KR20220043003A - Method, server and computer program for providing rpoducts automatic ordering service of unmanned store - Google Patents

Abstract

Provided are a method, server, and computer program for providing an automatic product ordering service of an unmanned store. According to one embodiment of the present invention, the method for providing the automatic product ordering service of the unmanned store performed by a computing device comprises: a step of collecting data on a plurality of unmanned stores; a step of generating ordering data on each of the plurality of unmanned stores by analyzing the collected data; and a step of processing ordering for each of the plurality of unmanned stores by using the generated ordering data.

Description

Method of providing automatic product ordering service in unmanned stores, server and computer program {METHOD, SERVER AND COMPUTER PROGRAM FOR PROVIDING RPODUCTS AUTOMATIC ORDERING SERVICE OF UNMANNED STORE

Various embodiments of the present invention relate to a method for providing an automatic product ordering service in an unmanned store, a server, and a computer program.

Untact is a compound word of the prefix Un, which means negation, and Contact, which means contact. It means purchasing goods or receiving services without meeting people in person.

Recently, a culture that does not want to communicate directly with people is spreading, especially among the younger generation, so it is common to see employees taking orders through kiosk 2 rather than taking orders directly in downtown or university restaurants. This phenomenon is recognized as a culture and is referred to as an untact culture. Unmanned retail industry is accelerating due to the spread of the untact culture and the advantages of reducing labor costs.

In addition, due to the influence of the environment where highly contagious viruses such as Corona 19 (COVID-19) are prevalent, non-face-to-face digital conversion (non-face-to-face payment, etc.) has been accelerated across all fields, and accordingly, online and non-face-to-face local consumption is reduced. An active distribution environment was formed.

With the spread of the untact culture, more and more companies are applying unmanned systems, centered on the retail industry. Unmanned stores in Korea that introduced advanced technology at the level of advanced companies such as Amazon and Alibaba also appeared. An unmanned system with advanced technology can provide convenience to daily life and reduce labor costs and rent. However, there are problems in that high technology cost and customer-friendly service cannot be provided.

The problem to be solved by the present invention is to analyze various data related to a plurality of unmanned stores to determine the ordered product and the order quantity of the product, and to process the automatic order for the product based on the determined type and order amount of the ordered product. It is to provide a method, server and computer program for providing automatic product ordering service in unmanned stores that can not only improve the convenience of store owners, but also maximize the efficiency of product sales.

Another problem to be solved by the present invention is to provide a product sales service in an unmanned store to improve the problems of conventional unmanned stores, thereby providing customer-friendly services such as product recommendation and event & promotion. It is to provide a method for providing automatic ordering service, a server and a computer program.

The problems to be solved by the present invention are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

In a method performed by a computing device, the method for providing an automatic product ordering service in an unmanned store according to an embodiment of the present invention for solving the above-described problem includes the steps of collecting data about a plurality of unmanned stores, the collecting It may include generating order data for each of the plurality of unmanned stores by analyzing the obtained data, and processing an order for each of the plurality of unmanned stores by using the generated order data.

In various embodiments, the collected data includes inventory amount data for a plurality of products displayed in each of the plurality of unmanned stores, and the generating of the order data includes analyzing the inventory amount data and selecting one of the plurality of products. Selecting one or more products in which the inventory amount is less than or equal to a preset number, and generating order data including ordering information for the selected one or more products, wherein the order information includes information about the product to be ordered and an order quantity. may include

In various embodiments, the generating of the order data may include scoring each of the plurality of products by analyzing the collected data, and for each of the plurality of products based on a scoring result for each of the plurality of products. The method may include determining whether to process an order and an order quantity, and generating order data including information on whether or not an order is processed for each of the determined plurality of products and information on the order quantity.

In various embodiments, the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores, and the scoring of each of the plurality of products includes analyzing the sales data to obtain the plurality of products. calculating the number of sales per one payment for each product of , and weighting each of the plurality of products based on the calculated number of sales per one payment, and using the assigned weights to the plurality of products It may include correcting the scoring result for each.

In various embodiments, the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores, and the scoring of each of the plurality of products includes analyzing the sales data to obtain the plurality of products. Calculating the amount of change in sales volume over time for each product of , and assigning a weight to each of the plurality of products based on the calculated amount of change in sales over time, each of the plurality of products by using the assigned weight It may include correcting the scoring result for .

In various embodiments, the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores, and the scoring of each of the plurality of products includes analyzing the sales data to obtain the plurality of products. Calculating the sales volume by season and the sales volume by weather for each product of It may include assigning a weight to each of the plurality of products based on the respective sales volume, and correcting a scoring result for each of the plurality of products by using the weighted weight.

In various embodiments, the collected data includes customer infrastructure data for each of the plurality of unmanned stores, and the step of scoring each of the plurality of products includes analyzing the customer infrastructure data to each of the plurality of unmanned stores calculates the number of companies and the salary level of company employees located in the vicinity of , assigns a weight to each of the plurality of products based on the calculated number of companies and the calculated salary level, and uses the assigned weight It may include correcting the scoring result for each of the plurality of products.

In various embodiments, the collected data includes sales volume data and customer infrastructure data for each of a plurality of products displayed in the plurality of unmanned stores, and scoring each of the plurality of products includes the sales data and calculating a repurchase rate for each of the plurality of products by analyzing the customer infrastructure data, and assigning a weight to each of the plurality of products based on the calculated repurchase rate, and using the assigned weight It may include correcting the scoring result for each product.

In various embodiments, the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores, and the scoring of each of the plurality of products includes analyzing the sales data to obtain the plurality of products. Calculating the expected fair price for each unmanned store for each of the products of It may include differentially assigning a weight to each of the plurality of products, and correcting a scoring result for each of the plurality of products by using the differentially assigned weight.

In various embodiments, the collected data includes location data of each of the plurality of unmanned stores, and the step of generating the order data includes assigning a weight to each of the plurality of products based on the location data, It may include correcting the scoring result for each of the plurality of products by using the assigned weight.

In various embodiments, the collected data includes social data for the plurality of unmanned stores and a plurality of products displayed in each of the plurality of unmanned stores, and the generating of the order data includes: extracting one or more keywords, assigning a weight to each of the plurality of products based on the extracted one or more keywords, and correcting a scoring result for each of the plurality of products using the assigned weight may include

In various embodiments, the collected data includes sales volume data and customer infrastructure data for each of a plurality of products displayed in the plurality of unmanned stores, and the generating of the order data includes: Selecting one or more unmanned stores having the same or similar properties to the properties of the new unmanned store, the properties including at least one of the size, location, and customer infrastructure of the unmanned store, and sales data of the selected one or more unmanned stores It may include the step of generating order data for the first order quantity of the new unmanned store by analyzing the.

In various embodiments, the processing of the order includes performing a simulation of product sales in the first unmanned store using the first order data generated by analyzing data about the first unmanned store, but the simulation A scenario applied to is set based on the sales data of the first unmanned store, and based on the results of the simulation, verification of the first order data is performed, and the first order data is It may include determining a processing method of the first order data based on the verification result.

A product automatic ordering service providing server of an unmanned store according to another embodiment of the present invention for solving the above-described problems is a processor, a network interface, a memory, and a computer program loaded into the memory and executed by the processor Including, wherein the computer program includes, an instruction for collecting data on a plurality of unmanned stores, an instruction for analyzing the collected data to generate order data for each of the plurality of unmanned stores, and the generated order It may include instructions for processing an order for each of the plurality of unmanned stores using data.

A computer program recorded on a computer-readable recording medium according to another embodiment of the present invention for solving the above problems is combined with a computing device to collect data about a plurality of unmanned stores, the collecting A computer-readable record for executing the steps of generating order data for each of the plurality of unmanned stores by analyzing the collected data and processing an order for each of the plurality of unmanned stores using the generated order data may be stored in the medium.

Other specific details of the invention are included in the detailed description and drawings.

According to various embodiments of the present invention, by analyzing various data related to a plurality of unmanned stores to determine an ordered product and an order amount of the product, and processing an automatic order for a product based on the determined type and order amount of the ordered product, It has the advantage of not only improving the convenience of store owners, but also maximizing the efficiency of product sales.

In addition, by providing a product sales service in an unmanned store to improve the problems of the conventional unmanned stores, there is an advantage in that it is possible to provide customer-friendly services such as product recommendation, event & promotion, and the like.

Effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 is a diagram illustrating a system for providing a service for selling products in an unmanned store according to an embodiment of the present invention.
2 is a hardware configuration diagram of a service providing server for selling products in an unmanned store according to another embodiment of the present invention.
3 is a flowchart of a method for providing a product sales service in an unmanned store according to another embodiment of the present invention.
4 is a flowchart illustrating a procedure for purchasing a product using a user terminal, according to various embodiments of the present disclosure;
5 is a flowchart illustrating a procedure for purchasing a product using a kiosk in an unmanned store, according to various embodiments.
6 is a flowchart for explaining an individual subscription procedure for using a service for selling products in an unmanned store, according to various embodiments of the present disclosure;
7 is a flowchart for explaining a company subscription procedure for using a service for selling products in an unmanned store, according to various embodiments of the present disclosure;
8 is a flowchart for explaining a method of providing an automatic product ordering service in an unmanned store, according to various embodiments of the present disclosure;
9 is a diagram illustrating a process of automatically placing an order for products in an unmanned store, according to various embodiments of the present disclosure;
10 is a diagram exemplarily showing data on an unmanned store necessary to provide an automatic product ordering service of an unmanned store, according to various embodiments.
11 is a flowchart illustrating a procedure for receiving a product purchased using a user terminal at a place and time desired by a purchaser, according to various embodiments of the present disclosure;
12 is a flowchart illustrating a procedure for providing advertisements suitable for purchasers, according to various embodiments of the present disclosure;
13 is a flowchart illustrating a procedure for selling alcoholic beverages to a purchaser, according to various embodiments of the present disclosure;
14 is a diagram illustrating a process of data processing and automatic ordering processing using data generated in an unmanned store and artificial intelligence technology, according to various embodiments of the present disclosure;

Advantages and features of the present invention and methods of achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms, and only the present embodiments allow the disclosure of the present invention to be complete, and those of ordinary skill in the art to which the present invention pertains. It is provided to fully understand the scope of the present invention to those skilled in the art, and the present invention is only defined by the scope of the claims.

