Unmanned store product calculation method and device

Abstract

A commodity calculation method and device for an unmanned store are disclosed. The commodity calculation device for an unmanned store according to an embodiment of the present invention includes a transport unit for transporting commodities, a commodity recognition unit for recognizing that a commodity is placed on the transport unit, a scanning unit for scanning a barcode and an image of the commodity transported by the transport unit, a weight sensor for measuring the weight of the scanned commodity, a processor for identifying what the commodity is, a commodity classification unit for classifying the commodity into a first zone or a second zone based on the commodity identification result, and a calculation unit for calculating a total price by summing up a first price obtained by summing up the prices of the commodities classified into the first zone and a second price obtained by summing up the prices of the commodities classified into the second zone and confirmed by a manager.

Description

[Technical field]

[0001] The present invention relates to a commodity calculation method and device for an unmanned store. [Background technology]

[0002] The following description is merely intended to provide background information related to one embodiment of the present invention and is not intended to constitute prior art.

[0003] Attempts are being made to automate the entire logistics process, including product production, shipping, transportation, unloading, packaging, storage, and calculation, in order to reduce manpower and improve accuracy. Automating logistics has the effect of reducing costs by reducing the number of personnel and preventing safety accidents, shortening the time required for logistics, and enabling systematic management.

[0004] In particular, when calculating the cost of merchandise at a sales floor, a store employee must scan the barcode of each item using a barcode scanning device to calculate the cost of merchandise. This increases the time required to calculate the cost of merchandise, which not only increases the chronic and unnecessary waiting time of customers, but also increases the congestion in the store. This creates a problem in that store operation and management costs also increase due to the need to hire employees to calculate the cost of merchandise.

[0005] This has created a demand for technology that can quickly and accurately perform calculations for products that customers are calculating without human intervention. Summary of the Invention [Problem to be solved by the invention]

[0006] An object of the present invention is to provide a method for calculating merchandise items in an unmanned store.

[0007] Another object of the present invention is to improve the recognition rate of products through artificial intelligence learning data, thereby enabling quick and accurate product calculation.

[0008] Another object of the present invention is to reduce the operational and management costs of a store by reducing personnel. [Means for solving the problem]

[0009] According to an embodiment of the present invention, a product calculation device for an unmanned store includes a transport unit that transports products to be purchased by a user so that the products can be scanned; a product recognition unit that is installed at a first location where the transport unit starts transporting the products and recognizes that the products have been placed on the transport unit so that the transport unit can start operating; a scan unit that is installed at a preset distance from the transport unit and scans barcodes and images of the products transported by the transport unit; a weight sensor that is installed at one side of a lower portion of the transport unit and measures weight for verifying the scanned products; a processor that identifies the products using artificial intelligence learning data based on the barcodes and images of the products scanned by the scan unit and the weight of the products measured by the weight sensor; a product classification unit that is installed at a second location where the transport unit finishes transporting the products and classifies the products into a first zone or a second zone based on the product identification result; and a calculation unit that calculates a total price by adding up a first price obtained by adding up prices of the products classified in the first zone and a second price obtained by adding up prices of the products classified in the second zone and confirmed by an administrator.

[0010] The scanning unit may include a barcode scanner that recognizes the barcode of the product, and an image scanner that scans an image of the product to obtain image information.

[0011] If the barcode is recognized, the processor identifies the product as a scanned product corresponding to the identification information contained in the barcode; if the barcode cannot be recognized, the processor obtains a product name and character string from the image information, and identifies the product as a scanned product based on the image information, product name and character string using artificial intelligence learning data; compares the weight of the product measured using the weight sensor with the weight information contained in the product information corresponding to the scanned product; if the comparison verifies that the product is the scanned product, the processor transmits a first signal to the product classification unit instructing the scanned product to be sent to a user; if the product is not identified as the scanned product or the comparison verifies that the product is not the scanned product, the processor transmits a second signal to the product classification unit instructing the product to be sent to an administrator.

