Retail merchandise monitoring method, apparatus, device and program product

Abstract

This application relates to the field of business intelligence, and more particularly to a method, device, equipment, and program product for monitoring retail goods. The method includes: acquiring retail equipment data and contract data through a business intelligence platform; determining the correspondence between retail equipment and retail equipment data, and determining the correspondence between retail equipment and contract data; based on the correspondence, detecting retail goods on the retail equipment using prohibited goods characteristics, and detecting the prices of goods on the retail equipment based on the contract price requirements of the goods; and determining the monitoring results of the retail goods based on the detection results of the retail goods and the detection results of the prices. This method only requires importing contract data and retail equipment data to efficiently monitor and investigate goods, greatly reducing the monitoring cost of retail goods, improving investigation efficiency and accuracy, and effectively enhancing the real-time performance of retail goods monitoring.

Description

Technical Field

[0001] This application relates to the field of business intelligence, and more particularly to a method, apparatus, equipment, and program product for monitoring retail goods. Background Technology

[0002] With the rapid development of the unmanned retail industry, operators have deployed a large number of vending machines in locations such as schools, factories, and office buildings. To ensure operational compliance and service quality, operators need to sign contracts with each venue (hereinafter referred to as "clients") to limit the products that can be sold in specific vending machines.

[0003] To meet the above compliance requirements, it is common practice to periodically export sales data from vending machines from the business system and screen and investigate to check for the existence of illegal contract goods. However, this method is inefficient, costly, and has a long time interval between the occurrence and discovery of an anomaly, resulting in significant delays and a high risk of missed or incorrect judgments. Summary of the Invention

[0004] In view of this, embodiments of this application provide methods, apparatus, devices and program products to solve the problems of low screening efficiency, high cost, serious lag and easy omission or misjudgment in the monitoring of retail goods in the prior art.

[0005] A first aspect of this application provides a retail goods monitoring method, the method comprising:

[0006] The business intelligence platform acquires retail equipment data and contract data. The retail equipment data includes the retail goods and prices of each retail equipment, and the contract data includes the characteristics of prohibited goods and the contract price requirements for the goods. Determine the correspondence between the retail equipment and the retail equipment data, and determine the correspondence between the retail equipment and the contract data; Based on the aforementioned correspondence, the retail goods of the retail equipment are detected by the prohibited goods characteristics of the retail equipment, and the prices of the goods of the retail equipment are detected by the contract price requirements of the retail equipment. Based on the detection results of the retail goods and the detection results of the goods prices, the monitoring results of the retail goods of the retail equipment are determined.

[0007] In conjunction with the first aspect, in a first possible implementation of the first aspect, determining the correspondence between the retail device and the contract data includes: Obtain the monitoring scope included in the contract text data; Obtain the location information of the retail device; Based on the matching relationship between the location information and the monitoring range, the correspondence between the retail device and the contract data is determined.

[0008] In conjunction with the first aspect, in a second possible implementation of the first aspect, after determining the correspondence between the retail device and the contract data, the method further includes: A rule configuration table is generated based on the contract data; The system receives user configuration data and updates the rule configuration table using the configuration data, which includes at least one of adding, deleting, and modifying contract items.

[0009] In conjunction with the first aspect, in a third possible implementation of the first aspect, determining the monitoring results of the retail goods on the retail equipment based on the detection results of the retail goods and the detection results of the goods prices includes: When it is detected that the characteristics of the retail product do not match those of the prohibited product, and the price of the product meets the contract price requirements, the monitoring result of the retail product is determined to be a normal product. When the retail product is detected to match the characteristics of the prohibited product, the monitoring result of the retail product is determined to be a prohibited product; When it is detected that the characteristics of the retail product do not match those of the prohibited product, and the price of the product does not meet the contract price requirements, the monitoring result of the retail product is determined to be a product with abnormal price.

[0010] In conjunction with the third possible implementation of the first aspect, in the fourth possible implementation of the first aspect, detecting that the commodity price meets the contract price requirement includes: Obtain the location information of the retail device; Based on the location information, determine the supermarket price of the retail goods sold in the retail equipment located in the vicinity of the retail equipment; When the price of a retail item in the retail device is not higher than the supermarket selling price, the price of the item is determined to meet the contract price requirement.