The terminology used herein is for the purpose of describing the embodiments and is not intended to limit the present invention. In this specification, the singular also includes the plural unless specifically stated otherwise in the phrase. As used herein, “comprises” and/or “comprising” does not exclude the presence or addition of one or more other components in addition to the stated components. Like reference numerals refer to like elements throughout, and "and/or" includes each and every combination of one or more of the recited elements. Although "first", "second", etc. are used to describe various elements, these elements are not limited by these terms, of course. These terms are only used to distinguish one component from another. Accordingly, it goes without saying that the first component mentioned below may be the second component within the spirit of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used herein will have the meaning commonly understood by those of ordinary skill in the art to which this invention belongs. In addition, terms defined in a commonly used dictionary are not to be interpreted ideally or excessively unless specifically defined explicitly.

As used herein, the term “unit” or “module” refers to a hardware component such as software, FPGA, or ASIC, and “unit” or “module” performs certain roles. However, “part” or “module” is not meant to be limited to software or hardware. A “unit” or “module” may be configured to reside on an addressable storage medium or to reproduce one or more processors. Thus, as an example, “part” or “module” refers to components such as software components, object-oriented software components, class components and task components, processes, functions, properties, Includes procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. Components and functionality provided within “parts” or “modules” may be combined into a smaller number of components and “parts” or “modules” or as additional components and “parts” or “modules”. can be further separated.

Spatially relative terms "below", "beneath", "lower", "above", "upper", etc. It can be used to easily describe the correlation between a component and other components. Spatially relative terms should be understood as terms including different directions of components during use or operation in addition to the directions shown in the drawings. For example, when a component shown in the drawing is turned over, a component described as “beneath” or “beneath” of another component may be placed “above” of the other component. can Accordingly, the exemplary term “below” may include both directions below and above. Components may also be oriented in other orientations, and thus spatially relative terms may be interpreted according to orientation.

In this specification, a computer refers to all types of hardware devices including at least one processor, and may be understood as encompassing software configurations operating in the corresponding hardware device according to embodiments. For example, a computer may be understood to include, but is not limited to, smart phones, tablet PCs, desktops, notebooks, and user clients and applications running on each device.

In addition, in the present specification, a product sales service providing method of an unmanned store that is applied to an unmanned store without a manpower who works all the time in the store to sell products in the unmanned store, provide advertisements and promotions, manage inventory, and perform automatic order processing, etc. and a method of providing an automatic product ordering service in an unmanned store is described, but this is only an example and is not limited thereto, and may be applied to a general store in which a manpower is always working in the store.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Each step described in this specification is described as being performed by a computer, but the subject of each step is not limited thereto, and at least a portion of each step may be performed in different devices according to embodiments.

1 is a diagram illustrating a system for providing a service for selling products in an unmanned store according to an embodiment of the present invention.

The product sales service providing system of the unmanned store according to an embodiment of the present invention may include the product sales service providing server 100 of the unmanned store, the user terminal 201 , the kiosk 202 , and the external server 300 . .

Here, the product sales service providing system of the unmanned store shown in FIG. 1 is according to an embodiment, and its components are not limited to the embodiment shown in FIG. 1 , and may be added, changed, or deleted as necessary. there is.

In one embodiment, the product sales service providing server 100 of the unmanned store may provide the product sale service of the unmanned store.

Here, unmanned stores can be opened in banks, general private companies, 24-hour special companies (eg logistics centers), sports facilities (indoors and outdoors), lodging facilities (resorts, pensions, general hotels in downtown areas, etc.), general residential areas, etc. , it may mean a store that does not have a manpower who is always on duty in the store. However, the present invention is not limited thereto.

In addition, here, the product sales service of the unmanned store receives one or more products displayed in the unmanned store, performs a payment process for the inputted one or more products, and sells the corresponding products in response to the payment process being completed It may mean a service that approves and outputs sales data (eg, a receipt) accordingly. However, the present invention is not limited thereto.

In various embodiments, the product sales service providing server 100 of the unmanned store may provide software (eg, an application) for providing the product sales service of the unmanned store to the user terminal 201 and the kiosk 202 , respectively. . Thereafter, each of the user terminal 201 and the kiosk 202 may run software provided from the product sales service providing server 100 of the unmanned store, thereby executing and providing the product sale service of the unmanned store by themselves.

In an embodiment, the user terminal 201 (eg, a storekeeper terminal of an unmanned store and a buyer terminal of an unmanned store) may be connected to the product sales service providing server 100 of the unmanned store through the network 400 , and the unmanned store may be connected to the user terminal 201 . It is possible to receive the product sales service of the unmanned store from the product sales service providing server 100 of the.

Here, the network 400 may mean a connection structure capable of exchanging information between each node, such as a plurality of terminals and servers. For example, the network 400 includes a local area network (LAN), a wide area network (WAN), the Internet (WWW), a wired/wireless data communication network, a telephone network, a wired/wireless television communication network, and the like. do.

In addition, here, the wireless data communication network is 3G, 4G, 5G, 3rd Generation Partnership Project (3GPP), 5th Generation Partnership Project (5GPP), Long Term Evolution (LTE), World Interoperability for Microwave Access (WIMAX), Wi-Fi (Wi- Fi), Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), RF (Radio Frequency), Bluetooth (Bluetooth) network, Near-Field Communication (NFC) networks, satellite broadcast networks, analog broadcast networks, Digital Multimedia Broadcasting (DMB) networks, and the like are included, but are not limited thereto.

In various embodiments, the user terminal 201 downloads, installs, and executes an application provided from the product sales service providing server 100 of the unmanned store through, and thus may receive the product sale service of the unmanned store. To this end, the user terminal 201 may include an operating system (eg, Android, ios, etc.) capable of driving an application.

In various embodiments, the user terminal 201 is connected to the product sales service providing server 100 of the unmanned store through the network 400 , and the product of the unmanned store is provided by the product sale service providing server 100 of the unmanned store. A sales service provision user interface (UI) may be output. To this end, the user terminal 201 may be a smartphone including a display on at least a portion of the user terminal 201 . However, the present invention is not limited thereto, and the user terminal 201 is a wireless communication device that guarantees portability and mobility, and includes navigation, Personal Communication System (PCS), Global System for Mobile communications (GSM), Personal Digital Cellular (PDC), and PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet) It may include, but is not limited to, all types of handheld-based wireless communication devices such as terminals, smartpads, and tablet PCs.

In one embodiment, the kiosk 202 is connected to the product sales service provision server 100 of the unmanned store through the network 400, and receives and executes software from the product sale service provision server 100 of the unmanned store, Buyers may provide a product sales service in an unmanned store through the kiosk 202 .

In various embodiments, the kiosk 202 may include a display at least in part to output the product sales service provision UI of the unmanned store provided by the product sale service provision server 100 of the unmanned store as described above.

In various embodiments, the kiosk 202 may be provided in an unmanned store, and a plurality of kiosks 202 may be provided in one unmanned store. However, the present invention is not limited thereto.

In an embodiment, the external server 300 may be connected to the product sales service providing server 100 of the unmanned store through the network 400 , and the product sales service providing server 100 of the unmanned store sells products in the unmanned store. It is possible to store and manage various types of information and data necessary to provide services.

In addition, the external server 300 may receive, store and manage various types of information and data generated while the product sales service providing server 100 of the unmanned store provides the product sales service of the unmanned store. For example, the external server 300 may be a storage server separately provided outside the product sales service providing server 100 of the unmanned store, but is not limited thereto. Hereinafter, with reference to FIG. 2 , the hardware configuration of the product sales service providing server 100 of the unmanned store providing the product selling service will be described.

2 is a hardware configuration diagram of a service providing server for selling products in an unmanned store according to another embodiment of the present invention.

Referring to FIG. 2 , a product sales service providing server 100 (hereinafter, “computing device 100”) of an unmanned store according to another embodiment of the present invention is configured by one or more processors 110 and processors 110 . It may include a memory 120 for loading the computer program 151 to be executed, a bus 130 , a communication interface 140 , and a storage 150 for storing the computer program 151 . Here, only the components related to the embodiment of the present invention are shown in FIG. 2 . Accordingly, one of ordinary skill in the art to which the present invention pertains can see that other general-purpose components other than those shown in FIG. 2 may be further included.

The processor 110 controls the overall operation of each component of the computing device 100 . The processor 110 includes a central processing unit (CPU), a micro processor unit (MPU), a micro controller unit (MCU), a graphic processing unit (GPU), or any type of processor well known in the art. can be

In addition, the processor 110 may perform an operation for at least one application or program for executing the method according to the embodiments of the present invention, and the computing device 100 may include one or more processors.

In various embodiments, the processor 110 temporarily and/or permanently stores a signal (or data) processed inside the processor 110 , a random access memory (RAM) and a read access memory (ROM). -Only Memory, not shown) may be further included. In addition, the processor 110 may be implemented in the form of a system on chip (SoC) including at least one of a graphic processing unit, a RAM, and a ROM.

The memory 120 stores various data, commands and/or information. The memory 120 may load the computer program 151 from the storage 150 to execute methods/operations according to various embodiments of the present disclosure. When the computer program 151 is loaded into the memory 120 , the processor 110 may perform the method/operation by executing one or more instructions constituting the computer program 151 . The memory 120 may be implemented as a volatile memory such as RAM, but the technical scope of the present disclosure is not limited thereto.

The bus 130 provides a communication function between components of the computing device 100 . The bus 130 may be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

The communication interface 140 supports wired/wireless Internet communication of the computing device 100 . In addition, the communication interface 140 may support various communication methods other than Internet communication. To this end, the communication interface 140 may be configured to include a communication module well known in the art. In some embodiments, the communication interface 140 may be omitted.

The storage 150 may non-temporarily store the computer program 151 . When the automatic product ordering service providing process of the unmanned store is performed through the computing device 100 , the storage 150 may store various types of information necessary to provide the automatic product ordering service providing process of the unmanned store.

The storage 150 is a non-volatile memory such as a read only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, a hard disk, a removable disk, or well in the art to which the present invention pertains. It may be configured to include any known computer-readable recording medium.

The computer program 151 may include one or more instructions that, when loaded into the memory 120 , cause the processor 110 to perform methods/operations according to various embodiments of the present invention. That is, the processor 110 may perform the method/operation according to various embodiments of the present disclosure by executing the one or more instructions.

In one embodiment, the computer program 151 collects data on a plurality of unmanned stores, analyzes the collected data to generate order data for each of the plurality of unmanned stores, and uses the generated order data It may include one or more instructions for performing a method of providing an automatic product ordering service of an unmanned store, which includes processing an order for each of a plurality of unmanned stores.

The steps of a method or algorithm described in relation to an embodiment of the present invention may be implemented directly in hardware, as a software module executed by hardware, or by a combination thereof. A software module may contain random access memory (RAM), read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, hard disk, removable disk, CD-ROM, or It may reside in any type of computer-readable recording medium well known in the art to which the present invention pertains.