[0012] The transport unit does not operate if it is not recognized through the product recognition unit that a product has been placed, operates to transport the product when it recognizes that a product has been placed, and can stop operating if it is not recognized through the product recognition unit that another product has been placed within a preset time period after it recognizes that a product has been placed through the product recognition unit.

[0013] In addition, a method for calculating product prices in an unmanned store according to one embodiment of the present invention may include the steps of receiving user information from a user terminal, recognizing a product placed on a transport unit through a product recognition unit, and if the product is recognized, scanning the product transported by the transport unit through a scanning unit, verifying the product based on the scan result of the product, and classifying the product by a product classification unit so that the product is sent to a user or administrator based on the verification result, calculating a total amount by adding up the prices of the classified products by a calculation unit, and providing the total amount to the user terminal.

[0014] The step of scanning the product includes the steps of: if the barcode of the product is recognized, scanning the barcode to obtain scanned product information corresponding to the barcode; if the barcode of the product cannot be recognized, scanning the entire image of the product to obtain image information; if the barcode of the product cannot be recognized or image information of the product cannot be obtained, designating the product as an unconfirmed product; if the barcode of the product cannot be recognized after the product scanning step, obtaining a product name of the product from the image information; and using artificial intelligence learning data to obtain scanned product information corresponding to the product whose image information has been obtained based on the image information and the product name, wherein the artificial intelligence learning data may include learned data on the size, product name, and weight of products sold in unmanned stores.

[0015] The step of classifying the scanned product may include the steps of measuring the weight of the product using a weight sensor, comparing the weight information of the scanned product included in the scanned product information with the measured weight of the product, and if the comparison verifies that the product is the scanned product, classifying the product into a first zone to be sent to a user, and if the comparison verifies that the product is another product or the product is an unconfirmed product, classifying the product into a second zone to be sent to an administrator, and transmitting the number of products classified into the second zone, device information, and the user information to an administrator terminal.

[0016] The step of calculating the total amount may involve recognizing that the user has purchased both the products classified in the first zone or the second zone, and calculating a third price by adding together a first price obtained by totaling the prices of the products classified in the first zone and a second price obtained by totaling the prices of the products classified in the second zone.

[0017] The step of receiving the user information may include a step of receiving membership information of the user generated using the user information, and after the step of providing the total amount, when the payment for the product by the user is completed, may include a step of accumulating purchase points corresponding to a third price to the member points included in the membership information.

[0018] The step of accumulating the purchase points may grant additional purchase points of a preset first rate corresponding to the rate of the number of products whose barcodes are recognized through a scanning unit according to the number of products purchased by the user, and the step of providing the total amount may provide to the user terminal a fourth price obtained by applying a discount rate of a preset second rate corresponding to the range in which the membership points are included to the third price. Effect of the Invention

[0019] According to the present invention, a calculation method for products in an unmanned store can be provided.

[0020] In addition, according to the present invention, the product recognition rate can be improved through artificial intelligence learning data, and product calculations can be performed quickly and accurately.

[0021] Furthermore, according to the present invention, the operational and management costs of the store can be reduced by reducing the number of staff. [Brief description of the drawings]