[0011] In conjunction with the third possible implementation of the first aspect, in the fifth possible implementation of the first aspect, after determining the monitoring results of the retail goods on the retail device based on the detection results of the retail goods and the detection results of the goods prices, the method further includes: Identify the maintenance personnel for the retail equipment; Send the monitoring results of the retail goods to the maintenance personnel, and / or send adjustment instructions to the retail equipment based on the monitoring results, the adjustment instructions including suspending the sale of the prohibited goods, and / or adjusting the sales price of the abnormally priced goods.

[0012] In conjunction with the fifth possible implementation of the first aspect, in the sixth possible implementation of the first aspect, when multiple maintenance personnel are assigned to a retail device, determining the maintenance personnel for the retail device includes: Obtain the workload of multiple maintenance personnel corresponding to the retail equipment; Based on the workload of the maintenance personnel, maintenance personnel are assigned to the retail equipment to be maintained; Alternatively, obtain the sales data of the retail equipment; Based on the sales data, predict the first popularity of the prohibited goods and the second popularity of the goods with abnormal prices, and determine the third popularity of the retail equipment based on the first popularity and the second popularity; The maintenance personnel are assigned retail equipment to be maintained based on the third popularity of the retail equipment.

[0013] A second aspect of this application provides a retail goods monitoring device, the device comprising: The data acquisition unit is used to acquire retail equipment data and contract data through the business intelligence platform. The retail equipment data includes the retail goods and prices of each retail equipment, and the contract data includes the characteristics of prohibited goods and the contract price requirements for goods. A correspondence determination unit is used to determine the correspondence between the retail equipment and the retail equipment data, and to determine the correspondence between the retail equipment and the contract data; The detection unit is used to detect the retail goods of the retail equipment based on the prohibited goods characteristics of the retail equipment according to the correspondence, and to detect the price of the goods of the retail equipment based on the contract price requirements of the retail equipment. The monitoring result determination unit is used to determine the monitoring result of the retail goods on the retail equipment based on the detection result of the retail goods and the detection result of the goods price.

[0014] A third aspect of this application provides a retail merchandise monitoring device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the retail merchandise monitoring device performs the method described in any of the first aspects.

[0015] A fourth aspect of this application provides a computer program product that, when run on a computer, causes the computer to execute the methods described in the first aspect or its various implementations.

[0016] A fifth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in any of the first aspects.

[0017] A sixth aspect of this application provides a chip for implementing the methods in the various implementations of the first aspect described above. Specifically, the chip includes a processor for calling and running a computer program from a memory, causing a device equipped with the chip to perform the methods as described in the first aspect or its various implementations.

[0018] The beneficial effects of this application embodiment compared with the prior art are as follows: This application embodiment obtains retail equipment data and contract data through a business intelligence platform, determines the correspondence between retail equipment data and retail equipment, and the correspondence between retail equipment and contract data. Based on this correspondence, it detects retail goods in retail equipment through the prohibited goods characteristics of retail equipment, and detects the prices of goods in retail equipment through the contract price requirements. Based on the detection results of retail goods and the detection results of goods prices, it determines the monitoring results of retail goods in retail equipment. Only contract data and retail equipment data need to be imported to efficiently monitor and investigate goods, which greatly reduces the monitoring cost of retail goods, improves the efficiency and accuracy of investigation, and effectively enhances the real-time monitoring of retail goods. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram illustrating an implementation scenario of a method for monitoring retail goods provided in this application. Figure 2 This is a schematic diagram illustrating the implementation process of a retail goods monitoring method provided in an embodiment of this application; Figure 3 This is a schematic diagram illustrating the implementation process for determining the correspondence between retail equipment and contract data, provided in an embodiment of this application. Figure 4 This is a schematic diagram illustrating the implementation process of a method for detecting retail goods provided in an embodiment of this application; Figure 5 This is a schematic diagram of a monitoring device for retail goods provided in an embodiment of this application; Figure 6This is a schematic diagram of a retail merchandise monitoring device provided in an embodiment of this application. Detailed Implementation

[0021] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0022] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0023] With the rapid development of the unmanned retail industry, operators have deployed a large number of vending machines in locations such as schools, factories, and office buildings. To ensure operational compliance and service quality, operators need to sign agreements with each location (hereinafter referred to as "customers") to limit the products sold by specific vending machines.

