Settlement and inventory management method and system based on RFID scanning table

Abstract

The invention relates to the technical field of commodity settlement management, and discloses a settlement and inventory management method and system based on an RFID scanning platform, and the method comprises the steps: continuously scanning an RFID tag on a commodity unit, obtaining the commodity positioning information in real time, feeding back the commodity positioning information to a commodity scene digital model, and monitoring the time sequence change of a commodity scene, thereby achieving the settlement and inventory management of the commodity. After initial settlement information is obtained based on an RFID scanning device, accurate settlement is ensured through tracking and verification, commodity layout is optimized through multi-dimensional correlation analysis, inventory management and settlement efficiency is improved, and the method and the device have the advantages of being high in practicability and easy to popularize and use. According to the method, the problems of inaccurate commodity positioning, incomplete settlement verification and insufficient layout optimization are effectively solved, the operation efficiency and customer experience of the unmanned supermarket are improved, and the problem of insufficient settlement accuracy of the unmanned supermarket in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of commodity settlement management, and in particular to a settlement and inventory management method and system based on an RFID scanning station. Background Art

[0002] Unmanned supermarkets are a new business model that has rapidly developed in the retail industry in recent years. Their main feature is the replacement of traditional manual services with automation and digital technologies. Although unmanned supermarkets have significant advantages in improving operational efficiency, reducing costs, and enhancing customer experience, they still have shortcomings in the accuracy of checkout and inventory management, and the real-time tracking of goods. In traditional RFID applications, the positioning and tracking of goods mainly rely on the deployment of RFID scanning equipment. However, existing systems often face problems such as blind spots in RFID tag recognition and signal interference, making it difficult to accurately locate goods within the mall. Especially in large shopping malls, real-time tracking information of goods is subject to delays or errors. In the checkout area, although RFID scanning devices can obtain preliminary checkout information of goods, they usually lack real-time tracking and verification of the goods' location and movement. Customers may place items in the shopping cart but not actually check out, or even lose items. Existing systems cannot fully verify the final checkout information of the goods, leading to potential checkout errors or theft. Summary of the Invention

[0003] The purpose of the present invention is to provide a settlement and inventory management method and system based on an RFID scanning station, aiming to solve the problem of insufficient settlement accuracy in unmanned supermarkets in the prior art.

[0004] The present invention is implemented as follows: In a first aspect, the present invention provides a settlement and inventory management method based on an RFID scanning station, comprising: Continuously scan wireless signals from RFID tags pre-detachably mounted on commodity units to obtain commodity location information fed back by the RFID tags on each commodity unit; Feeding back the commodity positioning information to the commodity scene digital model to provide real-time digital feedback on the commodity scene where the commodity units are arranged; Monitoring the temporal changes of the digital model of the commodity scene to obtain movement characteristics of commodity units in the commodity scene, and tracking and locating the commodity units based on the movement characteristics of the commodity units to obtain tracking and positioning characteristics of each of the commodity units; Based on the RFID scanning device pre-set in the settlement area of the commodity scene, the commodity units entering the settlement area are scanned by wireless signals to obtain initial settlement information; Tracking and verifying the initial settlement information according to the tracking and positioning characteristics of each commodity unit to obtain verified settlement information, and performing settlement processing on the commodity units in the settlement area according to the verified settlement information; Performing a multi-dimensional correlation analysis on the tracking and positioning features of the digital model of the commodity scene and the verification and settlement information to obtain the collaborative settlement correlation of various commodity units in the commodity scene; Based on the collaborative settlement correlation, the layout pattern of commodity units in the commodity scene digital model is optimized and simulated to obtain commodity scene layout optimization suggestions.

[0005] In a second aspect, the present invention provides a settlement and inventory management system based on an RFID scanning station, which is used to implement the settlement and inventory management method based on an RFID scanning station described in any one of the first aspects, comprising: A digital feedback module is used to feed back the commodity positioning information to the commodity scene digital model, so as to provide real-time digital feedback on the commodity scene where the commodity unit is arranged; a tracking and positioning module, configured to monitor the temporal changes of the digital model of the commodity scene to obtain movement characteristics of commodity units in the commodity scene, and to track and position the commodity units based on the movement characteristics of the commodity units to obtain tracking and positioning characteristics of each commodity unit; The initial settlement module is used to scan the commodity units entering the settlement area with wireless signals based on the RFID scanning device pre-set in the settlement area of the commodity scene to obtain initial settlement information; a verification and settlement module, configured to perform tracking and verification processing on the initial settlement information according to the tracking and positioning characteristics of each of the commodity units to obtain verification and settlement information, and perform settlement processing on the commodity units in the settlement area according to the verification and settlement information; A correlation analysis module is used to perform a multi-dimensional correlation analysis on the tracking and positioning features of the digital model of the commodity scene and the verification and settlement information to obtain the collaborative settlement correlation of various commodity units in the commodity scene; The layout optimization module is used to optimize and simulate the layout pattern of commodity units in the commodity scene digital model based on the collaborative settlement correlation to obtain commodity scene layout optimization suggestions.

[0006] The present invention provides a settlement and inventory management method based on an RFID scanning station, which has the following beneficial effects: The present invention continuously scans the RFID tags on the commodity units, obtains the commodity positioning information in real time and feeds it back to the digital model of the commodity scene, monitors the temporal changes of the commodity scene, tracks the movement characteristics of the commodity, realizes accurate positioning and settlement verification, obtains the initial settlement information based on the RFID scanning device, ensures the settlement accuracy through tracking verification, optimizes the commodity layout by using multi-dimensional correlation analysis, improves inventory management and settlement efficiency, effectively solves the problems of inaccurate commodity positioning, incomplete settlement verification and insufficient layout optimization, improves the operating efficiency and customer experience of unmanned supermarkets, and solves the problem of insufficient settlement accuracy in unmanned supermarkets in the existing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 This is a schematic diagram of the steps of a settlement and inventory management method based on an RFID scanning station provided by an embodiment of the present invention; Figure 2 This is a structural diagram of a settlement and inventory management system based on an RFID scanning station provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0008] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0009] The implementation of the present invention is described in detail below with reference to specific embodiments.

[0010] Reference Figure 1 、 Figure 2 As shown, a preferred embodiment of the present invention is provided.

[0011] In a first aspect, the present invention provides a settlement and inventory management method based on an RFID scanning station, comprising: S1: Continuously scan wireless signals from RFID tags pre-detachably mounted on commodity units to obtain commodity location information fed back by the RFID tags on each commodity unit; S2: Feedback the commodity positioning information to the commodity scene digital model to provide real-time digital feedback on the commodity scene where the commodity unit is arranged; S3: monitoring the temporal changes of the digital model of the commodity scene to obtain movement characteristics of commodity units in the commodity scene, and tracking and locating the commodity units based on the movement characteristics of the commodity units to obtain tracking and positioning characteristics of each commodity unit; S4: Based on the RFID scanning device pre-set in the settlement area of the commodity scene, the commodity unit entering the settlement area is scanned by wireless signals to obtain initial settlement information; S5: performing tracking and verification processing on the initial settlement information according to the tracking and positioning characteristics of each of the commodity units to obtain verified settlement information, and performing settlement processing on the commodity units in the settlement area according to the verified settlement information; S6: Performing a multi-dimensional correlation analysis on the tracking and positioning features of the digital model of the commodity scene and the verification and settlement information to obtain the collaborative settlement correlation of various commodity units in the commodity scene; S7: Based on the collaborative settlement correlation, the commodity scene digital model is optimized and simulated in terms of the layout pattern of the commodity units to obtain a commodity scene layout optimization suggestion.

[0012] Specifically, in step S1 of the embodiment provided herein, an RFID tag is pre-installed on each unit of merchandise when the merchandise is produced or put into storage. This RFID tag is typically a radio frequency identification device that stores a unique identifier and other relevant information about the merchandise (such as model, production date, price, etc.). The RFID tag should be removable to ensure easy removal and replacement when the merchandise is sold or the scene is updated, adapting to dynamic merchandise layout and inventory management requirements. An RFID scanning device (such as a scanning platform or sensor installed in the merchandise scene) periodically scans the RFID tags on the merchandise units using wireless signals. These RFID scanning devices typically operate within a specific frequency range and wirelessly communicate with the RFID tags. The scanning device continuously transmits electromagnetic wave signals to the merchandise units and waits for the tag's response. When the tag responds, it feeds back its stored merchandise information to the scanning device via wireless signals.

[0013] More specifically, after receiving the feedback signal from the RFID tag, the scanning device extracts the product information contained therein and infers the location of the product through positioning technology (such as a multi-antenna array or a combination of multiple RFID readers). By continuously scanning and combining the feedback data of multiple RFID devices in the environment, the specific location of each product unit can be obtained, thereby realizing real-time tracking of all product units in the product scene. The received product positioning information is associated with other information in the product database for real-time data processing. The system will update the location status of the product and form a dynamic product scene model in the system to display the real-time distribution and inventory status of the product. These positioning information not only includes the current location of the product, but may also include the historical trajectory and movement path of the product, which is helpful for analyzing the flow pattern and storage efficiency of the product.

[0014] It is understandable that through continuous wireless signal scanning, RFID tags can provide real-time product positioning information, thereby realizing accurate tracking of product units in the product scene. The system can grasp the location of the product at any time, greatly improving the accuracy of inventory management. Whether it is the static position of the product or the dynamic movement path, it can be captured and updated in real time, supporting more efficient warehouse and store management. Through the scanning and position feedback of RFID tags, inventory data is more real-time and accurate, reducing errors and omissions in manual inventory. The system can automatically detect out-of-stock, slow-selling or expired products and make timely adjustments. In inventory counting, inventory query, product allocation and other operations, RFID technology makes operations faster and more efficient.

[0015] Specifically, in step S2 of the embodiment provided by the present invention, RFID tags are pre-installed on commodity units, and the positioning information of each commodity unit is obtained by wireless signal scanning. The scanning device periodically obtains signal feedback from the RFID tag and extracts the commodity information and location information contained therein (such as the coordinates, ID, category, etc. of the commodity). This information is transmitted to the central control system or database via wireless communication for further processing and analysis. The collected commodity positioning information is processed, including location coordinates, commodity type, quantity, etc., and converted into a format that can be used in the digital model. This data will be mapped with the actual physical environment of the commodity scene. The processed data will generate a real-time status diagram of the commodity scene in a digital manner, forming a highly accurate and dynamically changing digital model. The model not only shows the location of the commodity, but also reflects the status of the commodity (such as inventory, sales status, activity status, etc.).

[0016] More specifically, in the digital model, the product scene is broken down into multiple virtual space units (such as shelves, display areas, inventory areas, etc.). The location of each product unit is identified by a coordinate system, and the RFID positioning data of each product unit is updated in real time to the digital model to ensure that the virtual space model is synchronized with the real scene. Based on the product positioning information, the system will automatically update the product scene model to display the latest status and layout of the product. This process usually involves real-time data exchange between actual hardware (such as RFID readers and sensors) and software (such as product management systems and warehousing systems).