[0022] [Figure 1] and [Diagram 2] 1 and 2 are diagrams showing a commodity planning system for an unmanned store according to an embodiment of the present invention. [Diagram 3] FIG. 3 is a block diagram showing the configuration of a scanning unit of a commodity calculation device for an unmanned store according to one embodiment of the present invention. [Figure 4] FIG. 4 is a diagram showing a user's movement path and a manager's position in a commodity calculation device in an unmanned store according to an embodiment of the present invention. [Diagram 5]FIG. 5 is a block diagram showing entities for product calculation in an unmanned store according to an embodiment of the present invention. [Figure 6] FIG. 6 is an operational flowchart showing a commodity calculation method for an unmanned store according to one embodiment of the present invention. [Figure 7] FIG. 7 is an operational flowchart showing a commodity calculation method for an unmanned store according to one embodiment of the present invention. [Figure 8] FIG. 8 is an operational flowchart showing a commodity calculation method for an unmanned store according to one embodiment of the present invention. [Figure 9] FIG. 9 is an operational flowchart showing a commodity calculation method for an unmanned store according to one embodiment of the present invention. [Figure 10] FIG. 10 is a diagram illustrating a computer system according to one embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Hereinafter, the present invention will be described in detail with reference to the accompanying drawings. Hereinafter, detailed descriptions of known functions and configurations that may be repeated or unnecessarily obscure the gist of the present invention will be omitted. The embodiments of the present invention are provided to more completely explain the present invention to those having average knowledge in the art. Therefore, the shapes and sizes of elements in the drawings may be exaggerated for clearer explanation.

[0024] Throughout the specification, when a part is said to "comprise" a certain element, this does not mean to exclude other elements, but means that the part may further include other elements, unless specifically stated to the contrary.

[0025] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0026] 1 and 2 are diagrams showing the configuration of a commodity calculation device for an unmanned store according to one embodiment of the present invention.

[0027] FIG. 1 is a diagram showing a configuration of a commodity calculation device for an unmanned store according to an embodiment of the present invention.

[0028] FIG. 2 is a block diagram showing a configuration of a commodity calculation device for an unmanned store according to an embodiment of the present invention.

[0029] Referring to Figures 1 and 2, an unmanned store product device according to one embodiment of the present invention may include a transport unit 110, a product recognition unit 120, a scanning unit 130, a weight sensor 140, a product classification unit 150, a processor 210, and a calculation unit 220.

[0030] The transport unit may transport a product that a user wishes to purchase in order to scan the product.

[0031] The product recognition unit is installed at a first location where the transport unit starts transporting the product, and is capable of recognizing that a product has been placed on the transport unit so that operation of the transport unit can be started.

[0032] The scanning unit is installed at a preset distance from the transporting unit and can scan barcodes and images of products transported by the transporting unit.

[0033] The weight sensor is installed on one side of the lower portion of the conveyor and can measure the weight of the scanned product for verification.

[0034] The processor can use artificial intelligence learning data to identify what the product is based on the barcode, image, and weight of the product scanned by the scanning unit and the weight of the product measured by the weight sensor.

[0035] The product classification unit is installed at a second location where the transportation of the product by the transportation unit ends, and can classify the product into a first zone or a second zone based on the identification result of the product.

[0036] The calculation unit can calculate a total amount by adding up a first price, which is the total of the prices of products classified in the first zone, and a second price, which is the total of the prices of products classified in the second zone and confirmed by the administrator.

[0037] Here, the transport unit does not operate if it is not recognized through the product recognition unit that a product has been placed, operates to transport the product when it recognizes that a product has been placed, and can stop operating if it is not recognized through the product recognition unit that another product has been placed within a preset time period after it recognizes that a product has been placed through the product recognition unit.

[0038] FIG. 3 is a block diagram showing the configuration of a scanning unit of a commodity calculation device for an unmanned store according to one embodiment of the present invention.

[0039] Referring to FIG. 3, the scanning unit of the product calculation device for an unmanned store according to an embodiment of the present invention may include a barcode scanner 131 and an image scanner 132.

[0040] The barcode scanner can recognize the barcode of the product. The image scanner can scan the image of the product to obtain image information.

[0041] If the barcode is recognized, the processor identifies the product as a scanned product corresponding to the identification information contained in the barcode; if the barcode cannot be recognized, the processor obtains the product name and character string from the image information, and uses artificial intelligence learning data to identify the product as a scanned product based on the image information, product name, and character string.

[0042] In addition, the weight of the product measured using the weight sensor can be compared with weight information included in the product information corresponding to the scanned product, and if the comparison results in the product being verified to be the scanned product, a first signal can be transmitted to the product classification unit instructing the scanned product to be sent to a user, and if the product is not identified as the scanned product or the comparison results in the product being verified to be not the scanned product, a second signal can be transmitted to the product classification unit instructing the product to be sent to an administrator.

