WO2024105716A1 - 商品管理装置、商品管理方法、および記録媒体 - Google Patents

商品管理装置、商品管理方法、および記録媒体 Download PDF

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Publication number
WO2024105716A1
WO2024105716A1 PCT/JP2022/042167 JP2022042167W WO2024105716A1 WO 2024105716 A1 WO2024105716 A1 WO 2024105716A1 JP 2022042167 W JP2022042167 W JP 2022042167W WO 2024105716 A1 WO2024105716 A1 WO 2024105716A1
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Prior art keywords
product
individual
price
information
products
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Ceased
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PCT/JP2022/042167
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English (en)
French (fr)
Japanese (ja)
Inventor
寧 李
孝 立河
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NEC Corp
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NEC Corp
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Priority to US19/106,321 priority Critical patent/US20260073439A1/en
Priority to PCT/JP2022/042167 priority patent/WO2024105716A1/ja
Priority to JP2024558484A priority patent/JP7838675B2/ja
Publication of WO2024105716A1 publication Critical patent/WO2024105716A1/ja
Anticipated expiration legal-status Critical
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0623—Electronic shopping [e-shopping] by investigating goods or services
    • G06Q30/0625—Electronic shopping [e-shopping] by investigating goods or services by formulating product or service queries, e.g. using keywords or predefined options
    • G06Q30/06291—Electronic shopping [e-shopping] by investigating goods or services by formulating product or service queries, e.g. using keywords or predefined options for generating comparative results
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0641—Electronic shopping [e-shopping] utilising user interfaces specially adapted for shopping
    • G06Q30/0643—Electronic shopping [e-shopping] utilising user interfaces specially adapted for shopping graphically representing goods, e.g. 3D product representation
    • G06Q30/06435—Electronic shopping [e-shopping] utilising user interfaces specially adapted for shopping graphically representing goods, e.g. 3D product representation by generating side-by-side comparisons of goods or services

Definitions

  • This disclosure relates to technology for managing individual products.
  • Patent document 1 describes a technology that determines discount information based on the condition of the product and its sales deadline.
  • One example of the objective of this disclosure is to provide technology that allows multiple identical products to be managed according to their individual differences.
  • the product management device includes an acquisition means for acquiring sensor information including a plurality of identical products displayed, a state estimation means for estimating an individual state of each of the plurality of identical products displayed based on the sensor information, an extraction means for extracting, as a specific product, an individual product having a relatively different individual state from the plurality of identical products based on the individual state of each of the plurality of identical products, and an output means for outputting specific product information regarding the specific product.
  • a computer acquires sensor information including a plurality of identical products displayed, estimates the individual state of each of the plurality of identical products displayed based on the sensor information, extracts individual products with relatively different individual states from the plurality of identical products as specific products based on the individual states of each of the plurality of identical products, and outputs specific product information regarding the specific products.
  • a recording medium stores a program that causes a computer to execute a process of acquiring sensor information including a plurality of identical products displayed, estimating an individual state of each of the plurality of identical products displayed based on the sensor information, extracting individual products with relatively different individual states from the plurality of identical products as specific products based on the individual states of each of the plurality of identical products, and outputting specific product information regarding the specific products.
  • One example of the benefits of this disclosure is the ability to manage multiple identical products according to their individual differences.
  • FIG. 1 is a block diagram showing a configuration of a product management device in a first embodiment. 4 is a flowchart showing an operation of the product management device in the first embodiment.
  • FIG. 11 is a block diagram showing a configuration of a product management device in a second embodiment.
  • FIG. 11 is a diagram showing an example of price information in the second embodiment.
  • FIG. 11 is a diagram illustrating an example of an output in the second embodiment.
  • 10 is a flowchart showing an operation of a product management device in a second embodiment.
  • FIG. 13 is a block diagram showing a configuration of a product management device in a first modified example.
  • FIG. 11 is a block diagram showing a configuration of a product management device in a second modified example.
  • FIG. 13 is a diagram showing an example of output in Modification 2.
  • FIG. 2 is a diagram showing a hardware configuration in which a product management device according to the present disclosure is realized by a computer device and its peripheral devices.
  • each product management device may be realized by a terminal device used by a customer or a store clerk in a store, a combination of a terminal device and a server connected to the terminal device via a network, or a server.
  • the user who uses the terminal device may be, for example, a store clerk or a customer.
  • each product management device manages products displayed on shelves or in boxes in the sales floor of a store, products kept as inventory in the back yard of a store, or products displayed in a market where purchasing is performed. These products are called displayed products.
  • the processing related to products displayed on shelves in the sales floor of a store is mainly described, but the description of each embodiment and variation may be appropriately interpreted as other displayed products.
  • multiple identical products are grouped together and displayed in one or several places. Identical products are products of the same type. Products of the same type are, for example, products with the same product identification information.
  • Product identification information is, for example, information that identifies the type of product, such as an identification number included in a barcode.
  • product management refers to management related to the sale of products, such as setting (changing) prices, deciding display locations, and managing sales.