[0017] More specifically, the digital model provides real-time feedback on the location, status, inventory and other information of commodity units, and provides a dynamically updated visual commodity scene diagram. This information may be presented to administrators, staff or customers through a visual interface, such as through a computer display or mobile device. The system generates digital feedback based on the real-time status of the commodity, including the current distribution of the commodity, inventory changes, commodity sales, etc. This feedback helps managers understand the real-time status of the commodity scene and make adjustments according to demand. The digital model of the commodity scene can not only provide real-time feedback on the status of the commodity, but also optimize the commodity layout through data analysis. The management system can analyze the liquidity, demand forecast and consumer preferences of the commodity based on real-time positioning information, and thus make real-time adjustments to the layout of the commodity. For example, some commodities may need to be rearranged to a more conspicuous location due to high customer demand, and these adjustments can be made automatically or manually through the digital model.

[0018] It is understandable that by feeding back the product positioning information to the digital model of the product scene, managers can monitor the location and status of the product in real time. The digital model of the product scene will be continuously updated to ensure that the model always reflects the actual situation, greatly improving the real-time nature of scene management. This real-time feedback ensures that the layout and inventory status of the product scene can be updated in the shortest time, providing accurate data support. The digital model of the product scene makes inventory management more accurate and efficient. Managers can view the location, status and remaining quantity of each product, and adjust inventory and product display in a timely manner. Through the digital model, the system can predict the replenishment needs of the product, automatically generate replenishment instructions or adjust the placement of products, thereby improving the automation and accuracy of inventory management.

[0019] More specifically, digital models can analyze the synergy between products, customer flow paths, and product sales trends, thereby providing real-time optimization suggestions for product layout. Managers can adjust the layout of products based on digital feedback to improve product visibility and sales opportunities. By analyzing which products are less visited or sold, the system can propose improvement measures, such as repositioning products, increasing promotional activities, etc. The digital model of the product scene is not only effective for managers, but also provides customers with an interactive experience. For example, customers can scan products through mobile devices to obtain real-time inventory information, price changes, recommended products, etc. This intelligent experience can improve customer satisfaction, enhance their shopping experience, and increase sales opportunities.

[0020] More specifically, the system enables automated decision-making based on real-time digital feedback from product scenarios. For example, when inventory levels for a particular product fall below a threshold, the system automatically issues a restocking reminder or prompts to rearrange the product, reducing manual intervention and decision-making errors. Through the digital platform, managers can easily make data-driven decisions, improving management efficiency and reducing human error. Product location information in the digital model can enhance the security of the scenario. For example, the location and status of an item can be linked to the monitoring system. When an item leaves a designated area, the system can promptly issue an alarm, effectively reducing theft. The combination of real-time feedback from RFID tags and the digital model provides an additional layer of product security.

[0021] Specifically, in step S3 of the embodiment provided by the present invention, based on the commodity positioning information obtained by continuous wireless signal scanning, the system records the location data of each commodity unit at different times in a time series. These data are dynamically written into the digital model of the commodity scene. The model not only contains the current state, but also retains the history of commodity location changes over a period of time. A timestamp mechanism is established to record the moment of each commodity positioning, and multiple RFID scans are used to form a "time-location" data stream.

[0022] More specifically, a differential analysis is performed on the "time-position" sequence of each product unit (i.e., the change in position between adjacent moments) to determine movement characteristics such as whether the product has moved, the direction of movement, speed, and frequency. For example, if product A is at coordinates (x1, y1), (x2, y2), and (x3, y3) at 10:01, 10:02, and 10:03, respectively, the system calculates the position differential and determines whether there is a movement trend. Identifiable features include: movement path (trajectory), whether it is frequently moved (heat index), and identification of dwelling areas (where a customer browses and then puts it back to its original location). More specifically, the aforementioned movement features are used to connect the trajectories of commodity units within the scene to form a complete movement path and state evolution sequence. The tracking mechanism ensures that even in the case of partial signal loss or obstruction, the location of the commodity can be inferred from the trajectories at previous and subsequent moments (such as based on Kalman filtering, trajectory prediction and other algorithms). The system also generates a unique tracking and positioning feature code for each commodity unit for subsequent data matching, behavior analysis and anti-theft monitoring.

[0023] More specifically, the system monitors the behavior patterns of commodity units through continuous time series data and identifies the following situations: abnormal movement (such as commodities entering non-open areas), frequent movement without settlement, and long periods of non-movement (inventory backlog warning). Based on these changes, the system updates the commodity's status, location, popularity and other indicators in real time.

[0024] It is understandable that the entire process of commodity units from entry to settlement is tracked, and the trajectory is visualized, which greatly improves the visualization and management granularity of commodities. Even in non-settlement areas or when there is no one operating, the system can determine whether the commodity has been illegally moved or lost through historical trajectories. Commodities are not "static existence" but "dynamic entities". Through the time series model system, the behavioral changes of inventory commodities can be understood, and accurate predictions can be made on which commodities need to be replenished, rearranged or promoted.

[0025] More specifically, the movement characteristics of goods can also indirectly reflect customer paths and focus points, providing data support for optimizing shelf placement and the layout of hot and cold areas. It can realize the superimposed analysis of "customer movement lines" and "goods heat maps". If a product disappears from the scene without passing through the checkout area, or moves to an unauthorized area, an alarm can be triggered immediately, and the behavior can be reviewed in combination with camera data.

[0026] More specifically, based on data such as a product's movement frequency, dwell time, and return rate, we can determine the product's attractiveness and decision-making hesitation points, and thus infer the product design or marketing strategy.

[0027] Specifically, in step S4 of the embodiment provided by the present invention, RFID scanning devices (usually RFID readers) are pre-installed in the settlement area (such as the cash register, settlement channel, automatic settlement area, etc.). These devices must cover every entrance and exit and important location of the settlement area. Each commodity unit is pre-installed with an RFID tag, which contains the unique identification code (UID) of the commodity, commodity category, price, inventory status and other information.

[0028] More specifically, when a commodity unit (with an RFID tag) enters the settlement area, the RFID scanning device automatically detects the wireless signal emitted by the commodity tag. The scanning device communicates with the commodity tag through radio frequency (RF) signals and reads the commodity information stored in the tag. Through the reflection and reception of the wireless signal, the RFID reader identifies and records each commodity unit entering the settlement area.

[0029] More specifically, the product information read by the scanning device from the product tag includes: product ID (unique identifier), product name / category, product price, and other relevant attributes of the product (such as weight, size, brand, etc.). The system will match this information with the inventory management system to ensure the accuracy of the product information and generate pre-settlement data for the product.

[0030] More specifically, after reading the product information, the RFID scanning device transmits the information to the settlement system or payment system. The system will automatically record the product information and prepare for payment. The settlement information is usually summarized with the products in the shopping cart, the total amount is calculated, and a payment interface is provided to the customer (whether it is cash payment, credit card, mobile payment, etc.). The system can automatically handle discounts, coupons, points redemption, etc. based on the product information obtained in real time.

[0031] More specifically, information from the checkout process is fed back to checkout staff or customers in real time. Customers can view their checkout details through self-service checkout devices, cashiers, or self-service payment systems. Before payment, the system verifies that all items have been scanned and correctly priced. If any items are missing, the system will issue a warning or prompt to ensure the integrity of the checkout information.

[0032] More specifically, after payment is completed, the RFID scanning device will reconfirm that the goods have been settled, record the outbound shipment, remove the goods from the inventory, and update the inventory data synchronously. At the same time, if necessary, an electronic receipt will be automatically generated after the payment is successful, and the customer can choose to print it or obtain it through the mobile phone.

[0033] It is understandable that the use of RFID scanning devices to automatically detect goods eliminates the need for manual barcode scanning or manual entry of product information, greatly improving the efficiency of the settlement process. Through the linkage between RFID tags and scanning devices, the system can obtain product information in real time, reducing errors or missed scans in manual operations. The product information stored in RFID tags is unique and accurate, ensuring the accuracy of information at settlement (such as product price, inventory status, category, etc.), avoiding errors that may occur during manual entry, and reducing price differences, repeated scanning or loss of products.

[0034] More specifically, customers do not need to wait for the cashier to scan the items one by one. The entire checkout process can be completed in seconds, which greatly improves the customer's checkout experience. During peak hours, RFID technology can effectively alleviate queuing pressure and improve customer satisfaction. Whenever an item enters the checkout area, the RFID scanning device reports the item information to the background system in real time, and the inventory data will be updated immediately to ensure the real-time accuracy of the item inventory data. After the payment is completed, the item outbound information will also be updated in real time, further improving the automation and transparency of inventory management.

[0035] More specifically, automated scanning reduces manual intervention in the settlement process, reduces human errors and operating costs, and the system can detect in real time whether goods are missed or errors occur, thereby ensuring the accuracy of the settlement process. The RFID scanning device in the settlement area can not only record product information, but also enhance the anti-theft function. Goods that have not passed the scanning of the settlement device cannot be smoothly taken out of the settlement area, thereby effectively preventing theft. During settlement, the system can verify in real time whether the goods have been fully settled. If unsettled goods are found, the system will promptly alarm or prompt staff to handle it.

[0036] Specifically, in step S5 of the embodiment provided by the present invention, when the commodity unit enters the settlement area, the RFID scanning device will automatically scan the commodity and transmit the unique identification information of the commodity (such as commodity ID, price, quantity, etc.) to the background system to generate initial settlement information. This initial settlement information will include commodity ID, commodity price, commodity type, etc. as the basic data for settlement.

[0037] More specifically, the movement trajectory and positioning characteristics of each commodity unit in the settlement area will also be tracked in real time through RFID devices and other sensors (such as cameras, sensor networks, etc.). The tracking and positioning characteristics include the time-space changes of the commodity, such as the path of the commodity from the shelf to the settlement area, the residence time, and the movement situation. These tracking information usually include: the time when the commodity enters the settlement area, the residence time of the commodity in the settlement area, the movement trajectory of the commodity (whether it is taken away or put back by others in the middle), and whether the commodity has been scanned once during settlement.

[0038] More specifically, the system verifies the initial settlement information based on the tracking and positioning characteristics of the goods in the settlement area. That is, the system checks whether any goods have been missed, scanned incorrectly, or have not been verified in the settlement area. The system will verify whether the movement of each unit of goods is in line with expectations and ensure that they have all entered the settlement area. If the time the goods stay in the settlement area is abnormal (such as too long or too short), the system may prompt that the settlement information is incorrect. If the goods have not been scanned during settlement (that is, they have not entered the settlement area), the system will automatically alarm or remind you to avoid missed scans.