[0024] To meet relevant compliance requirements, the common practice is to periodically export sales data from vending machines from the business system and manually screen and check for unauthorized sales of goods. This method is inefficient and costly, and there is usually a long time delay from the occurrence of an anomaly to its discovery, resulting in not only delayed response but also a high risk of omissions or misjudgments.

[0025] To address the aforementioned problems, this application proposes a method for monitoring retail goods. Figure 1 The following is a schematic diagram illustrating the implementation scenario of this method, such as... Figure 1 As shown, this implementation scenario includes a retail goods monitoring device 1, a maintenance terminal 2, and multiple retail devices 3. Each retail device 3 contains multiple retail goods 31, each with a set price, which customers can use to purchase the goods. The retail goods monitoring device 1 can be a server equipped with a business intelligence platform. It can acquire contract data and retail device data, determine the correspondence between retail devices 3 and their data, and between retail devices 3 and their contract data. It can then detect retail goods 31 in the contract data based on prohibited item features and the contract price requirements. Based on the detection results of retail goods 31 and their prices, the monitoring results are determined, enabling the retail devices 3 to perform anomaly monitoring efficiently, at low cost, and with low latency, thus improving the accuracy of the monitoring results.

[0026] Figure 2A schematic diagram illustrating the implementation process of a retail goods monitoring method provided in this application is described in detail below: In S201, retail equipment data and contract data are obtained through the business intelligence platform.

[0027] The retail equipment data includes the retail goods and prices of each retail equipment, while the contract data includes the characteristics of prohibited goods and the contract price requirements.

[0028] When acquiring retail equipment data through a business intelligence platform, a communication link can be established between the retail merchandise monitoring equipment and the retail equipment. This communication link allows for real-time acquisition of retail equipment data, including the merchandise on sale and its prices. Business intelligence platforms can include platforms such as Quick BI.

[0029] Not limited to this, retail equipment can also include the goods sold within the retail equipment. The sales records of the retail equipment can be used to obtain information such as the sold goods, their prices, and the time of sale.

[0030] When monitoring retail goods, retail equipment data and contract data can be acquired according to a predetermined monitoring cycle. For example, the monitoring cycle can be one day, and retail equipment data and contract data can be acquired daily to obtain the monitoring results of retail goods.

[0031] In one possible implementation, the status changes of retail equipment can also be monitored. Status information includes retail goods and their prices. When a change in status information is detected, the changed status information is acquired, and detection is performed based on this change. For example, if a change in the retail goods in the status information is detected, the newly added retail goods are acquired, and these are matched against the prohibited goods characteristics in the contract data. If the newly added retail goods match the prohibited goods characteristics in the contract data, then the newly added retail goods are determined to be prohibited goods. If a change in the price of goods in the status information is detected, the retail goods whose prices have increased after the price change are acquired, and their increased prices are matched against the contract price requirements in the contract data. If the increased price of the retail goods does not meet the contract price requirements, then the retail goods are determined to be goods with abnormal prices.

[0032] When acquiring contract data, one can first obtain the contract text data. By parsing the contract text data, information such as the characteristics of prohibited goods and the contract price requirements can be obtained. This can be achieved by calling a large language model to retrieve the characteristics of prohibited goods and the contract price requirements. Alternatively, pre-defined keywords can be used to determine these information.

[0033] For example, contract text data can be parsed, and the characteristics of prohibited goods included in the contract text data can be extracted through keywords such as "not allowed to be sold" and "prohibited from sale". For example, if the contract text data includes "not allowed to sell high-sugar beverages and alcoholic beverages", the characteristics of prohibited goods "high sugar" & "beverages" and "alcoholic" & "beverages" can be extracted.

[0034] Alternatively, the contract text data can be parsed, and the contract price requirement can be obtained by analyzing keywords such as "price requirement" and "price regulation". For example, if the contract text data includes "price requirement: not higher than the price of nearby supermarkets", then the contract price requirement can be extracted as "not higher than the price of nearby supermarkets".