  • product management refers to management related to the sale of products, such as setting (changing) prices, deciding display locations, and managing sales.
  • individual differences affect how easily or difficult products sell. Therefore, management according to individual differences in products is required.
  • individual differences in products that change significantly in quality over time affect customer purchasing activities and product sales activities.
  • An example of a product that changes significantly in quality over time is food.
  • electrical appliances generally change less significantly in quality over time compared to food. Therefore, in the following embodiments and variants, the management of food products, which change significantly in quality over time, will be mainly described.
  • the products to be managed are not particularly limited, and products other than food products may also be used.
  • Fig. 1 is a block diagram showing the configuration of a product management device 100 according to the first embodiment.
  • the product management device 100 includes an acquisition unit 101, a state estimation unit 102, an extraction unit 103, and an output unit 104.
  • the acquisition unit 101 is an example of an acquisition means for acquiring sensor information including multiple identical products displayed.
  • the multiple identical products displayed are, for example, products displayed on shelves or in boxes in a sales area of a store, products stored as inventory in a back yard of a store, or products displayed in a market where purchases are made.
  • the sensor information including multiple identical products displayed is sensor information including some or all of the multiple identical products displayed.
  • the sensor information is two-dimensional data or three-dimensional data.
  • the sensor information may also be a combination of two-dimensional data and three-dimensional data.
  • the two-dimensional data is, for example, image data captured by a camera.
  • the three-dimensional data is, for example, data including distance acquired by a distance measuring sensor.
  • the distance measuring sensor is, for example, a TOF (Time Of Flight) distance measuring sensor, but is not limited to this.
  • TOF Time Of Flight
  • an image is mainly used as the sensor information
  • processing may be performed in the same manner as in the case of an image.
  • Images that include multiple identical items on display may include product information about the displayed items, such as bar codes or labels.
  • the acquisition unit 101 acquires sensor information including the multiple identical products displayed from a sensor.
  • the sensor is, for example, a camera that detects two-dimensional data, or a distance measurement sensor that detects three-dimensional data.
  • the acquisition unit 101 may acquire sensor information including the multiple identical products displayed from a memory unit in which the sensor information is transmitted and stored.
  • the camera may be a sensor installed in the store, or a sensor provided in a terminal device.
  • the sensor installed in the store is connected to the product management device 100 via a network, for example.
  • the acquisition unit 101 acquires sensor information in response to a user instruction.
  • the acquisition unit 101 may acquire the detected sensor information at a predetermined time interval.
  • the state estimation unit 102 is an example of a state estimation means that estimates the individual state of each of a plurality of identical products displayed based on sensor information. Below, an example will be described in which the state estimation unit 102 mainly estimates the individual state of each of a plurality of identical products displayed based on an image.
  • the individual state is, for example, at least one of the size of the individual product, the color of the individual product, whether or not the individual product has scratches, the shape of the individual product, whether or not the individual product has unevenness, the expiration date of the individual product, or the arrival date of the individual product.
  • the individual state may each include the degree of scratches on the individual product or the degree of unevenness of the individual product. Here, the degree may be, for example, size or number. Furthermore, the degree of scratches on the individual product may be poor color.
  • the state estimation unit 102 estimates the size, color, presence or absence of scratches, and shape of each individual product based on the image acquired by the acquisition unit 101. For example, the state estimation unit 102 first identifies multiple identical products that are displayed. For example, identifying multiple identical products that are displayed means identifying product identification information of multiple identical products that are displayed. Next, the state estimation unit 102 detects individual products based on the image acquired by the acquisition unit 101. Here, the detection of individual products means the image area of each individual product in the image. A publicly known image recognition technique may be used to detect individual products. For example, the state estimation unit 102 detects the outline of the individual product in the image. Then, the state estimation unit 102 estimates the individual state of each individual product based on the pixel information of each individual product. The state estimation unit 102 may estimate the individual state of each individual product by other methods.
  • the acquisition unit 101 acquires an image captured by a camera in a store.
  • the state estimation unit 102 identifies multiple identical products displayed in the image based on, for example, the position and shooting direction of the camera installed in the store. For example, identification information of the camera installed in the store, information on the camera's position and shooting direction, and identification information of the products arranged in the area captured by the camera's position and shooting direction are associated in advance and stored in a storage unit (not shown).
  • the storage unit (not shown) may be provided inside the product management device or externally connected to the product management device so as to be able to communicate with it.
  • the state estimation unit 102 may identify multiple identical products included in the image from the identification information of the camera that acquired the image by the acquisition unit 101 by referring to the storage unit. Note that if the shooting direction of the camera can be changed, the acquisition unit 101 acquires the image, the identification information of the camera that acquired the image, and the shooting direction of the camera. Note that the identification of multiple identical products displayed in the image may be performed by other methods.
  • the acquisition unit 101 may acquire the product identification information of the product included in the captured image input by the user on the terminal device at the time of shooting, in association with the image.