[0039] More specifically, during the tracking and verification process, the system will correct the initial settlement information based on the actual location and movement trajectory of the goods to eliminate potential errors. Once the tracking and positioning features of all goods are verified and successfully compared with the initial settlement information, the system will generate verified settlement information. The verified settlement information includes an accurate list of goods, prices, quantities and other relevant attributes, and ensures that all goods units have been correctly settled.

[0040] More specifically, once the settlement information is verified and confirmed to be correct, the system will proceed with the final settlement processing. The system will calculate the total amount based on the verified settlement information, including possible discounts, coupons, etc. The system will generate a payment interface, and customers will pay through mobile payment, card swiping, cash, etc. After the payment is completed, the system will update the inventory, remove the settled items, and generate an electronic receipt or print a paper receipt.

[0041] More specifically, if the system detects a discrepancy between the tracking information for an item in the checkout area and the initial checkout information (e.g., an item has entered the checkout area without being scanned), it will immediately issue an alarm or flag the item as "abnormal." For identified anomalies, the system will automatically pause checkout and prompt staff for manual review. Staff can then review the item's tracking history and rescan the item to ensure the accuracy of the checkout information.

[0042] It is understandable that accurate product tracking and positioning can monitor the behavior of products entering the settlement area in real time, ensure that each product is scanned in the settlement area, and avoid missed scans. By combining RFID and the movement trajectory of the product, the system can verify whether the product enters the settlement area according to the correct process, avoiding problems such as incorrect scanning and repeated scanning. The verification of tracking and positioning features can help correct any inaccuracies or missing parts in the settlement information, ensuring that each product is settled according to the actual situation. For example, if the product is taken from the shelf but does not pass the scan of the settlement area, the system will prompt in time to avoid paying for unsettled products or missing unpaid products.

[0043] More specifically, the system can obtain and process the tracking and positioning data of goods in real time, reducing the intervention of manual operations and improving the degree of automation of settlement. Efficient tracking and verification can quickly identify and solve problems, reduce the waiting time of customers and staff, and increase the settlement speed. Through accurate settlement information verification and settlement speed improvement, the customer's settlement experience is significantly improved. Customers do not need to wait for too long, the settlement process is smoother, and the number of erroneous settlements and missed settlements is reduced, making customers more confident in the settlement process and increasing customer satisfaction.

[0044] More specifically, real-time tracking and verification of settlement information ensures the accuracy of inventory data. After goods are settled, the system automatically updates inventory, reducing inventory discrepancies. Product movement and settlement information is recorded and updated, providing merchants with more accurate inventory management data. By matching tracking location information with settlement data, the system can detect any abnormal behavior, such as an item attempting to leave the checkout area without being scanned, and promptly issue an alarm. This not only helps prevent settlement errors but also enhances anti-theft capabilities, minimizing the risk of stolen goods.

[0045] More specifically, by tracking and verifying the data collected by the system, merchants can conduct further sales data analysis, product behavior analysis, etc. The system can provide in-depth analysis on product flow, settlement efficiency, etc., helping merchants make more targeted marketing and inventory management decisions.

[0046] Specifically, in step S6 of the embodiment provided by the present invention, digital technology (such as 3D modeling, AR, sensors, etc.) is used to create a virtual model of the product scene. This model will include elements such as the location, layout, settlement area, and customer behavior path of the product. The model not only includes the location of the product, but also involves the category, brand, price range, popularity, promotional information, etc. of the product. This information is crucial for subsequent analysis. Each product is equipped with an RFID tag that can record the product's unique identification code, warehousing time, sales status, settlement information, etc. The RFID information of the product is combined with the location data in the digital model of the product scene to form a digital product file. The status and location of the product can be tracked in real time through the digital model.

[0047] More specifically, RFID scanning devices, cameras, sensors and other technologies are used to monitor the movement trajectory, residence time, and transfer between shelves of goods in real time. From the time a product enters the store to the time it reaches the checkout area, every movement is recorded and associated with the tracking and positioning characteristics of the product. Dynamic information about the product in the scene is recorded, such as the frequency of the product's appearance, coexistence mode with other products, and the interaction between the product and customers. Information such as the adjacency of the products, combination sales, and placement methods will also be taken into account for subsequent analysis.

[0048] More specifically, through RFID devices, the settlement information of each product in the settlement area is obtained, including product ID, price, quantity, payment method, etc. The system will record the timestamp of settlement, the quantity and price of the product, the customer's payment method, etc. to ensure the accuracy of the settlement data, and associate the tracking and positioning characteristics of the product with the settlement information to ensure that the settlement information is consistent with the actual location, movement path and other data of the product.

[0049] More specifically, multi-dimensional analysis standards are selected, such as: product category, price range, promotional activities, customer behavior, settlement time, product combination sales, product residence time, etc., and the collaborative relationship of products in the settlement area is analyzed according to different dimensions. Product combination analysis is based on the frequency of appearance of products in the settlement area and settlement information, analyzing which products are often settled together and whether there is a pattern of bundling sales or common matching. Customer behavior pattern analysis is based on customer purchasing behavior, analyzing which product units are more likely to be purchased together by customers and whether there is a matching trend for certain specific products. Product liquidity and settlement efficiency analysis is based on the relationship between product liquidity and customer settlement efficiency, to understand which products have a longer settlement time and may need to optimize the placement or promotion strategy of the products. Hot-selling products and settlement association analysis is based on the relationship between hot-selling products and settlement areas, to find out which hot-selling products have high collaborative settlement, and to help merchants make more accurate strategies when promoting sales.

[0050] More specifically, visualization tools (such as charts, heat maps, flow diagrams, etc.) are used to demonstrate the collaborative settlement relationship between products. Settlement data is combined with product tracking and positioning data to generate interactive heat maps that show the purchase trends and settlement linkages between different products. This shows which products are most often settled together, which products have a longer settlement time, and which products are often ignored by customers. Based on the analysis results, a detailed analysis report is generated, and decision-making support is provided, such as suggestions on how to optimize product layout, adjust promotion strategies, and improve settlement efficiency.

[0051] More specifically, based on the results of correlation analysis, merchants can adjust product layout, inventory management, promotional activities, etc. in real time. Through continuous data monitoring and analysis, they can optimize the placement of products and the settlement process, thereby improving the customer purchasing experience. As settlement data accumulates, the system can continuously learn and optimize, gradually identifying more refined product collaborative settlement models, and providing long-term data support and decision-making recommendations.

[0052] It is understandable that through multi-dimensional analysis, merchants can gain an in-depth understanding of the collaborative settlement relationship between different commodities, revealing which commodities are usually purchased together, so as to design more effective promotional activities, bundling sales or location optimization strategies, identify potential opportunities for commodity combinations, increase the merchant's overall sales volume and customer purchase unit price, analyze the correlation between commodities and settlement areas, and help optimize the placement of commodities, so that customers can find the commodities they need more quickly and reduce waiting time at settlement. By analyzing the settlement time, merchants can optimize the design or process of the settlement area, improve settlement efficiency, and thus improve customer satisfaction.

[0053] More specifically, based on the collaborative settlement analysis of goods, merchants can more accurately predict which goods will have high sales demand in the future, thereby optimizing inventory management and reducing inventory backlogs or out-of-stocks. When making dynamic inventory adjustments, the system can adjust the order quantity, shelf location and promotion strategy of goods based on real-time analysis results. Through visual data analysis, merchants can more intuitively understand the interactive relationship between goods and make more accurate pricing, promotion and inventory decisions. Through data-driven decision support, merchants can quickly respond to market changes, adjust strategies and improve business efficiency.

[0054] More specifically, merchants can flexibly adjust their marketing strategies based on the collaborative settlement model of goods, such as regularly launching bundled sales, coupon-matching products, and guiding customers to purchase related products, to enhance customers' desire to buy. The system can continuously optimize product display, customer shopping paths and settlement experience based on continuous data analysis results, thereby achieving continuous business growth and improved customer stickiness.

[0055] Specifically, in step S7 of the embodiment provided by the present invention, based on the previous digital model of the commodity scene, the location information, category, size, inventory data, settlement information, etc. of the commodity are collected and organized. The model should include the specific location of the commodity, the spatial relationship between commodities, commodity classification, brand, price range, promotional information, etc. Based on the existing commodity collaborative settlement correlation analysis, the collaborative purchasing pattern of commodities, commodity matching situation, settlement information of hot-selling commodities, etc. are collected and organized, and the data such as the collaborative settlement frequency between commodities, purchase matching trends, and customer purchase paths are summarized.

[0056] More specifically, the core goal of optimizing the merchandise unit layout model is to enhance the collaborative settlement between commodities, improve the convenience of customer purchases and settlement efficiency. Specific goals include: improving the purchase linkage between commodities, placing commodities that are often purchased together as close as possible, improving the convenience of purchase, and reducing the customer's shopping path. Commodity layout should minimize the time required for customers to find commodities, improve shopping efficiency, improve settlement efficiency, optimize the layout of commodities in the settlement area, reduce congestion during the settlement process, and shorten the settlement time.

[0057] More specifically, the available layout space is determined based on the actual size of the product display area. Based on the type, quantity, size and other characteristics of the products, ensure that the optimized layout meets sales needs without causing congestion. Customers' shopping habits, flow paths, dwell time and other behavioral characteristics will affect the final layout design. The available inventory quantity and the timeliness of promotional strategies may affect the priority of product placement.

[0058] More specifically, simulation tools integrated in the digital model of the commodity scene (such as physical simulation, virtual reality, augmented reality, etc.) are used to simulate different layout schemes. During the simulation, factors such as the relative position of commodities, customer flow paths, and congestion in the settlement area are taken into consideration. Multiple rounds of testing and optimization are carried out, and algorithms suitable for commodity layout optimization are adopted, such as: genetic algorithm: used to solve the combinatorial optimization problem of commodity placement, and continuously find the optimal solution through multi-generation evolution; simulated annealing algorithm: find the optimal commodity layout scheme by simulating the physical annealing process; particle swarm optimization algorithm: find the optimal layout by simulating the search process of multiple particles in space; data-based recommendation algorithm recommends the placement pattern of high-frequency linked purchase commodities according to the collaborative settlement analysis results, designs a multi-objective optimization function, and combines the collaborative settlement frequency of commodities, customer mobility, physical distance between commodities, settlement efficiency and other factors, and uses this as the objective function for optimization calculation.

[0059] More specifically, based on the merchandise layout plan obtained by the optimization algorithm, a virtual simulation is performed in the digital model to observe the merchandise display effect, customer shopping path, and smoothness of the checkout area under different layout plans. The simulation results are used to evaluate the impact of each merchandise layout plan on the customer's purchase path, shopping experience, and checkout efficiency. The simulation results are compared with actual sales data to verify the effectiveness of the optimized layout plan. Combined with customer feedback and actual on-site conditions, the layout plan is adjusted and optimized.