[0035] In S202, the correspondence between the retail device and the retail device data is determined, and the correspondence between the retail device and the contract data is determined.

[0036] When determining the correspondence between retail equipment and its data, the equipment identifier of the retail equipment can be obtained simultaneously with the data when the retail merchandise monitoring equipment establishes a communication connection with the retail equipment. Since the equipment identifier uniquely identifies the retail equipment, the correspondence between the retail equipment and its data can be determined.

[0037] The contract text data used to determine contract data typically does not explicitly identify the retail device to which the contract text data pertains. It is necessary to determine the matching retail device based on the monitoring scope of the contract data to establish the correspondence between the retail device and the contract data. Specifically, this can be done as follows: Figure 3 As shown, it includes: In S301, obtain the monitoring scope included in the contract text data.

[0038] The monitoring scope included in the contract text data can be obtained by parsing the contract text data. This can be achieved through large language model parsing or keyword parsing. The monitoring scope refers to the location range of the configured retail equipment as specified in the contract text data.

[0039] One possible implementation is to determine the monitoring scope included in the contract text data through keyword matching. This includes using keywords such as "deployment location" or "deployment position" to determine the monitoring scope within the contract text data. For example, if the contract text data includes "deployment location: all floors of XX building," then based on the keyword matching for "deployment location," the monitoring scope following that keyword can be determined to include "XX building."

[0040] In S302, the location information of the retail device is obtained.

[0041] Retail devices are equipped with wireless communication modules, which can determine the location information of the retail device based on the base station connected to the wireless communication module. This base station can be a mobile communication base station, or a Wi-Fi base station, etc.

[0042] In S303, the correspondence between the retail device and the contract data is determined based on the matching relationship between the location information and the monitoring range.

[0043] The location information of retail equipment is matched with the monitoring range. If the location information of the retail equipment falls within the range defined by the monitoring range, it can be determined that the contract data corresponds to the retail equipment. If the location information of the retail equipment falls outside the range defined by the monitoring range, it can be determined that the contract data does not correspond to the retail equipment.

[0044] Since multiple retail devices may be deployed when an operating contract is signed, the contract data in the established correspondence may correspond to more than one retail device.

[0045] To optimize the contract data corresponding to retail devices, this embodiment of the application, after determining the correspondence between retail devices and contract data, can further optimize the contract data by generating a rule configuration table based on the parsed contract data. This rule configuration table includes the acquired contract data. Furthermore, user configuration data can be received and used to update the rule configuration table.

[0046] For example, you can add contract data by clicking the "Add Contract Item" button in the configuration interface, or delete contract data by clicking the "Delete Contract Item" button. Alternatively, you can modify the rules of existing contract items by changing their values ​​or categories to obtain optimized contract items. This makes the rule configuration table more flexible and adaptable to the personalized requirements of different scenarios and retail devices.

[0047] For example, you can select a specific retail device, retrieve the rule configuration table for that device, update and optimize the rule configuration table, and adjust the monitoring rules for a single retail device to meet more detailed monitoring requirements.

[0048] In one possible implementation, two or more retail devices can be selected from multiple retail devices corresponding to the same contract data, and the rule configuration tables of the selected two or more retail devices can be uniformly adjusted to improve the optimization efficiency of the rule configuration tables of retail devices.

[0049] In S203, based on the correspondence, the retail goods of the retail equipment are detected by the prohibited goods characteristics of the retail equipment, and the price of the goods of the retail equipment is detected by the contract price requirement of the retail equipment.

[0050] After determining the correspondence between retail equipment and contract data, as well as the correspondence between retail equipment and retail equipment data, we can obtain the characteristics of prohibited goods corresponding to the retail goods in the retail equipment data, and the contract price requirements corresponding to the commodity prices in the retail equipment data.

[0051] In S204, the monitoring results of the retail goods of the retail equipment are determined based on the detection results of the retail goods and the detection results of the goods prices.