[0043] In an optional embodiment, the unmanned store product computing device may include a second product recognition unit that is installed at a third location where the products enter the first zone and recognizes products that have been classified by the product classification unit to be sent to the first zone.

[0044] Specifically, the second product recognition unit can recognize products that are classified by the product classification unit and then moved to the first zone, and can count the number of products that have moved to the first zone.

[0045] At this time, the product calculation device of the unmanned store compares the number of times the first signal was transmitted to be sent to the first zone through the processor with the number of products counted through the second product recognition unit, and if the comparison results in a difference, creates a list of products classified to be sent to the first zone and transmits the list to an administrator terminal.

[0046] Here, the manager can check the list through the manager terminal and determine whether the products included in the list have been erroneously classified.

[0047] This allows for the issue to be resolved through the verification process if the scanned and verified product is mistakenly classified into the second zone.

[0048] FIG. 4 is a diagram showing a user's movement path and a manager's position in a commodity calculation device in an unmanned store according to an embodiment of the present invention.

[0049] Referring to FIG. 4, in an embodiment of the present invention, two commodity calculation devices for an unmanned store are installed side by side, and a manager zone 410 may be located between them.

[0050] Here, in each device, among the zones in which the products are classified, the zone located next to the manager's zone can be the second zone, and the zone on the opposite side can be the first zone.

[0051] In this case, the user can place all the products he or she wishes to purchase in the transport section, and then move along the movement path 420 through the first zone to the second zone, picking up the products he or she has purchased.

[0052] This allows one manager to check unconfirmed items using two devices, resulting in reduced staff numbers and a reduction in store operating and management costs.

[0053] FIG. 5 is a block diagram showing entities for product calculation in an unmanned store according to an embodiment of the present invention.

[0054] Referring to FIG. 5, an entity for calculating a commodity in an unmanned store according to an embodiment of the present invention includes: an unmanned store commodity calculation device 100, a user terminal 510, and an administrator terminal 520.

[0055] The product calculation device 100 of the unmanned store may refer to a device that receives user information from a user terminal 510, recognizes a product scanned by a scanning unit as being purchased by the user using the user terminal, and calculates a total price.

[0056] The unmanned store commodity calculation device 100 may be a device that provides the calculated total amount to the user terminal 510.

[0057] The product calculation device 100 in the unmanned store may be a device that transmits information on unconfirmed products among the scanned products to the manager terminal 520.

[0058] The user terminal 510 may be a device that provides user information to the commodity calculation device 100 in an unmanned store.

[0059] The user terminal 510 may be a device that receives the total amount from the commodity calculation device 100 in an unmanned store.

[0060] The manager terminal 520 may be a device that receives information on unconfirmed products among the products scanned from the product calculation device 100 in the unmanned store.

[0061] The unmanned store product calculation device 100 and the user terminal 510, and the unmanned store product calculation device 100 and the manager terminal 520 can be interconnected through a communication network.

[0062] The communication network means a connection path for transmitting and receiving data between the above-mentioned entities. For example, the communication network can include wired networks such as LANs (Local Area Networks), WANs (Wide Area Networks), MANs (Metropolitan Area Networks), and ISDNs (Integrated Service Digital Networks), and wireless networks such as wireless LANs, CDMA, Bluetooth, and satellite communications, but the scope of the communication network applicable to the present invention is not limited to these.

[0063] FIG. 6 is an operational flowchart showing a commodity calculation method for an unmanned store according to another embodiment of the present invention.

[0064] Referring to FIG. 6, the method for calculating product prices for an unmanned store according to an embodiment of the present invention may first receive user information from a user terminal (S610).

[0065] Next, the product placed on the transfer section can be recognized by the product recognition section (S620).