The components of the present invention may be implemented as a program (or application) to be executed in combination with a computer, which is hardware, and stored in a medium. Components of the present invention may be implemented as software programming or software components, and similarly, embodiments may include various algorithms implemented as data structures, processes, routines, or combinations of other programming constructs, including C, C++ , may be implemented in a programming or scripting language such as Java, assembler, or the like. Functional aspects may be implemented in an algorithm running on one or more processors. Hereinafter, a method of providing a product sales service in an unmanned store performed by the computing device 100 will be described with reference to FIG. 3 .

3 is a flowchart of a method for providing a product sales service in an unmanned store according to another embodiment of the present invention.

The method of providing a product sales service in an unmanned store according to FIG. 3 is described as being performed by the computing device 100 , but is not limited thereto, and the user terminal 201 (or a processor in the user terminal 201 ) is a computing device The product sales service providing method of the unmanned store is performed by executing the application provided from the 100 , or the kiosk 202 (or the processor in the kiosk 202 ) executes the software provided from the computing device 100 . It may be implemented in the form of performing a sales service providing method.

Referring to FIG. 3 , in step S110 , the computing device 100 may receive one or more products to be purchased from the purchaser.

For example, the computing device 100 inputs one or more products to be purchased from the purchaser through the product sales service UI of the unmanned store, which is output as the application is executed in the user terminal 201 of the purchaser (eg, the user terminal ( 201) through the display touch panel) can be received.

In addition, the computing device 100 inputs one or more products to be purchased from the buyer through the product sales service UI of the unmanned store that is output as the software is executed in the kiosk 202 (eg, the display touch panel of the kiosk 202 ) touch input) can be received.

Also, the computing device 100 may receive one or more products to be purchased by recognizing a barcode printed on each of the one or more products through a barcode reader included in the kiosk 202 . However, the present invention is not limited thereto, and any method of receiving one or more products to be purchased from the buyer may be applied.

In step S120, the computing device 100 may perform a payment process for one or more products input in step S110.

Here, the payment process may refer to a process of paying for one or more products input by a buyer. For example, the payment process includes an operation of guiding payment details (eg, information about one or more products input by a buyer and an operation of guiding the payment amount for one or more products), an operation of receiving a selection of a payment method for the payment amount; It may include an operation of processing the payment amount by using the payment method. However, the present invention is not limited thereto, and other general operations applicable to the payment process (eg, discount and accumulation selection operation, point use selection operation, etc.) may be additionally applied.

In various embodiments, the computing device 100 allows the buyer to complete input of one or more products, and a user input indicating a payment application for the input one or more products (eg, selecting a payment request button placed on the UI) user input), a payment process for one or more products input by the buyer may be performed. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 is an external camera module (eg, an internal camera module provided in the user terminal 201 or the kiosk 202 , the user terminal 201 or the kiosk 202 ). of the product) can be used to collect raw material information of products printed on one or more products, and whether the purchaser is suitable to consume the product based on allergy and avoidance food information input from the purchaser and raw material information of the product may be determined, and the determination result may be provided to the user terminal 201 or the kiosk 202 of the purchaser.

At this time, when the purchaser logs in to his or her account before selecting the product, the computing device 100 receives the product selection from the purchaser and allergy and avoidance food information previously input by the purchaser (input at the time of membership registration) information) and product raw material information are provided to the user terminal 201 or the kiosk 202 to prevent the purchaser from purchasing the product when it is determined that the product is not suitable.

On the other hand, since the computing device 100 cannot check the information about the buyer until the sales data is generated by performing the payment, when the buyer logs in to his/her own account after completing the payment for the product. At the time when information is recognized (eg, when sales data is generated according to payment), the user immediately checks the result determined according to the allergy and avoidance food information (informed at the time of membership registration) entered by the buyer and the raw material information of the product. By providing it to the terminal 201 or the kiosk 202 , the buyer may not consume the product or refund if it is determined that the product is not suitable.

In step S130, when the payment process for one or more products is completed through step S120, the computing device 100 approves the sale of one or more products paid in response to the payment process being completed, and You can create and output sales data related to sales.

Here, the sales data refers to data including various information such as information on one or more products, price information and payment method, and whether or not a payment process is completed. For example, the sales data may be a receipt (paper receipt or electronic receipt), but is not limited thereto.

In various embodiments, the computing device 100 generates sales data related to the sale of one or more products, and determines an output method (eg, electronic receipt or paper receipt) of the sales data or outputs the sales data according to a request of a buyer. may not However, the present invention is not limited thereto. Hereinafter, with reference to FIGS. 4 and 5 , a method of selling a product through the user terminal 201 of a purchaser and a method of selling a product through the kiosk 202 will be described in more detail.

4 is a flowchart illustrating a procedure for purchasing a product using a user terminal, according to various embodiments of the present disclosure;

The procedure for purchasing a product using the user terminal of the buyer according to FIG. 4 is described as being performed by the computing device 100, but is not limited thereto, and the user terminal 201 (or a processor in the user terminal 201) ) may be implemented in the form of performing a procedure for purchasing a product using the user terminal 201 by executing the application provided from the computing device 100 .

Referring to FIG. 4 , in step S210 , the computing device 100 may execute an application. For example, the computing device 100 may cause the corresponding application to be executed according to a user input for selecting an application for providing a product sales service of an unmanned store from among a plurality of applications previously installed in the user terminal 201 from the purchaser.

In various embodiments, the computing device 100 may provide the URL of a web page that provides a product sales service of an unmanned store to the user terminal 201 , and the purchaser may access the product sale service provision page of the unmanned store through the URL. can However, the present invention is not limited thereto.

In step S220 , the computing device 100 may select one or more products that the buyer wants to purchase. For example, the computing device 100 may provide a UI for outputting a product list including information on a plurality of products sold in an unmanned store as an application pre-installed on the purchaser's user terminal 201 is executed. , one or more products to be purchased among a plurality of products included in the product list may be selected from the purchaser through the UI.

In various embodiments, the computing device 100 may receive one or more keywords related to a product from a purchaser, and may select one or more products corresponding to the inputted one or more keywords. For example, the computing device 100 may provide a UI for searching for a product to be purchased, may receive one or more keywords for searching for a specific product from a buyer through the UI, and search according to the input keyword It is possible to select one or more products to be used (or any one product selected by the purchaser among one or more searched products).

In various embodiments, the computing device 100 provides a UI to the user terminal 201 , and receives one or more products to be purchased from a buyer through the UI, and sells products in an unmanned store provided by the computing device 100 . A UI can be provided only when a member has signed up for the service, or one or more products can be selected from a buyer. To this end, the computing device 100 may determine whether a buyer who wants to purchase a product is subscribed to the product sales service of the unmanned store as a member, and if not, may provide a membership registration process for membership registration. . Here, the membership sign-up process refers to a procedure of registering a buyer account to use the product sales service of the unmanned store. A more detailed description of the membership registration process will be described with reference to FIGS. 6 and 7 to be described later.

In step S230 , the computing device 100 may determine a payment method for payment of one or more products selected in step S220 .

In various embodiments, the computing device 100 may perform payment for one or more products using at least one of cash and a card according to a request of a purchaser.

In various embodiments, when receiving a request to use the first point from the purchaser, the computing device 100 may pay at least a portion of the payment amount for one or more products with the first point according to a preset first ratio. Here, the first point may mean an external point such as a partner card company point or a partner communication company point, but is not limited thereto.

In various embodiments, when receiving a request to use the second point from the purchaser, the computing device 100 may pay at least a portion of the payment amount for one or more products with the second point according to a preset second ratio. Here, the second point may mean a company welfare point issued from each of a plurality of companies affiliated with the unmanned store.

In various embodiments, the computing device 100 may pay at least a portion of the payment amount for one or more products by simultaneously applying the first point and the second point, and using only the first point and the second point, one or more You can pay the entire amount of payment for the product. However, the present invention is not limited thereto.

In step S240 , the computing device 100 may perform a payment process for one or more products. For example, the computing device 100 may pay a payment amount for one or more products according to the payment method determined in step S230 . Here, the payment process performing operation performed by the computing device 100 may be performed in the same or similar form as the payment process performing operation (eg, S120 step) of FIG. 3 , but is not limited thereto.

In step S250, the computing device 100 approves the sale of one or more products when the payment process for one or more products is completed through step S240, and sales data (eg, electronic receipt data, transaction history data, etc.) can be created and printed. Here, the sales data output operation performed by the computing device 100 may be performed in the same or similar form to the sales data output operation (eg, step S130 ) of FIG. 3 , but is not limited thereto.

5 is a flowchart illustrating a procedure for purchasing a product using a kiosk in an unmanned store, according to various embodiments.

The procedure for purchasing a product using the kiosk in the unmanned store according to FIG. 5 is described as being performed by the computing device 100, but is not limited thereto, and the kiosk 202 (or the processor in the kiosk 202) By executing software provided from the computing device 100 , it may be implemented in the form of performing a procedure for purchasing a product using a kiosk.

Referring to FIG. 5 , in step S310 , the computing device 100 may identify one or more products that the buyer wants to purchase through product selection and barcode recognition operations.

For example, the purchaser may pick up a product to purchase from among a plurality of products displayed in an unmanned store, and input a barcode printed on the product to be purchased into a barcode reader provided in the kiosk 202 . Thereafter, the computing device 100 may scan the barcode of the product to be purchased through the barcode reader, and may identify the product the buyer wants to purchase according to the type of the scanned barcode.

In various embodiments, the computing device 100 may provide a UI for outputting a product list including information on a plurality of products sold in an unmanned store through a display provided in the kiosk 202, and through the UI One or more products to be purchased may be selected from the purchaser among a plurality of products included in the product list. However, the present invention is not limited thereto.

In step S320 , the computing device 100 may generate a one-time security QR code for security by driving an application for providing a product sales service in an unmanned store.

In step S330, the computing device 100 may determine a payment method for payment of one or more products identified in step S310. Here, the operation of determining the payment method performed by the computing device 100 may be performed in the same or similar form as the operation of determining the payment method of FIG. 4 (eg, step S230 ), but is not limited thereto.

In step S340 , the computing device 100 may perform a payment process for one or more products. Here, the payment process performed by the computing device 100 may be performed in the same or similar form as the payment process (eg, step S240 ) performed in FIG. 4 , but is not limited thereto.