[0052] Based on the above correspondence, it is possible to detect whether the prohibited product characteristics in the contract data match their corresponding retail products, and to detect whether the contract price of a product in the contract data matches its corresponding product price. Specifically, this can be done as follows: Figure 4 As shown, it includes: In S401, the characteristics of retail goods and prohibited goods are checked to see if they match.

[0053] When detecting whether the characteristics of a retail product match those of a prohibited product, the product's characteristics can be extracted first, such as at least one of the product's material characteristics and category characteristics. For example, if the main ingredient in the product's material characteristics is white sugar, then the product matches a portion of the prohibited product characteristics for "high sugar." If the main ingredient in the product's material characteristics is water, then the product matches a portion of the prohibited product characteristics for "beverages." Assuming the complete expression of the prohibited product characteristics is "high sugar" & "beverage," if the main ingredients in the product's material characteristics are white sugar and water, then the product's material characteristics match the complete expression of the prohibited product characteristics, and the product is determined to be a prohibited product.

[0054] In S402, if the characteristics of a retail product match those of a prohibited product, the retail product is determined to be a prohibited product under monitoring.

[0055] If a retail item matches the characteristics of a prohibited item, it means that the characteristics of the retail item completely match the characteristics of a prohibited item, and the retail item can be directly identified as a prohibited item.

[0056] In S403, if the characteristics of a retail product match those of a prohibited product, the price of the product is checked to see if it meets the contract price requirements.

[0057] If a retail item only partially matches the characteristics of a prohibited item, or if the retail item does not match the characteristics of a prohibited item at all, then the item is determined to be a non-prohibited item. Further analysis can then be conducted to determine whether the price of the retail item meets the contract price requirements.

[0058] The contract price requirement for goods can include ensuring that the price of retail goods does not exceed a predetermined value. For example, the contract price requirement could be that the price of retail goods sold on the retail equipment does not exceed the selling price of the retail goods in nearby supermarkets. In this case, the location information of the retail equipment can be obtained, and based on this information, the nearest supermarket that meets the predetermined size requirement can be identified. Then, based on the found supermarket, the supermarket selling price of the retail goods sold on the retail equipment can be checked.

[0059] The system can retrieve nearby supermarkets from map data. The size of these supermarkets must meet pre-defined requirements, and their names can be pre-set, such as "XX Supermarket" or "XX Department Store." Based on these names, the system searches for nearby supermarkets and selects the one closest to the retail equipment. This is used to compare the prices of the retail equipment's goods with the equipment's prices to determine if they meet the contract price requirements.

[0060] In S404, if the price of a product does not meet the contract price requirements, the retail product is identified as a product with an abnormal price during monitoring.

[0061] If the price of a retail item in a retail facility is higher than its supermarket selling price, the price of that item is determined to be abnormal. The item is then classified as an abnormally priced item and its price needs to be adjusted to conform to the contract data.

[0062] In S405, if the price of a commodity meets the requirements of the commodity contract price, the monitoring result of the retail commodity is determined to be a normal commodity.

[0063] If the price of a product meets the requirements of the product contract price, and the characteristics of the retail product do not match those of prohibited products, then the monitoring result of the product is determined to be a normal product, and it can be sold normally.

[0064] In this embodiment of the application, after monitoring the retail goods of the retail equipment, the method can further identify the maintenance personnel of the retail equipment, send the monitoring results of the retail goods to the maintenance personnel, and send adjustment instructions to the retail equipment based on the monitoring results. These adjustment instructions can be used to suspend the sale of prohibited goods to avoid contract disputes arising from the sale of prohibited goods, or to adjust the sales price of goods with abnormal prices to meet the requirements of contract data.

[0065] When sending monitoring results for retail goods to maintenance personnel, information such as the names of prohibited items, the names of items with abnormal prices, and the time they were put on the shelves can be included. This facilitates maintenance personnel in quickly addressing abnormal items.

[0066] In one possible implementation, when the same area includes multiple retail devices and multiple maintenance personnel, in order to improve maintenance efficiency, when determining the maintenance personnel for a retail device, the workload of multiple maintenance personnel corresponding to the retail device can be obtained. Based on the workload of the maintenance personnel, maintenance personnel are assigned to the retail device to be maintained, and maintenance personnel with less workload are given priority to perform maintenance on the retail device to be maintained, thereby improving the response efficiency of device maintenance.