[0060] More specifically, it outputs an optimized merchandise layout diagram, indicating the specific location of each merchandise, the display area, the relative relationship between merchandise, and other information. It integrates the merchandise layout with information such as the customer's travel path and the checkout area, generates a detailed layout optimization report, and outputs optimal layout suggestions for promotional merchandise, hot-selling merchandise, and matching merchandise. It also provides specific layout implementation plans, including adjustments to the physical space, the order and location of merchandise placement, and adjustments to the checkout area. It also provides merchants with promotional strategy suggestions. For example, for high-frequency matching merchandise in promotional activities, a more conspicuous location can be designed to increase the chance of purchase.

[0061] It is understandable that by optimizing the layout of merchandise units, the collaborative settlement of merchandise can be improved, increasing the probability of customers making joint purchases. Placing goods that are often purchased together together not only increases the product's exposure, but also stimulates customers' desire to buy, thereby improving overall sales efficiency. The display and location of goods will directly affect customer choices. The optimized layout can effectively promote the sales of hot-selling and promotional goods. After the merchandise layout is optimized, the customer's shopping path in the store will be smoother, reducing the time required for customers to find goods. Through effective path design, customers can easily find their target products, improving their shopping experience. The optimized layout will reduce the congestion of goods, avoid excessive congestion in the checkout area, and improve customers' comfort and satisfaction at checkout.

[0062] More specifically, by optimizing the layout of the settlement area, reducing interference factors in the commodity settlement process, and optimizing the customer's settlement path, the settlement efficiency is improved, the customer's waiting time is reduced, and the overall operational efficiency of the mall is improved. Reasonable commodity placement can also improve the work efficiency of the checkout staff and reduce settlement errors or delays caused by commodity accumulation. The optimization of commodity layout can not only improve sales and customer experience, but also effectively reduce inventory management and logistics allocation costs. Through a reasonable layout, inventory display can be optimized and backlog of goods can be reduced. Layout optimization can reduce the number of times goods are moved, simplify the shelving and replenishment process of goods, and reduce the labor costs of merchants.

[0063] More specifically, after initial optimization, merchants can continuously adjust the layout through real-time data feedback and customer behavior monitoring to continuously improve the efficiency and effectiveness of product display. The optimized layout can provide merchants with continuous sales and customer behavior data analysis support, helping merchants dynamically adjust strategies based on market changes and customer needs.

[0064] The present invention provides a settlement and inventory management method based on an RFID scanning station, which has the following beneficial effects: The present invention continuously scans the RFID tags on the commodity units, obtains the commodity positioning information in real time and feeds it back to the digital model of the commodity scene, monitors the temporal changes of the commodity scene, tracks the movement characteristics of the commodity, realizes accurate positioning and settlement verification, obtains the initial settlement information based on the RFID scanning device, ensures the settlement accuracy through tracking verification, optimizes the commodity layout by using multi-dimensional correlation analysis, improves inventory management and settlement efficiency, effectively solves the problems of inaccurate commodity positioning, incomplete settlement verification and insufficient layout optimization, improves the operating efficiency and customer experience of unmanned supermarkets, and solves the problem of insufficient settlement accuracy in unmanned supermarkets in the existing technology.

[0065] Preferably, the step of continuously scanning the wireless signals of the RFID tags pre-detachably mounted on the commodity units to obtain the commodity location information fed back by the RFID tags on each commodity unit includes: S11: activating the RFID scanning unit of each detection location node pre-set in the commodity scene, causing the RFID scanning unit of each detection location node to continuously scan the corresponding target detection area for wireless signals to obtain regional RFID detection data of the target detection area corresponding to each detection location node; wherein the regional RFID detection data includes identification data of the RFID tags on the commodity units arranged in the target detection area, and the identification data of the RFID tags is used to register commodity information of the commodity units detachably provided with the RFID tags; S12: Analyzing the region overlap status of each of the target detection areas based on the relative positional relationship between the detection location nodes provided with RFID scanning units and the detection performance of the RFID scanning units provided at each of the detection location nodes to obtain region overlap status characteristics of each of the target detection areas; S13: performing a commodity unit layout relationship analysis on the RFID detection data collected by each RFID scanning unit based on the area overlap characteristics of each target detection area to obtain commodity positioning information of each commodity unit in the commodity scene.

[0066] Specifically, in the commodity scene, it is first necessary to activate the RFID scanning units set at each detection position node. These scanning units are usually installed in key locations of the store, such as shelves, ceilings, door frames, etc., so as to cover the detection area of the entire commodity scene. Each RFID scanning unit is responsible for scanning a specific target detection area to ensure that each commodity location is monitored. The activated RFID scanning units will perform continuous wireless signal scanning on their corresponding target detection areas, which means that each scanning unit will periodically send radio frequency signals and receive signals fed back by all RFID tags in the area, ensuring that the signals fed back by the RFID tags on each commodity unit are obtained in real time to form a data stream.

[0067] More specifically, regional RFID detection data includes the identification data of all RFID tags within the target detection area. This data includes the unique ID of the RFID tag, the identification of the product, the tag location and other information. The RFID tag data of the product unit is associated with the product information to realize the registration and real-time update of product information. According to the scanned RFID tag identification data, the corresponding product information (such as product name, price, inventory quantity, etc.) is registered and saved in the database to form a digital information file of the product, realize the automatic tracking and management of the product, and improve the efficiency of product management.

[0068] More specifically, since the RFID scanning unit has a certain coverage range, the coverage areas of different scanning units may overlap. Based on the relative position relationship and performance of the RFID scanning units, the regional overlap status of the target detection area is analyzed, and the overlap of different areas is evaluated to ensure that the scanning unit covers no blind spots, while avoiding repeated detection or missed detection. Based on the regional overlap status, the characteristics of each target detection area are extracted. For example, some areas may have more overlaps, indicating the intersection of signals from multiple scanning devices; some areas may have blind spots or weak signal areas, which need to be adjusted to provide data support for subsequent layout optimization, ensure the optimal layout of the RFID scanning unit, and avoid information loss.

[0069] More specifically, based on the characteristics of regional overlap, the RFID data collected by the RFID scanning unit is analyzed to determine the layout relationship of the commodity units in the scene. By combining the actual location of the commodity, the identification data of the commodity label and the analysis of regional overlap, the precise positioning of the commodity in the commodity scene is constructed, the actual position of each commodity unit in the entire scene is obtained, and the placement and layout of the commodities are optimized.

[0070] More specifically, through data processing and analysis, the accurate positioning information of the product is ultimately output, for example, the location coordinates of the product are displayed, or the positioning information is presented digitally to the management system or other user systems, providing real-time and accurate product positioning information, and providing support for product management, inventory updates, customer service and other aspects.

[0071] It can be understood that through the continuous signal scanning of the RFID scanning unit, the data feedback from the RFID tag of each commodity unit can be obtained in real time, so as to accurately grasp the position of the commodity in the entire commodity scene. This method does not rely on manual operation or customer scanning, ensuring that the positioning data of the commodity is real-time and efficient, realizing high-precision commodity tracking and real-time updates, and obtaining commodity location and inventory data in real time, which can help merchants monitor the flow status of commodities at any time. For example, merchants can accurately understand whether a certain commodity has been taken away, whether it is in inventory, or whether it needs to be replenished, realizing automated inventory management and reducing the cost and time of manual inventory.

[0072] More specifically, by analyzing the overlapping conditions and layout relationships of the regions, merchants can obtain the optimal layout plan for commodity units. For example, they can reasonably adjust the position of commodities according to the customer's behavior path, the flow of hot-selling commodities, etc., improve sales and customer experience, optimize the display effect of commodities, and improve the display efficiency of commodities and the customer's purchasing experience. Due to the wireless scanning characteristics of RFID technology, merchants can obtain commodity information without manually scanning commodities or frequently adjusting the position of commodities, which makes commodity information collection more efficient, real-time and seamless. Technical effect: Improves the efficiency and accuracy of commodity information collection, reduces human errors and operating costs.

[0073] More specifically, within the system, RFID tag identification data enables the automatic registration, updating, and management of product information without manual intervention. This helps reduce inventory counts and information updates, automates the management and rapid updating of product information, and improves the accuracy and timeliness of product management. Precise product location and real-time information updates provide customers with a more efficient shopping experience, enabling them to quickly find products of interest, improving shopping convenience and satisfaction, increasing shopping efficiency, and increasing customer satisfaction with their purchase experience. By collecting and analyzing RFID tag detection data, merchants can make more informed decisions based on this data, such as product adjustments, layout optimization, and promotional strategies. These decisions contribute to the long-term operational optimization of merchants, providing data-driven intelligent decision-making support and helping them achieve refined management and continuous optimization.

[0074] Preferably, the step of feeding back the commodity positioning information to the commodity scene digital model to provide real-time digital feedback of the commodity scene where the commodity units are arranged includes: S21: Pre-constructing a digital model of a commodity scene for digitally simulating the commodity scene according to layout information of the commodity scene; S22: dividing the commodity scene digital model into target detection areas according to each of the RFID scanning units and the corresponding detection position nodes, so as to divide model areas corresponding to the target detection areas on the commodity scene digital model; S23: constructing a digital model of the commodity unit for the corresponding model area in the commodity scene digital model according to the commodity positioning information of each commodity unit, so as to obtain a unit model of each commodity unit; S24: Assign unit information to the unit model according to the commodity information of the commodity unit, so that the unit model and the commodity unit have consistent commodity information, thereby enabling the commodity scene digital model to provide real-time digital feedback on the commodity scene where the commodity unit is arranged.

[0075] Specifically, based on the actual layout information of the commodity scene, a digital model of the commodity scene is constructed. This digital model can reflect the physical layout of the commodity scene, including shelves, display areas, channels, etc. As a virtual platform for commodity management and optimization, a digital model that can accurately represent the layout of the commodity scene is created to provide a basis for subsequent commodity positioning and feedback. According to the position of each RFID scanning unit and the detection area it covers, the digital model of the commodity scene is adjusted and divided into target detection areas. Each target detection area corresponds to an actual commodity area, which corresponds to the physical layout in the commodity scene. The scanning range of each area is marked in the digital model so that subsequent commodity positioning information can be accurately fed back to a specific area.

[0076] More specifically, based on the product positioning information of each product unit, a digital model of the product unit is constructed on the target detection area corresponding to the digital model. The key to this step is to accurately reflect the actual position and status of the product unit in the digital model, create a unit model, and accurately represent the position, status, size and other information of each product unit in the digital model to provide data support for subsequent management and optimization. The digital model of each product unit is given product information. This product information usually includes the name, price, quantity, specifications, category, etc. of the product. By connecting with the identification data of the RFID tag, it is ensured that the product information is consistent with its unit model in the digital model, ensuring that the digital model of the product unit not only reflects its physical location, but also accurately contains its product information, so that the product in the digital model is consistent with the actual product information.