  • the acquisition unit 101 may acquire an image of a product specified by the user's operation of the terminal device from a camera in the store.
  • the acquisition unit 101 instructs a camera capable of capturing an image of the specified product to capture an image including multiple identical products displayed, based on the product identification information of the product specified by the user's operation of the terminal device, by referring to the storage unit. If the shooting direction of the camera can be changed, the shooting instruction includes the shooting direction.
  • the acquisition unit 101 acquires an image including multiple identical products displayed, which are products specified by the user's operation of the terminal device. Then, the state estimation unit 102 identifies multiple identical products displayed, based on the image captured by the camera in the store acquired by the acquisition unit 101, and the product specified by the user's operation of the terminal device associated with the image. Also, for example, the acquisition unit 101 acquires from the terminal device information representing a product specified by a user's operation of the terminal device, and an image including multiple identical products displayed and captured by the terminal device. The state estimation unit 102 may then identify multiple identical products displayed based on the image acquired by the acquisition unit 101, captured by the camera of the terminal device, and the product specified by the user's operation of the terminal device, associated with the image.
  • the state estimation unit 102 may identify a product by information on the characters or barcode of a price tag on a product shelf included in an image including multiple identical products displayed, or included in another image acquired in association with an image including multiple identical products displayed. For example, the state estimation unit 102 may recognize characters included in an image by character recognition. The state estimation unit 102 may identify, from among the recognized characters, the name of a product included in a product information database to which the product name and product identification information are associated, as the name of the multiple identical products displayed. Also, for example, the state estimation unit 102 may read a barcode included in the image. The state estimation unit 102 may identify a character string read from the barcode as the product identification number of the multiple identical products displayed.
  • the state estimation unit 102 In estimating individual states by the state estimation unit 102, after identifying the multiple identical products displayed in the image as described above, the state estimation unit 102 detects the image area of each individual product.
  • the state estimation unit 102 detects each of the multiple identical products on display that were identified in the above-mentioned identification process from the acquired image, for example, using deep learning or other image analysis methods. Specifically, the state estimation unit 102 detects image areas of the multiple identical products included in the acquired image. The state estimation unit 102 detects image areas of individual products for each of the multiple identical products from among the image areas of the detected multiple identical products. For example, the state estimation unit 102 may detect the outline of each individual product.
  • the state estimation unit 102 estimates the individual states of the individual products.
  • the state estimation unit 102 estimates at least one of the size, shape, and color of the individual product as the individual state from the data of the image area of the individual product.
  • the information representing the size and shape of the individual product may be information representing the outline of the individual product.
  • the information representing the color may be RGB values, brightness, saturation, etc.
  • the state estimation unit 102 estimates the product state from a portion of the image area of the individual product shown in the image.
  • the individual state may also include information indicating that the entire individual product is not shown, i.e., that the estimation of the individual state is incomplete.
  • the state estimation unit 102 may further estimate the individual state based on the information representing the outline of the individual product or the information representing the color of the individual product described above. For example, the state estimation unit 102 may estimate the presence or absence of unevenness as information representing the shape of the individual product. Since it is assumed that a shadow will be cast on a dent in a product, the state estimation unit 102 may estimate the presence or absence of unevenness of the individual product by determining that a pixel having a lower brightness than the surrounding pixels is a dent based on information representing the color of the pixels in the image area of the individual product.
  • the state estimation unit 102 may estimate the presence or absence of scratches on the individual product by determining that a pixel area having an RGB value significantly different from the surrounding pixels is a scratch based on information representing the color of the pixels in the image area of the individual product. Note that the estimation of the presence or absence of unevenness of the individual product and the estimation of the presence or absence of scratches on the individual product may be performed by the extraction unit 103 described below.
  • the state estimation unit 102 may also estimate the individual state based on the image acquired by the acquisition unit 101 using a trained model.
  • the trained model is generated in advance by executing a learning process using machine learning with training data including images of products without scratches, images of products with scratches, images of products with good color, images of products with poor color, images of products with good shape, and images of products with poor shape.
  • the state estimation unit 102 inputs the product image into the trained model.
  • the trained model outputs the individual states of the products included in the image area of the individual products, such as whether or not they have scratches, whether their color is good or bad, and whether their shape is good or bad.
  • the state estimation unit 102 then regards the output individual states as the estimation results.
  • the state estimation unit 102 may estimate the expiration date or arrival date as the individual state of the individual product based on the image acquired by the acquisition unit 101.
  • the state estimation unit 102 may estimate the expiration date or arrival date of the individual product, for example, by recognizing characters printed on the label of the individual product included in the image.
  • the state estimation unit 102 may read a two-dimensional code printed on the label of the individual product included in the image, and acquire the expiration date or arrival date of the individual product associated with the two-dimensional code.
  • the state estimation unit 102 may also add environmental information regarding the environment in which the product is displayed to the individual state.
  • the environmental information regarding the environment in which the product is displayed is, for example, the temperature or humidity received from a sensor not shown.