In step S350, when the payment process for one or more products is completed through step S340, the computing device 100 authorizes sales of one or more products, and generates and outputs sales data (eg, a paper receipt). there is. Here, the sales data output operation performed by the computing device 100 may be performed in the same or similar form to the sales data output operation (eg, step S130 ) of FIG. 3 , but is not limited thereto. Hereinafter, a membership registration process performed by the computing device 100 will be described with reference to FIGS. 6 and 7 .

6 is a flowchart for explaining an individual subscription procedure for using a service for selling products in an unmanned store, according to various embodiments of the present disclosure.

The personal subscription procedure for using the service for selling products in the unmanned store according to FIG. 6 is described as being performed by the computing device 100, but is not limited thereto, and the user terminal 201 (or the user terminal 201) The processor in the kiosk 202 performs the personal sign-up procedure by executing an application provided from the computing device 100 , or the kiosk 202 (or the processor in the kiosk 202 ) executes software provided from the computing device 100 , thereby performing the personal sign-up process. It can be implemented in a form that performs

Referring to FIG. 6 , in step S410 , the computing device 100 may receive an individual subscription application from a purchaser. For example, the computing device 100 may provide a UI for performing a membership registration process, and may receive a personal subscription application from a purchaser by obtaining a user input regarding an individual subscription application through the UI. However, the present invention is not limited thereto.

In step S420 , the computing device 100 may perform a self-authentication procedure for a purchaser who has entered an individual subscription application. For example, the computing device 100 is a self-authentication method using a mobile phone, a self-authentication method using an identification card, a self-authentication method using a card (credit card and check card), and a self-authentication method using a QR code (eg, PASS) A self-authentication procedure for the purchaser may be performed using at least one of the self-authentication methods. However, the present invention is not limited thereto, and any method capable of performing the identity authentication procedure for the purchaser may be applied.

In step S430 , the computing device 100 may issue an account to the purchaser who has entered the individual subscription application. For example, the computing device 100 may receive an ID and password input from the purchaser, and may issue an account to the purchaser using the ID and password input by the purchaser.

In various embodiments, the computing device 100 may receive personal information from a user along with a personal subscription application, and an ID and password corresponding to the purchaser by combining random numbers and N characters based on the received personal information. can be issued automatically. However, the present invention is not limited thereto.

In step S440 , the computing device 100 may register personal payment information for the purchaser. For example, the computing device 100 may register information on one or more cards to be paid for when the payment method for the product is a card, and may register information on one or more cards to be transferred when the payment method for the product is an account transfer. information can be registered. However, the present invention is not limited thereto, and for at least a portion of the payment amount for the product, various information related to payment, such as information on the first point to be used when paying the first point, may be registered. However, the present invention is not limited thereto.

7 is a flowchart for explaining a company subscription procedure for using a service for selling products in an unmanned store, in various embodiments.

Although the company subscription procedure for using the product sales service of the unmanned store according to FIG. 7 is described as being performed by the computing device 100, it is not limited thereto, and the user terminal 201 (or the user terminal 201) The processor in the kiosk 202 performs the company sign-up procedure by executing an application provided from the computing device 100 , or the kiosk 202 (or the processor in the kiosk 202 ) executes the software provided from the computing device 100 . It can be implemented in a form that performs

Referring to FIG. 7 , in step S510 , the computing device 100 may receive a company subscription application from a purchaser. For example, the computing device 100 may provide a UI for performing a membership registration process to the purchaser's user terminal 201 or the kiosk 202, and by obtaining a user input regarding a company subscription application through the UI , it is possible to receive input from the purchaser to join the company. However, the present invention is not limited thereto.

In step S520 , the computing device 100 may receive a selection of an affiliated company from the purchaser. For example, the computing device 100 may provide a company list including information on a plurality of companies contracted in advance in relation to the use of company welfare points through the UI, and a plurality of lists included in the company list Any one of the companies may be selected as the affiliated company.

In various embodiments, the computing device 100 receives one or more keywords about the affiliated company from the user (eg, affiliated company name, business registration number of the affiliated company, etc.), and purchases a company corresponding to the inputted one or more keywords. may be selected as an affiliated company of However, the present invention is not limited thereto.

In step S530, the computing device 100 may perform a self-authentication procedure for the purchaser who has entered the company subscription application. Here, the identity authentication procedure performed by the computing device 100 may be performed in the same or similar form to the identity authentication procedure of FIG. 6 (eg, step S420 ), but is not limited thereto.

In step S540, the computing device 100 transmits the information about the purchaser who has entered the company subscription application and the company subscription application input by the buyer to the company server selected by the purchaser in step S520 or the user terminal 201 of the person in charge. can

At this time, the computing device 100 transmits information about the purchaser who has entered the company subscription application and the company subscription application input by the purchaser to the company server or the user terminal 201 of the company's person in charge, and at the same time, the purchaser may inquire for information about whether or not is employed by the company and the amount of company welfare points paid to the purchaser. However, the present invention is not limited thereto.

In step S550 , the computing device 100 may issue an account for the purchaser who has entered the company subscription application. Here, the operation of issuing an account to the purchaser performed by the computing device 100 may be performed in the same or similar form as the operation of issuing an account to the purchaser of FIG. 6 (eg, step S430 ), but limited thereto doesn't happen

In various embodiments, the computing device 100 responds to the transfer of information about the purchaser who has inputted the company subscription application and the content of the company subscription application input by the buyer in step S540, when approval is processed from the person in charge of the company can only issue an account to the buyer

In step S560 , the computing device 100 may provide the company welfare points issued by the affiliated company to the account of the purchaser issued through step S550 .

In step S570, the computing device 100 may register personal payment information for the purchaser. Here, the operation of registering personal payment information for the purchaser may be performed in the same or similar form as the operation of registering personal payment information of FIG. 6 (eg, step S440), but is not limited thereto.

In various embodiments, the computing device 100 selects an affiliated company when the purchaser who has requested the company subscription procedure is a member already subscribed according to the individual subscription procedure of FIG. 6 (eg, step S520), to the affiliated company representative Only the operation of delivering the subscription application (eg, step S540) and the operation of paying the welfare point of the affiliated company (eg, step S560) are additionally performed, and the result is stored in the buyer's account created according to the personal subscription procedure of FIG. can reflect Hereinafter, with reference to FIGS. 8 to 10 , a method for providing an automatic product ordering service in an unmanned store performed by the computing device 100 will be described.

8 is a flowchart for explaining a method for providing an automatic product ordering service in an unmanned store, in various embodiments is a diagram exemplarily showing data about an unmanned store necessary to provide an automatic product ordering service of an unmanned store, in various embodiments.

The method for providing an automatic product ordering service in an unmanned store according to FIGS. 8 to 10 is described as being performed by the computing device 100, but is not limited thereto, and the user terminal 201 (or user terminal 201) of the store owner is not limited thereto. The processor in the kiosk 202 may be implemented by executing an application provided from the computing device 100 , or the kiosk 202 (or the processor in the kiosk 202 ) may be implemented by executing software provided from the computing device 100 . there is.

8 to 10 , in step S610 , the computing device 100 may collect data regarding a plurality of unmanned stores.

Here, the data on the plurality of unmanned stores 10 includes information on the number of people, sales, sales by product, sales number per one payment, sales time, sales volume of the previous day/previous month/previous year, etc. as shown in FIG. 10 . Store (sales) data, season/seasonal data, season/weather data including information on yellow dust/heat wave/cold wave/humidity, snow/rain, etc., salary level, repurchase status, member age, and store properties Product data including information on infrastructure/demographic data, price, category/type, release date/production date, reviews/rating, brand, profit per sale, health, SNS, main ingredient, diet/functionality, etc. Issue data and other data (eg, inventory data for a plurality of products displayed in each of the plurality of unmanned stores 10, etc.) may be included, but is not limited thereto.

In step S620 , the computing device 100 may analyze the data on the plurality of unmanned stores 10 collected in step S610 to generate order data for each of the plurality of unmanned stores 10 .

Here, the order data is data for processing an order for a specific product, and may include information about the product, whether the product has been ordered, and information on the order amount of the product.

In various embodiments, when the first product is selected as an order target, the computing device 100 may generate order data such that the selected first product is ordered by a preset order amount. However, it is not limited thereto, and the order quantity for the first product is determined according to the result of analyzing the data on the plurality of unmanned stores 10 (eg, determined according to the expected sales volume), or According to the result of analyzing the related data, it may be determined in the form of correcting the pre-set order quantity (eg, when it is determined that the sales volume will increase, increase a predetermined ratio from the order quantity set for circumstances).

In various embodiments, the computing device 100 analyzes the inventory amount data for a plurality of products displayed in each of the plurality of unmanned stores 10, and selects one or more products whose inventory amount is less than or equal to a preset number among the plurality of products, Order data including order information for one or more selected products (eg, information on products to be ordered and order quantity) may be generated. For example, the computing device 100 may select a product having an inventory amount of 30% or less as an order target product.

In this case, the computing device 100 may generate the order data and set a preset number based on a time point at which the order is to be processed using the generated order data. For example, the computing device 100 may select a product having an inventory amount of 30% or less as an order target product when the timing at which the order is to be processed is Monday, Tuesday or Wednesday, and the timing at which the order is to be processed is Thursday or Friday. In this case, in consideration of weekends or holidays, products with an inventory of 40% or less may be selected as target products. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 scores each of the plurality of products by analyzing the data about the plurality of unmanned stores 10 collected in step S610, and ordering data based on the scoring result for each of the plurality of products can create

First, the computing device 100 may score each of the plurality of products by analyzing data about the plurality of unmanned stores 10 .

Here, the method of scoring each of the plurality of products by analyzing the data on the plurality of unmanned stores 10 is based on a score table for a plurality of items (eg, sales volume, unit price, etc.) for a specific product included in the data. a model that calculates the score for each of a plurality of products (e.g., 1 point if the sales volume of the first product is less than or equal to the first size, 2 points if the sales volume of the first product is less than or equal to the first size, 3 points if the sales volume of the first product is greater than or equal to the second size A method of using a model that calculates a final score by giving a score and adding up the scores given to each item) may be applied, but is not limited thereto, and scores for each of a plurality of products by analyzing data according to a preset standard Any method of calculating .

In this case, the computing device 100 excludes one or more products having a stock amount of a certain level or more among a plurality of products from the scoring target, that is, from the ordering target, in order to prevent unnecessary ordering of products with a large inventory amount in the unmanned store 10 . can However, the present invention is not limited thereto, and there are cases where an additional order is required even if the amount of stock is large. Based on the stock amount of each of the plurality of products, the plurality of products are sorted in ascending order from the product with the low stock amount, and based on the sorted order By differentially assigning weights so that the highest weight is given to the product located at the topmost level and the smallest weight is given to the product located at the bottommost level, it is possible to set the order so that products with a small inventory amount are prioritized.