[0066] Next, if the product is recognized, the scanning unit can scan the product being transported by the transport unit (S630).

[0067] In this case, if the barcode of the product is recognized, the barcode is scanned to obtain scanned product information corresponding to the barcode, and if the barcode of the product cannot be recognized, the entire image of the product is scanned to obtain image information.

[0068] Additionally, if the barcode of a product cannot be recognized or image information of the product cannot be obtained, the product can be designated as an unconfirmed product.

[0069] Next, the product can be verified based on the scanning result of the product, and the product can be classified through a product classification unit according to the verification result so that the product can be sent to a user or an administrator (S640).

[0070] Next, the prices of the classified items can be added up to calculate a total amount through a calculation unit (S650).

[0071] The total amount can then be provided to the user terminal (S660).

[0072] FIG. 7 is an operational flowchart showing a commodity calculation method for an unmanned store according to one embodiment of the present invention.

[0073] Referring to FIG. 7, in an embodiment of the present invention, a commodity calculation method for an unmanned store may obtain a commodity name of the commodity from the image information if the barcode of the commodity cannot be recognized after the commodity scanning step (S710).

[0074] Next, using the artificial intelligence learning data, scanned product information corresponding to the product whose image information has been acquired can be acquired based on the image information and the product name (S720).

[0075] Here, the artificial intelligence learning data may include data learned about the size, product name, and weight of products sold in the unmanned store.

[0076] FIG. 8 is an operational flowchart showing a commodity calculation method for an unmanned store according to one embodiment of the present invention.

[0077] Referring to FIG. 8, the method for calculating the price of a commodity in an unmanned store according to an embodiment of the present invention may first measure the weight of the commodity using a weight sensor (S810).

[0078] Next, the weight information of the scanned product included in the scanned product information can be compared with the measured weight of the product (S820).

[0079] Then, if the comparison verifies that the item is the scanned item, the item can be classified into a first zone to be sent to a user, and if the comparison verifies that the item is another item or is an unconfirmed item, the item can be classified into a second zone to be sent to an administrator (S830).

[0080] Next, the number of products classified into the second zone, the device information, and the user information can be transmitted to an administrator terminal (S840).

[0081] In this case, step S650 may recognize that the user has purchased both the products classified in the first zone and the products classified in the second zone, and may calculate a third price by adding up the first price obtained by adding up the prices of the products classified in the first zone and the second price obtained by adding up the prices of the products classified in the second zone.

[0082] FIG. 9 is an operational flowchart showing a commodity calculation method for an unmanned store according to one embodiment of the present invention.

[0083] Referring to FIG. 9, in the method for calculating product prices for an unmanned store according to an embodiment of the present invention, first, in step S610, membership information of the user generated using the user information may be received.

[0084] After the total amount is provided, if the user has already paid for the product, purchase points corresponding to the third price can be accumulated in the member points included in the member information (S910).

[0085] At this time, in step S910, a preset first percentage of additional purchase points may be awarded, which corresponds to the ratio of the number of products whose barcodes are recognized through the scanner, according to the number of products purchased by the user.

[0086] In addition, step S660 can provide the user terminal with a fourth price to which a preset second percentage discount rate has been applied, the fourth price corresponding to the section in which the third price includes the member's points.

[0087] In an optional embodiment, before step S660, a first product list for products classified in the first zone and a second product list for products classified in the second zone may be created, and the created first product list and second product list may be provided to a user terminal.

[0088] Specifically, the product calculation device of the unmanned store may first generate a first product list for products classified into a first zone.

[0089] At this time, a preset first mark or second mark can be displayed next to each product name included in the first product list.

[0090] Here, the preset first mark may mean that the barcode is scanned through a barcode scanner to obtain product information, and the obtained scanned product information is verified to match the product information.

[0091] In addition, the second preset mark may mean that image information of the product is obtained through an image scanner, scanned product information is obtained based on the image information, and the scanned product information is verified to match the obtained scanned product information.