  • the environmental information may also include the presence or absence of sunlight. This environmental information changes depending on the location in which the product is displayed. In general, the same product may be displayed in different environments.
  • the locations in which the product is displayed may be, for example, products displayed indoors, products displayed outdoors, or products displayed in a refrigerator.
  • the state estimation unit 102 identifies the display location of the individual products. That is, the state estimation unit 102 may identify the location where an image including multiple identical products displayed was taken. If the camera from which the acquisition unit 101 acquires an image is a camera installed in a store, the state estimation unit 102 may identify the display location of the products included in the acquired image from information indicating the camera position and shooting direction of the acquired image based on pre-stored information on the position and shooting direction of the camera installed in the store and information on the location where the image is captured at that camera position and shooting direction. Furthermore, for example, the state estimation unit 102 may identify the display location based on the image and information on the shooting location input by the user at the time of shooting, acquired by the acquisition unit 101.
  • the state estimation unit 102 may estimate the individual state based on three-dimensional data including a plurality of individual items displayed.
  • the state estimation unit 102 may estimate the individual state based on an image including a plurality of individual items displayed and three-dimensional data including a plurality of individual items displayed.
  • the state estimation unit 102 estimates the individual state using three-dimensional data, it becomes possible to more accurately estimate the size, volume, and dents of the individual items, among the individual states.
  • the extraction unit 103 is an example of an extraction means for extracting individual products with relatively different individual states from a plurality of identical products as specific products based on the individual states of the individual products.
  • a specific product is an individual product with a relatively different individual state among a plurality of identical products.
  • a product with a relatively different individual state may be a product with a poor individual state among a plurality of identical products, or a product with a good individual state.
  • the product management device 100 manages products for specific products and individual products other than the specific products. For example, the extraction unit 103 compares the individual states of the plurality of identical products to extract an individual product with a relatively poor individual state as a specific product from a plurality of identical products.
  • the extraction unit 103 may also compare the individual states of the plurality of identical products to extract an individual product with a good individual state as a specific product.
  • the extraction unit 103 can extract specific products with relatively different individual states based on the individual states of the plurality of identical products, taking into account the overall state of the plurality of identical products that changes depending on the time of year, timing, etc.
  • the extraction unit 103 extracts specific products whose individual conditions differ relatively, making it possible to appropriately manage individual products according to the overall condition and individual differences of multiple identical products that change depending on the time of year, timing, etc.
  • the extraction unit 103 may extract a specific product by comparing a criterion based on the individual state of the individual product with the individual state of the individual product.
  • the criterion based on the individual state of the individual product is a criterion calculated based on the overall individual state of each of the individual products, which are multiple identical products displayed in the image.
  • the criterion based on the individual state of the individual product is a criterion relative to each of the individual products, which are multiple identical products displayed in the image. For example, it is the average value of the individual states of the individual products in the multiple identical products displayed.
  • the relative criterion may be calculated by the state estimation unit 102 or the extraction unit 103.
  • the extraction unit 103 extracts a specific product that is likely to sell well by comparing the criterion with the individual state of each individual product.
  • a specific product that is likely to sell well is a product that is an appropriate size, a large product, a product without scratches, a product with a good color, or a product with a good shape.
  • a product that is appropriate size is a product whose size is within a predetermined range.
  • the extraction unit 103 may extract a specific product that is unlikely to sell well based on the criterion. For example, certain products that are unlikely to sell are products that are the wrong size, small, scratched, have the wrong color, or are misshapen.
  • the criteria may be a reference value or a range of reference values for each individual state of the same product.
  • the criteria may be a reference value or a range of reference values representing the size, shape, or color of an individual product.
  • the extraction unit 103 may use absolute criteria in addition to relative criteria to extract a specific product.
  • the absolute criteria is a preset absolute criteria.
  • the absolute criteria is, for example, a preset range of pixel values that indicate the appropriate color of a banana.
  • the individual state estimated by the state estimation unit 102 is binary identification information indicating whether the size is appropriate or not, whether the size is large or small, whether the color is good or bad, or whether the shape is good or bad, or binary identification information indicating the presence or absence of scratches or the presence or absence of unevenness, no criteria are required.
  • the binary identification information may be, for example, the presence or absence of a flag.
  • the extraction unit 103 may extract individual products that are in an inappropriate size, poor color, poor shape, or have scratches or unevenness as specific products based on information indicating the inappropriate size, poor color, poor shape, or the presence of scratches or unevenness.
  • the extraction unit 103 compares each value or level with a criterion for determining that the individual product is a specific product in a predetermined state, and extracts the specific product.
  • the output unit 104 is an example of an output means that outputs specific product information related to a specific product.
  • the output unit 104 also outputs the specific product information to a store clerk or customer who is the user.
  • the output unit 104 outputs the specific product information to a display unit of a terminal device used by a customer or store clerk in the store.
  • the output unit 104 may output, as specific product information, information indicating that there are specific products with relatively different individual states. Alternatively, the output unit 104 may output, as specific product information, information that allows the specific product to be identified and the individual state of the specific product.