In various embodiments, the computing device 100 may analyze sales volume data for each of a plurality of products displayed in the plurality of unmanned stores 10 to calculate the number of sales per one payment for each of the plurality of products, , a weight may be assigned to each of the plurality of products based on the calculated number of sales per one time payment, and a scoring result for each of the plurality of products may be corrected based on the weight. Here, the weight is set to have a value (eg, 1 to 2) within a preset range, but may be set in proportion to the number of sales per one time payment.

For example, when the number of sales per one payment of the first product is equal to or greater than the first reference number, the computing device 100 assigns a weight of 1.1 and applies the weight of 1.1 to the scoring result for the first product as 1.1 By multiplying by , it is possible to correct the scoring result for the first product. That is, small products for which several products are sold at one time payment can be depleted faster than large products, and these products can be set to be ordered with priority.

Here, the method of correcting the scoring result for a product using the weight is described as multiplying the final scoring result (eg, a value obtained by adding up the scores for each of a plurality of items) by the weight assigned to it. However, this is an example for more easily explaining a method of correcting a score using a weight, and since the weight for each of the plurality of items can be set individually, the score of the item related to the weight among the plurality of items is It is preferable to apply in the form of multiplying weights individually.

In various embodiments, the computing device 100 may analyze the sales volume data to calculate a change in sales volume over time for each of the plurality of products, and based on the calculated amount of change in sales volume over time, each of the plurality of products A weight may be assigned, and the scoring result for each of a plurality of products may be corrected using the assigned weight.

For example, the computing device 100 analyzes the sales volume data and when it is determined that the sales volume change of the first product has a positive value over time, that is, when it is determined that the sales volume of the first product is continuously increasing, By assigning a weight to the first product, a product whose sales volume is continuously increasing may be set to be ordered with priority.

In various embodiments, the computing device 100 may calculate sales volume by season and sales volume by weather for each of a plurality of products by analyzing sales data, and seasonal information for a predetermined period based on a time point at which the sales data is analyzed and a weight may be assigned to each of the plurality of products based on the weather information and the calculated sales volume for each season and the sales volume for each of the plurality of products, and a scoring result for each of the plurality of products may be corrected using the assigned weight. can

For example, the computing device 100 determines that the rainy season starts based on season information and weather information for a predetermined period based on the time of analyzing the sales volume data, and seasonal sales volume and weather for each of a plurality of products When it is determined that the sales volume of the first product on a rainy day is high based on the individual sales volume, a greater weight may be assigned to the first product than other products having a relatively low sales volume on a rainy day. In addition, the computing device 100 assigns weights so that seasonal foods (eg, strawberry confectionery, etc.) can be ordered more during the season based on the season information and weather information for a predetermined period, so that the It can be set so that suitable products can be ordered with priority.

In various embodiments, the computing device 100 analyzes customer infrastructure data for each of the plurality of unmanned stores 10 to calculate the number of companies located in the vicinity of each of the plurality of unmanned stores 10 and the salary levels of company employees And, a weight may be assigned to each of a plurality of products based on the calculated number of companies and a salary level, and a scoring result for each of the plurality of products may be corrected using the weighted value.

For example, the computing device 100 gives a high weight to a high-priced product as the salary level of the employees of a nearby company in the unmanned store 10 is high, and gives a high weight to a low-priced product as the salary level is low. It is set to order a lot of relatively high-priced products from unmanned stores 10 located near companies with high salary levels, and relatively low-priced products are placed in unmanned stores 10 located near companies with relatively low salary levels. It can be set to order a lot.

In various embodiments, the computing device 100 analyzes sales volume data and customer infrastructure data, calculates a repurchase rate for each of a plurality of products, and each of the plurality of products based on the calculated repurchase rate for each of the plurality of products may be assigned a weight, and the scoring result for each of a plurality of products may be corrected using the assigned weight.

For example, the computing device 100 may set a product with a high repurchase rate to be ordered preferentially by giving a greater weight to a product having a relatively high repurchase rate than a product having a relatively low repurchase rate.

In various embodiments, the computing device 100 analyzes sales volume data to calculate an expected fair value for each unmanned store 10 for each of a plurality of products, and a plurality of products based on the calculated expected fair value for each unmanned store 10 . may be arranged in descending order, a weight may be differentially assigned to each of the plurality of products based on the order in which each of the plurality of products is sorted, and a scoring result for each of the plurality of products may be corrected using the differentially assigned weight. In this way, it is possible to set more orders for products with a higher expected fair price than for products with a relatively low expected fair price.

In various embodiments, the computing device 100 analyzes the location data of each of the plurality of unmanned stores 10, assigns a weight to each of the plurality of products, and scores each of the plurality of products using the assigned weight The results can be corrected.

For example, when it is determined that the unmanned store 10 is located in the golf course, the computing device 100 gives weight to the beverage product, and when it is determined that the unmanned store 10 is located in the apartment complex, the alcoholic beverage product is By assigning weights, it is possible to set the unmanned store 10 to preferentially order products optimized based on the location.

At this time, sales data of other unmanned stores 10 (eg, when the first unmanned store 10 is located within the golf course, golf course It may be set based on sales data of other unmanned stores 10 located within), but is not limited thereto, and various methods such as preset by an administrator may be applied.

In various embodiments, the computing device 100 provides social data (eg, SNS, news, reviews of online shopping malls, etc.) for a plurality of unmanned stores 10 and a plurality of products displayed in each of the plurality of unmanned stores 10 . can be analyzed to extract one or more keywords, and weights can be assigned to each of a plurality of products based on the extracted one or more keywords, and the scoring results for each of the plurality of products can be corrected using the assigned weights. .

For example, the computing device 100 may collect text-type social data for the first product, analyze the collected social data (eg, OCR analysis) to extract one or more keywords, and By comparing pre-stored attribute data for each keyword, it is possible to determine an attribute for one or more keywords, and through this, an attribute (eg, positive or negative) for the first product itself can be determined. In this case, when it is determined that the first product has a positive attribute, the computing device 100 may set a weight within the range of 1 to 2 so that the first product can be ordered preferentially, and if the first product is negative When it is determined to have the attribute, a weight within the range of 0 to 1 may be assigned to lower the order priority of the first product.

In various embodiments, the computing device 100 may calculate the number of customers for each age group visiting each of the plurality of unmanned stores 10 by analyzing customer infrastructure data, and a plurality of products based on the calculated number of customers for each age group A weight may be assigned to each, and a scoring result for each of a plurality of products may be corrected using the assigned weight.

For example, when it is determined that customers in their twenties visit the first unmanned store 10 the most, the computing device 100 assigns weights to products preferred by customers in their twenties and products preferred by customers in their twenties. By setting the order to be prioritized, it is possible to increase the consumption of customers and increase the sales of the unmanned store 10 .

In various embodiments, the computing device 100 analyzes social data, extracts one or more keywords (eg, a product name) for each of a plurality of products, and assigns a weight to each of the plurality of products based on the number of extracted keywords can be given That is, the computing device 100 may set a weight to be given to products (popularity products) frequently mentioned on SNS, etc., so that these products are preferentially ordered.

In various embodiments, the computing device 100 may assign weights to health-friendly food among a plurality of products, and may set the health-friendly food to be ordered preferentially.

In various embodiments, the computing device 100 may assign a weight to a product including a specific function according to social norms among a plurality of products, and set such products to be ordered preferentially.

In various embodiments, the computing device 100 may receive an unfavorable product group set in advance from a user (eg, an administrator or a store owner of the unmanned store 10 ), and may include 0 to By assigning a weight within the range of 1, it is possible to lower the order priority of these products.

In various embodiments, the computing device 100 may receive a preferred brand setting from a user (eg, an administrator or a store owner of the unmanned store 10 ) in advance, and a weight is given to a product corresponding to the preferred brand among a plurality of products. can be set so that these products are ordered preferentially.

In various embodiments, the computing device 100 may calculate sales revenue for each of a plurality of products by analyzing sales volume data, and may sort the plurality of products in descending order based on the calculated sales revenue, and according to the sorted order By differentially assigning weights so that the highest weight is given to the product located at the top and the smallest weight is given to the product located at the bottom, it is possible to set the order so that the product with a large operating profit is ordered first.

Thereafter, the computing device 100 determines whether or not to process an order for each of the plurality of products and an order amount for each of the plurality of products based on the scoring result for each of the plurality of products, and information on whether or not to process an order for each of the determined plurality of products and the amount of the order Including order data can be created.

For example, the computing device 100 may sort a plurality of products in descending order based on the scoring result (corrected scoring result), and select N products from the topmost product as an order processing target. However, the present invention is not limited thereto, and, based on the scoring results for each of the plurality of products, the computing device 100 selects one or more products having a scoring result (score) equal to or greater than a preset reference score as an order processing target. Various methods are available. can be applied.

Also, the computing device 100 may determine an order amount of a product selected as an order processing target. For example, when receiving order amount information for each product from a user (eg, an unmanned store manager) in advance, the computing device 100 may determine the order amount of a product selected as an order processing target based on the registered information. However, the present invention is not limited thereto, and may be determined based on sales volume and sales volume variation (eg, sales volume/sale volume variation for a predetermined period based on the time of ordering) for the product selected for order processing.

In various embodiments, the computing device 100 may calculate the display number of each of a plurality of products in the unmanned store 10 by analyzing sales volume data, and use information on the calculated number of display of each of the plurality of products to the user. can be provided to

In various embodiments, the computing device 100 may analyze sales data to calculate a sales volume for each of a plurality of products, adjust a unit price for each of a plurality of products based on the calculated sales volume, and adjust the plurality of products Unit price information for each may be provided to the user.

In various embodiments, the computing device 100 analyzes the sales volume data to calculate the hourly sales volume of each of the plurality of products, and determines the display priority of each of the plurality of products in the unmanned store 10 based on the calculated hourly sales volume It can be set, and information on the display priority of each of the set plurality of products can be provided to the user.

In various embodiments, the computing device 100 analyzes the sales volume data to calculate a turnover rate of each of a plurality of products displayed in the first unmanned store 10 , and orders a first product for which the calculated turnover is less than a preset turnover rate can be excluded from In this case, in response to the first product being excluded from the order target, the computing device 100 may select a second product different from the first product as an order target.

Here, the second product is a product (particularly, a product with a high turnover) having a turnover greater than or equal to a preset turnover rate among a plurality of products (excluding the first product) displayed in the first unmanned store 10, or the first unmanned store 10 Among the plurality of products displayed in each of the plurality of second unmanned stores 10 having properties similar to the properties (eg location, size, age of buyer, gender, occupation, surrounding environment, commercial district, etc.) At the same time, it may be a product that is not displayed in the first unmanned store 10 . However, the present invention is not limited thereto.