[0067] In possible implementations, embodiments of this application may also acquire sales data from retail equipment, predict the first popularity of prohibited goods and the second popularity of goods with abnormal prices based on the sales data. A third popularity of the retail equipment is determined based on the first and second popularity. Retail equipment to be maintained is assigned to maintenance personnel based on the third popularity, prioritizing equipment with higher third popularity. If the retail equipment to be maintained only contains prohibited goods and no goods with abnormal prices, the first popularity is directly used as the third popularity. Similarly, if the retail equipment to be maintained only contains goods with abnormal prices and no prohibited goods, the second popularity is directly used as the third popularity.

[0068] The first popularity metric represents the predicted number of times prohibited items might be purchased, the second popularity metric represents the predicted number of times items with abnormal pricing might be purchased, and the third popularity metric represents the predicted number of times abnormal items (including items with abnormal pricing and prohibited items) might be purchased. By prioritizing the processing of retail devices with higher third popularity metrics, the number of violations involving abnormal items can be reduced in a timely manner, thereby improving compliance satisfaction with retail devices.

[0069] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0070] Figure 5 This is a schematic diagram of a retail merchandise monitoring device provided in an embodiment of this application. The device includes: The data acquisition unit 501 is used to acquire retail equipment data and contract data through the business intelligence platform. The retail equipment data includes the retail goods and prices of each retail equipment, and the contract data includes the characteristics of prohibited goods and the contract price requirements for goods. The correspondence determination unit 502 is used to determine the correspondence between the retail equipment and the retail equipment data, and to determine the correspondence between the retail equipment and the contract data; The detection unit 503 is used to detect the retail goods of the retail equipment based on the prohibited goods characteristics of the retail equipment according to the correspondence, and to detect the price of the goods of the retail equipment based on the contract price requirements of the retail equipment. The monitoring result determination unit 504 is used to determine the monitoring result of the retail goods of the retail equipment based on the detection result of the retail goods and the detection result of the price of the goods.

[0071] Figure 5 The retail merchandise monitoring device shown is, with Figure 2 The retail product monitoring method shown corresponds to this.

[0072] Figure 6 This is a schematic diagram of a retail goods monitoring device provided in an embodiment of this application. Figure 6 As shown, the retail merchandise monitoring device 6 of this embodiment includes: a processor 60, a memory 61, and a computer program 62, such as a retail merchandise monitoring program, stored in the memory 61 and executable on the processor 60. When the processor 60 executes the computer program 62, it implements the steps in the various retail merchandise monitoring method embodiments described above. Alternatively, when the processor 60 executes the computer program 62, it implements the functions of each module / unit in the various device embodiments described above.

[0073] For example, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 62 in the retail merchandise monitoring device 6.

[0074] The retail merchandise monitoring device 6 can be a desktop computer, laptop, handheld computer, or cloud server, etc. The retail merchandise monitoring device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 6This is merely an example of a retail merchandise monitoring device 6 and does not constitute a limitation on the retail merchandise monitoring device 6. It may include more or fewer components than shown, or combine certain components, or different components. For example, the retail merchandise monitoring device may also include input / output devices, network access devices, buses, etc.

[0075] The processor 60 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0076] The memory 61 can be an internal storage unit of the retail merchandise monitoring device 6, such as a hard drive or memory. The memory 61 can also be an external storage device of the retail merchandise monitoring device 6, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the retail merchandise monitoring device 6. Furthermore, the memory 61 can include both internal and external storage units of the retail merchandise monitoring device 6. The memory 61 is used to store the computer program and other programs and data required by the retail merchandise monitoring device. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0077] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0078] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0079] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0080] In the embodiments provided in this application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0081] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0083] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0084] In addition, this application also provides a computer program product that, when run on a computer, causes the computer to execute the methods in the above-described implementations.