  • the information that allows the specific product to be identified may be, for example, an image in which a symbol indicating the specific product is superimposed on an image including multiple identical products.
  • the information that allows the specific product to be identified may be, for example, an image in which the specific product is circled in an image including multiple identical products.
  • the output unit 104 may output information that allows the specific product to be identified and information regarding the management of the specific product.
  • the output unit 104 may output, as specific product information, information that allows the specific product to be identified and a price set for the specific product to a customer. Also, for example, the output unit 104 may output, as specific product information, information that allows the specific product to be identified and an appropriate display location for the specific product to a store clerk. Examples of output by the output unit 104 are not limited to these.
  • the output unit 104 may project the specific product information onto the display location of the product, which is within the range of the image capture.
  • the output unit 104 outputs the specific product information to a projector capable of projecting an image onto the display location of the product, which is within the range of the image capture.
  • the output unit 104 may superimpose the specific product information onto an image of the specific product on display.
  • the specific product information output by the output unit 104 may include identification information of the specific product.
  • the identification information of the specific product may be information that allows the specific product to be identified from identical products.
  • the identification information of the specific product may be, for example, an identification number.
  • the identification information of the specific product may also be an image of the specific product. In this case, it is preferable that the image of the specific product includes external features of the specific product.
  • FIG. 2 is a flowchart showing an overview of the operation of the product management device 100 in the first embodiment. Note that the processing according to this flowchart may be executed based on program control by a processor.
  • the acquisition unit 101 acquires sensor information including multiple identical products displayed (step S101).
  • the state estimation unit 102 estimates the individual state of each of the multiple identical products displayed based on the sensor information (step S102).
  • the extraction unit 103 extracts individual products having relatively different individual states from the multiple identical products as specific products based on the individual states of each of the multiple identical products (step S103).
  • the output unit 104 outputs specific product information related to the specific product (step S104).
  • the product management device in the present embodiment described above includes an acquisition unit, a state estimation unit, an extraction unit, and an output unit.
  • the acquisition unit acquires sensor information including a plurality of identical products displayed.
  • the state estimation unit estimates the individual state of each of the plurality of identical products displayed based on the sensor information.
  • the extraction unit extracts, as specific products, individual products with relatively different individual states from the plurality of identical products based on the individual states of each of the plurality of identical products. Then, the output unit 104 outputs specific product information related to the specific products.
  • the product management device in this embodiment can manage multiple identical products according to their individual differences. This allows the product management device in this embodiment to streamline tasks related to management according to individual differences in products. For example, the product management device in this embodiment can streamline tasks related to management so that products that are thought to be difficult to sell can be sold appropriately according to individual differences in the products.
  • FIG. 3 is a block diagram showing the configuration of a product management device according to a second embodiment of the present disclosure.
  • the product management device 200 of the second embodiment includes a price setting unit 205 in addition to the configuration of the first embodiment.
  • the price setting unit 205 is an example of a price setting means that sets the price of a specific product based on price information that indicates the relationship between the price of the same product and its individual state and the individual state of the specific product.
  • the price information that indicates the relationship between the price of the same product and its individual state is set in advance, for example, by week, day, or hour.
  • the price setting unit 205 sets the price of a specific product by referring to the price information based on the individual state of the specific product extracted by the extraction unit 103.
  • the price information may be stored in the product management device 200 or in a database connected to the product management device 200 via a network. Note that setting the price includes changing the price from a preset price.
  • Figure 4 shows an example of price information that indicates the relationship between the price and individual condition of the same product.
  • Figure 4 shows the price according to the individual condition of the same product. According to Figure 4, when the individual condition is normal, that is, when it is not extracted as a specific product, the price of the individual product is 120 yen. Also, Figure 4 shows prices according to color, size, and the presence or absence of scratches.
  • Figure 4 is an example of price information, and price information is not limited to these examples.
  • the extraction unit 103 may extract individual products that are in the individual state indicated in the price information based on the price information and the individual state estimated by the state estimation unit 102.
  • the price setting unit 205 may also set the price of an individual product according to the difference between a standard and the individual state of the specific product.
  • the standard may be based on the individual state of the individual product.
  • the price setting unit 205 may determine the price of the specific product based on price information that indicates the relationship between the price of the same product and the difference between the standard and the individual state of the specific product.
  • the output unit 104 outputs the price of the specific product as specific product information related to the specific product.
  • An example of the output of the price of the specific product is shown in FIG. 5.
  • the price is displayed for each product.
  • the product may be shown by an image acquired by the acquisition unit 101, or may be shown by an illustration based on an image acquired by the acquisition unit 101.
  • the prices of 75 yen and 85 yen are superimposed on the product image for potatoes that are relatively different in color from the colors of the multiple identical products displayed.
  • a price of 80 yen is displayed for potatoes that are relatively small compared to the size of the multiple identical products displayed.
  • a price of 75 yen is displayed for potatoes that are damaged.