[0077] More specifically, using the above steps, the digital model of the commodity scene can continuously receive the commodity positioning information fed back by the RFID scanning unit, and update the commodity unit position and status in the digital model based on this information, thereby realizing real-time status feedback of the commodity scene, and providing a dynamic commodity scene digital model that can reflect the layout and status changes of the commodity units in real time, and support operations such as commodity management, layout optimization and inventory management.

[0078] It is understandable that the digital model of the product scene can update the layout and status of the product unit in real time according to the product positioning information fed back by the RFID scanning unit. This real-time feedback can help merchants to timely understand the actual location, inventory status, sales status, etc. of the product, realize the dynamic management and monitoring of the product scene, and improve the efficiency and accuracy of product management. The digital model of the product unit is highly consistent with the actual product information and can provide merchants with detailed product information, such as the real-time location of the product, inventory quantity, replenishment needs, etc. This precise digital model provides solid data support for the management, layout and inventory optimization of the product, improves the accuracy of inventory management, reduces the loss or out-of-stock of products, and helps merchants make accurate inventory decisions.

[0079] More specifically, through real-time digital feedback, merchants can see the changes in the position of each commodity unit in the commodity scene and adjust the commodity layout based on the feedback. For example, the arrangement of commodities on the shelves can be optimized based on data such as customer shopping behavior and the location of hot-selling commodities, thereby improving the rationality of commodity layout and sales efficiency, helping customers to quickly find the commodities they need and enhancing the shopping experience. By associating with RFID tag data, the digital model of the commodity unit can automatically update commodity information. This automated update mechanism can greatly reduce manual intervention, improve the efficiency and accuracy of data updates, realize the automated update and management of commodity information, reduce manual operation errors, and improve the intelligence level of the system.

[0080] More specifically, the digital model of the product scene can not only provide real-time feedback, but also monitor the product location information. For example, when the inventory level of a certain product is lower than the set threshold, the system can automatically issue a replenishment warning to ensure that the product always has sufficient inventory. It provides a real-time product monitoring and early warning mechanism, which helps merchants take measures in advance to avoid out-of-stock, overstock or other operational problems. By feeding the product unit information into the digital model, merchants can conduct more intelligent analysis and decision-making on the product scene. For example, it can be dynamically optimized based on factors such as the product placement, inventory status, sales data, etc. to improve sales results. It provides data-driven intelligent decision-making support to help merchants make more accurate product layout, marketing strategies and inventory adjustment decisions.

[0081] More specifically, digital models of product scenarios can help merchants optimize product display and inventory management, improve customer shopping convenience, and enable customers to find the products they need more quickly, thereby improving their shopping experience and satisfaction, improving their shopping efficiency and satisfaction, and enhancing their shopping experience, indirectly promoting sales and brand loyalty.

[0082] Preferably, the steps of monitoring the temporal changes of the digital model of the commodity scene to obtain the movement characteristics of the commodity units in the commodity scene, and tracking and locating the commodity units based on the movement characteristics of the commodity units to obtain the tracking and locating characteristics of each commodity unit include: S31: constructing a time coordinate axis having a plurality of sequentially arranged time observation coordinate scales, and performing a real-time positioning status analysis of each commodity unit in the entire scene on the commodity scene digital model at time intervals corresponding to the time observation coordinate scales, so as to obtain the overall scene positioning characteristics of the commodity scene digital model at time points corresponding to each time observation coordinate scale; S32: setting the overall positioning features of each scene at the corresponding time observation coordinate scale on the time coordinate axis to obtain a time series monitoring sequence of the commodity scene; S33: performing a difference analysis on the overall scene positioning features of adjacent time observation coordinate scales on the time series monitoring sequence to obtain positioning change features of each time observation coordinate scale; S34: analyzing the movement trajectory of each commodity unit according to the positioning change characteristics of each time observation coordinate scale to obtain the commodity unit movement characteristics of each commodity unit between each time observation coordinate scale; S35: analyzing the movement changes of the commodity units between the time observation coordinate scales, and classifying the commodity units into moving units and non-moving units according to the analysis results; S36: performing time-series connection processing on the commodity units classified as mobile units, based on the commodity unit movement characteristics at each time observation coordinate scale, to obtain tracking and positioning characteristics of each of the commodity units.

[0083] Specifically, based on the time range to be monitored, a time axis is constructed with several sequentially arranged time observation coordinate scales. Each scale on the time axis represents a specific time point. Typically, the intervals between these scales correspond to the actual observation time interval of the product scene digital model. This creates a time axis for monitoring the temporal changes of the product scene digital model. This time axis can help track the temporal movement characteristics of product units.

[0084] More specifically, according to each time observation coordinate scale, the time interval that conforms to the time observation coordinate scale is used to analyze the real-time positioning status of all commodity units in the digital model of the commodity scene, and the overall positioning characteristics of the commodity scene at different time points are obtained. These characteristics may include the position, status, etc. of the commodity unit. The overall positioning characteristics of the commodity scene at different time points are obtained to facilitate the subsequent analysis of the movement trajectory of the commodity units.

[0085] More specifically, the overall positioning features of the scene on each time observation coordinate scale are set on the corresponding time coordinate axis to form a time series monitoring sequence. Through the time series monitoring sequence, the changes in the overall positioning features of the commodity scene at different time points can be clearly seen, providing data support for subsequent difference analysis.

[0086] More specifically, we perform a difference analysis on the overall positioning features of the scene at adjacent time observation coordinate scales in the time series monitoring sequence. By comparing the positioning features at different time points, we extract positioning change characteristics. These differences can reflect the movement of the commodity units. By analyzing the changes in positioning characteristics, we can identify the movement behavior of the commodity units and provide a basis for further analysis of the commodity units' trajectories.

[0087] More specifically, based on the positioning change characteristics of the observation coordinate scales at each time, the movement trajectory of each commodity unit between different time scales is analyzed. This step will help identify the specific movement path and speed of the commodity unit, determine the movement characteristics of the commodity unit, such as direction, speed, movement range, etc., and understand the specific trajectory of the commodity unit.

[0088] More specifically, the movement characteristics of each commodity unit are analyzed. By comparing the movement changes between the coordinate scales observed at different times, we can identify which commodity units are "mobile units" and which are "non-mobile units". Mobile units are usually commodities that have undergone changes in spatial position, while non-mobile units have not undergone obvious position changes. According to the movement of commodity units, "mobile units" and "non-mobile units" are distinguished, providing valuable information for further tracking and management.

[0089] More specifically, for commodity units classified as mobile units, the movement characteristics of the commodity units between the observation coordinate scales at each time are processed in a time-series manner, and the change characteristics of these mobile units at different time points are analyzed. By connecting these movement characteristics, the tracking and positioning characteristics of the commodity units are generated, and the tracking and positioning characteristics of each commodity unit are obtained. These characteristics may include movement path, speed, direction, etc., and provide more accurate commodity management and optimization decision support.

[0090] It is understandable that through time-series change monitoring, merchants can understand the movement trajectory of commodity units in real time. This information is crucial for optimizing commodity layout, inventory management and replenishment decisions, ensuring timely feedback on the dynamic changes of commodities in the scene. Through precise movement trajectory analysis, merchants can understand the flow routes and stop locations of commodities. Based on this analysis, merchants can optimize the display and placement of commodities to improve sales efficiency. The system can automatically divide commodity units into mobile units and non-mobile units. Through this automated classification, merchants can obtain accurate commodity movement status without manual intervention, reducing manual errors and workload.

[0091] More specifically, by tracking the real-time movement characteristics and trajectories of commodity units, merchants can optimize the layout of commodity scenes based on the actual movement of commodities, improve commodity visibility and customer purchasing experience, and avoid inventory backlogs or out-of-stock problems. Based on the analysis results of time-series change monitoring and tracking positioning, merchants can manage commodities more accurately and make dynamic adjustments, thereby improving the overall intelligence level of commodity management and promoting more efficient operational management. The trajectory analysis of mobile units can provide important basis for inventory adjustment, replenishment and promotion strategies. For example, merchants can predict the popularity of certain commodity units based on their movement characteristics, and adjust shelf positions or formulate promotion strategies in advance to increase sales.

[0092] More specifically, through mobile monitoring of merchandise units, merchants can better analyze customer behavior and merchandise demand trends, thereby optimizing merchandise display methods and improving customer shopping experience and satisfaction. The system can provide merchants with powerful decision-making support through real-time monitoring and analysis of merchandise scenarios, helping merchants make data-driven decisions in inventory management, merchandise display, and replenishment.

[0093] Preferably, the step of performing wireless signal scanning on commodity units entering the settlement area based on an RFID scanning device pre-set in the settlement area of the commodity scene to obtain initial settlement information includes: S41: Detecting settlement actions in a settlement area in a commodity scene through a multiple detection mechanism, and generating a work trigger instruction for an RFID scanning device pre-installed in the settlement area based on the detection results; wherein the multiple detection mechanism includes a commodity tracking and positioning mechanism and a multi-source auxiliary detection mechanism. The commodity tracking and positioning mechanism determines the position of the commodity unit relative to the settlement area by using the tracking and positioning characteristics of the commodity unit, and the multi-source auxiliary detection mechanism monitors data of the settlement area through a multi-source sensor module pre-installed in the settlement area; S42: When the RFID scanning device pre-installed in the settlement area receives a work trigger instruction, the RFID is activated to perform wireless signal scanning of the commodity units in the settlement area to obtain the commodity information registered by each commodity unit in the settlement area, which is used as the initial settlement information.

[0094] Specifically, it is first necessary to set up a multiple detection mechanism in the settlement area, which includes two main sub-mechanisms: a commodity tracking and positioning mechanism, which analyzes the tracking and positioning characteristics of the commodity unit to determine whether the commodity unit has entered the settlement area. This mechanism makes judgments based on the changes in the spatial position of the commodity in the settlement area; a multi-source auxiliary detection mechanism, which monitors the status of the settlement area in real time through the multi-source sensor modules (such as cameras, infrared sensors, pressure sensors, etc.) set up in the settlement area, and assists in determining whether the commodity unit has entered the settlement area. Through the collaboration of these two mechanisms, accurate detection of commodity units entering the settlement area can be achieved, reducing false detections and missed detections.

[0095] More specifically, when multiple detection mechanisms (product tracking and positioning mechanism and multi-source auxiliary detection mechanism) jointly detect that a product unit enters the settlement area, the system will generate a work trigger instruction based on the detection results. The instruction will instruct the RFID scanning device to start scanning, ensuring that the RFID scanning device only starts scanning after the product unit actually enters the settlement area, avoiding invalid scanning and improving system efficiency.

[0096] More specifically, when the RFID scanning device receives a work trigger instruction, the RFID device starts working immediately. It scans the commodity unit through wireless signals, reads the information in the RFID tag attached to the commodity unit, obtains the commodity information, and uses RFID technology to automatically identify the commodity units in the settlement area, accurately obtains the commodity information, and provides initial data for the settlement system.