[0092] Next, the product calculation device of the unmanned store can generate a second product list for the products classified in the second zone when the manager has completed checking the products classified in the second zone.

[0093] At this time, a preset third marker can be displayed next to each product name included in the second product list.

[0094] Here, the preset third mark may indicate that the product is an unconfirmed product, or that the product is verified as being different from the scanned product information and has been confirmed by an administrator.

[0095] In an optional embodiment, when step S660 provides a total price to the user terminal, the total price may include the first product list and the second product list and be provided to the user terminal.

[0096] The first product listing and the second product listing may then include prices for each of the products in the listing.

[0097] As a result, the user can check the products whose barcodes have been scanned through the barcode scanner. Also, the more products whose barcodes have been scanned, the more points the member accumulates, and the higher the member's points, the higher the discount rate, so when the user places products on the transfer section, the user is guided to place them so that the barcodes can be easily scanned. As a result, as the number of products whose barcodes have been scanned increases, the number of products that the administrator needs to check decreases, which has the effect of shortening the time it takes to calculate the product.

[0098] FIG. 10 is a diagram illustrating a computer system according to one embodiment of the present invention.

[0099] The product calculation device for an unmanned store according to an embodiment of the present invention can be embodied in a computer system 1000 such as a computer-readable recording medium.

[0100] 10, a computer system 1000 may include one or more processors 1010, memory 1030, user interface input devices 1040, user interface output devices 1050, and storage 1060, which communicate with each other via a bus 1020. The computer system 1000 may further include a network interface 1070 that is connected to a network 1080. The processor 1010 may be a central processing unit or a semiconductor device that executes processing instructions stored in the memory 1030 and / or the storage 1060. The memory 1030 and / or the storage 1060 may be in various forms of volatile or non-volatile storage media. For example, the memory may include a ROM 1031 and / or a RAM 1032.

[0101] The specific implementation described in the present invention is an embodiment and does not limit the scope of the present invention in any way. For the sake of brevity of the specification, descriptions of conventional electronic configurations, control systems, software, and other functional aspects of the system may be omitted. Note that the line connections or connecting members between components shown in the drawings are illustrative of functional connections and / or physical or circuit connections, and may be represented as alternative or additional various functional connections, physical connections, or circuit connections in an actual device. Also, unless specifically described as "essential" or "important", a component is not essential for application of the present invention.

[0102] Therefore, the concept of the present invention should not be limited to the above-described embodiments, and all modifications equivalent to or equivalent to the scope of the claims described below are within the scope of the concept of the present invention. [Industrial Applicability]

[0103] In addition, the product calculation device for an unmanned store according to the embodiment of the present invention scans the products being transported, measures their weight to identify the products, classifies the products based on the identification results, and calculates the total price, thereby enabling product calculations to be performed quickly and accurately, and thus has industrial applicability.

Claims

1. a transport unit for transporting a product that a user wishes to purchase so that the product can be scanned; a product recognition unit that is installed at a first location where the transport unit starts transporting the product and recognizes that the product has been placed on the transport unit so that the operation of the transport unit is started; a scanning unit installed at a predetermined distance from the transporting unit to scan barcodes and images of the products transported by the transporting unit; a weight sensor installed on one side of a lower portion of the conveying unit to measure a weight of the scanned product for verification; A processor that uses artificial intelligence learning data to identify the product based on the barcode and image of the product scanned by the scanning unit and the weight of the product measured by the weight sensor; a product sorting unit that is installed at a second location where the transport of the products by the transport unit is completed, and that sorts the products into a first zone or a second zone based on a result of the identification of the products; a calculation unit that calculates a total amount by adding up a first price obtained by totaling the prices of the products classified in the first zone and a second price obtained by totaling the prices of the products classified in the second zone and confirmed by the manager; The unmanned store product calculation device includes:

2. The scanning unit includes: a barcode scanner for recognizing the barcode of the product; an image scanner for scanning an image of the product to obtain image information; The unmanned store product calculation device according to claim 1 .