  • the prices of products other than the specific products may also be displayed.
  • the time at which the price was set may be displayed as in FIG. 5 so that the user can know at what point in time the price was set.
  • the output unit 104 may output the identification information of the specific product and the price of the specific product as the specific product information.
  • the output unit 104 may further output the reason for setting the price of the specific product. For example, in self-scan shopping where a customer registers purchased products while shopping around the store, the output unit 104 may output the identification information of the specific product and the price of the specific product to a list of purchased products.
  • the output unit 104 may output the identification information of the specific product and the price of the specific product to a sticker issuing device as the specific product information.
  • the output unit 104 may output a two-dimensional code including the identification information of the specific product and the price of the specific product to the sticker issuing device as the specific product information.
  • the output unit 104 may output a two-dimensional code including the identification information of the specific product and the price of the specific product to a printing device using edible ink as the specific product information.
  • the price setting unit 205 may also set a price range for a specific product based on the price information and the individual state of the specific product.
  • the price information includes a price range as the price of the same product.
  • the output unit 104 outputs the price range for the specific product to the user using the product management device 200.
  • the output unit 104 outputs the price range of the specific product to a store clerk who is a user using the product management device 200.
  • the store clerk who is a user using the product management device 200 may determine the price of the specific product within the output price range of the specific product.
  • the price setting unit 205 may determine the price according to the individual state estimated based on the reacquired sensor information.
  • the image may be interpreted as sensor information, shooting as detection, and a shooting instruction as a detection instruction.
  • the output unit 104 further outputs a photographing instruction to the user, clerk or customer, to photograph a specific product image, which is an image of the specific product, in addition to the price range of the specific product.
  • the photographing instruction is an instruction to photograph the specific product closer than an image including multiple identical products displayed.
  • the photographing instruction may also be an instruction to photograph the specific product from multiple directions.
  • the acquisition unit 101 further acquires the specific product image photographed based on the photographing instruction.
  • the state estimation unit 102 re-estimates the individual state based on the acquired specific product image.
  • the price setting unit 205 sets the price of the specific product based on the price information representing the relationship between the price and the individual state of the identical product and the individual state of the specific product.
  • the price setting unit 205 may further set the price of the specific product within the previously set price range.
  • the output of the photographing instruction for the specific product and the process of re-estimating the individual state may be performed when the individual state of the specific product has not been sufficiently estimated.
  • the case where the individual state of the individual product has not been sufficiently estimated is, for example, a case where it is estimated that a part or most of the individual product is hidden in an image including multiple identical products.
  • FIG. 6 is a flowchart showing an example of the operation of the product management device 200 in the second embodiment. Note that the processing according to this flowchart may be executed based on program control by a processor.
  • the acquisition unit 101 acquires an image including multiple identical products displayed (step S201).
  • the state estimation unit 102 estimates the individual state of each of the multiple identical products displayed based on the image (step S202).
  • the extraction unit 103 extracts a specific product for which a price is to be set from among the individual products (step S203). If a specific product for which a price is to be set is not extracted in step S203, the output unit 104 may output a message indicating that a specific product has not been extracted, and the product management device 200 may end its operation.
  • the price setting unit 205 sets a price range for the specific product based on the individual condition and price information of the specific product (step S204).
  • the output unit 104 outputs the price range of the specific product set in step S204 and an instruction to capture an image of the specific product (step S205).
  • the acquisition unit 101 acquires the specific product image captured by the user based on the image capture instruction (step S206).
  • the state estimation unit 102 re-estimates the individual state based on the specific product image (step S207).
  • the price setting unit 205 sets the price of the specific product based on the re-estimated individual condition and price information of the specific product (step S208).
  • the output unit 104 outputs the set price of the specific product (step S209).
  • the product management device in the present embodiment described above includes an acquisition unit, a state estimation unit, an extraction unit, an output unit, and a price setting unit.
  • the acquisition unit acquires sensor information including a plurality of identical products displayed.
  • the state estimation unit estimates the individual state of each of the plurality of identical products displayed based on the sensor information.
  • the extraction unit extracts, as specific products, individual products having relatively different individual states from the plurality of identical products based on the individual states of each of the plurality of identical products.
  • the price setting unit sets the price of the specific product based on the price information indicating the relationship between the price and individual state of the identical products and the individual state of the specific product. Then, the output unit 104 outputs specific product information regarding the specific product.
  • the product management device in this embodiment can manage multiple identical products according to their individual differences.
  • the product management device in this embodiment can set prices according to individual differences among multiple identical products. For example, by appropriately setting prices according to individual differences among products, it is possible to improve the customer's sense of satisfaction and satisfaction with the price of the purchased product. Also, for example, by appropriately setting prices according to individual differences among products, products that are difficult to sell due to individual differences become easier to sell.
  • the product management device in this embodiment can improve the efficiency of the work of store clerks in setting prices according to individual differences in products.
  • the product management device in this embodiment allows the user (store clerk) to easily find a specific product that can be priced among multiple identical products.