[0097] More specifically, the RFID scanning device reads the RFID tag information of each commodity unit during the scanning process and summarizes this information. All this commodity information (such as commodity ID, name, price, etc.) constitutes the initial settlement information. The RFID information of the commodity is collected as the preliminary input of the settlement system to provide accurate commodity data for the settlement process.

[0098] More specifically, the product information obtained through RFID scanning will be transmitted to the settlement system to constitute the initial settlement data. This data will be used for subsequent payment processing, inventory updates, etc., to ensure that the settlement system can obtain complete product information and make accurate settlements based on this.

[0099] It is understandable that through automated RFID scanning technology, the system can read product information quickly and accurately. Compared with traditional barcode scanning, this process is more efficient, especially in the rapid settlement of a large number of products, which reduces waiting time in queues and improves user experience. The multiple detection mechanism combines product tracking and positioning with multi-source auxiliary detection, which not only ensures accurate judgment of whether the product unit enters the settlement area, but also reduces the problem of misjudgment or missed judgment caused by a single sensor. This makes the RFID scan only activated when the product actually enters the settlement area, improving the accuracy of the system.

[0100] More specifically, based on the combination of RFID and multiple detection mechanisms, the entire settlement process is highly automated. The system can automatically identify goods and generate initial settlement information, reducing the need for manual intervention, lowering the risk of operational errors, and improving the intelligence level of settlement. The automatic scanning and recording of product information reduces the need for manual scanning and input, thereby effectively reducing errors caused by improper manual operation. This automated system can reduce the problems of missed and wrong orders during the settlement process and improve settlement accuracy.

[0101] More specifically, through the combination of multi-source sensors and product tracking and positioning mechanisms, merchants can exercise more precise control over the settlement area. This flexible detection mechanism can adapt to different settlement area layouts, different product types and their movement methods, ensuring the efficient operation of the settlement area. Wireless RFID scanning can reduce customers' waiting time at checkout and improve the shopping experience. Customers no longer need to wait in long lines for manual scanning of products. The settlement process becomes smoother and more convenient, improving customer satisfaction.

[0102] More specifically, RFID technology provides the settlement system with accurate, real-time product data, helping merchants better manage inventory and analyze sales data. This data integration capability enables merchants to make decisions more efficiently, such as inventory updates, price adjustments, and replenishment. The combination of multiple detection mechanisms and RFID technology provides strong support for system expansion. Merchants can flexibly adjust the monitoring mechanism of the settlement area according to different business needs, easily expand to different regions or branches, and maintain system consistency and efficiency.

[0103] Preferably, the steps of tracking and verifying the initial settlement information according to the tracking and positioning characteristics of each commodity unit to obtain verified settlement information, and performing settlement processing on the commodity units in the settlement area according to the verified settlement information include: S51: When the RFID scanning device in the settlement area generates initial settlement information, a tracking process is performed on the tracking and positioning features of each commodity unit in the commodity scene to determine that the end position of the tracking track fed back by the tracking and positioning features is each commodity unit in the settlement area, and each commodity unit is marked as a settlement verification object; S52: parsing the registered commodity information of the settlement verification object to obtain commodity information of each commodity unit included in the settlement verification object, and verifying the initial settlement information based on the commodity information of each commodity unit included in the settlement verification object to obtain verified settlement information; S53: Calculating the commodity values of the commodity units to be settled in the settlement area according to the verified settlement information to obtain the value to be settled, and generating a corresponding commodity transaction interface based on the value to be calculated, so that the shopper can interact with the interface to pay the value to be settled; S54: After the settlement of the pending value is completed, the RFID tags of each commodity unit in the settlement area are disassembled and recycled, and the commodity information registered on the disassembled and recycled RFID tags is cleared, so that the RFID tags can be detachably set on the commodity units newly arranged in the commodity scene in the subsequent process.

[0104] Specifically, after the RFID scanning device in the settlement area generates the initial settlement information, it analyzes the tracking and positioning characteristics of each commodity unit in the commodity scene. This process tracks the position and trajectory of the commodity unit, determines the current position of the commodity unit and its corresponding settlement area, and accurately obtains the position information of each commodity unit in the settlement area, ensuring that only the commodity units in the settlement area are included in the initial settlement information.

[0105] More specifically, the tracking trajectory of the commodity unit is processed to determine the end position of the tracking trajectory, that is, whether the commodity unit is in the settlement area, and each qualified commodity unit is marked as a "settlement verification object" to ensure that only those commodity units that actually enter the settlement area are regarded as objects to be settled, thereby improving the accuracy of settlement.

[0106] More specifically, the registered commodity information of the settlement verification object (commodity unit) is parsed to extract the commodity information of each commodity unit (such as commodity ID, name, price, etc.). Then, the initial settlement information is verified based on this commodity information to ensure the accuracy of all commodity data. By verifying the commodity information, the accuracy of the initial settlement information is ensured to prevent settlement problems caused by information errors.

[0107] More specifically, based on the verified settlement information, the commodity values of all commodity units to be settled in the settlement area are counted, and the total value to be settled is calculated. Subsequently, the system generates a commodity transaction interface based on this value to be settled for shoppers to make interactive payments, ensuring that the value information of the commodity is accurate. Users can conveniently pay the corresponding amount through an intuitive interface.

[0108] More specifically, after the shopper completes payment, the system will remove and recycle the RFID tag of each unit of merchandise in the settlement area. At the same time, the product information registered with the RFID tag will be cleared to ensure that the tag can be reconfigured for the next round of use, realizing the recycling of RFID tags, reducing costs and ensuring the availability of tags in subsequent processes.

[0109] More specifically, the disassembled and recycled RFID tags will clear the previously registered product information and be reconfigured to new products based on the new product units. In this way, the RFID tags can continue to be used without the need to purchase new tags each time, reducing the consumption cost of RFID tags, improving resource utilization, and ensuring the timely update and accuracy of product information.

[0110] It is understandable that through the precise application of the tracking and positioning mechanism, the location information of the commodity unit in the settlement area can be accurately determined, thereby ensuring the authenticity and accuracy of the initial settlement information. This process reduces the risk of erroneous settlement and enhances the accuracy of settlement. The registration, parsing and verification process of commodity information ensures that the detailed information of each commodity unit (such as name, price, quantity, etc.) is recorded accurately, which not only provides accurate data for settlement, but also provides reliable support for inventory management and subsequent business operations.

[0111] More specifically, through the combination of RFID tags and automated tracking and verification, the entire checkout process has achieved a high degree of automation, reducing the need for manual intervention and significantly improving the checkout speed. Shoppers can complete the checkout operation in a short time, optimizing the shopping experience. Based on the commodity transaction interface generated by the verified settlement information, shoppers can complete the payment operation through simple interaction. The digitization and intelligence of the payment process make the customer experience smoother and more convenient, reducing waiting time in queues.

[0112] More specifically, after payment is completed, the product information registered on the RFID tag is cleared and recycled to ensure that the tag can be reused in subsequent product scenarios. This mechanism not only improves resource utilization, but also reduces tag costs. It also enables dynamic updates of product information and the recycling of RFID tags, avoiding tag waste and reducing enterprise costs. The tag information is cleared and reconfigured after each removal, ensuring the long-term usability of the RFID tag.

[0113] More specifically, this checkout process not only adapts to the management of different product types, but also allows for flexible adjustments to the layout of the checkout area. As product scenarios constantly change, the RFID tags and tracking system can easily adapt to various new arrangements. Through efficient and accurate checkout processing, the system significantly improves the shopper's shopping experience. The emergence of an interactive payment interface makes it easier for customers to complete payments, saving time while reducing the inconvenience caused by queues and checkout errors. The automated and intelligent design of the entire checkout process makes product scenario management more intelligent, improving merchants' operational efficiency and management capabilities. This automated process based on RFID and tracking technology provides merchants with a more efficient and low-cost management model.

[0114] Preferably, the step of performing a multi-dimensional correlation analysis on the tracking and positioning features and verification settlement information of the commodity scene digital model to obtain the collaborative settlement correlation of various commodity units in the commodity scene includes: S61: Performing a probability analysis of simultaneous settlement of each commodity unit on the verified settlement information to obtain a probability characteristic of collaborative settlement between each commodity unit; S62: Analyzing the collaborative settlement probability matching degree of each verification settlement information based on the collaborative settlement probability characteristics between each commodity unit to obtain a feature matching parameter of each verification settlement information relative to the collaborative settlement probability characteristics between each commodity unit; S63: Based on the feature matching parameters of each verification and settlement information relative to the collaborative settlement probability characteristics between each commodity unit, multiple classification processing is performed on each verification and settlement information to obtain a probability matching list; wherein the probability matching list includes a probability feature coordinate axis and a plurality of feature matching coordinate axes perpendicular to the probability feature coordinate axis, the probability feature coordinate axis is used to set each collaborative settlement probability characteristic, and the feature matching coordinate axis is used to set each verification and settlement information with the feature matching parameters from high to low; S64: Retrieving the tracking and positioning features of the commodity units for each verification and settlement information on the feature matching coordinate axis, so as to use the tracking and positioning features of the commodity units corresponding to each verification and settlement information as the objects of probability matching analysis for each verification and settlement information; S65: performing a correlation analysis between shopping paths and collaborative settlement on the probability matching analysis objects of each verification settlement information corresponding to the collaborative settlement probability feature, so as to obtain the correlation of the influence of various types of shopping paths on the shopping paths of the collaborative settlement probability feature; S66: performing a correlation impact analysis between the layout positions of the commodity units and the shopping path for each of the tracking and positioning features based on the layout positions of the commodity units in the commodity scene digital model, so as to obtain a layout path correlation between the layout positions of the commodity units in the commodity scene and the shopping path; S67: Combine the collaborative settlement probability characteristics, shopping path influence correlation, and layout path correlation between each type of commodity unit to obtain the collaborative settlement correlation of each type of commodity unit.

[0115] Specifically, the verification settlement information is analyzed to calculate the probability of simultaneous settlement of each commodity unit. This process obtains the probability characteristics of collaborative settlement between commodity units by examining the settlement behavior between different commodity units. Through probability analysis, the tendency of different commodity units to settle at the same time is understood, which helps to determine which commodity units are more likely to settle together, providing a basis for subsequent collaborative settlement analysis.

[0116] More specifically, based on the collaborative settlement probability characteristics between various types of commodity units, the collaborative settlement probability matching degree of each verification settlement information is analyzed. This analysis will generate feature matching parameters to quantify the matching degree between the verification settlement information and the commodity unit, and obtain the probability matching degree between the verification settlement information and the commodity unit, thereby providing data support for multi-dimensional correlation analysis.

[0117] More specifically, the verification and settlement information is multi-classified based on the feature matching parameters to generate a probability matching list, which includes: the probability feature coordinate axis sets the collaborative settlement probability feature, the feature matching coordinate axis sets the matching degree from high to low, and presents the matching situation between each verification and settlement information and the commodity unit. By generating a matching list, the relationship between the verification and settlement information and the commodity unit is presented in a graphical form, providing structured data for subsequent in-depth analysis.