In various embodiments, the computing device 100 calculates a margin rate for a plurality of products displayed in the first unmanned store 10 , but orders a product for which the calculated margin rate is less than a preset margin rate, that is, a first product with a low margin rate may be excluded from the subject. In this case, in response to the first product being excluded from the order target, the computing device 100 may select a second product different from the first product as an order target.

Here, the second product is a product (particularly, a product with a high margin) or a product with a margin higher than or equal to a preset margin rate among a plurality of products (excluding the first product) displayed in the first unmanned store 10, or the first unmanned store 10 Among the plurality of products displayed in each of the plurality of second unmanned stores 10 having properties similar to those of , the margin ratio is greater than or equal to a preset margin ratio and may be products not displayed in the first unmanned store 10 at the same time. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 analyzes the sales volume data, so that the margin rate of the first product is less than a preset margin rate, but the first product is sold together with other products, such as a second product or a third product. When the pattern is displayed and the turnover and margin of the second product or the third product sold together with the first product is equal to or greater than the preset turnover and the preset margin, the first product may be selected as an order target.

In various embodiments, the computing device 100 may determine the order amount according to the attribute of the product to be ordered. For example, in the case of dairy products or fresh food, it is difficult to place an order for a large quantity even if the sales volume is high or the turnover and margin are high because the shelf life is short compared to products such as sweets and ramen. In consideration of this, if the product has a relatively short shelf life, such as dairy products or fresh food, according to the properties of the product, the computing device 100 may determine to order a relatively small amount compared to a product with a long expiration date. .

At this time, the computing device 100 increases the number and cycle of ordering processing in consideration of the sales volume of the corresponding product (eg, increasing the reference value for selecting an order target), thereby preventing the product from being consumed due to the high sales volume of the product. can be prevented

In step S630 , the computing device 100 may process an order for each of the plurality of unmanned stores 10 using the order data generated in step S620 .

In various embodiments, the computing device 100 may perform a simulation of product sales in the unmanned store 10 using the order data generated according to the above method, and based on the execution result of the simulation, order data can be verified, and a processing method for the generated order data can be determined based on the verification result.

Here, the simulation is performed according to a scenario set in advance, and the scenario may be set based on the sales data of the first unmanned store 10 , but is not limited thereto, and by the manager or the store owner of the unmanned store 10 . It can be set by inputting directly.

In this case, the computing device 100 may perform a plurality of simulations using one scenario, but is not limited thereto, and generates a plurality of scenarios by modifying the reference scenario (eg, the type and number of products included in the scenario) A plurality of simulations may be performed using a plurality of scenarios generated by changing a predetermined ratio within a predetermined range or changing a customer visit time, etc.).

In various embodiments, when the sales of the unmanned store 10 is greater than or equal to a reference value as a result of performing a simulation based on the generated order data, the computing device 100 may process an order using the corresponding order data. Meanwhile, the computing device 100 may re-perform step S620 to regenerate the order data when, as a result of performing a simulation based on the generated order data, the sales of the unmanned store 10 is less than the reference value.

As described above, the computing device 100 analyzes data about the plurality of unmanned stores 10 to determine the optimal order target product and order quantity, and automatically performs order processing based on the determined order target product and order quantity. , there is an advantage that it is possible to improve the convenience of the owner of the unmanned store 10 as well as maximize the sales of the unmanned store 10 .

In various embodiments, the computing device 100 analyzes data about the plurality of unmanned stores 10 to perform automatic ordering processing for the existing unmanned stores 10 as well as the initial drawings of the new unmanned stores 10 . You can determine the quantity and process the order for the determined initial quantity.

For example, the computing device 100 analyzes sales volume data and customer infrastructure data for each of a plurality of products displayed in the plurality of unmanned stores 10 , and the new unmanned stores 10 of the plurality of unmanned stores 10 are analyzed. Select one or more unmanned stores 10 having the same or similar properties as attributes (eg location, size, buyer age group, gender, occupation, surrounding environment, commercial district, etc.), and sales data of the selected one or more unmanned stores 10 can be analyzed to generate order data for ordering the first quantity of the new unmanned store 10 .

In consideration of the fact that the cost burden for inventory at the time of initial opening is a large business model, the sales data of the unmanned stores 10 having properties most similar to those of the new unmanned store 10 to be opened are analyzed, and using this By determining the type and inventory amount of products to be sold in the new unmanned store 10 , there is an advantage in that the cost problem for such inventory can be solved.

In various embodiments, the computing device 100 analyzes data about the plurality of unmanned stores 10 to process automatic disposal (collection, return) of a plurality of products displayed in each of the plurality of unmanned stores 10 . can

In various embodiments, the computing device 100 may automatically collect and automatically return each of the plurality of products based on the discard date of each of the plurality of products displayed in the unmanned stores 10 and 10 . For example, the computing device 100 may be included within a preset period based on the time of automatic collection and automatic return processing, or the expiration date and disposal date of each of the plurality of products, or already based on the time of automatic collection and automatic return processing. If it has elapsed, the product can be automatically collected and returned.

In various embodiments, the computing device 100 may automatically collect and automatically return at least a portion of the additionally ordered product when the external factor disappears with respect to the product additionally ordered by an external factor or the like. For example, if the computing device 100 normally orders only 10 candies, but orders 50 candies in consideration of the White Day season, White Day among 40 candies additionally ordered in response to the end of the White Day season. Candy can be automatically collected and returned automatically after being sold during the season.

In various embodiments, the computing device 100 is an external camera module (eg, an internal camera module provided in the user terminal 201 or the kiosk 202 , the user terminal 201 or the kiosk 202 ). camera module) to scan barcodes printed on one or more products and at the same time identify the expiration dates for one or more products, and automatically dispose of one or more products according to the identified expiration dates (e.g., automatic collection and returns can be processed).

For example, since the barcode of fresh food displays only information about the product and not the expiration date of the product, when a product is identified through a barcode, it is possible to recognize whether the product is fresh food, but There is a problem in that it is not possible to determine whether the sale can be made within the deadline, that is, the validity of the sale. In consideration of this, the computing device 100 extracts (eg, OCR analysis) text about the expiration date marked on the packaging of fresh food through the camera module, and uses a text analysis model (eg, artificial intelligence model) to The expiration date is identified by analyzing the text, and the sales effectiveness of the product can be determined according to the identified expiration date.

In addition, when it is determined that the sale of the corresponding product is not valid (eg, the expiration date has passed or the expiration date is imminent), the computing device 100 commands to discard the product whose expiration date is imminent among the remaining inventory of the product. may be ordered and notified. Hereinafter, with reference to FIG. 11 , a method of allowing a purchaser to receive a product to be purchased at a desired place and a desired date according to a request of the purchaser, performed by the computing device 100 , will be described.

11 is a flowchart illustrating a procedure for receiving a purchased product at a place and time desired by a purchaser using a user terminal, according to various embodiments of the present disclosure;

The procedure for receiving the purchased product using the purchaser's user terminal according to FIG. 11 at the place and time desired by the purchaser is described as being performed by the computing device 100 , but is not limited thereto, and the user terminal 201 . (or the processor in the user terminal 201) executes the application provided from the computing device 100, so that the purchaser uses the user terminal of the purchaser to perform a procedure for receiving the purchased product at the desired place and time. can be

Referring to FIG. 11 , in step S710 , the computing device 100 may execute an application according to a request of a purchaser. Here, the application execution operation performed by the computing device 100 may be performed in the same or similar form to the application execution operation (eg, step S210 ) of FIG. 4 , but is not limited thereto.

In step S720 , the computing device 100 may select one or more products that the buyer wants to purchase. Here, the operation of receiving selection of one or more products from the purchaser performed by the computing device 100 may be performed in the same or similar form as the operation of receiving selection of one or more products of FIG. 4 (eg, step S220 ), but limited thereto doesn't happen

In various embodiments, the computing device 100 uses the user terminal 201 for a product search function according to a search word and a product name, a product search function according to a product category, a product search function according to a price range, a preference according to gender, age, and store preference. A product search function and a product search function according to a purchase history may be provided, and a purchaser may search for and select a product using any one of the product search functions of the product search function.

In operation S730, the computing device 100 may receive information on a receiving place and a receiving date to receive one or more products from the purchaser.

In various embodiments, the computing device 100 may provide a pick-up place search function according to a search term, a pick-up place search function according to a category, a pick-up place search function according to map selection, and a pick-up place search function according to a purchase history, The purchaser may search for and select a receiving place by using any one of the receiving place search functions among the above receiving place search functions.

In various embodiments, the computing device 100 is located in a place adjacent to the purchaser based on the location of the purchaser (eg, location information collected from a location sensor (eg, a GPS sensor) provided in the user terminal 201 of the purchaser). An unmanned store located can be recommended as a pick-up location.

Here, the receiving place input from the buyer is described as being an unmanned store in any one of a plurality of unmanned stores, but it is not limited thereto, and in some cases, the address (eg, home, company, etc.) entered by the buyer is used as the receiving place. You can choose. For example, when a plurality of buyers belonging to the first company purchase a product, the place where the plurality of buyers will receive the product in response to the number of purchasers who purchased the product (or the order quantity of the product) reaching a certain amount or more may be selected as the first company.

Also, here, the computing device 100 is described as being performed in the order of an operation of selecting a product to be purchased (eg, S720) and an operation of inputting a receiving place and a receipt date (eg, S730), but is not limited thereto. , the operation of inputting the place and date of receipt (eg S730) before the operation of selecting the product to be purchased (eg S720), or the operation of selecting the product to be purchased (eg S720) and the receiving location and An operation of inputting a receipt date (eg, S730) may be simultaneously performed. However, the present invention is not limited thereto.

In step S740, the computing device 100 may provide information on a plurality of purchase histories generated by the purchaser purchasing the product, and in response to selecting any one of the purchase histories from among the plurality of purchase histories from the buyer, You can choose the product and pickup location so that you can repurchase your existing product. In this case, the computing device 100 may reselect only the receipt date of the product when the purchaser intends to repurchase the product that has been previously purchased because the receipt date input in the purchase history corresponds to a date in the past.