  • the product management device in this embodiment can also assist customers in finding products they want to purchase from among identical products with individual differences.
  • individual products with relatively different individual conditions are extracted as specific products, and a price or price range is output as specific product information, allowing customers to easily find products that are cheaper, for example.
  • FIG. 7 is a block diagram showing the configuration of a product management device 200A according to a first modification of the second embodiment.
  • the product management device 200A according to the first modification may further include a change request receiving unit 206 in addition to the configuration of the product management device 200 according to the second embodiment.
  • the change request receiving unit 206 is an example of a change request receiving means that receives a price change request, which is a request to change the price of a specific product for which specific product information has been output by the output unit 104.
  • the specific product information includes a price or a price range.
  • the change request receiving unit 206 receives a price change request from a user to whom the price or price range of a specific product has been output, for example, from a touch panel display provided on a terminal device.
  • the user who inputs the price change request is a store clerk or a customer.
  • the price change request may include the reason for the change request. For example, if the reason for the change request is the appearance of the product, the change request receiving unit 206 may receive an image including the part of the product that is the reason for the change request as the reason for the change request.
  • the price setting unit 205 sets the price of a specific product based on the price change request received by the change request receiving unit 206, the price information, the individual state of the specific product, and a preset price tolerance range.
  • the price tolerance range is the range of prices permitted in setting the price of a product.
  • the price setting unit 205 sets the price or price range of a specific product within the price tolerance range.
  • the price tolerance range may be set in advance for each product. Alternatively, the price tolerance range may be set for all products or for each product category, for example, within a specified percentage of the base price.
  • the change request receiving unit 206 receives a price change request, and the price setting unit 205 sets the price, so that the product management device 200A in this modified example enables more appropriate pricing of individual products according to their individual conditions.
  • This allows the product management device 200A to, for example, increase the customer's sense of satisfaction and satisfaction with the price of individual products.
  • the product management device 200A can support store clerks in more appropriate pricing of individual products according to their individual conditions.
  • FIG. 8 is a block diagram showing the configuration of a product management device according to the second modification of the present disclosure.
  • the product management device 300 of the second modification includes a business support information generation unit 307 in addition to the configuration of the first embodiment.
  • the business support information generating unit 307 generates business support information according to the individual state of each of the multiple identical products displayed.
  • the business support information is, for example, information on the price of the individual products, information on the display location of the individual products, and information on the sales of the individual products.
  • the output unit 104 outputs the business support information.
  • the business support information generating unit 307 generates, for example, information related to setting the price of an individual product.
  • the business support information is information that supports the price setting work of a store clerk, more specifically, the work of a store clerk reducing the price of a product.
  • the business support information generating unit 307 that generates information related to the price of an individual product has the function of the price setting unit 205 in the second embodiment.
  • the business support information generating unit 307 generates business support information including a specific product for which a price should be set and the price to be set, based on price information that indicates the relationship between the price and individual state of the same product and the individual state of the specific product.
  • the business support information generating unit 307 may also generate business support information that includes the specific product for which a price should be set and the price to be set, as well as the reason for setting the price.
  • the business support information generating unit 307 also generates information on the display location of individual products, for example.
  • the business support information is information that supports the display work of store clerks in displaying products. More specifically, the business support information is information that supports the work of identifying clearance items to be displayed on dedicated shelves. Clearance items are products that are reduced in price because they are unlikely to sell.
  • the business support information generating unit 307 Based on display location information that indicates the display location according to a preset individual state and the individual state of the specific product whose display location should be changed, the business support information generating unit 307 outputs business support information including the specific product whose display location should be changed and the display location of the specific product.
  • the display location information may include, as information indicating the display location according to the individual state, not displaying products that are in an individual state that are unsellable.
  • An individual state that is unsellable is, for example, a state in which the product is heavily damaged or the degree of damage to the product is large.
  • the output unit 104 outputs information about the display location of a specific product based on the display location information that indicates the display location according to the individual state.
  • the business support information generation unit 307 generates information about the display location of individual products, and the output unit 104 outputs information about the display location of a specific product, so that the product management device 300 can make it more efficient for store clerks to manage the display locations according to the individual differences of the products. In other words, the product management device 300 can save the store clerk the trouble of checking the individual differences of the products and considering the display locations according to the situation differences of the products.
  • the business support information generating unit 307 also generates sales information related to the sales of individual products, for example.
  • the business support information generating unit 307 that generates sales information is also referred to as a sales information generating unit.
  • the sales information generating unit is an example of a sales information generating means that identifies sales of individual products based on sensor information and individual states in the store, and generates sales information that associates the sales of the identified individual products with the individual states.
  • the sales information generating unit first identifies individual products that have been removed from the product shelves based on changes over time in sensor information including multiple identical products displayed. Products that have been removed from the product shelves are presumed to be products purchased by customers.
  • the sales information generating unit generates the individual states of the individual products removed from the product shelves and the individual states of the remaining individual products as sales information.
