indicates the volume of the product.

10. A shopping mall self-service checkout intelligent management system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for intelligent management of self-service checkout in a shopping mall as claimed in any one of claims 1 to 9 is implemented.

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