In step S750 , the computing device 100 analyzes information on a plurality of purchase histories generated by the purchaser purchasing a product, and one or more recommended products (eg, recommended products by time period, recommended products by location, product ranking, event product, discount product, etc.) may be selected, and information on one or more selected recommended products may be provided to the purchaser. For example, the computing device 100 analyzes a plurality of sales data generated by a plurality of buyers selling each of a plurality of products in an unmanned store, and another buyer having attributes similar to the buyer, such as the buyer's age, gender, occupation, etc. You can select a product that many people have purchased, a product with a good evaluation (review or rating), and the like, and recommend the selected product to the buyer as a recommended product.

Thereafter, the computing device 100 may receive a selection of any one recommended product from among one or more recommended products, and may receive an input location and a receipt date of the selected one or more recommended products.

In step S760, the computing device 100 may perform a purchase and payment process for the product the buyer wants to purchase among the product selected through steps S720 and S730, the product selected through step S740, and the product selected through step S750. there is. Here, the payment process performing operation performed by the computing device 100 may be performed in the same or similar form as the payment process performing operation (eg, S120 step) of FIG. 3 , but is not limited thereto.

In step S770 , the computing device 100 may perform a purchase authentication procedure for the purchaser when the purchaser intends to receive the product purchased at the receiving location after the payment process is completed in step S760 . For example, the computing device 100 authenticates the sales data generated as a result of performing the payment process together with the identity authentication procedure for the buyer (eg, step S420 of FIG. 6 ), thereby indicating that the buyer has purchased the product. You can decide whether it is correct or not. However, the present invention is not limited thereto.

In step S780 , the computing device 100 may provide a product purchased by the purchaser to the purchaser when purchase authentication for the purchaser is completed through operation S770 .

In various embodiments, the computing device 100 receives information about a buyer, information on a target to be delivered, a delivery address, etc., and delivers a delivery service (or delivery service) to a delivery location according to the received information. ) can be provided. For example, the buyer may deliver a specific product from the first unmanned store to the second unmanned store, request a courier service (or delivery service) that allows the second buyer to receive the delivered specific product, and request the courier service In response to receiving, the specific product may be delivered from the first unmanned store to the second unmanned store. Hereinafter, with reference to FIG. 12 , a method of providing an advertisement suitable for a buyer, performed by the computing device 100 , will be described.

12 is a flowchart illustrating a procedure for providing advertisements suitable for purchasers, according to various embodiments of the present disclosure;

The procedure for providing an advertisement suitable for the purchaser according to FIG. 12 is described as being performed by the computing device 100, but is not limited thereto, and the purchaser's user terminal 201 (or a processor in the user terminal 201) The kiosk 202 (or a processor in the kiosk 202) performs a procedure for providing advertisements suitable to the purchaser by executing the application provided from the computing device 100, or by executing the software provided from the computing device 100 to the purchaser. It may be implemented in the form of performing a procedure for providing a suitable advertisement.

Referring to FIG. 12 , in step S810 , the computing device 100 may collect buyer information and sales history data (eg, sales data). For example, the computing device 100 performs a membership sign-up process to use the product sales service of the unmanned store, thereby storing information about a plurality of purchasers (members) (eg, age information, gender information, etc.) and a plurality of unmanned Sales data generated in each store (eg, product information purchased through the purchaser's user terminal 201 and kiosk 202 , purchase number information, purchase time information, etc.) may be collected.

In various embodiments, the computing device 100 may analyze buyer information and sales data to analyze a buyer's propensity and purchase pattern.

In various embodiments, the computing device 100 may group a plurality of buyers who purchased each of a plurality of products displayed in an unmanned store into a plurality of groups according to a preset criterion, and the plurality of purchasers purchase each of the plurality of products A plurality of sales data generated by purchasing may be analyzed to extract a purchase pattern of each of the plurality of groups. However, the present invention is not limited thereto.

That is, the computing device 100 may construct an enterprise resource planning (ERP) system in which a purchaser analyzes a purchase pattern (consumption pattern) by analyzing a plurality of sales data.

In various embodiments, the computing device 100 receives information on the age, gender, and number of employees belonging to the affiliated company from the affiliated company (or affiliated company server, the affiliated company's representative terminal) located in a place adjacent to the unmanned store. It is possible to analyze the purchasing pattern by gender and age of the buyer by using the data collected from the affiliated company and the data on the product paid with the company welfare point of the affiliated company.

Current general stores (eg, nearby commercial areas such as convenience stores) have a problem in that the purchaser is not specified, so it is impossible to analyze a specific age and gender, and even if possible, the analysis result is inaccurate. Accordingly, the computing device 100 collects information on age, gender, and number of employees from neighboring affiliate companies and standardizes all employees of the affiliated company to a specific age and specific gender, thereby specifically targeting buyers, and By combining them, it is possible to extract a more accurate purchase pattern for each buyer. For example, if there are 10 employees belonging to an affiliated company, 8 of them are female, and 7 of them are in their 20s, it is possible to standardize all 10 employees of the affiliated company as being female in their 20s. However, the present invention is not limited thereto.

In step S820 , the computing device 100 performs a plurality of advertisement contents (eg, new products, seasons) waiting to be transmitted based on the purchaser's propensity and purchase pattern (or each of a plurality of groups and purchase patterns) analyzed in step S810 . product, issue product, promotion, etc.) can judge the suitability of each.

Here, the suitability for the advertisement content is based on the purchase pattern of the buyer or the purchase pattern of the group to which the buyer belongs, whether the product included in the advertisement content is a product with a high probability of being purchased by the buyer or the group to which the buyer belongs, and whether the purchase amount is high. It may mean a score calculated by scoring according to whether it is a product, etc., but is not limited thereto.

In step S830, the computing device 100 may transmit advertisement content based on the suitability determined in step S820. For example, when the first purchaser operates the user terminal 201 or the kiosk 202 of the purchaser to use the product sales service of the unmanned store, the computing device 100 may include the user terminal 201 of the first purchaser or Through the display provided in the kiosk 202 , it is possible to output advertisement content having a high degree of compatibility with the first purchaser among a plurality of advertisement contents.

In various embodiments, the computing device 100 performs an advertisement output device (eg, Digital Out-Of-Home Advertising, DOOH) provided in each of the plurality of unmanned stores in the unmanned stores among the plurality of advertising contents. It is possible to output advertising content that has a high degree of relevance to the buyer who has visited the website. To this end, the unmanned store may include one or more display terminals for outputting advertisement content, a main server, and a hub and a control device connecting one or more display terminals and the main server. However, the present invention is not limited thereto.

In step S840, the computing device 100 may generate the content of transmitting the advertisement content through step S830 and result data according to the transmission of the advertisement content. For example, the computing device 100 transmits information on which advertisement content is transmitted to a certain buyer and whether the buyer is interested in a product included in the corresponding advertisement content as the advertisement content is transmitted (eg, whether a product of interest is selected , result data that points to information about whether it was added to a shopping cart or purchased).

Thereafter, the computing device 100 may regenerate a daily and hourly advertisement content transmission schedule by analyzing the contents of the advertisement content and the result data of the advertisement content transmission.

The above-described method for providing a product sales service in an unmanned store has been described with reference to the flowchart shown in the drawings. For the sake of simplicity, the method of providing a product sales service in an unmanned store has been illustrated and described as a series of blocks, but the present invention is not limited to the order of the blocks, and some blocks are performed in an order different from that shown and operated in this specification or may be performed simultaneously. In addition, new blocks not described in the present specification and drawings may be added, or some blocks may be deleted or changed. Hereinafter, with reference to FIG. 13 , a procedure for selling alcoholic beverages to a purchaser will be described.

13 is a flowchart illustrating a procedure for selling alcoholic beverages to a purchaser, according to various embodiments of the present disclosure;

The procedure for selling the alcoholic product to the purchaser according to FIG. 13 is described as being performed by the computing device 100 , but is not limited thereto, and the user terminal 201 (or the processor in the user terminal 201 ) is the computing device The kiosk 202 (or the processor in the kiosk 202 ) performs a procedure of selling a liquor product to a buyer by executing the application provided from the computing device 100 , thereby executing the software provided from the computing device 100 , thereby providing a liquor product to the buyer. It can be implemented in the form of performing a procedure to sell

Referring to FIG. 13 , in step S910 , when the buyer wants to purchase alcohol, the computing device 100 identifies a face through a face recognition method (eg, Face ID) with respect to the buyer, and information on the identified face You can obtain prior consent to use For example, the computing device 100 may obtain prior consent for the face recognition method while the purchaser performs a membership registration process (eg, FIGS. 6 and 7 ). However, the present invention is not limited thereto.

In step S920 , when transmitting a request to purchase an alcoholic beverage from a purchaser, the computing device 100 may perform a real name authentication procedure (eg, adult authentication) for the purchaser in response to the purchase request for alcoholic beverages.

For example, a liquor refrigerator for displaying and storing a plurality of alcoholic beverages may be provided in the unmanned store, and the computing device 100 locks the state of the alcoholic beverage refrigerator until the real name authentication procedure for the purchaser is completed. can keep

At this time, when the computing device 100 transmits a request to purchase an alcoholic beverage from the purchaser, that is, when a request to change the state of the alcoholic beverage refrigerator from the locked state to the open state is requested, the external real-name authentication tool (eg, an external platform (eg, Naver) , Kakao, etc.) can perform the real-name authentication procedure for the purchaser using a QR code generated through a real-time QR generator provided by the company. Here, the external real-name authentication tool is described as a QR code generated through a real-time QR generator provided by an external platform, but is not limited thereto, and various tools for real-name authentication are applicable.

In step S930 , the computing device 100 may obtain a payment request for a liquor product from a purchaser. For example, when real name authentication for the purchaser is completed through step S920, the computing device 100 may change the locked alcoholic beverage refrigerator to the open state.

Also, the computing device 100 may receive an input of alcoholic beverages picked up from the alcoholic beverage refrigerator from the purchaser, and may obtain a user input indicating a payment request for the inputted alcoholic beverages. However, the present invention is not limited thereto.

In this case, the computing device 100 may proceed with the procedure of selling alcoholic beverages only when the purchaser who has obtained the payment request has signed up for the product sales service of the unmanned store provided by the computing device 100 . However, the present invention is not limited thereto.

In step S940 , the computing device 100 responds to the payment request obtained from the purchaser in step S930 , to the purchaser's phone number (eg, the purchaser's user terminal 201 or mobile phone number input through the kiosk 202 ). A face recognition request may be transmitted through a face recognition method.

Thereafter, the purchaser may perform a face recognition procedure through the application of his/her user terminal 201 , and the computing device 100 responds to transmitting the face recognition request through the face recognition method, the user terminal 201 As the face recognition procedure is performed, information on the identified buyer's face can be obtained.

Also, the computing device 100 may authenticate the purchaser based on the identified information on the purchaser's face.