[0118] More specifically, the tracking and positioning features of the commodity units are retrieved for each verified settlement information in the matching list, and the tracking and positioning features of the corresponding commodity units are used as the objects of probability matching analysis. By extracting the tracking and positioning features, the correlation between the commodity units and the settlement information is further refined to ensure the accuracy of the analysis.

[0119] More specifically, the correlation between shopping paths and collaborative settlement is analyzed for each probability matching analysis object, the impact of different shopping paths on the collaborative settlement probability characteristics is examined, how different types of shopping paths affect the collaborative settlement probability between commodity units is identified, and the shopping paths are optimized to improve the efficiency and accuracy of the settlement system.

[0120] More specifically, based on the digital model of the commodity scene, the correlation between the layout position of the commodity units and the shopping path is analyzed. This step includes examining how the layout of the commodity units affects the choice of shopping paths and its impact on collaborative settlement. Through the analysis of the layout path, the impact of the location arrangement between commodity units on the shopping path and collaborative settlement relationship is identified, providing a decision-making basis for optimizing the commodity layout and shopping paths.

[0121] More specifically, a comprehensive analysis is conducted on the collaborative settlement probability characteristics, shopping path influence correlation, and layout path correlation between various commodity units to obtain the collaborative settlement correlation of various commodity units. Through comprehensive analysis, a comprehensive collaborative settlement relationship model is formed to help merchants make more accurate decisions in terms of commodity layout, shopping path planning, and settlement optimization.

[0122] It is understandable that by conducting a multi-dimensional analysis of the probability characteristics of collaborative settlement between various types of commodity units, the collaborative settlement relationship between commodity units can be accurately captured, thereby improving the accuracy of settlement and reducing the occurrence of erroneous settlement and missed settlement. Through the correlation analysis of layout paths and shopping paths, merchants can optimize the layout of commodity units in space, reasonably arrange shopping paths, and enhance customer shopping experience. At the same time, the layout optimization of commodities can also promote a more efficient settlement process. The correlation analysis of shopping paths and collaborative settlement helps to design shopping paths that are more in line with customer behavior patterns, reduce the time customers stay in the settlement area, improve overall settlement efficiency, and enhance the shopping experience.

[0123] More specifically, based on the analysis of digital models of product scenarios, the system can dynamically adjust product locations and path designs to adapt to different shopping scenarios, meet different customer needs, and achieve dynamic optimization. The analysis of collaborative settlement relevance can provide merchants with decision-making support on product layout, settlement paths, etc. Through big data analysis and machine learning technology, the system can continuously optimize itself and provide more intelligent operational decision-making recommendations.

[0124] More specifically, multi-dimensional correlation analysis can effectively identify which units of goods are more likely to be settled together, thereby helping merchants adjust inventory management and resource allocation to achieve efficient resource utilization. By optimizing shopping paths, improving settlement efficiency and reasonable product layout, customers' shopping experience is improved, thereby enhancing customer satisfaction and loyalty. Merchants can also improve settlement efficiency through these optimizations, thereby improving overall profitability. This digital model-based analysis method can adapt to shopping malls of different sizes and types and has strong scalability. Merchants can adjust product layout, shopping paths and settlement area configurations according to actual needs and flexibly adapt to market changes.

[0125] Preferably, the step of performing an optimization simulation of the arrangement pattern of commodity units on the commodity scene digital model based on the collaborative settlement correlation to obtain an optimization suggestion for the commodity scene arrangement includes: S71: performing an adjustment simulation of the layout positions of various commodity units in the commodity scene digital model based on the shopping path influence correlation and layout path correlation between various commodity units in the collaborative settlement correlation, and calculating a theoretical collaborative settlement probability characteristic corresponding to the adjustment simulation; S72: Based on the theoretical collaborative settlement probability characteristics, the layout position adjustment simulation results of each type of commodity unit are used to perform an overall commodity layout optimization simulation for the commodity scene, and the overall layout optimization strategy of the commodity scene and the corresponding strategy optimization value are obtained, which are used together as commodity scene layout optimization suggestions.

[0126] Specifically, based on the shopping path impact correlation and layout path correlation in the collaborative settlement correlation, a commodity unit layout position adjustment simulation is carried out. The core of this adjustment simulation is to identify the most suitable location allocation by analyzing the collaborative settlement relationship between commodity units. The shopping path impact correlation analyzes the impact of the customer's movement path in the commodity scene on the settlement probability between commodity units, optimizes the layout, makes the customer's shopping path smoother, and the settlement behavior is more in line with natural laws. The layout path correlation analyzes the guiding role of the layout position of the commodity unit on the customer's shopping path, adjusts the layout to optimize the customer flow direction, adjusts the position of the commodity unit, minimizes the customer's movement cost, improves settlement efficiency, and ensures that the collaborative settlement probability between commodity units is maximized.

[0127] More specifically, the simulation results after the layout position adjustment are calculated to obtain a new theoretical collaborative settlement probability feature. This feature reflects the change in settlement probability between commodity units after the adjustment, which can help merchants understand the specific impact of layout changes on settlement efficiency. By using the collaborative settlement probability feature between commodity units and the new layout adjustment information, the increase or decrease in settlement probability is calculated through the model. During the simulation process, it may be necessary to adjust the algorithm parameters to adapt to the actual needs of different commodity units, ensure the accuracy of the calculation, accurately quantify the impact of layout adjustment on the collaborative settlement probability, and provide quantitative support for overall layout optimization.

[0128] More specifically, based on the calculated theoretical collaborative settlement probability characteristics, the overall commodity scenario is simulated for layout optimization. This step mainly includes using optimization algorithms (such as genetic algorithms, simulated annealing, etc.) to repeatedly adjust the commodity layout to maximize the overall collaborative settlement probability characteristics, simulate the impact of different commodity layout patterns on the overall shopping path, customer flow and settlement efficiency, identify the best commodity layout plan, and find an optimal commodity layout pattern through simulation to optimize the customer shopping experience while improving settlement efficiency.

[0129] More specifically, based on the overall merchandise layout optimization simulation results, the overall layout optimization strategy of the merchandise scene is refined, and the optimization value of the strategy is evaluated. Based on the simulation results, a detailed merchandise layout optimization plan is formulated, and specific layout adjustment suggestions are put forward. The value of the optimized layout in improving settlement efficiency, customer satisfaction, and resource utilization is evaluated, forming operational merchandise scene layout optimization suggestions, and supporting the implementation value of the optimization suggestions through data analysis.

[0130] More specifically, the results of the above steps are summarized to output the final product scene layout optimization suggestions. These suggestions will include: the optimal product layout plan, the expected settlement efficiency and customer experience improvement after optimization, and the specific implementation strategy details and steps. This will provide merchants with a systematic and scientific product scene layout optimization plan to ensure that the optimization measures are executable and can bring actual benefits.

[0131] It is understandable that by optimizing and adjusting the layout of commodity units, the probability of coordinated settlement between commodity units can be increased, thereby reducing customer settlement time and improving overall settlement efficiency. By optimizing the commodity layout and shopping paths, unnecessary movement of customers during the shopping process can be reduced, the smoothness of the shopping process can be improved, and customer satisfaction and shopping experience can be enhanced. By reasonably arranging commodity units, the efficiency of space utilization can be improved. The optimized layout can make full use of the mall space and avoid waste of shelf resources or poor customer flow.

[0132] More specifically, by calculating the relationship between collaborative settlement probability characteristics and shopping paths and layout paths, merchants can accurately evaluate the actual effects of layout adjustments and provide data support for decision-making. Layout optimization simulation can be dynamically adjusted according to the needs of different product scenarios. Merchants can flexibly adjust product layouts based on changes in customer behavior, product demand, etc. to achieve refined management. This optimization simulation technology provides merchants with a powerful decision-making support tool to help them optimize product layouts from a data and scientific perspective and improve operational management efficiency.

[0133] More specifically, by optimizing the layout of merchandise units and shopping routes, the overall operational efficiency of the mall is improved, the customer shopping process is more efficient, the checkout area is smoother, and the overall operational level of the mall is improved. Reasonable layout can reduce the time required for customers to shop, especially in the checkout area, by reducing unnecessary congestion and dwell time, thereby improving customer satisfaction and checkout efficiency. With the deepening of data analysis, merchants can adjust layout strategies according to different market demands and customer behaviors, and support personalized merchandise layout to better meet the needs of different customer groups.

[0134] Reference Figure 2As shown, in a second aspect, the present invention provides a settlement and inventory management system based on an RFID scanning station, which is used to implement the settlement and inventory management method based on an RFID scanning station described in any one of the first aspects, including: The product positioning module is used to continuously scan the wireless signals of the RFID tags pre-detachably mounted on the product units to obtain the product positioning information fed back by the RFID tags on each product unit; A digital feedback module is used to feed back the commodity positioning information to the commodity scene digital model, so as to provide real-time digital feedback on the commodity scene where the commodity unit is arranged; a tracking and positioning module, configured to monitor the temporal changes of the digital model of the commodity scene to obtain movement characteristics of commodity units in the commodity scene, and to track and position the commodity units based on the movement characteristics of the commodity units to obtain tracking and positioning characteristics of each commodity unit; The initial settlement module is used to scan the commodity units entering the settlement area with wireless signals based on the RFID scanning device pre-set in the settlement area of the commodity scene to obtain initial settlement information; a verification and settlement module, configured to perform tracking and verification processing on the initial settlement information according to the tracking and positioning characteristics of each of the commodity units to obtain verification and settlement information, and perform settlement processing on the commodity units in the settlement area according to the verification and settlement information; A correlation analysis module is used to perform a multi-dimensional correlation analysis on the tracking and positioning features of the digital model of the commodity scene and the verification and settlement information to obtain the collaborative settlement correlation of various commodity units in the commodity scene; The layout optimization module is used to optimize and simulate the layout pattern of commodity units in the commodity scene digital model based on the collaborative settlement correlation to obtain commodity scene layout optimization suggestions.

[0135] In this embodiment, for the specific implementation of each module in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0136] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A settlement and inventory management method based on RFID scanning station, characterized in that: include: Continuously scan wireless signals from RFID tags pre-detachably mounted on commodity units to obtain commodity location information fed back by the RFID tags on each commodity unit; Feeding back the commodity positioning information to the commodity scene digital model to provide real-time digital feedback on the commodity scene where the commodity units are arranged; Monitoring the temporal changes of the digital model of the commodity scene to obtain movement characteristics of commodity units in the commodity scene, and tracking and locating the commodity units based on the movement characteristics of the commodity units to obtain tracking and locating characteristics of each commodity unit; Based on the RFID scanning device pre-set in the settlement area of the commodity scene, the commodity units entering the settlement area are scanned by wireless signals to obtain initial settlement information; Tracking and verifying the initial settlement information according to the tracking and positioning characteristics of each commodity unit to obtain verified settlement information, and performing settlement processing on the commodity units in the settlement area according to the verified settlement information; Performing a multi-dimensional correlation analysis on the tracking and positioning features of the digital model of the commodity scene and the verification and settlement information to obtain the collaborative settlement correlation of various commodity units in the commodity scene; Based on the collaborative settlement correlation, the layout pattern of commodity units in the commodity scene digital model is optimized and simulated to obtain commodity scene layout optimization suggestions.