3. The processor, If the barcode is recognized, the product is identified as a scanned product corresponding to the identification information contained in the barcode; If the barcode cannot be recognized, obtain a product name and character string from the image information, and identify the product as a scanned product based on the image information, product name, and character string using artificial intelligence learning data; comparing a weight of the product measured using the weight sensor with weight information included in the product information corresponding to the scanned product, and if the result of the comparison indicates that the product is the scanned product, transmitting a first signal to the product sorter to instruct the scanned product to be sent to a user; 3. The unmanned store product calculation device according to claim 2, wherein when the product is not identified as the scanned product or when the comparison result verifies that the product is not the scanned product, a second signal is transmitted to the product sorting unit to instruct the product to be sent to a manager.

4. The transport unit includes: When the product recognition unit does not recognize that a product is placed on the product, the device does not operate. When the product recognition unit recognizes that a product is placed on the product, the device operates to transfer the product.

2. The unmanned store commodity calculation device according to claim 1, wherein the device stops operation if the commodity recognition unit does not recognize that another commodity has been placed on the unmanned store until a preset time has elapsed after the commodity recognition unit recognizes that a commodity has been placed on the unmanned store.

5. receiving user information from a user terminal; Recognizing the product placed on the transfer unit through a product recognition unit; When the product is recognized, scanning the product being transported by the transport unit through a scanning unit; verifying the product based on the scanning result of the product, and classifying the product by a product classification unit according to the verification result so that the product is sent to a user or an administrator; A calculation unit calculates a total amount by adding up the prices of the classified products; providing the total amount to the user terminal; Including, how to calculate products for unmanned stores.

6. The step of scanning the item includes: If the barcode of the product is recognized, the barcode is scanned to obtain scanned product information corresponding to the barcode; if the barcode of the product is not recognized, the entire image of the product is scanned to obtain image information; If the barcode of the product cannot be recognized or the image information of the product cannot be obtained, the product will be designated as an unconfirmed product. After the product scanning step, if the barcode of the product cannot be recognized, acquiring the product name of the product from the image information; Using artificial intelligence learning data to obtain scanned product information corresponding to the product whose image information is obtained based on the image information and the product name; Including, The artificial intelligence learning data includes: The unmanned store commodity calculation method according to claim 5, further comprising learned data on the size, commodity name and commodity weight of commodities sold in the unmanned store.

7. The step of classifying the scanned items includes: measuring the weight of the product using a weight sensor; comparing weight information of the scanned product included in the scanned product information with the measured weight of the product; If the result of the comparison indicates that the item is the scanned item, classifying the item into a first zone to be sent to a user; if the result of the comparison indicates that the item is another item or is an unconfirmed item, classifying the item into a second zone to be sent to an administrator; transmitting the number of products classified into the second zone, the device information, and the user information to an administrator terminal; The unmanned store commodity calculation method according to claim 6, comprising:

8. The step of calculating the total amount includes:

8. The unmanned store product calculation method of claim 7, further comprising: recognizing that all of the products classified in the first zone or the second zone have been purchased by the user; and calculating a third price by adding together a first price obtained by summing up the prices of the products classified in the first zone and a second price obtained by summing up the prices of the products classified in the second zone.

9. The step of receiving user information includes: receiving membership information of the user generated using the user information; After the total amount providing step, The unmanned store product calculation method according to claim 8, further comprising a step of accumulating purchase points corresponding to the third price to the member's points included in the member information when the user completes payment for the product. It is possible.

10. The step of accumulating purchase points includes: a first preset percentage of additional purchase points is awarded to the user in accordance with the number of products purchased by the user, the percentage being determined based on the number of products whose barcodes are recognized by the scanning unit; The step of providing the total amount includes: The unmanned store product calculation method of claim 9, further comprising providing to the user terminal a fourth price to which a preset second percentage discount rate corresponding to the section in which the member points are included has been applied to the third price.

Images