  • the sales information generating unit may also identify a sales trend according to the individual states based on the individual states of the individual products removed from the product shelves and the individual states of the remaining individual products.
  • the sales information generating unit may then generate sales information based on the sales trends according to the individual states.
  • the output unit 104 may output the sales information in response to a user request.
  • FIG. 9 is an example of the output of business support information.
  • the price according to the individual state of a specific product and the display location according to the individual state are displayed as business support information.
  • the prices of 75 yen for potatoes with relatively different colors and 75 yen for potatoes with blemishes are displayed for the specific products in the image.
  • the specific products, potatoes with relatively different colors and potatoes with blemishes are displayed in circles so that they can be easily identified.
  • FIG. 9 displays business instructions for the specific products as business support information.
  • the products may be shown by an image acquired by the acquisition unit 101, or may be shown by an illustration based on an image acquired by the acquisition unit 101.
  • the individual state and the price of the same product may change when the time changes, so the time at which the price and display location were set may be displayed so that the user can know at what point in time the price and display location were set.
  • the business support information generating unit 307 generates sales information that associates the individual state of each individual product with the sales of each individual product, and the output unit 104 outputs the sales information, so that the product management device 300 can provide sales information according to individual differences to the store clerk.
  • the product management device 300 can provide information related to the sales of products according to individual differences such as product procurement and display to the store clerk.
  • the information processing device 1000 includes, as an example, the following configuration.
  • I/F Input/output I/F 1010 for inputting and outputting data
  • bus 1011 that connects each component It should be noted that I/F is an abbreviation for Interface.
  • each component of each device or system is realized by the CPU 1001 acquiring and executing a program that realizes these functions.
  • the programs that realize the functions of each component of each device are stored in advance in the storage device 1005 or RAM 1003, for example, and are read by the CPU 1001 as needed.
  • the program 1004 may be supplied to the CPU 1001 via a communications network, or may be stored in advance on the recording medium 1006, and the drive device 1007 may read out the program and supply it to the CPU 1001.
  • each device is realized.
  • each device or system may be realized by any combination of a separate information processing device 1000 and a program for each component.
  • multiple components of each device may be realized by any combination of a single information processing device 1000 and a program.
  • each device or system may be realized by a general-purpose or dedicated circuit including a processor, or a combination of these.
  • the circuit may be, for example, a CPU, a GPU (Graphics Processing Unit), an FPGA (Field Programmable Gate Array), or an LSI (Large Scale Integration).
  • the LSI may be, for example, an LSI dedicated to AI (Artificial Intelligence) processing. These may be configured by a single chip, or may be configured by multiple chips connected via a bus.
  • AI Artificial Intelligence
  • Some or all of the components of each device may be realized by a combination of the above-mentioned circuits, etc., and a program.
  • the multiple information processing devices, circuits, etc. may be centrally located or distributed.
  • the information processing devices, circuits, etc. may be realized as a client-server system, cloud computing system, etc., in a form in which each is connected via a communication network.
  • the product management device may be modified to include the product management device 200 of the second embodiment or the product management device 200A of the first modified example, as a product management device that includes the business support information generation unit 307.
  • the multiple operations are described in sequence in the form of a flowchart, the order of description does not limit the order in which the multiple operations are performed. Therefore, when implementing each embodiment, the order of the multiple operations may be changed to the extent that does not interfere with the content.

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Citations (6)

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Publication number Priority date Publication date Assignee Title
JP2002083369A (ja) * 2000-09-06 2002-03-22 Sharp Corp 商品管理システム
JP2002293416A (ja) * 2001-03-29 2002-10-09 Fujitsu Ltd 遠隔棚卸システム並びに同システム用店舗側端末装置および遠隔管理装置
JP2010231615A (ja) * 2009-03-27 2010-10-14 Toshiba Tec Corp 情報処理装置
JP2011113265A (ja) * 2009-11-26 2011-06-09 Toshiba Tec Corp 販売支援システム及び販売支援方法
JP2021009537A (ja) * 2019-07-01 2021-01-28 株式会社野村総合研究所 商品期限管理システム
JP2021159263A (ja) * 2020-03-31 2021-10-11 ダイキン工業株式会社 陳列装置

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Publication number Priority date Publication date Assignee Title
JP2002083369A (ja) * 2000-09-06 2002-03-22 Sharp Corp 商品管理システム
JP2002293416A (ja) * 2001-03-29 2002-10-09 Fujitsu Ltd 遠隔棚卸システム並びに同システム用店舗側端末装置および遠隔管理装置
JP2010231615A (ja) * 2009-03-27 2010-10-14 Toshiba Tec Corp 情報処理装置
JP2011113265A (ja) * 2009-11-26 2011-06-09 Toshiba Tec Corp 販売支援システム及び販売支援方法
JP2021009537A (ja) * 2019-07-01 2021-01-28 株式会社野村総合研究所 商品期限管理システム
JP2021159263A (ja) * 2020-03-31 2021-10-11 ダイキン工業株式会社 陳列装置

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