2. The settlement and inventory management method based on the RFID scanning station according to claim 1, characterized in that: The steps of continuously scanning wireless signals from RFID tags pre-detachably mounted on commodity units to obtain commodity location information fed back by the RFID tags on each commodity unit include: Activate the RFID scanning unit of each detection location node pre-set in the commodity scene, and make the RFID scanning unit of each detection location node continuously scan the corresponding target detection area for wireless signals to obtain regional RFID detection data of the target detection area corresponding to each detection location node; wherein the regional RFID detection data includes identification data of the RFID tag on the commodity unit arranged in the target detection area, and the identification data of the RFID tag is used to register commodity information of the commodity unit to which the RFID tag is detachably provided; Analyzing the regional overlap conditions of each of the target detection areas based on the relative positional relationships between the detection location nodes provided with RFID scanning units and the detection performance of the RFID scanning units provided at each of the detection location nodes to obtain regional overlap characteristics of each of the target detection areas; Based on the area overlapping characteristics of each target detection area, the layout relationship of the commodity unit is analyzed on the RFID detection data collected by each RFID scanning unit to obtain the commodity positioning information of each commodity unit in the commodity scene.

3. The settlement and inventory management method based on the RFID scanning station according to claim 2, characterized in that: Feedback of the commodity positioning information to the commodity scene digital model to provide real-time digital feedback of the commodity scene where the commodity units are arranged includes: Pre-constructing a digital model of a commodity scene for digitally simulating the commodity scene based on the layout information of the commodity scene; Dividing the commodity scene digital model into target detection areas according to each of the RFID scanning units and the corresponding detection position nodes, so as to divide model areas corresponding to each of the target detection areas on the commodity scene digital model; According to the commodity positioning information of each commodity unit, a digital model of the commodity unit is constructed for the corresponding model area in the commodity scene digital model to obtain a unit model of each commodity unit; The unit model is assigned unit information according to the commodity information of the commodity unit so that the unit model and the commodity unit have consistent commodity information, thereby enabling the commodity scene digital model to provide real-time digital feedback on the commodity scene where the commodity unit is arranged.

4. The settlement and inventory management method based on RFID scanning station according to claim 1, characterized in that: The steps of monitoring the temporal changes of the digital model of the commodity scene to obtain the movement characteristics of the commodity units in the commodity scene, and tracking and locating the commodity units based on the movement characteristics of the commodity units to obtain the tracking and positioning characteristics of each of the commodity units include: Constructing a time coordinate axis having a plurality of sequentially arranged time observation coordinate scales, and performing a real-time positioning status analysis of each commodity unit in the entire scene on the commodity scene digital model at time intervals corresponding to the time observation coordinate scales, so as to obtain the overall scene positioning characteristics of the commodity scene digital model at time points corresponding to each time observation coordinate scale; Setting the overall positioning features of each scene at the corresponding time observation coordinate scale on the time coordinate axis to obtain a time-series monitoring sequence of the commodity scene; Performing a difference analysis on the overall scene positioning features of adjacent time observation coordinate scales on the time series monitoring sequence to obtain positioning change features of each time observation coordinate scale; Analyze the movement trajectory of each commodity unit according to the positioning change characteristics of each time observation coordinate scale to obtain the commodity unit movement characteristics of each commodity unit between each time observation coordinate scale; Analyze the movement changes of the commodity unit movement characteristics between the observation coordinate scales at each time, and classify the commodity units into moving units and non-moving units according to the analysis results; The commodity units classified as mobile units are subjected to time-series connection processing of the commodity unit movement characteristics at each time observation coordinate scale to obtain tracking and positioning characteristics of each of the commodity units.

5. The settlement and inventory management method based on RFID scanning station according to claim 1, characterized in that: The steps of performing wireless signal scanning on commodity units entering the settlement area based on an RFID scanning device pre-set in the settlement area of the commodity scene to obtain initial settlement information include: The settlement action is detected in the settlement area of the commodity scene through a multiple detection mechanism, and a work trigger instruction is generated for the RFID scanning device pre-installed in the settlement area based on the detection results. The multiple detection mechanism includes a commodity tracking and positioning mechanism and a multi-source auxiliary detection mechanism. The commodity tracking and positioning mechanism determines the position of the commodity unit relative to the settlement area by using the tracking and positioning characteristics of the commodity unit, and the multi-source auxiliary detection mechanism monitors the data of the settlement area through a multi-source sensor module pre-installed in the settlement area. When the RFID scanning device pre-installed in the settlement area receives a work trigger instruction, the RFID is activated to perform wireless signal scanning of the commodity units in the settlement area to obtain the commodity information registered by each commodity unit in the settlement area, which is used as the initial settlement information.

6. The settlement and inventory management method based on RFID scanning station according to claim 1, characterized in that: The steps of tracking and verifying the initial settlement information according to the tracking and positioning characteristics of each commodity unit to obtain verified settlement information, and performing settlement processing on the commodity units in the settlement area according to the verified settlement information include: When the RFID scanning device of the settlement area generates initial settlement information, a tracking process is performed on the tracking and positioning features of each commodity unit in the commodity scene to determine that the end position of the tracking track fed back by the tracking and positioning features is each commodity unit in the settlement area, and each commodity unit is marked as a settlement verification object; parsing the registered commodity information of the settlement verification object to obtain commodity information of each commodity unit contained in the settlement verification object, and verifying the initial settlement information based on the commodity information of each commodity unit contained in the settlement verification object to obtain verified settlement information; Counting the commodity values of the commodity units to be settled in the settlement area according to the verified settlement information to obtain the value to be settled, and generating a corresponding commodity transaction interface based on the value to be calculated, so that the shopper can interact with the interface to pay the value to be settled; After the settlement of the pending value is completed, the RFID tags of each commodity unit in the settlement area are disassembled and recycled, and the commodity information registered on the disassembled and recycled RFID tags is cleared, so that the RFID tags can be detachably set on the commodity units newly arranged in the commodity scene in the subsequent process.

7. The settlement and inventory management method based on RFID scanning station according to claim 1, characterized in that: The steps of performing a multi-dimensional correlation analysis on the tracking and positioning features and verification settlement information of the commodity scene digital model to obtain the collaborative settlement correlation of various commodity units in the commodity scene include: Performing a probability analysis of simultaneous settlement of each commodity unit on the verified settlement information to obtain a probability characteristic of collaborative settlement between each commodity unit; Based on the collaborative settlement probability characteristics between various commodity units, analyzing the collaborative settlement probability matching degree of each of the verification and settlement information to obtain feature matching parameters of each of the verification and settlement information relative to the collaborative settlement probability characteristics between the commodity units; Based on the feature matching parameters of each verification and settlement information relative to the collaborative settlement probability characteristics between each commodity unit, multiple classification processing is performed on each verification and settlement information to obtain a probability matching list; wherein the probability matching list includes a probability feature coordinate axis and a plurality of feature matching coordinate axes perpendicular to the probability feature coordinate axis, the probability feature coordinate axis is used to set each collaborative settlement probability characteristic, and the feature matching coordinate axis is used to set each verification and settlement information with the feature matching parameters from high to low; Retrieving the tracking and positioning features of the commodity units for each verification and settlement information on the feature matching coordinate axis, so as to use the tracking and positioning features of the commodity units corresponding to each verification and settlement information as the objects of probability matching analysis for each verification and settlement information; Performing a correlation analysis between shopping paths and collaborative settlement on the probability matching analysis objects of each of the verified settlement information corresponding to the collaborative settlement probability feature, so as to obtain the influence correlation of various types of shopping paths on the shopping paths of the collaborative settlement probability feature; Based on the layout positions of each commodity unit in the commodity scene digital model, performing a correlation influence analysis between the layout positions of each commodity unit and the shopping path on each tracking and positioning feature to obtain a layout path correlation between the layout positions of each commodity unit in the commodity scene and the shopping path; The collaborative settlement probability characteristics, shopping path influence correlation, and layout path correlation between various commodity units are combined to obtain the collaborative settlement correlation of various commodity units.

8. The settlement and inventory management method based on the RFID scanning station according to claim 7, characterized in that: The steps of performing an optimization simulation of the arrangement pattern of commodity units in the commodity scene digital model based on the collaborative settlement correlation to obtain an optimization suggestion for the commodity scene arrangement include: Adjusting and simulating the layout positions of various commodity units in the commodity scene digital model based on the shopping path influence correlation and layout path correlation between various commodity units in the collaborative settlement correlation, and calculating theoretical collaborative settlement probability characteristics corresponding to the adjusted simulation; According to the theoretical collaborative settlement probability characteristics, the adjustment simulation results of the layout positions of various commodity units are used to perform an overall commodity layout optimization simulation of the commodity scene, and the overall layout optimization strategy of the commodity scene and the corresponding strategy optimization value are obtained, which are used together as commodity scene layout optimization suggestions.

9. A settlement and inventory management system based on RFID scanning station, characterized in that: A settlement and inventory management method based on an RFID scanning station for implementing any one of claims 1-8: The product positioning module is used to continuously scan the wireless signals of the RFID tags pre-detachably mounted on the product units to obtain the product positioning information fed back by the RFID tags on each product unit; A digital feedback module is used to feed back the commodity positioning information to the commodity scene digital model, so as to provide real-time digital feedback on the commodity scene where the commodity unit is arranged; a tracking and positioning module, configured to monitor the temporal changes of the digital model of the commodity scene to obtain movement characteristics of commodity units in the commodity scene, and to track and position the commodity units based on the movement characteristics of the commodity units to obtain tracking and positioning characteristics of each commodity unit; The initial settlement module is used to scan the commodity units entering the settlement area with wireless signals based on the RFID scanning device pre-set in the settlement area of the commodity scene to obtain initial settlement information; a verification and settlement module, configured to perform tracking and verification processing on the initial settlement information according to the tracking and positioning characteristics of each of the commodity units to obtain verification and settlement information, and perform settlement processing on the commodity units in the settlement area according to the verification and settlement information; A correlation analysis module is used to perform a multi-dimensional correlation analysis on the tracking and positioning features of the digital model of the commodity scene and the verification and settlement information to obtain the collaborative settlement correlation of various commodity units in the commodity scene; The layout optimization module is used to optimize and simulate the layout pattern of commodity units in the commodity scene digital model based on the collaborative settlement correlation to obtain commodity scene layout optimization suggestions.

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