In operation S950 , the computing device 100 may provide a payment process for selling alcoholic beverages when authentication of the purchaser is completed in operation S940 .

In various embodiments, the computing device 100 may preset the number of alcoholic products that can be purchased per purchaser, and provides a payment process that allows only the preset number of alcoholic products to be paid for (eg, 2 per person). A payment process that restricts the purchase of alcoholic beverages) may be possible.

That is, the computing device 100 allows the purchaser to close and purchase the alcoholic beverage product through the authentication procedure (adult verification procedure) over two times while at the same time allowing the alcoholic product to be picked up from the alcoholic beverage refrigerator through real-name authentication, This has the advantage of reliably preventing minors from purchasing alcoholic beverages. Hereinafter, with reference to FIG. 14 , a process of data processing and automatic ordering processing using data generated in an unmanned store and artificial intelligence technology will be described.

14 is a diagram illustrating a process of data processing and automatic ordering processing using data generated in an unmanned store and artificial intelligence technology, according to various embodiments of the present disclosure;

The process of data processing and automatic ordering processing using data generated in the unmanned store according to FIG. 14 and artificial intelligence technology is described as being performed by the computing device 100, but is not limited thereto, and the user terminal 201 (or the processor in the user terminal 201 ) executes the application provided from the computing device 100 to perform data processing and automatic ordering processing using data and artificial intelligence technology generated in the unmanned store, or the kiosk 202 ) (or the processor in the kiosk 202) executes the software provided from the computing device 100 to perform data processing and automatic ordering processing using data generated in an unmanned store and artificial intelligence technology. can

Referring to FIG. 14 , first, when a situation in which a buyer purchases a product in each of the plurality of unmanned stores occurs, the computing device 100 performs each data generated by selling the product to the buyer (eg, sales volume data (online , offline sales information), sales environment data (communication company alliance, commercial area analysis, company (store) information, credit card, discount information), collection/linkage data (sales product information, seasonal product sales information, buyer age information, buyer location) information, buyer affiliated company information, repurchase information, order information, sales amount information, etc.) may be loaded into the analysis server in the computing device 100 (1-1).

The computing device 100 distributes each data loaded into the analysis server for each analysis model categorized in advance (eg, daily/weekly/monthly information, statistics, FF (Fresh Food) pre-order, purchase information through the application, etc. ) can do.

Thereafter, the computing device 100 analyzes each data using an artificial intelligence model, thereby making a recommendation order of artificial intelligence (AI) (eg, exhausted products, popular products, new products, high margin products, etc.) Can be created (1-2). For example, the computing device 100 analyzes the above data to perform predictive analysis and visualization (eg, sales budget and product prediction, automatic ordering and order prediction, season/issue/promotion product prediction, sales prediction, new product sales period prediction, new store sales forecast, new store product composition prediction), and a recommended order can be created based on this.

Here, the artificial intelligence model may be a model pre-trained based on machine learning technology using various data related to sales and changes in sales volume for each product as learning data, but is not limited thereto.

Thereafter, the computing device 100 may present a recommended order proposal in order to consider the recommended order of artificial intelligence (AI) generated using the artificial intelligence model (1-3).

In addition, the computing device 100 compares product sales volume with other unmanned stores for each unmanned store (sales/purchase analysis) to check increase/decrease data for each product, and to check whether a problem affecting sales volume has occurred accordingly It can be (2-1).

Thereafter, the computing device 100 may create a product list with insufficient stock based on the inventory amount for each product, and may generate an order request according to the product list with insufficient stock ( 2-2 ).

Thereafter, the computing device 100 may perform the automatic ordering process in consideration of the recommended ordering proposal and the ordering request according to the product list lacking in stock together (2-3).

In addition, the computing device 100 automatically processes the order in consideration of the recommended order proposal and the order request according to the product list with insufficient stock, but in the case of a product lacking in stock, it is replaced with a recommended product to finally proceed with automatic ordering. You can (3-1).

In addition, the computing device 100 stores and automatically reports sales by providing the accounting data (eg, deposit slip, expense slip, withdrawal slip, VAT report, cost calculation and tax invoice) generated during product sales (order receipt) to the settlement server. It can be processed (4-1).

As mentioned above, although embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art to which the present invention pertains know that the present invention may be embodied in other specific forms without changing the technical spirit or essential features thereof. you will be able to understand Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive.

100: server (or computing device) providing product sales service in unmanned stores
201: user terminal
202 : Kiosk
300 : external server
400: network

Claims (15)

A method performed by a computing device, comprising:
collecting data on a plurality of unmanned stores;
generating order data for each of the plurality of unmanned stores by analyzing the collected data; and
Including the step of processing an order for each of the plurality of unmanned stores using the generated order data,
A method of providing automatic product ordering service in unmanned stores. According to claim 1,
The collected data is
Including inventory data for a plurality of products displayed in each of the plurality of unmanned stores,
The step of generating the order data is,
Analyze the inventory data data to select one or more products whose inventory is less than or equal to a preset number among a plurality of products, and order information for the selected one or more products. Including the step of generating order data comprising a,
A method of providing automatic product ordering service in unmanned stores. According to claim 1,
The step of generating the order data is,
analyzing the collected data to score each of the plurality of products; and
Based on the scoring result for each of the plurality of products, it is determined whether or not to process the order for each of the plurality of products and the order amount, and order data including information on whether or not the order is processed for each of the determined plurality of products and the amount of the order comprising the step of creating
A method of providing automatic product ordering service in unmanned stores. 4. The method of claim 3,
The collected data is
Includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores,
The step of scoring each of the plurality of products,
calculating the number of sales per one payment for each of the plurality of products by analyzing the sales data; and
Giving each of the plurality of products a weight based on the calculated number of sales per one time payment, and correcting the scoring result for each of the plurality of products by using the weighted weight,
A method of providing automatic product ordering service in unmanned stores. 4. The method of claim 3,
The collected data is
Includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores,
The step of scoring each of the plurality of products,
calculating a change in sales volume over time for each of the plurality of products by analyzing the sales volume data; and
Comprising the step of assigning a weight to each of the plurality of products based on the calculated amount of sales volume change according to the passage of time, and correcting a scoring result for each of the plurality of products using the weighted weight,
A method of providing automatic product ordering service in unmanned stores. 4. The method of claim 3,
The collected data is
Includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores,
The step of scoring each of the plurality of products,
calculating the sales volume by season and the sales volume by weather for each of the plurality of products by analyzing the sales data; and
A weight is given to each of the plurality of products based on the season information and weather information for a predetermined period based on the time of analyzing the sales volume data, and the sales volume by season and sales volume by weather for each of the calculated plurality of products, Comprising the step of correcting the scoring result for each of the plurality of products by using the given weight,
A method of providing automatic product ordering service in unmanned stores. 4. The method of claim 3,
The collected data is
Includes customer infrastructure data for each of the plurality of unmanned stores,
The step of scoring each of the plurality of products,
Analyze the customer infrastructure data to calculate the number of companies and the salary level of company employees located in the vicinity of each of the plurality of unmanned stores, and each of the plurality of products based on the calculated number of companies and the calculated salary level A weight is given to , and the step of correcting the scoring result for each of the plurality of products by using the weighted weight,
A method of providing automatic product ordering service in unmanned stores. 4. The method of claim 3,
The collected data is
Includes sales volume data and customer infrastructure data for each of a plurality of products displayed in the plurality of unmanned stores,
The step of scoring each of the plurality of products,
calculating a repurchase rate for each of the plurality of products by analyzing the sales volume data and the customer infrastructure data; and
Comprising the step of assigning a weight to each of the plurality of products based on the calculated repurchase rate, and correcting a scoring result for each of the plurality of products by using the assigned weight,
A method of providing automatic product ordering service in unmanned stores. 4. The method of claim 3,
The collected data is
Includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores,
The step of scoring each of the plurality of products,
analyzing the sales volume data to calculate an expected fair price for each unmanned store for each of the plurality of products;
sequentially arranging the plurality of products from the products having the calculated high expected fair prices for each unmanned store; and
Differentially assigning a weight to each of the plurality of products based on an order in which each of the plurality of products is sorted, and correcting a scoring result for each of the plurality of products by using the differentially assigned weight,
A method of providing automatic product ordering service in unmanned stores. 4. The method of claim 3,
The collected data is
Includes location data of each of the plurality of unmanned stores,
The step of generating the order data is,
Comprising the step of assigning a weight to each of the plurality of products based on the location data, and correcting a scoring result for each of the plurality of products by using the assigned weight,
A method of providing automatic product ordering service in unmanned stores. According to claim 1,
The collected data is
Includes social data for the plurality of unmanned stores and a plurality of products displayed in each of the plurality of unmanned stores,
The step of generating the order data is,
extracting one or more keywords from the social data;
assigning a weight to each of the plurality of products based on the extracted one or more keywords; and
Comprising the step of correcting the scoring result for each of the plurality of products by using the given weight,
A method of providing automatic product ordering service in unmanned stores. According to claim 1,
The collected data is
Includes sales volume data and customer infrastructure data for each of a plurality of products displayed in the plurality of unmanned stores,
The step of generating the order data is,
selecting one or more unmanned stores having the same or similar attributes to the attributes of the new unmanned store among the plurality of unmanned stores, wherein the attributes include at least one of the size, location, and customer infrastructure of the unmanned store; and
Analyzing the sales volume data of the selected one or more unmanned stores, comprising the step of generating order data for the first order quantity of the new unmanned store,
A method of providing automatic product ordering service in unmanned stores. According to claim 1,
The step of processing the order,
A simulation of product sales in the first unmanned store is performed using the first order data generated by analyzing data about the first unmanned store, and the scenario applied to the simulation is sales data of the first unmanned store Which is set based on the step; and
Comprising the steps of performing verification on the first order data based on the simulation result, and determining a processing method of the first order data based on the verification result of the first order data,
A method of providing automatic product ordering service in unmanned stores. processor;
network interface;
Memory; and
A computer program loaded into the memory and executed by the processor,
The computer program is
an instruction for collecting data about a plurality of unmanned stores;
instructions for analyzing the collected data to generate order data for each of the plurality of unmanned stores; and
Containing instructions for processing an order for each of the plurality of unmanned stores using the generated order data,
A server that provides automatic product ordering service for unmanned stores. combined with a computing device,
collecting data on a plurality of unmanned stores;
generating order data for each of the plurality of unmanned stores by analyzing the collected data; and
Stored in a computer-readable recording medium to execute the step of processing an order for each of the plurality of unmanned stores using the generated order data,
A computer program recorded on a computer-readable recording medium.

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