[0085] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for monitoring retail goods, characterized in that, The method includes: The business intelligence platform acquires retail equipment data and contract data. The retail equipment data includes the retail goods and prices of each retail equipment, and the contract data includes the characteristics of prohibited goods and the contract price requirements for the goods. Determine the correspondence between the retail equipment and the retail equipment data, and determine the correspondence between the retail equipment and the contract data; Based on the aforementioned correspondence, the retail goods of the retail equipment are detected by the prohibited goods characteristics of the retail equipment, and the prices of the goods of the retail equipment are detected by the contract price requirements of the retail equipment. Based on the detection results of the retail goods and the detection results of the goods prices, the monitoring results of the retail goods of the retail equipment are determined.

2. The method according to claim 1, characterized in that, Determining the correspondence between retail devices and the contract data includes: Obtain the monitoring scope included in the contract text data; Obtain the location information of the retail device; Based on the matching relationship between the location information and the monitoring range, the correspondence between the retail device and the contract data is determined.

3. The method according to claim 1, characterized in that, After determining the correspondence between retail devices and the contract data, the method further includes: A rule configuration table is generated based on the contract data; The system receives user configuration data and updates the rule configuration table using the configuration data, which includes at least one of adding, deleting, and modifying contract items.

4. The method according to claim 1, characterized in that, Based on the detection results of the retail goods and the detection results of the goods prices, the monitoring results of the retail goods of the retail equipment are determined, including: When it is detected that the characteristics of the retail product do not match those of the prohibited product, and the price of the product meets the contract price requirements, the monitoring result of the retail product is determined to be a normal product. When the retail product is detected to match the characteristics of the prohibited product, the monitoring result of the retail product is determined to be a prohibited product; When it is detected that the characteristics of the retail product do not match those of the prohibited product, and the price of the product does not meet the contract price requirements, the monitoring result of the retail product is determined to be a product with abnormal price.

5. The method according to claim 4, characterized in that, Detecting that the price of the commodity meets the contract price requirements includes: Obtain the location information of the retail device; Based on the location information, determine the supermarket price of the retail goods sold in the retail equipment located in the vicinity of the retail equipment; When the price of a retail item in the retail device is not higher than the supermarket selling price, the price of the item is determined to meet the contract price requirement.

6. The method according to claim 4, characterized in that, After determining the monitoring results of the retail goods on the retail equipment based on the detection results of the retail goods and the detection results of the goods prices, the method further includes: Identify the maintenance personnel for the retail equipment; Send the monitoring results of the retail goods to the maintenance personnel, and / or send adjustment instructions to the retail equipment based on the monitoring results, the adjustment instructions including suspending the sale of the prohibited goods, and / or adjusting the sales price of the abnormally priced goods.

7. The method according to claim 6, characterized in that, When a retail device is assigned to multiple maintenance personnel, the maintenance personnel for the retail device are determined as follows: Obtain the workload of multiple maintenance personnel corresponding to the retail equipment; Based on the workload of the maintenance personnel, maintenance personnel are assigned to the retail equipment to be maintained; Alternatively, obtain the sales data of the retail equipment; Based on the sales data, predict the first popularity of the prohibited goods and the second popularity of the goods with abnormal prices, and determine the third popularity of the retail equipment based on the first popularity and the second popularity; The maintenance personnel are assigned retail equipment to be maintained based on the third popularity of the retail equipment.

8. A retail merchandise monitoring device, characterized in that, The device includes: The data acquisition unit is used to acquire retail equipment data and contract data through the business intelligence platform. The retail equipment data includes the retail goods and prices of each retail equipment, and the contract data includes the characteristics of prohibited goods and the contract price requirements for goods. A correspondence determination unit is used to determine the correspondence between the retail equipment and the retail equipment data, and to determine the correspondence between the retail equipment and the contract data; The detection unit is used to detect the retail goods of the retail equipment based on the prohibited goods characteristics of the retail equipment according to the correspondence, and to detect the price of the goods of the retail equipment based on the contract price requirements of the retail equipment. The monitoring result determination unit is used to determine the monitoring result of the retail goods on the retail equipment based on the detection result of the retail goods and the detection result of the goods price.

9. A retail merchandise monitoring device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it causes the retail merchandise monitoring device to implement the method as described in any one of claims 1-7.

10. A computer program product comprising computer program instructions, characterized in that, When the computer program is run, the method as described in any one of claims 1-7 is performed.

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